dairy technology research papers

Dairy Technology - Science topic

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

Our systems are now restored following recent technical disruption, and we’re working hard to catch up on publishing. We apologise for the inconvenience caused. Find out more: https://www.cambridge.org/universitypress/about-us/news-and-blogs/cambridge-university-press-publishing-update-following-technical-disruption

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings .

Login Alert

• < Back to search results
• Journal of Dairy Research

Journal of Dairy Research

• Submit your article

This journal utilises an Online Peer Review Service (OPRS) for submissions. By clicking "Continue" you will be taken to our partner site http://www.journalofdairyresearch.org/ . Please be aware that your Cambridge account is not valid for this OPRS and registration is required. We strongly advise you to read all "Author instructions" in the "Journal information" area prior to submitting.

• Information
• Journal home
• Journal information
• Research Reflections
• Key Reviews
• FirstView articles
• Latest issue
• Open access articles

• Get access Subscribe Check if you have access via personal or institutional login Log in Register
• Contains open access

• ISSN: 0022-0299 (Print) , 1469-7629 (Online)
• Editor: Professor C. Knight Institute of Veterinary Clinical and Animal Sciences|University of Copenhagen|Dyrlægevej 100 |1870 Frederiksberg C
• Editorial board

Latest articles

Two major bovine milk whey proteins induce distinct responses in iec-6 intestinal cells.

• Mizuho Inagaki , Midori Nohara , Chihiro Kobayashi , Mayuko Fukuoka , Xijier , Keisuke Matsumura , Kiyomi Ohashi , Haru Enomoto , Tomio Yabe , Yoshihiro Kanamaru
• Journal of Dairy Research , First View

Udder health, bacterial isolation and antimicrobial sensitivity of Staphylococcus species from non-dairy goats on smallholder farms in Hong Kong

• Rachel W. H. Lau , Fraser I. Hill , Kate J. Flay

Geometry of milk liners affects milking performance in dairy cows

• H. M Gayani P. Herath , Dino Kudrass , Racheal H. Bryant , Omar Al-Marashdeh

Variation in bovine milk stability according to lactational stage and genetic group

• Bruna Schmitz , Olmar Antônio Denardin Costa , Ana Carolina Fluck , Leonardo Piffer de Borba , Adriano Henrique do Nascimento Rangel , Vivian Fischer

In vitro antimicrobial and antibiofilm activity of phage cocktail against Mammaliicoccus sciuri , a causative agent of bovine mastitis

• Puthiya Maliyekkal Shahana Shirin , Archana Chandran , Pathiyarathvalappill Subrahmanian Surabhi , Ramachandran Latha Rathish , Mundakka Paramban Rahila

Relationship between body weight and hip width in dairy buffaloes ( Bubalus bubalis )

• Alvar Alonzo Cruz-Tamayo , Marco Antonio Ramírez-Bautista , Daniel Mota-Rojas , José Carlos Escobar-España , Ricardo García-Herrera , Antonio Leandro Chaves Gurgel , Tairon Pannunzio Dias-Silva , Marcos Jácome de Araújo , Juliana Caroline Santos Santana , Isadora Osorio Maciel Aguiar , Luís Carlos Vinhas Ítavo , Alfonso Juventino Chay-Canul

Effect of double-premilking teat disinfection protocols on bacterial counts on teat skin of cows and milker gloves in a free-stall-housed dairy herd

• Thiago Resin Niero , Roberto Kappes , Angelica Leticia Scheid , Andreina Ferreira Ramos , Eduardo Becker Ribeiro , Leonardo Leite Cardozo , Sandra Maria Ferraz , André Thaler Neto

Investigating the relationship between heat load and shade seeking behaviour in dairy buffaloes

• Syed I. Hussain , Muhammad A. Rashid , Muhammad Q. Shahid

JDR Editor's Choice Blog

The three “Ms” of green and healthy lactation research: Metabolism, Mastitis and Milking efficiency

• 17 February 2021, Rupert Bruckmaier and Chris Knight
• The Journal of Dairy Research Editor’s Choice Article is “Influence of nutrient availability on in vitro growth of major bovine mastitis pathogens” by...

Goats: much more than a poor lab’s cow!

• 17 February 2020, Giger-Reverdin et al.
• The Journal of Dairy Research Editor’s Choice Article for February is “Rumen function in goats, an example of adaptive capacity” by Giger-Reverdin et al.…...

Journal of Dairy Research Twitter

Hannah Dairy Research Foundation Twitter

2023 Journal Citation Reports © Clarivate Analytics

Proteinases in normal bovine milk and their action on caseins

• Anthony T. Andrews
• Journal of Dairy Research , Volume 50 , Issue 1

The Society has a range of rigorous technical publications, consisting of a scientific journal and a range of technical publications.

International Journal of Dairy Technology ISSN: 1364-727X This journal, now published in association with Wiley-Blackwell, ranks amongst the leading dairy journals published worldwide and is the Society's flagship.

Published quarterly, it is free to all members as part of their annual membership subscription; but it is valued at £197 to non-member subscribers. An electronic version is now also available from Wiley-Blackwell.

This Journal publishes original research papers submitted from all over the world, consistent with its growing international standing. These contributions are scrupulously peer reviewed, and also scrutinised by the Scientific Editorial Team and the Publications Committee.

The Journal also contains non-research contributions, embracing both review articles and more general papers of a technical or commercial nature presented at the Society's Symposia and Conferences.

The Society welcomes suitable papers, whether original research, review paper or Symposium/Conference contribution, for publication in its Journal. Interested authors are encouraged to submit their articles for publication to the Society at its address given in the Contact Us section

The contents of this prestigious publication are abstracted by the leading international databases. Full text articles are available online for society members to access.

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Journal Proposal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• PubMed/Medline
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Digital and precision technologies in dairy cattle farming: a bibliometric analysis.

Simple Summary

1. introduction, 2. materials and methods, 2.1. research procedure, 2.2. selection and organization procedures, 2.3. bibliometric mapping and clustering, 3. results and discussion, 3.1. relevant publications and characteristics of papers, 3.2. most influential journals, 3.3. author publications, 3.4. most influential countries, 3.5. main affiliations, 3.6. keywords related to digital and precision livestock, 3.7. trends in research on digital and precision livestock, 4. limitations and challenges of a bibliometric analysis, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Pastell, M.; Kujala, M.; Aisla, A.-M.; Hautala, M.; Poikalainen, V.; Praks, J.; Veermäe, I.; Ahokas, J. Detecting cow’s lameness using force sensors. Comput. Electron. Agric. 2008 , 64 , 34–38. [ Google Scholar ] [ CrossRef ]
• Laca, E.A. Precision livestock production: Tools and concepts. [SciELO—Brasil—Precision livestock production: Tools and concepts Precision livestock production: Tools and concepts]. Rev. Bras. Zootec. 2009 , 38 , 123–132. [ Google Scholar ] [ CrossRef ]
• Antanaitis, R.; Juozaitienė, V.; Džermeikaitė, K.; Bačėninaitė, D.; Šertvytytė, G.; Danyla, E.; Rutkauskas, A.; Viora, L.; Baumgartner, W. Change in Rumination Behavior Parameters around Calving in Cows with Subclinical Ketosis Diagnosed during 30 Days after Calving. Animals 2023 , 13 , 595. [ Google Scholar ] [ CrossRef ]
• Halachmi, I.; Guarino, M.; Bewley, J.; Pastell, M. Smart animal agriculture: Application of real-time sensors to improve animal well-being and production. Annu. Rev. Anim. Biosci. 2019 , 7 , 403–425. [ Google Scholar ] [ CrossRef ]
• Leliveld, L.M.; Lovarelli, D.; Finzi, A.; Riva, E.; Provolo, G. Effects of cow reproductive status, parity and lactation stage on behaviour and heavy breathing indications of a commercial accelerometer during hot weather conditions. Int. J. Biometeorol. 2023 , 67 , 1263–1272. [ Google Scholar ] [ CrossRef ]
• Vázquez-Diosdado, J.A.; Gruhier, J.; Miguel-Pacheco, G.; Green, M.; Dottorini, T.; Kaler, J. Accurate prediction of calving in dairy cows by applying feature engineering and machine learning. Prev. Veter. Med. 2023 , 219 , 106007. [ Google Scholar ] [ CrossRef ]
• Ali, A.S.; Jacinto, J.G.P.; Mϋnchemyer, W.; Walte, A.; Kuhla, B.; Gentile, A.; Abdu, M.S.; Kamel, M.M.; Ghallab, A.M. Study on the Discrimination of Possible Error Sources That Might Affect the Quality of Volatile Organic Compounds Signature in Dairy Cattle Using an Electronic Nose. Veter. Sci. 2022 , 9 , 461. [ Google Scholar ] [ CrossRef ]
• Laurindo, G.M.; Ferraz, G.A.e.S.; Damasceno, F.A.; Nascimento, J.A.C.D.; dos Santos, G.H.R.; Ferraz, P.F.P. Thermal Environment and Behavior Analysis of Confined Cows in a Compost Barn. Animals 2022 , 12 , 2214. [ Google Scholar ] [ CrossRef ]
• Xu, X.; Wang, Y.; Hua, Z.; Yang, G.; Li, H.; Song, H. Light-weight recognition network for dairy cows based on the fusion of YOLOv5s and channel pruning algorithm. Trans. Chin. Soc. Agric. Eng. 2023 , 39 , 153. [ Google Scholar ]
• Siberski-Cooper, C.J.; Mayes, M.S.; Gorden, P.J.; Hayman, K.; Hardie, L.; Shonka-Martin, B.N.; Koltes, D.A.; Healey, M.; Goetz, B.M.; Baumgard, L.H.; et al. The impact of health disorders on automated sensor measures and feed intake in lactating Holstein dairy cattle. Front. Anim. Sci. 2023 , 3 , 1064205. [ Google Scholar ] [ CrossRef ]
• Kang, X.; Liu, G.; Chu, M.; Li, Q.; Wang, Y. Advances and Challenges in Physiological Parameters Monitoring and Diseases Diagnosing of Dairy Cows Based on Computer Vision. Smart Agric. 2022 , 4 , 1. [ Google Scholar ]
• Wang, X.; Dai, B.; Wei, X.; Shen, W.; Zhang, Y.; Xiong, B. Vision-based measuring method for individual cow feed intake using depth images and a Siamese network. Int. J. Agric. Biol. Eng. 2023 , 16 , 233–239. [ Google Scholar ] [ CrossRef ]
• Kadlec, R.; Indest, S.; Castro, K.; Waqar, S.; Campos, L.M.; Amorim, S.T.; Bi, Y.; Hanigan, M.D.; Morota, G. Automated acquisition of top-view dairy cow depth image data using an RGB-D sensor camera. Transl. Anim. Sci. 2022 , 6 , txac163. [ Google Scholar ] [ CrossRef ]
• Zhang, J.; Lei, J.; Wu, J.; Lu, H.; Guo, H.; Pezzuolo, A.; Kolpakov, V.; Ruchay, A. Automatic method for quantitatively analyzing the body condition of livestock from 3D shape. Comput. Electron. Agric. 2023 , 214 , 108307. [ Google Scholar ] [ CrossRef ]
• Norton, T.; Berckmans, D. Developing precision livestock farming tools for precision dairy farming. Anim. Front. 2017 , 7 , 18–23. [ Google Scholar ] [ CrossRef ]
• Wu, D.; Wang, Y.; Han, M.; Song, L.; Shang, Y.; Zhang, X.; Song, H. Using a CNN-LSTM for basic behaviors detection of a single dairy cow in a complex environment. Comput. Electron. Agric. 2021 , 182 , 106016. [ Google Scholar ] [ CrossRef ]
• Alvarez, J.R.; Arroqui, M.; Mangudo, P.; Toloza, J.; Jatip, D.; Rodríguez, J.M.; Teyseyre, A.; Sanz, C.; Zunino, A.; Machado, C.; et al. Body condition estimation on cows from depth images using Convolutional Neural Networks. Comput. Electron. Agric. 2018 , 155 , 12–22. [ Google Scholar ] [ CrossRef ]
• Noyons, E.C.M.; Moed, H.F.; Luwel, M. Combining mapping and citation analysis for evaluative bibliometric purposes: A bibliometric study. J. Am. Soc. Inf. Sci. 1999 , 50 , 115–131. [ Google Scholar ] [ CrossRef ]
• Soares, P.B.; Carneiro, T.C.; Calmon, J.L.; Castro, L.O. Análise bibliométrica da produção científica brasileira sobre Tecnologia de Construção e Edificações na base de dados Web of Science. Ambient. Constr. 2016 , 16 , 175–185. [ Google Scholar ]
• Quevedo-Silva, F.; Santos, E.B.A.; Brandão, M.M.; Vils, L. Bibliometric study: Guidelines on its application. REMark Rev. Bras. Mark. 2016 , 15 , 246–262. [ Google Scholar ] [ CrossRef ]
• Garfield, E. Citation indexes for science; A new dimension in documentation through association of ideas. Science 1955 , 122 , 108–111. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Filho, V.A.V.; Goi, M.Y.O. Supply chain management 4.0: Content analysis in the most relevant articles from Scopus and Web of Science databases. Braz. J. Develop. 2021 , 7 , 117868–117889. [ Google Scholar ] [ CrossRef ]
• Mueller, S. Estudos métricos da informação em ciência e tecnologia no Brasil realizados sobre a unidade de análise artigos de periódicos? Liinc Rev. 2013 , 9 , 6–27. [ Google Scholar ] [ CrossRef ]
• Nardi, P.; Di Matteo, G.; Palahi, M.; Scarascia Mugnozza, G. Structure and evolution of mediterranean forest research: A science mapping approach. PLoS ONE 2016 , 11 , e0155016. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Coman, M.A.; Marcu, A.; Chereches, R.M.; Leppälä, J.; Broucke, S.V.D. Educational interventions to improve safety and health literacy among agricultural workers: A systematic review. Int. J. Environ. Res. Public Health 2020 , 17 , 1114. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Silva, G.G.B.S.; Ferraz, P.F.P.; Damasceno, F.A.; Zotti, M.L.A.N.; Barbari, M. Compost Barns: A Bibliometric Analysis. Animals 2022 , 12 , 2492. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Derviş, H. Bibliometric Analysis using Bibliometrix an R Package. J. Sci. Res. 2019 , 8 , 156–160. [ Google Scholar ] [ CrossRef ]
• Aria, M.; Cuccurullo, C. bibliometrix: An R-tool for comprehensive science mapping analysis. J. Informetr. 2017 , 11 , 959–975. [ Google Scholar ] [ CrossRef ]
• Van Eck, N.J.; Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010 , 84 , 523–538. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Van Eck, N.J.; Waltman, L. VOSviewer Manual ; Univeristeit Leiden: Leiden, The Netherlands, 2013; Volume 1, pp. 1–53. [ Google Scholar ]
• Van Eck, N.J.; Waltman, L. Visualizing Bibliometric Networks. In Measuring Scholarly Impact: Methods and Practice , 1st ed.; Ding, Y., Rousseau, R., Wolfram, D., Eds.; Springer: Cham, Switzerland, 2014; pp. 285–320. [ Google Scholar ]
• Bewley, J.; Boehlje; Gray, A.; Hogeveen, H.; Kenyon, S.; Eicher, S.; Schutz, M. Assessing the potential value for an automated dairy cattle body condition scoring system through stochastic simulation. Agric. Financ. Rev. 2010 , 70 , 126–150. [ Google Scholar ] [ CrossRef ]
• Bewley, J.M.; E Boyce, R.; Hockin, J.; Munksgaard, L.; Eicher, S.D.; E Einstein, M.; Schutz, M.M. Influence of milk yield, stage of lactation, and body condition on dairy cattle lying behaviour measured using an automated activity monitoring sensor. J. Dairy Res. 2009 , 77 , 1–6. [ Google Scholar ] [ CrossRef ]
• Frigeri, K.D.M.; Kachinski, K.D.; Ghisi, N.d.C.; Deniz, M.; Damasceno, F.A.; Barbari, M.; Herbut, P.; Vieira, F.M.C. Effects of Heat Stress in Dairy Cows Raised in the Confined System: A Scientometric Review. Animals 2023 , 13 , 350. [ Google Scholar ] [ CrossRef ]
• Diosdado, J.A.V.; Barker, Z.E.; Hodges, H.R.; Amory, J.R.; Croft, D.P.; Bell, N.J.; Codling, E.A. Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system. Anim. Biotelemetry 2015 , 3 , 15. [ Google Scholar ] [ CrossRef ]
• Alonso, R.S.; Sittón-Candanedo, I.; García, Ó.; Prieto, J.; Rodríguez-González, S. An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario. Ad Hoc Netw. 2020 , 98 , 102047. [ Google Scholar ] [ CrossRef ]
• Zehner, N.; Umstätter, C.; Niederhauser, J.J.; Schick, M. System specification and validation of a noseband pressure sensor for measurement of ruminating and eating behavior in stable-fed cows. Comput. Electron. Agric. 2017 , 136 , 31–41. [ Google Scholar ] [ CrossRef ]
• Spoliansky, R.; Edan, Y.; Parmet, Y.; Halachmi, I. Development of automatic body condition scoring using a low-cost 3-dimensional Kinect camera. J. Dairy Sci. 2016 , 99 , 7714–7725. [ Google Scholar ] [ CrossRef ]
• Bezen, R.; Edan, Y.; Halachmi, I. Computer vision system for measuring individual cow feed intake using RGB-D camera and deep learning algorithms. Comput. Electron. Agric. 2020 , 172 , 105345. [ Google Scholar ] [ CrossRef ]
• Porto, S.M.; Arcidiacono, C.; Anguzza, U.; Cascone, G. The automatic detection of dairy cow feeding and standing behaviours in free-stall barns by a computer vision-based system. Biosyst. Eng. 2015 , 133 , 46–55. [ Google Scholar ] [ CrossRef ]
• Dolecheck, K.A.; Silvia, W.J.; Heersche, G., Jr.; Chang, Y.M.; Ray, D.L.; Stone, A.E.; Wadsworth, B.A.; Bewley, J.M. Behavioral and physiological changes around estrus events identified using multiple automated monitoring technologies. J. Dairy Sci. 2015 , 98 , 8723–8731. [ Google Scholar ] [ CrossRef ]
• Achour, B.; Belkadi, M.; Filali, I.; Laghrouche, M. Image analysis for individual identification and feeding behaviour monitoring of dairy cows based on Convolutional Neural Networks (CNN). Biosyst. Eng. 2020 , 198 , 31–49. [ Google Scholar ] [ CrossRef ]
• Pallottino, F.; Biocca, M.; Nardi, P.; Figorilli, S.; Menesatti, P.; Costa, C. Science mapping approach to analyze the research evolution on precision agriculture: World, EU and Italian situation. Precis. Agric. 2018 , 19 , 1011–1026. [ Google Scholar ] [ CrossRef ]
• Computers and Electronics in Agriculture. Available online: https://www.sciencedirect.com/journal/computers-and-electronics-in-agriculture (accessed on 14 November 2023).
• Journal of Dairy Science. Official Publication of the American Dairy Science Association. Available online: https://www.journalofdairyscience.org/ (accessed on 14 November 2023).
• Biosystems Engineering. Available online: https://www.sciencedirect.com/journal/biosystems-engineering (accessed on 14 November 2023).
• Animals. Available online: https://www.mdpi.com/journal/animals (accessed on 14 November 2023).
• Animal. Available online: https://www.cambridge.org/core/journals/animal (accessed on 14 November 2023).
• Animal Biotelemetry. Available online: https://animalbiotelemetry.biomedcentral.com/ (accessed on 14 November 2023).
• Adc Hoc Networks. Available online: https://www.sciencedirect.com/journal/ad-hoc-networks (accessed on 14 November 2023).
• Journal of Dairy Research. Available online: https://www.cambridge.org/core/journals/journal-of-dairy-research (accessed on 14 November 2023).
• Mumu, J.R.; Saona, P.; Russell, H.I.; Azad, A.K. Corporate governance and remuneration: A bibliometric analysis. J. Asian Bus. Econ. Stud. 2021 , 28 , 242–262. [ Google Scholar ] [ CrossRef ]
• Hirsch, J.E. An index to quantify an individual’s scientific research output. Proc. Natl. Acad. Sci. USA 2005 , 102 , 16569–16572. [ Google Scholar ] [ CrossRef ]
• Donthu, N.; Kumar, S.; Mukherjee, D.; Pandey, N.; Lim, W.M. How to conduct a bibliometric analysis: An overview and guidelines. J. Bus. Res. 2021 , 133 , 285–296. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

Share and Cite

de Oliveira, F.M.; Ferraz, G.A.e.S.; André, A.L.G.; Santana, L.S.; Norton, T.; Ferraz, P.F.P. Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis. Animals 2024 , 14 , 1832. https://doi.org/10.3390/ani14121832

de Oliveira FM, Ferraz GAeS, André ALG, Santana LS, Norton T, Ferraz PFP. Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis. Animals . 2024; 14(12):1832. https://doi.org/10.3390/ani14121832

de Oliveira, Franck Morais, Gabriel Araújo e Silva Ferraz, Ana Luíza Guimarães André, Lucas Santos Santana, Tomas Norton, and Patrícia Ferreira Ponciano Ferraz. 2024. "Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis" Animals 14, no. 12: 1832. https://doi.org/10.3390/ani14121832

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

• Search Close search
• Find a journal
• Search calls for papers
• Journal Suggester
• Open access publishing

We’re here to help

Find guidance on Author Services

Open access

Dairy 3.0: cellular agriculture and the future of milk

• Cite this article
• https://doi.org/10.1080/15528014.2021.1888411

1. Introduction

2. technology and agriculture, 3. cellular agriculture, 4. fermentation-derived dairy, 5. key areas of interest for cellular agriculture, 6. lessons from plant-based milk substitutes, 7. conclusions and further directions, disclosure statement, additional information.

• Full Article
• Figures & data
• Reprints & Permissions
• View PDF PDF View EPUB EPUB

Animal-derived and plant-derived dairy products will soon be joined by dairy produced using fermentation-derived cellular agriculture. Most cellular agriculture literature focuses on “cultured meats,” but fermentation-derived dairy products are likely to reach consumer markets earlier as the technological barriers are much lower. An analysis of literature on dairy and on broader cellular agriculture literature suggests several barriers to adoption, including acceptance of technology, cultural capital associated with animal-based products, and policies that define parameters for producing and marketing dairy alternatives. This paper positions fermentation-derived dairy products within the dialogs on dairy alternatives and on cellular agriculture, identifying key areas that scholars, policymakers, and industry need to address before Dairy 3.0 reaches grocery shelves.

• Cellular agriculture
• food policy
• fermentation-derived dairy
• consumer perceptions and acceptance
• dairy alternatives
• food culture

The global dairy industry is currently in flux. Farm size is increasing, production is shifting into the Global South, and stagnant markets in traditional dairy regions are balanced by rapid increase in demand elsewhere (Douphrate et al. Citation 2013 ; Lagrange, Whitsett, and Burris Citation 2015 ). With global milk production estimated at 843 million tons of milk in 2018 alone (FAO Citation 2019 ), dairy remains a major agricultural product. The critique of dairy products, however, is on the rise with focus on health, environmental impacts, and ethical implications. Though Thorning et al. ( Citation 2016 ) found no demonstrated population-level negative health effects of dairy consumption, they noted increasing skepticism among consumers about health consequences of eating dairy. On the environmental front, though the impact of dairy cattle is not yet fully understood, Rojas-Downing and colleagues (Rojas-Downing et al. Citation 2017 ) provide a thorough overview citing the impact of greenhouse emissions on the land base. They report that global livestock production in total generates more greenhouse gasses (GHGs) than the transportation sector, the main sources of emissions being the feed production and processing (45% of the total), outputs of greenhouse gases during digestion by cows (39%), and manure decomposition (10%). While others have estimated that world milk production is responsible for between 2.65% and 3.94% of global anthropogenic GHG emissions, an accurate estimate is difficult given the diversity of farming practices in place around the world (Hagemann et al. Citation 2012 ). For example, in France, agroecology-based farming practices were found to reduce GHG emissions by 19% per kg of milk, and by 25% per hectare, compared to single commodity farm practices that increased emissions by 6% and 28% respectively (Martin and Willaume Citation 2016 ). Though ethical concerns over dairy production tend to be fewer than over other sectors of animal agriculture, Croney and Anthony ( Citation 2011 ) note a rise overall in ethical concerns driving increased interest in plant-based diets. Despite these concerns, consumer demand for dairy products remains steady and is growing in non-traditional markets. Dairy products remain a popular component of the Western diet on strengths of flavor and nutrition at a reasonable cost. In addition, dairy products, particularly cheese, maintain strong cultural capital (Garanti and Berberoglu Citation 2018 ).

Since antiquity, societies have held strong cultural connections to milk, through contexts ranging from mythology and religion to media. As Valenze ( Citation 2011 ) notes, “Situated in culture, milk is a mirror of its host society, reflecting attitudes toward nature, the human body, and technology” (p. 5). While milk’s associations with women’s bodies and children are nearly universal, in North America, Britain, and Europe, milk and dairying have been key elements of the rural idyll, as images of dairy cattle, barns, and the act of milking have been part of idealized pastoral scenes ranging from centuries-old landscape paintings to contemporary television (Peeren and Souch Citation 2019 ; Smith-Howard Citation 2013 ; Woods Citation 2011 ). As Valenze asserts, dairy production remains a “placeholder for a vision of a vanishing agrarian past” (p 291); yet, in the twentieth and twenty-first centuries, milk and dairy have also been inextricably linked to laboratory-based technology with increasingly sophisticated artificial insemination practices and growth hormones being two ways that cow’s milk has been manipulated (Smith-Howard Citation 2013 ).

Emerging technologies are changing the production and consumption landscapes of many foods, including cheese and other dairy products, potentially allowing for continued consumption of culturally valued products with reduced environmental and ethical concerns. In particular, a group of technologies collectively referred to as “cellular agriculture” has garnered attention among scholars and the popular press for their potential to produce cultured meat products such as lab-grown beef (Mattick Citation 2018 ); however, there has been limited public and scholarly discourse about the technology’s potential to create milk without cows. In this article, we describe the technology of fermentation-derived milk production and discuss its potential economic, environmental, cultural, and social implications in Canadian and U.S. contexts. We situate the cellular agriculture application of fermentation-derived dairy production within existing literature on cultured meat and on plant-based milk alternatives and how they have been received. We compare examples of policy debates around other food technologies and around the dairy industry and discuss the cultural embeddedness of animal-derived dairy. Finally, we discuss possible future directions for research as fermentation-derived dairy enters the consumer market.

Alongside fondness for the rural idyll, there is technophobia that acts as a brake on adoption of food and agriculture technology among farmers and consumers. As Flett et al. ( Citation 2004 ) noted in their study of the dairy industry, economic models that frame adaptation of technology as a balance of perceived usefulness and perceived ease of use tend to be overly optimistic about technological adaptation in the sector. The standard Technology Acceptance Model (TAM) introduced by Davis ( Citation 1989 ) misses a cultural element present in the farming community, though Flett et al. ( Citation 2004 ) do not explore what this is.

On the consumer side, there are complex interactions with the term “natural.” Siegrist ( Citation 2008 ) stresses that perceived benefit, perceived risk, and perceived naturalness are important factors for the acceptance of new food technologies, arguing the technologies are difficult to fully understand, and so the public falls back upon the catch phrase “natural.” Rozin et al. ( Citation 2004 ) showed that associations with the word “natural” are almost entirely positive. Egolf and colleagues (Egolf, Hartmann, and Siegrist Citation 2019 ) agree, claiming the distrust of new food technologies is deeply rooted in risk avoidance.

As Frewer et al. ( Citation 2011 ) note, perceptions of “unnaturalness” alone are unlikely to raise levels of public rejection, but they open the public to being overly negative toward agricultural innovation. Consumers are most likely to accept technologies that mirror existing ones, rather than those representing disruptive breaks in production methods. Frewer et al. ( Citation 2011 ) stress the need for further study into the psychological, social, political, and historical elements of commercialization.

Such resistance, however, does not completely stop adaptation over the long term. As Burton ( Citation 2019 ) explores in case studies of plant dyes and vanilla production, even in cases where “natural” is initially described as superior, a mixed market develops where plant- and animal-derived products coexist and compete for market share with manufactured alternatives. They highlight the unease generated by substitutionism, in which industrial applications eradicate the need for existing farming systems. He gives the example of the maddar root dye farming industry, which was eliminated by industrial alternatives.

This unease is not new, and has been present throughout agriculture’s technological development, which tends to move in bursts. Bonny and colleagues (Bonny et al. Citation 2015 ) note resistance to new agricultural technologies dates back to at least the industrial revolution of the 1800s. In their paper on the then-emerging schism between “conventional” and “alternative” production, Beus and Dunlap ( Citation 1990 ) describe debate between the two camps as a battle between classic worldviews. The authors describe the two sides as framing an argument of dominion over nature versus harmony with nature, grounded in an American tradition of agrarian reform.

Cellular agriculture as defined by Stephens et al. ( Citation 2018 ) encompasses a set of technologies for manufacturing products typically obtained from livestock farming using culturing techniques. At the time of writing no such meat products have come to market, though media attention given to cellular agriculture has risen sharply. Unlike plant-based meat and dairy replacements, the promise of cellular agriculture is the creation of biologically equivalent or near-equivalent replacements. Some hybrid products, including the commercially available Impossible Burger, call this viscerally equivalent (Stephens et al. Citation 2018 ). Cellular agriculture products currently in development include meats such as chicken, pork, and beef; egg whites; seafood including shrimp and fish; leather, gelatin, and horn; as well as milk and dairy products.

As noted by Mouat and Prince ( Citation 2018 ), cellular agriculture has been consumed as a narrative, if not as tangible foodstuffs. The current dialogue is one of potential. These technologies, for example, open the possibility of producing foods without the need to involve large numbers of animals. These technologies could create the potential for food production in northern and remote regions, particularly in Canada where it is impractical, if not impossible, to raise cattle, and the price of milk has been reported to be 1.48 times the average price in the nation’s southern areas (Nunavut Bureau of Statistics Citation 2015 ). Cellular agriculture also holds the potential to produce foods in which both macro- and micronutrient content is modified to support optimal health or taste, potentially creating a new class of superfoods. Fermentation-derived dairy fits within a larger dialogue of cellular agriculture that is strongly aspirational; as Isha Datar from New Harvest–a prominent cellular agriculture research institute–claims, the goal of producing traditionally animal-derived foods without animals is ‘the next and logical step in an agricultural (r)evolution’ (Datar, Kim, and d’Origny Citation 2016 , 122). In the near future, it is much more likely that fermentation-derived dairy products will fill a niche alongside animal-derived and plant-derived alternatives. The ultimate size of that niche is yet to be determined.

Cellular agriculture products remain new enough to defy a uniform nomenclature. The umbrella term “cellular agriculture” is favored by many as described by Datar, Kim, and d’Origny ( Citation 2016 ). They prefer “cellular agriculture products” for tissue-based products and “acellular agriculture products” where fermentation-based methods are used, though this is a confusing division. Other suggestions include “ in vitro ” (Stephens Citation 2010 ) “lab-grown” (Galusky Citation 2014 ), and the current iteration, “cultured” (Post Citation 2012 ). All of these terms developed primarily to reflect a focus on meat replacement through tissue culture; for dairy products, the term “cultured” (a current favorite) is problematic because of a preexisting conventional meaning; “cultured” is an accepted term for dairy products prepared using lacto-fermentation. For the purposes of this article, we suggest that dairy can be categorized as animal-derived, plant-derived, and fermentation-derived (also possible is yeast-derived, and flora-derived). The last of these is our focus.

Production of dairy products without cows receives far less attention than production of meat without animals, despite the process being much simpler and the technology being older and more established. Fermentation-derived dairy is currently commercially available in a limited amount in the United States only. Despite this limited availability, there are companies building the capacity to bring it to global markets within the next few years, based upon existing industrially scaled food processing infrastructure. Rennet, as a cellular agriculture product, is already produced on an industrial-scale, and there are multiple existing uses for milk solids, regardless of their origin.

At the time of writing, we know of three companies making fermentation-derived dairy: Perfect Day, LegenDairy Foods, and the Real Vegan Cheese project. The most developed of these is Perfect Day (previously Muufri), a San Francisco-based cellular agriculture company founded by Perumal Ghandi, Ryan Pandya, and Isha Datar. Perfect Day, which positions their product as “flora-based” (Perfect Day Citation 2020 ), has received considerable interest from both private investors and the food industry. In 2018 they secured 24.7 USD million in a Series A funding round lead by global investment company Temasek (Watson Citation 2018 ) and also partnered with Archer Daniels Midland, a major global food processing company, for further development and commercialization (Perfect Day Citation 2018 ). Most recently, Perfect Day has partnered with San Francisco–based company, Smitten Ice Cream, to produce “N’ice Cream”. Smitten Ice Cream now offers nationwide shipping in the United States (Smitten Ice Cream Citation 2020 ). At the other end of the business spectrum is the Real Vegan Cheese Project, composed of teams of self-described “biohackers” from BioCurious and Counter Culture labs. Their funding is largely crowd-sourced, including nearly 40,000 USD from a 2014 Indiegogo campaign, and they currently accept donations on their website (Graham Citation 2014 ; Real Vegan Cheese Citation 2019 ).

The creation of dairy through a fermentation process employs microflora, including bacteria and/or yeast to synthesize proteins that can then be added to plant fats and water to create milk (Tuomisto et al. Citation 2017 ). Perfect Day has reported their process as follows: 3-D printed bovine DNA that encodes protein synthesis instructions for casein and whey proteins (alpha-lactalbumin and beta-lactoglobulin) are spliced into the plasmid DNA of yeast cells (Compton Citation 2016 ; Pandya Citation 2014 ). The yeast carrying recombinant DNA then produce these milk proteins through a process of fermentation. Milk proteins are then filtered out and combined with specific ratios of plant-sourced fats, minerals, sugar, and clean water to create lab milk (Pandya Citation 2014 ). The final product, according to Perfect Day, will have a longer shelf life and be more food safe compared to regular milk, with the added benefit of being hormone-, antibiotic-, and lactose-free (Perfect Day Citation 2019 ). Though the culture of cells to create meat has largely been confined to the lab, bioengineered fermentation processes have been used commercially for decades.

This fermentation-derived technology was first developed and employed in an industrial setting with the production of insulin; before these processes were developed, insulin was obtained by harvesting the pancreata of pigs or cattle. In 1973, Cohen and colleagues laid the foundation for this technology with their work on genetic engineering when they successfully inserted plasmids carrying foreign DNA into bacteria Escherichia coli (Cohen et al. Citation 1973 ). In 1978, Riggs, Itakura, and Boyer built on this research and successfully inserted DNA coding for insulin into the same strain of bacteria, producing the first insulin identical to that produced by humans. A safe and stable supply of insulin was created using this technology and pioneered the field of biopharmaceuticals (Nielsen Citation 2013 ).

Application of this technology to food is not new either; it has been used to produce rennet (specifically the enzyme chymosin) since the 1980s. Rennet is a set of protease enzymes endogenous to the stomachs of ruminant animals which curdles casein proteins found in milk, making it an essential component of cheesemaking. Today, rennet can be produced through fermentation-derived processes using either bacteria, yeast, or fungi. Before this technology, rennet was produced by harvesting the fourth stomach of unweaned calves – a time-consuming and expensive process impractical for meeting global demand, particularly in the 1970s when cheese demand outgrew rennet supplies (Garg and Johri Citation 1994 ). Fermentation-derived rennet was lauded for producing a stable and pure supply free from contaminants including other enzymes and proteins found in calf stomachs. In 1990, rennet was the first genetically engineered food product approved by the United States Food and Drug Administration (USFDA) (Gladwell Citation 1990 ).

Recently, another acellular foodstuff has been developed and is on the market as the key ingredient in Impossible Foods’ Impossible Burger. Leghemoglobin is a protein derived from legume nodules and is responsible for the flavor and aroma of cooked meat. The USFDA approved the acellular production of leghemoglobin in the summer of 2018, with CNBC reporters describing it as a “big win” for the company and investors, including Google Ventures and Bill Gates (Shapiro Citation 2018 ). Leghemoglobin plays a key factor in the Impossible Burger’s visceral equivalence to beef burgers and may end up being important in consumer acceptance of cultured meat. It is likely still many years before cultured meat comes to the market, unlike dairy, which is already available for purchase across the United States.

Ethics, health and safety, the environment, and consumer perceptions are key areas of cellular agriculture research. While the literature regarding fermentation-derived dairy is limited, broader discussions on cellular agriculture-–particularly those focused on cultured meat–are useful as they provide insight into the potential of this technology. Although cultured meat and fermentation-derived dairy employ different processes, they both fall under the umbrella of cellular agriculture technologies producing biological equivalent foodstuffs without relying on animals. Therefore, both these processes raise similar questions about consumer perceptions and acceptance, and research on vegan consumer perceptions of fermentation-derived dairy has mirrored those of studies on cultured meat (X, Y, and Z, forthcoming).

5.1. Ethics

Cellular agriculture is fertile ground for ethics research and debate. Academic literature on the topic appears optimistic (see Dilworth and McGregor ( Citation 2015 ) for a review), with a strong focus placed on the acceptance of these new foodstuffs by the vegetarian and vegan communities. Milburn ( Citation 2018 ), for example, argues vegans should embrace fermentation-derived dairy and claims that arguments that creating animal-free milk affirms human superiority over cows are false as human breast milk could and should also be made using this technology. In earlier work, Milburn ( Citation 2016 ) defended “cannibalism simpliciter,” or victimless cannibalism, arguing in vitro flesh is not morally problematic in itself and encourages both vegans and animal ethicists to “cautiously embrace” its production (Milburn Citation 2016 , 249). While there are those who argue that we have a “moral obligation” to develop cellular agriculture (Hopkins and Dacey Citation 2008 )(579) others have suggested that it serves to continue the fetishization of meat (Cole and Morgan Citation 2013 ), or that it warrants caution because of potential to reinforce the corporate agri-food industrial complex (Miller Citation 2012 ). The latter point is particularly significant, as there are many unanswered questions regarding its production, implementation, ownership, and role within the global food system. Specifically, it has yet to be seen if cellular agriculture will allow us to make our own meat by harvesting cells from “pigs in our backyards” as suggested by Van Der Weele and Tramper ( Citation 2014 )(294) or if this technology will create a booming industry where small companies can create artisanal cellular agriculture products (Stephens et al. Citation 2018 ). It is conceivable, however, that this technology may lead to a new avenue of corporate control in the food system (J.-F. Hocquette Citation 2016 ), particularly if this technology is proprietary and cellular agriculture products subject to patents.

5.2. Health and safety

Proponents frame cellular agriculture, particularly cultured meat, as having potential to improve public health by reducing the use of antibiotics, fungicides, pesticides, and other substances associated with raising animals and animal feed (Kadim et al. Citation 2015 ). Reducing use of such products mitigates environmental contamination and worker exposure. Furthermore, Datar and Betti ( Citation 2010 ) have speculated that a decrease in zoonotic disease transmission would occur as a consequence of reducing animal-human interactions associated with farming. Mattick ( Citation 2018 ) suggests that rates of obesity and cardiovascular disease could decrease due to reduction or removal of trans-fats and cholesterol from cultured meat. In fermentation-derived dairy, similar adjustments could be made to improve public health including additional vitamins and nutraceuticals. New and unforeseen risks may also arise with cellular agriculture technology. Bhat and Fayaz ( Citation 2011 ), for example, see the possibility for substrates or culture medium to become contaminated, which may have more to do with production standards than with the technology itself. To circumvent this problem, the production of cellular agriculture products will require strict regulation and oversight to ensure food safety.

5.3. Environment

Cellular agriculture has the potential to mitigate impacts that intensive animal husbandry can have on the environment by reducing the number of animals needed for food production. The livestock sector is a significant contributor to climate change, responsible for an estimated 14.5% of total human-derived GHG emissions worldwide. Of livestock sector emissions, 65% are from cattle, with dairy cattle generating 20% of the total sector emissions (Gerber et al. Citation 2013 ). Furthermore, some forms of dairy farming impact biodiversity, fresh water quality, and the suitability of soils for other forms of agriculture (Baskaran, Cullen, and Colombo Citation 2009 ).

In a life cycle assessment for Perfect Day, when biologist Mark Steer ( Citation 2015 ) compared it to conventional dairy systems, large-scale fermentation-derived dairy production was estimated to reduce water use by 98%, land use by 77–91%, energy use by 24–48% and greenhouse gas emissions by 35–65%. Steer’s analysis was conducted using Perfect Day’s then-current methods of fermentation-derived dairy production, and he notes these preliminary estimates are subject to change as the technology develops.

Z (2020-forthcoming) cautions that there may be unintended environmental consequences from the scaling-up of cellular agriculture, particularly due to increased demand for sugar required for fermentation. Increased consumption of sugar or other required ingredients such as palm oil, could significantly impact on sensitive tropical environments through deforestation and animal loss, as explored in Goldstein and Mintz ( Citation 2015 ) and Tan et al. ( Citation 2009 ). Although these environmental impacts may be less compared to the current animal livestock industry, they still require consideration and potentially action to preserve environmentally sensitive areas.

Stephens et al. ( Citation 2018 ) note many narratives of cellular agriculture benefits, particularly cultured meat, assume this technology will have a “substitution effect, that is, foods produced using cellular agriculture technology would replace conventional production (162). They write, however, that it is possible that cellular agriculture will have an additive effect, where global meat (and other food) consumption may increase as individuals have the option to consume either or both. Accordingly, it is difficult to assess the impact this technology will have, particularly as variables including price, availability, and taste remain to be determined. Despite these unknowns, insight into impacts this technology will have on everyday lives can be gained from consumer perception studies. Numerous consumer perception studies have already been conducted on cultured meat; these studies explore the potential reception and adoption of this technology.

5.4. Consumer acceptance and perceptions of cellular agriculture

Consumer acceptance studies of cellular agriculture focused exclusively on meat production, have been conducted in various countries including Italy (Mancini and Antonioli Citation 2019 ), Netherlands (Bekker et al. Citation 2017 ; Verbeke, Sans, and Van Loo Citation 2015 ), France (Hocquette et al. Citation 2015 ), the UK (O’Keefe et al. Citation 2016 ), the US (Wilks and Phillips Citation 2017 ). Despite lack of uniformity in research method and design (Bryant and Barnett Citation 2018 ), commonalities regarding who is most willing to try and regularly consume cultured meat have emerged. Those most willing to try cultured meat have tended to be younger men with higher levels of education (Slade Citation 2018 ; Wilks, Phillips, and Romanach Citation 2017 ) and who live in cities (Tucker Citation 2014 ). Left leaning political orientation has also been identified as a predictor (Bryant et al. Citation 2019 ; Wilks, Phillips, and Romanach Citation 2017 ). Vegans and vegetarians, although supportive of cultured meat and more likely to perceive its benefits, are less likely to try and purchase it compared to meat eaters (Bryant and Barnett Citation 2018 ; Bryant et al. Citation 2019 ).

As reviewed by Bryant and Barnett ( Citation 2018 ), common concerns with cultured meat included price, taste, and appeal of the product, as well as the “naturalness” of it. Concerns over the impact of cellular agriculture on farmers and consolidation of power in the food system were also noted, as were anxieties over cannibalism and the inability to distinguish cultured meat from animal meat. Accordingly, consumers call for regulation and labeling of cultured meat, and likely cellular agriculture products in general.

Key findings from studies on cultured meat may be used as a starting point to examine how consumers may respond and accept fermentation-derived dairy. Arguments against fermentation-derived dairy are likely to hinge on its use of genetically modified organisms (GMOs), despite the product itself containing no GMOs (Milburn Citation 2018 ). Furthermore, we can draw from lessons on the reception of plant-based milk and examine current regulations surrounding dairy to infer how fermentation-derived dairy might be received in Canada and the US. Acceptance and commercialization of fermentation-derived dairy are complicated by the cultural and policy landscapes surrounding these products. Milk is among the most heavily regulated food products in countries worldwide (Gambert and Linné Citation 2018 ), and responses to plant-based milks shed light on what policy challenges may emerge during attempts to introduce fermentation-derived dairy to the consumer market.

Plant-derived milk has a long history. In China, there has been small-scale production of soy milk for at least 2000 years. Similar beverages include the horchata of central America, boza from Eastern Europe, and the malted millet beverages of East Africa (Mäkinen et al. Citation 2016 ). The cross-cultural existence of plant-based alternatives over human history points to a significant role for these beverages in human experience and in shaping societies.

Commercial production of soy milk is much more recent, emerging in Hong Kong in the 1940s and capturing a global market in the 1970s and 1980s, with rapid growth in the twenty-first century (Mäkinen et al. Citation 2016 ). Early products were known for gritty textures and somewhat “beany” flavors, but the current state of plant-based milks is reflected in their being the fastest growing segment in the specialty beverage category (Sethi, Tyagi, and Anurag Citation 2016 ). For example, in the United Kingdom, nearly a quarter (23%) of consumers reported consuming plant-based milk alternatives in 2019, up from 19% in 2018 (Mintel Citation 2019 ). In the US, sales of plant-based milks increased 61% between 2012 and 2017, with almond being the predominant beverage of choice holding 64% of market share, followed by soy (13%) and coconut (12%). New plant-derived dairy alternatives are experiencing fast growth including pecan and quinoa milk (Mintel Citation 2018 ) and the recent popularity of cashew milk and macadamia nut milk confirms this as a category that continues to diversify. Globally, it is projected the value of plant-based dairy alternatives will grow from the USD 21.4 billion in 2020 to USD 36.7 billion by 2025 (Markets and Markets Citation 2020 ). Increases in plant-based milk sales align with increasing popularity of plant-based diets, a trend summarized in Janssen et al. ( Citation 2016 ). Additional factors for consuming plant-derived beverages include health benefits attributed to plant-based milks, adding to the traditional market of the lactose-intolerant. Despite rapid uptake in the market and a widespread expansion of the variety of products available, plant-based milks remain understudied (Mylan et al. Citation 2019 ).

Multiple factors impede the spread of milk alternatives. Consumer acceptance can be a challenge, as products have sensory characteristics which can be objectionable to some palates (Mäkinen et al. Citation 2016 ; Sethi, Tyagi, and Anurag Citation 2016 ). The digestibility of plant-derived alternatives is also an issue, particularly for milks derived from soy. Soy, like other legumes, contains high levels of oligosaccharides which are fermented by bacteria in the colon producing high levels of gas (Suarez et al. Citation 1999 ) and can cause major discomfort in some individuals. Some diets limit intake of soy and other highly fermentable foods (Tuck et al. Citation 2018 ). The difficulty of successfully introducing plant-based food substitutes reflects broader consumer hesitance to try new products (Fuentes and Fuentes Citation 2017 ). Some plant-based milks have achieved broader appeal due to improved qualities such as better texture and flavor. Fermentation techniques play a role as well; plant milk substitutes can be fermented to produce dairy-free yogurt-type products, rendering the raw material more palatable (Mäkinen et al. Citation 2016 ). Plant-based milks follow a form of innovation diffusion that involves a radically divergent product occupying a technological niche, described by Smith and Raven ( Citation 2012 ) as protected spaces for nurturing and learning processes. To succeed an innovation must eventually move beyond its protective niche. Such innovations must eventually challenge entrenched regimes where processes operate to maintain the status quo or restrict change to established trajectories (Mylan et al. Citation 2019 ).

While fermentation-derived dairy eschews many of the concerns around animal-derived dairy, there remain questions about how it will be perceived and understood. When faced with the question of cultured meat, Stephens ( Citation 2010 ) refrains from calling it “meat” but also does not think that it is not meat. Rather he argues that “the best description of in vitro meat is an ‘as-yet undefined ontological object’” (p. 400). Put another way, there is no common ontological meaning, as discourses (or shared narratives and political identities) surrounding cultured meat have yet to emerge, and we argue the same is true for fermentation-derived dairy. Despite already being available for sale, little discussion into what fermentation-derived dairy is or is not , has taken place. Given the diverse and growing variety of plant-based milks on the market today, it is likely fermentation-derived dairy may find a sizable niche in the beverage market, either as a plant-based milk, animal-derived milk, or a third category.

6.1. Cultural barriers to adaptation

Cultural factors are a barrier to the adoption of alternatives to certain high-value dairy products. Cheeses, for example, can carry deep cultural meaning. Cheese is highly local as it carries flavors specific to the breed of cow (or other ruminant) and to the forage. This tie to landscape is sometimes described in the language of terroir (Paxson Citation 2010b ) or alternatively as “the taste of place” (Trubek Citation 2008 ). In the case of cheese, terroir blends these qualities with the technique of the cheese maker; several cheeses have been listed as having Protected Designation of Origin or Traditional Specialty Guaranteed under EU rules. Barham ( Citation 2003 ) sums this up as “the interplay of human ingenuity and curiosity with the natural givens of a place” (131). Such projects create what Cook and Crang ( Citation 1996 ) call “geological knowledges” (140). It is not obvious whether terroir can be evoked by synthetic biology.

Dairy cheese has not always been grounded in cultural connections. As Paxson ( Citation 2010a ) explores, cheese moved from a product of farm life made largely by women to one of the first successful industrial food products. By the mid-twentieth century in North America most cheese was free of local grounding; only in the last few decades has cheese become an artisanal product. Fonte ( Citation 2008 ) argues that globalization has spurred the popularity of local production of foods such as cheeses.

Regional grounding can be a powerful tool for marketing and branding. As Tellström, Gustafsson, and Mossberg ( Citation 2006 ) explore, association with regional origin can be an attractive way to interest urban consumers in new food products, and these links often reflect urban ideals of the countryside rather than reality. Place branding gives, in the words of Tellström, Gustafsson, and Mossberg ( Citation 2006 ), an authentic nimbus. This deep sense of attachment transcends age groups. As explored in Garanti and Berberoglu ( Citation 2018 ) post-millennials develop loyalty to products that carry good memories and are associated with strong identity elements fostering sense of belonging. This deep connection can and does override other concerns such as worry over animal welfare, social justice, and environmental impact. DeSoucey ( Citation 2010 ) describes this effect as “gastronationalism,” where a cultural attachment to a food can lead to protectionist action even in a globalizing world (432). Their example of foie gras in France’s culinary culture is relevant given that foie gras production has been banned in jurisdictions around the world over allegations of animal cruelty.

This said, terroir is fostered as a cultural artifact, and fermentation-derived cheeses are no exception. Paxson ( Citation 2010b ) gives the example of terroir in the US, and efforts of cheese makers to link their products to agrarian, environmental, social, and gastronomic values. They stress what their cheese isn’t: mass produced, placeless, and uniform. Szymanski ( Citation 2018 ) expands this concept to suggest a path forward for fermentation-derived cheese that embraces terroir. Humans can continue to cultivate our relationships with yeasts and bacteria in this new age. They suggest synthetic yeast can continue these connections as a microbial companion species. Szymanski ( Citation 2018 ) feels synthetic yeast products are part of “diverse geographies that coexisting humans and animals [or microorganisms] create” (43). Felder, Burns, and Chang ( Citation 2012 ) explore how the restaurant Momofuku is pushing the envelope of “microbial terroir.” This is also true of Noma, which runs a fermentation laboratory. Microbial terroir might play a part in the evolution of these products.

6.2. Other barriers to adaptation: lessons from plant-based milk substitutes

Responses from dairy industry groups to plant-derived dairy have varied, including pushes for tighter regulation on naming conventions, court challenges, and proactive efforts to counter-narratives of animal cruelty and environmental damage (Mylan et al. Citation 2019 ). These include incremental improvement strategies such as changes in management practices (e.g. more efficient feeding regimes), new breeding technologies, and agroecological production (Mylan et al. Citation 2015 ). Traditionally, the place of dairy in official recommendations for healthy eating was a strong selling point, but this no longer resonates as strongly with cultural practices; for example, Canada’s recently amended food guide no longer includes a separate dairy section (Health Canada Citation 2019 ). Nevertheless, the liquid dairy milk system is still stabilized by long-standing associations with good health, and policy supports the industry in some countries through subsidies and other protections.

Dairy supporters and some government bodies have attempted to differentiate plant-based dairy products through legislation, a process that has been limited in its success. At the urging of EU representatives, the intergovernmental Codex Alimentarius Commission regulations have recommended against allowing milk substitutes to use the term “milk” (Sethi, Tyagi, and Anurag Citation 2016 ). European Union law prohibits the use of the word milk for drinks not made from mammary secretions. Council Regulation 1234/2007 specifies “the term milk shall mean exclusively the normal mammary secretions obtained from one or more milkings” (Sethi, Tyagi, and Anurag Citation 2016 ). Coconut milk and almond milk are exempted from these rules.

In the U.S., efforts to protect dairy terms began in earnest at the beginning of the 21 st century when the National Milk Producers lobbied the Food and Drug Administration to control milk product language. The FDA currently defines milk as “the lacteal secretion, practically free from colostrum, obtained by the complete milking of one or more healthy cows” (Gambert and Linné Citation 2018 ), a definition that is out of date. In January 2017, Wisconsin senator Tammy Baldwin introduced the Dairy Pride Act, which would update the U.S. Code’s section on “misbranded food” to prohibit plant-based products from using terms such as “milk,” “yogurt” or “cheese,” and also update the definition of milk to include a broader range of species (Gambert and Linné Citation 2018 ). The Act was passed in an omnibus bill in March 2018, but beforehand received significant pushback from organizations including PETA (Wisconsin State Farmer Citation 2018 ), and the Good Food Institute (Byrd Citation 2017 ). This is unsurprising considering the FDA defines plant-based alternatives to milk as “nutritionally inferior” and closely regulates the placement of plant-based milks in stores, requiring them to be separated by a partition from traditional dairy products (Sethi, Tyagi, and Anurag Citation 2016 ).

In some cases, court actions against the use of the term “milk” are unsuccessful, such as Gitson v. Trader Joe’s Co . (Gambert and Linné Citation 2018 ). In other cases, lawsuits created unintended consequences. The Swedish Dairy Lobby (LRF Mjolk) successfully sued plant-based milk manufacturer Oatly in 2014 for using the term milk and claiming dairy is unhealthy (Mylan et al. Citation 2019 ), but publicity from the lawsuit boosted Oatly sales by 45% (Phair Citation 2015 ). Gambert and Linné ( Citation 2018 ) suggest that efforts to win the “milk wars” through legislation are unlikely to succeed, as “The reality is that despite legal restrictions and prevailing dictionary definitions, the word ‘milk’ is today culturally very much associated with plant-based drinks in the vernacular in the United States, the European Union, Australia, New Zealand, and elsewhere” (6). They suggest, perhaps tongue in cheek, that changing one letter (mylk) might thwart such efforts. Some elements of the plant-based milk story will likely be repeated with the rise of fermentation-derived dairy.

Definitions of milk as derived from lacteal secretions have impacted other dairy products including cheese. A small vegan cheese shop in Vancouver, BC, for example, was informed by the Canadian Food Inspection Agency that they could no longer label products as “cheese,” or use labels with hyphenated modifiers such as “dairy-free vegan cheese” (Nelms Citation 2019 ). For small- and medium-sized businesses, complying with these regulations generates a large financial burden, including redesigning labels, which for one small business, cost approximately 8,000 USD CAD (Nelms Citation 2019 ). While these small- and medium-sized businesses may not have the legal resources to challenge regulatory demands, larger companies, such as Perfect Day, may have more success challenging naming conventions, which could benefit smaller producers.

In addition to naming and labeling challenge, dairy produced through fermentation-derived processes raises several additional policy questions on land use, imports/exports, and production regulation. In the U.S. and Canada, many jurisdictions have strict regulations on what activities can occur on land zoned agricultural (Bunce Citation 1998 ; Newman, Powell, and Wittman Citation 2015 ). Food and beverage processing, in particular fermentation activities such as beer brewing, have been flashpoints for debates over farm land use in recent years (Powell Citation 2017 ; Shore Citation 2017 ) in these jurisdictions where land for both traditional agriculture and industry is limited and commands high dollar values when sold. For example, in British Columbia, storing, packing, preparing, or processing may only occur on land in the Agricultural Land Reserve (ALR) if at least 50% of the farm product being stored, packed, prepared, or processed is either produced on the farm; produced through a cooperative to which the farm owner belongs; or feed required for the farm’s production (Agricultural Land Commission Act Citation 2016a ). Alcohol production facilities, which include breweries, wineries, distilleries, cideries, and meaderies, can be located on an ALR parcel if at least 50% of the primary farm product ingredients used are raised either on the parcel or elsewhere in British Columbia, with specific provisions for parcel size and contract durations (Agricultural Land Commission Act, Citation 2016b ). Production of fermentation-derived dairy will generate new questions for policymakers, including whether the process is classified as suitable for locating on agricultural land, and if so, any geographic stipulations surround ingredient supply.

Production and distribution of dairy products in some jurisdictions are also part of systems which involve marketing boards, quotas, and subsidies. In Canada, for example, this system is called “supply management,” which was implemented through a series of policies in the 1960s and 1970s (Skogstad Citation 2008 ; Tamilia and Charlebois Citation 2007 ). Supply management includes controlled production, price setting, and restrictions and tariffs on imports for both fluid milk (consumed as beverages) and industrial milk (used to make other products, such as cheese, butter, and milk powder). Fluid milk is regulated provincially, while industrial milk is regulated federally (Gambling Citation 2016 ). Commercial availability of fermentation-derived milk, cheese, and other dairy products will require policymakers and stakeholders to consider if and how they fit into systems like supply management. Consultations with policy experts and others in the dairy industry are part of ongoing research into social implications of the introduction of fermentation-derived dairy products into the food market.

Fermentation-derived dairy is a new application of an old technology, which holds the potential to disrupt conventional dairy by providing an alternative to animal dairy, alongside plant-derived alternatives. While the scholarly literature on fermentation-derived dairy is still emerging, we can begin to understand the landscape surrounding the application of cellular agriculture technology by examining existing literature on cultured meat. Similarly, we can draw from the example of plant-derived alternatives to help inform potential regulatory responses, including issues over naming and classification.

Fermentation-derived dairy warrants attention given the relative ease with which it is made and its current availability in the U.S. Emerging areas of research surrounding fermentation-derived dairy include questions of land use, challenges around policy and regulation, and consumer acceptance as an alternative to culturally embedded dairy products.

This work was supported by Genome British Columbia under Grant SOC008 as well as by the Food and Agriculture Institute at the University of the Fraser Valley.

No potential conflict of interest was reported by the authors.

Notes on contributors

Zsofia mendly-zambo.

Zsofia Mendly-Zambo , MSc, is a PhD Candidate in the Health, Policy & Equity program at York University, School of Health Policy and Management. Her research focuses on various aspects of food policy in relation to health.

Lisa Jordan Powell

Lisa Jordan Powell is Associate Professor of Environmental Studies and Director of the Center for Human and Environmental Sustainability at Sweet Briar College.  She is also a Research Associate of the Food and Agriculture Institute of the University of the Fraser Valley. Her research focuses on agricultural land use, adoption of new technologies in the agri-food sector, food literacy education, and strengthening regional food systems.

Lenore L. Newman

Lenore Newman , PhD, is Director of the Food and Agriculture Institute at the University of the Fraser Valley and holds a Canada Research Chair in Food Security and the Environment. Her research focuses on agricultural land use, agricultural technology, and regional food cultures.

• Agricultural Land Commission Act. 2016a. “Agricultural Land Reserve Use, Subdivision and Procedure Regulation (BC Reg.171/2002), Section 2(1.1) And (2)(c) and Section 1 (1).” https://www.alc.gov.bc.ca/assets/alc/assets/legislation-and-regulation/policies/alc_-_policy_l-01_-_farm_product_processing.pdf   Google Scholar
• Agricultural Land Commission Act. 2016b. “Agricultural Land Reserve Use, Subdivision and Procedure Regulation (BC Reg. 171/2002), Sections 2 (1.1), (2.1) And 2 (2.4) And Section 1 (1).” https://www.alc.gov.bc.ca/assets/alc/assets/legislation-and-regulation/policies/alc_-_policy_l-03_-_alcohol_production_facilities.pdf   Google Scholar
• Barham, E. 2003. “Translating Terroir: The Global Challenge of French AOC Labeling.” Journal of Rural Studies 19 ( 1 ): 127–138. doi: https://doi.org/10.1016/S0743-0167(02)00052-9 .   Web of Science ® Google Scholar
• Baskaran, R., R. Cullen, and S. Colombo. 2009. “Estimating Values of Environmental Impacts of Dairy Farming in New Zealand.” New Zealand Journal of Agricultural Research 52 ( 4 ): 377–389. doi: https://doi.org/10.1080/00288230909510520 .   Web of Science ® Google Scholar
• Bekker, G. A., A. R. Fischer, H. Tobi, and H. C. Van Trijp. 2017. “Explicit and Implicit Attitude toward an Emerging Food Technology: The Case of Cultured Meat.” Appetite 108 : 245–254. doi: https://doi.org/10.1016/j.appet.2016.10.002 .   PubMed Web of Science ® Google Scholar
• Beus, C. E., and R. E. Dunlap. 1990. “Conventional versus Alternative Agriculture: The Paradigmatic Roots of the Debate.” Rural Sociology 55 ( 4 ): 590–616. doi: https://doi.org/10.1111/j.1549-0831.1990.tb00699.x .   Web of Science ® Google Scholar
• Bhat, Z. F., and H. Fayaz. 2011. “Prospectus of Cultured Meat—Advancing Meat Alternatives.„ Journal of Food Science and Technology 48 (2): 125–140.   Web of Science ® Google Scholar
• Bonny, S. P., G. E. Gardner, D. W. Pethick, and J.-F. Hocquette. 2015. “What Is Artificial Meat and What Does It Mean for the Future of the Meat Industry?” Journal of Integrative Agriculture 14 ( 2 ): 255–263. doi: https://doi.org/10.1016/S2095-3119(14)60888-1 .   Web of Science ® Google Scholar
• Bryant, C., and J. Barnett. 2018. “Consumer Acceptance of Cultured Meat: A Systematic Review.” Meat Science 143 : 8–17. doi: https://doi.org/10.1016/j.meatsci.2018.04.008 .   PubMed Web of Science ® Google Scholar
• Bryant, C., K. Szejda, N. Parekh, V. Deshpande, and B. Tse. 2019. “A Survey of Consumer Perceptions of Plant-Based and Clean Meat in the USA, India, and China.” Frontiers in Sustainable Food Systems 3 : 11. doi: https://doi.org/10.3389/fsufs.2019.00011 .   Google Scholar
• Bunce, M. 1998. “Thirty Years of Farmland Preservation in North America: Discourses and Ideologies of a Movement.” Journal of Rural Studies 14 ( 2 ): 233–247. doi: https://doi.org/10.1016/S0743-0167(97)00035-1 .   Web of Science ® Google Scholar
• Burton, R. J. 2019. “The Potential Impact of Synthetic Animal Protein on Livestock Production: The New “War against Agriculture”?” Journal of Rural Studies 68 : 33–45. doi: https://doi.org/10.1016/j.jrurstud.2019.03.002 .   Web of Science ® Google Scholar
• Byrd, E. 2017. “Dairy Pride Explained.” https://www.gfi.org/dairy-pride-explained   Google Scholar
• Cohen, S. N., A. C. Chang, H. W. Boyer, and R. B. Helling. 1973. “Construction of Biologically Functional Bacterial Plasmids in Vitro.” Proceedings of the National Academy of Sciences 70 ( 11 ): 3240–3244. doi: https://doi.org/10.1073/pnas.70.11.3240 .   PubMed Web of Science ® Google Scholar
• Cole, M., and K. Morgan. 2013. “Engineering Freedom? A Critique of Biotechnological Routes to Animal Liberation.” Configurations 21 ( 2 ): 201–229. doi: https://doi.org/10.1353/con.2013.0015 .   Web of Science ® Google Scholar
• Compton, N. 2016. “This Startup Is Making Dairy Milk Without Cows.” https://www.vice.com/en_us/article/vvq33j/this-startup-is-making-dairy-milk-without-cows   Google Scholar
• Cook, I., and P. Crang. 1996. “The World on a Plate: Culinary Culture, Displacement and Geographical Knowledges.” Journal of Material Culture 1 ( 2 ): 131–153. doi: https://doi.org/10.1177/135918359600100201 .   Web of Science ® Google Scholar
• Croney, C., and R. Anthony. 2011. “Invited Review: Ruminating Conscientiously: Scientific and Socio-ethical Challenges for US Dairy Production.” Journal of Dairy Science 94 ( 2 ): 539–546. doi: https://doi.org/10.3168/jds.2010-3627 .   PubMed Web of Science ® Google Scholar
• Datar, I., E. Kim, and G. d’Origny. 2016. “New Harvest: Building the Cellular Agriculture Economy.” In The Future of Meat without Animals , edited by B. Donaldson and C. Carter, 121–131. London: Rowman & Littlefield.   Google Scholar
• Datar, I., and M. Betti. 2010. “Possibilities for an in Vitro Meat Production System.” Innovative Food Science & Emerging Technologies 11 ( 1 ): 13–22. doi: https://doi.org/10.1016/j.ifset.2009.10.007 .   Web of Science ® Google Scholar
• Davis, F. D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly 13 ( 3 , September): 319–339. doi: https://doi.org/10.2307/249008 .   Web of Science ® Google Scholar
• DeSoucey, M. 2010. “Gastronationalism: Food Traditions and Authenticity Politics in the European Union.” American Sociological Review 75 ( 3 ): 432–455. doi: https://doi.org/10.1177/0003122410372226 .   Web of Science ® Google Scholar
• Dilworth, T., and A. McGregor. 2015. “Moral Steaks? Ethical Discourses of in Vitro Meat in Academia and Australia.” Journal of Agricultural & Environmental Ethics 28 ( 1 ): 85–107. doi: https://doi.org/10.1007/s10806-014-9522-y .   Web of Science ® Google Scholar
• Douphrate, D. I., G. R. Hagevoort, M. W. Nonnenmann, C. Lunner Kolstrup, S. J. Reynolds, M. Jakob, and M. Kinsel. 2013. “The Dairy Industry: A Brief Description of Production Practices, Trends, and Farm Characteristics around the World.” Journal of Agromedicine 18 ( 3 ): 187–197. doi: https://doi.org/10.1080/1059924X.2013.796901 .   PubMed Web of Science ® Google Scholar
• Egolf, A., C. Hartmann, and M. Siegrist. 2019. “When Evolution Works against the Future: Disgust’s Contributions to the Acceptance of New Food Technologies.” Risk Analysis 39 ( 7 ): 1546–1559. doi: https://doi.org/10.1111/risa.13279 .   PubMed Web of Science ® Google Scholar
• FAO. 2019. Dairy Market Review . Rome: Food and Agriculture Organization of the United Nations.   Google Scholar
• Felder, D., D. Burns, and D. Chang. 2012. “Defining Microbial Terroir: The Use of Native Fungi for the Study of Traditional Fermentative Processes.” International Journal of Gastronomy and Food Science 1 ( 1 ): 64–69. doi: https://doi.org/10.1016/j.ijgfs.2011.11.003 .   Google Scholar
• Flett, R., F. Alpass, S. Humphries, C. Massey, S. Morriss, and N. Long. 2004. “The Technology Acceptance Model and Use of Technology in New Zealand Dairy Farming.” Agricultural Systems 80 ( 2 ): 199–211. doi: https://doi.org/10.1016/j.agsy.2003.08.002 .   Web of Science ® Google Scholar
• Fonte, M. 2008. “Knowledge, Food and Place. A Way of Producing, A Way of Knowing.” Sociologia Ruralis 48 ( 3 ): 200–222. doi: https://doi.org/10.1111/j.1467-9523.2008.00462.x .   Web of Science ® Google Scholar
• Frewer, L. J., K. Bergmann, M. Brennan, R. Lion, R. Meertens, G. Rowe, M. Siegrist, and C. Vereijken. 2011. “Consumer Response to Novel Agri-food Technologies: Implications for Predicting Consumer Acceptance of Emerging Food Technologies.” Trends in Food Science & Technology 22 ( 8 ): 442–456. doi: https://doi.org/10.1016/j.tifs.2011.05.005 .   Web of Science ® Google Scholar
• Fuentes, C., and M. Fuentes. 2017. “Making a Market for Alternatives: Marketing Devices and the Qualification of a Vegan Milk Substitute.” Journal of Marketing Management 33 ( 7–8 ): 529–555. doi: https://doi.org/10.1080/0267257X.2017.1328456 .   Web of Science ® Google Scholar
• Galusky, W. 2014. “Technology as Responsibility: Failure, Food Animals, and Lab-grown Meat.” Journal of Agricultural & Environmental Ethics 27 ( 6 ): 931–948. doi: https://doi.org/10.1007/s10806-014-9508-9 .   Web of Science ® Google Scholar
• Gambert, I., and T. Linné 2018. “Got Mylk? The Disruptive Possibilities of Plant Milk.”   Google Scholar
• Gambling, S. J. 2016. “Canadian Supply Management: A Food Sovereignty Policy?: British Columbia and New Zealand Industry Stakeholder Perspectives on Dairy Policy in a Neoliberal Era.” MSc Thesis, University of British Columbia.   Google Scholar
• Garanti, Z., and A. Berberoglu. 2018. “Cultural Perspective of Traditional Cheese Consumption Practices and Its Sustainability among Post-Millennial Consumers.” Sustainability 10 ( 9 ): 3183. doi: https://doi.org/10.3390/su10093183 .   Web of Science ® Google Scholar
• Garg, S. K., and B. N. Johri. 1994. “Rennet: Current Trends and Future Research.” Food Reviews International 10 ( 3 ): 313–355. doi: https://doi.org/10.1080/87559129409541005 .   Web of Science ® Google Scholar
• Gerber, P. J., H. Steinfeld, B. Henderson, A. Mottet, C. Opio, J. Dijkman, … G. Tempio. 2013. Tackling Climate Change through Livestock: A Global Assessment of Emissions and Mitigation Opportunities. Rome: Food and Agriculture Organization of the United Nations (FAO).   Google Scholar
• Gladwell, M. 1990. “FDA Approves Bioengineered Cheese Enzyme.” Washington Post . https://www.washingtonpost.com/archive/politics/1990/03/24/fda-approves-bioengineered-cheese-enzyme/c4292eeb-1c74-45d2-94c3-b0eb09e4866c/?noredirect=on&utm_term=.fdfe4eaf6aa9   Google Scholar
• Goldstein, D., and S. Mintz. 2015. The Oxford Companion to Sugar and Sweets . New York: Oxford University Press.   Google Scholar
• Graham, A. 2014. “Real Vegan Cheese.” https://www.indiegogo.com/projects/real-vegan-cheese -/   Google Scholar
• Hagemann, M., A. Ndambi, T. Hemme, and U. Latacz-Lohmann. 2012. “Contribution of Milk Production to Global Greenhouse Gas Emissions.” Environmental Science and Pollution Research 19 ( 2 ): 390–402. doi: https://doi.org/10.1007/s11356-011-0571-8 .   PubMed Web of Science ® Google Scholar
• Health Canada. 2019. “Canada’s Food Guide.” https://food-guide.canada.ca/en/   Google Scholar
• Hocquette, A., C. Lambert, C. Sinquin, L. Peterolff, Z. Wagner, S. P. F. Bonny, A. Lebert, and J.-F. Hocquette. 2015. “Educated Consumers don’t Believe Artificial Meat Is the Solution to the Problems with the Meat Industry.” Journal of Integrative Agriculture 14 ( 2 ): 273–284. doi: https://doi.org/10.1016/S2095-3119(14)60886-8 .   Web of Science ® Google Scholar
• Hocquette, J.-F. 2016. “Is in Vitro Meat the Solution for the Future?” Meat Science 120 : 167–176. doi: https://doi.org/10.1016/j.meatsci.2016.04.036 .   PubMed Web of Science ® Google Scholar
• Hopkins, P. D., and A. Dacey. 2008. “Vegetarian Meat: Could Technology Save Animals and Satisfy Meat Eaters?” Journal of Agricultural & Environmental Ethics 21 ( 6 ): 579–596. doi: https://doi.org/10.1007/s10806-008-9110-0 .   Web of Science ® Google Scholar
• Janssen, M., C. Busch, M. Rödiger, and U. Hamm. 2016. “Motives of Consumers following a Vegan Diet and Their Attitudes Towards Animal Agriculture.” Appetite 105 : 643–651. doi: https://doi.org/10.1016/j.appet.2016.06.039 .   PubMed Web of Science ® Google Scholar
• Kadim, I. T., O. Mahgoub, S. Baqir, B. Faye, and R. Purchas. 2015. “Cultured Meat from Muscle Stem Cells: A Review of Challenges and Prospects.” Journal of Integrative Agriculture 14 ( 2 ): 222–233. doi: https://doi.org/10.1016/S2095-3119(14)60881-9 .   Web of Science ® Google Scholar
• Lagrange, V., D. Whitsett, and C. Burris. 2015. “Global Market for Dairy Proteins.” Journal of Food Science 80 ( S1 ): A16–A22. doi: https://doi.org/10.1111/1750-3841.12801 .   PubMed Google Scholar
• Mäkinen, O. E., V. Wanhalinna, E. Zannini, and E. K. Arendt. 2016. “Foods for Special Dietary Needs: Non-dairy Plant-based Milk Substitutes and Fermented Dairy-type Products.” Critical Reviews in Food Science and Nutrition 56 ( 3 ): 339–349. doi: https://doi.org/10.1080/10408398.2012.761950 .   PubMed Web of Science ® Google Scholar
• Mancini, M. C., and F. Antonioli. 2019. “Exploring Consumers‘ Attitude Towards Cultured Meat in Italy.” Meat Science 150 : 101–110. doi: https://doi.org/10.1016/j.meatsci.2018.12.014 .   PubMed Web of Science ® Google Scholar
• Markets and Markets. 2020. “Dairy Alternatives Market by Source (Soy, Almond, Coconut, Rice, Oats, Hemp), Application (Milk, Cheese, Yogurt, Ice Creams, Creamers), Distribution Channel (Supermarkets, Health Stores, Pharmacies), Formulation and Region – Global Forecast to 2025.” https://www.marketsandmarkets.com/Market-Reports/dairy-alternative-plant-milk-beverages-market-677.html   Google Scholar
• Martin, G., and M. Willaume. 2016. “A Diachronic Study of Greenhouse Gas Emissions of French Dairy Farms according to Adaptation Pathways.” Agriculture, Ecosystems & Environment 221 : 50–59. doi: https://doi.org/10.1016/j.agee.2016.01.027 .   Web of Science ® Google Scholar
• Mattick, C. S. 2018. “Cellular Agriculture: The Coming Revolution in Food Production.” Bulletin of the Atomic Scientists 74 ( 1 ): 32–35. doi: https://doi.org/10.1080/00963402.2017.1413059 .   Web of Science ® Google Scholar
• Milburn, J. 2016. “Chewing over in Vitro Meat: Animal Ethics, Cannibalism and Social Progress.” Res Publica 22 ( 3 ): 249–265. doi: https://doi.org/10.1007/s11158-016-9331-4 .   Google Scholar
• Milburn, J. 2018. “Death-free Dairy? The Ethics of Clean Milk.” Journal of Agricultural & Environmental Ethics 31 ( 2 ): 261–279. doi: https://doi.org/10.1007/s10806-018-9723-x .   Web of Science ® Google Scholar
• Miller, J. 2012. “In Vitro Meat: Power, Authenticity and Vegetarianism.” Journal for Critical Animal Studies 10 (4): 41–63.   Google Scholar
• Mintel. 2018. “US Non-dairy Milk Sales Grow 61% over the Last Five Years [Press Release].” https://www.mintel.com/press-centre/food-and-drink/us-non-dairy-milk-sales-grow-61-over-the-last-five-years   Google Scholar
• Mintel. 2019. “Milking the Vegan Trend: A Quarter (23%) of Brits Use Plant-based Milk [Press Release].” https://www.mintel.com/press-centre/food-and-drink/milking-the-vegan-trend-a-quarter-23-of-brits-use-plant-based-milk   Google Scholar
• Mouat, M. J., and R. Prince. 2018. “Cultured Meat and Cowless Milk: On Making Markets for Animal-free Food.” Journal of Cultural Economy  11 (4): 1–15.   Web of Science ® Google Scholar
• Mylan, J., C. Morris, E. Beech, and F. W. Geels. 2019. “Rage against the Regime: Niche-regime Interactions in the Societal Embedding of Plant-based Milk.” Environmental Innovation and Societal Transitions  31: 233–247.   Web of Science ® Google Scholar
• Mylan, J., F. Geels, S. Gee, A. McMeekin, and C. Foster. 2015. “Eco-innovation and Retailers in Milk, Beef and Bread Chains: Enriching Environmental Supply Chain Management with Insights from Innovation Studies.” Journal of Cleaner Production 107 : 20–30. doi: https://doi.org/10.1016/j.jclepro.2014.09.065 .   Web of Science ® Google Scholar
• Nelms, B. 2019. “Vegan Food Producer Ordered to Drop the Word ‘Cheese’ from Its Marketing.” The Globe & Mail . https://www.theglobeandmail.com/amp/business/small-business/marketing/article-vegan-food-producer-ordered-to-drop-the-word-cheese-from-its/   Google Scholar
• Newman, L., L. J. Powell, and H. Wittman. 2015. “Landscapes of Food Production in Agriburbia: Farmland Protection and Local Food Movements in British Columbia.” Journal of Rural Studies 39 : 99–110. doi: https://doi.org/10.1016/j.jrurstud.2015.03.006 .   Web of Science ® Google Scholar
• Nielsen, J. 2013. “Production of Biopharmaceutical Proteins by Yeast: Advances through Metabolic Engineering.” Bioengineered 4 ( 4 ): 207–211. doi: https://doi.org/10.4161/bioe.22856 .   PubMed Web of Science ® Google Scholar
• Nunavut Bureau of Statistics. 2015. “Nunavut Food Price Survey, CANSIM 326-0012.” https://assets.documentcloud.org/documents/2900528/2016-Nunavut-Food-Price-Survey-Comparison.pdf   Google Scholar
• O’Keefe, L., C. McLachlan, C. Gough, S. Mander, and A. Bows-Larkin. 2016. “Consumer Responses to a Future UK Food System.” British Food Journal 118 ( 2 ): 412–428. doi: https://doi.org/10.1108/BFJ-01-2015-0047 .   Web of Science ® Google Scholar
• Pandya, R. 2014. “Milk without the Moo.” New Scientist 222 ( 2975 ): 28–29. doi: https://doi.org/10.1016/S0262-4079(14)61260-4 .   Web of Science ® Google Scholar
• Paxson, H. 2010a. “Cheese Cultures: Transforming American Tastes and Traditions.” Gastronomica 10 ( 4 ): 35–47. doi: https://doi.org/10.1525/gfc.2010.10.4.35 .   Google Scholar
• Paxson, H. 2010b. “Locating Value in Artisan Cheese: Reverse Engineering Terroir for New-World Landscapes.” American Anthropologist 112 ( 3 ): 444–457. doi: https://doi.org/10.1111/j.1548-1433.2010.01251.x .   Web of Science ® Google Scholar
• Peeren, E., and I. Souch. 2019. “Romance in the Cowshed: Challenging and Reaffirming the Rural Idyll in the Dutch Reality TV Show Farmer Wants a Wife.” Journal of Rural Studies 67 : 37–45. doi: https://doi.org/10.1016/j.jrurstud.2019.02.001 .   Web of Science ® Google Scholar
• Perfect Day. 2018. “Perfect Day, ADM Sign JDA to Jointly Develop and Commercialize Animal-free Dairy Proteins.” http://www.perfectdayfoods.com/perfect-day-adm-sign-jda-to-jointly-develop-and-commercialize-animal-free-dairy-proteins/   Google Scholar
• Perfect Day. 2019. “Home.” http://www.perfectdayfoods.com/   Google Scholar
• Perfect Day. 2020, July 3rd 2019. “How It Works.” https://www.perfectdayfoods.com/how-it-works/   Google Scholar
• Phair, G. 2015. “Rise in Oat-based Milk Sales following Dairy Lobby’s Lawsuit.” https://thefuturescentre.org/signals-of-change/3779/rise-oat-based-milk-sales-following-dairy-lobby-s-lawsuit   Google Scholar
• Post, M. J. 2012. “Cultured Meat from Stem Cells: Challenges and Prospects.” Meat Science 92 ( 3 ): 297–301. doi: https://doi.org/10.1016/j.meatsci.2012.04.008 .   PubMed Web of Science ® Google Scholar
• Powell, L. 2017. “Changing Geographies of Beer and Hops in British Columbia’s Fraser Valley.” Paper Presented at the American Association of Geographers Annual Meeting, Boston, April 5.   Google Scholar
• Real Vegan Cheese. 2019. “Support Our Research!.” https://realvegancheese.org/?give_forms=735   Google Scholar
• Rojas-Downing, M. M., A. P. Nejadhashemi, T. Harrigan, and S. A. Woznicki. 2017. “Climate Change and Livestock: Impacts, Adaptation, and Mitigation.” Climate Risk Management 16 : 145–163. doi: https://doi.org/10.1016/j.crm.2017.02.001 .   Web of Science ® Google Scholar
• Rozin, P., M. Spranca, Z. Krieger, R. Neuhaus, D. Surillo, A. Swerdlin, and K. Wood. 2004. “Preference for Natural: Instrumental and Ideational/moral Motivations, and the Contrast between Foods and Medicines.” Appetite 43 ( 2 ): 147–154. doi: https://doi.org/10.1016/j.appet.2004.03.005 .   PubMed Web of Science ® Google Scholar
• Sethi, S., S. K. Tyagi, and R. K. Anurag. 2016. “Plant-based Milk Alternatives an Emerging Segment of Functional Beverages: A Review.” Journal of Food Science and Technology 53 ( 9 ): 3408–3423. doi: https://doi.org/10.1007/s13197-016-2328-3 .   PubMed Web of Science ® Google Scholar
• Shapiro, A. 2018. “Key Ingredient in ‘Impossible Burger’ Approved by FDA.” CNBC . https://www.cnbc.com/2018/07/24/key-ingredient-in-impossible-burger-approved-by-fda.html   Google Scholar
• Shore, R. 2017. “Province to Relax Rules for Farm-based Breweries.” Vancouver Sun . https://vancouversun.com/news/local-news/province-to-relax-rules-for-farm-based-breweries   Google Scholar
• Siegrist, M. 2008. “Factors Influencing Public Acceptance of Innovative Food Technologies and Products.” Trends in Food Science & Technology 19 ( 11 ): 603–608. doi: https://doi.org/10.1016/j.tifs.2008.01.017 .   Web of Science ® Google Scholar
• Skogstad, G. 2008. Internationalization and Canadian Agriculture: Policy and Governing Paradigms . Vol. 30. Toronto: University of Toronto Press.   Google Scholar
• Slade, P. 2018. “If You Build It, Will They Eat It? Consumer Preferences for Plant-based and Cultured Meat Burgers.” Appetite 125 : 428–437. doi: https://doi.org/10.1016/j.appet.2018.02.030 .   PubMed Web of Science ® Google Scholar
• Smith, A., and R. Raven. 2012. “What Is Protective Space? Reconsidering Niches in Transitions to Sustainability.” Research Policy 41 ( 6 ): 1025–1036. doi: https://doi.org/10.1016/j.respol.2011.12.012 .   Web of Science ® Google Scholar
• Smith-Howard, K. 2013. Pure and Modern Milk: An Environmental History since 1900 . New York: Oxford University Press.   Google Scholar
• Smitten Ice Cream. 2020. “NEW Smitten N’Ice Cream.” https://shop.smittenicecream.com/products/new-smitten-nice-cream-vegan-lactose-free-in-partnership-with-pefect-day   Google Scholar
• Steer, M. 2015. “A Comparison of Land, Water and Energy Use between Conventional and Yeast-derived Dairy Products: An Initial Analysis.” http://www.animalfreemilk.com/files/PD-LCA.pdf   Google Scholar
• Stephens, N. 2010. “In Vitro Meat: Zombies on the Menu.” SCRIPTed 7: 394.   Google Scholar
• Stephens, N., I. Dunsford, L. Di Silvio, M. Ellis, A. Glencross, and A. Sexton. 2018. “Bringing Cultured Meat to Market: Technical, Socio-political, and Regulatory Challenges in Cellular Agriculture.” Trends in Food Science & Technology  78: 155–166.   PubMed Web of Science ® Google Scholar
• Suarez, F. L., J. Springfield, J. K. Furne, T. T. Lohrmann, P. S. Kerr, and M. D. Levitt. 1999. “Gas Production in Humans Ingesting a Soybean Flour Derived from Beans Naturally Low in Oligosaccharides.” The American Journal of Clinical Nutrition 69 ( 1 ): 135–139. doi: https://doi.org/10.1093/ajcn/69.1.135 .   PubMed Web of Science ® Google Scholar
• Szymanski, E. A. 2018. “What Is the Terroir of Synthetic Yeast?” Environmental Humanities 10 ( 1 ): 40–62. doi: https://doi.org/10.1215/22011919-4385462 .   Web of Science ® Google Scholar
• Tamilia, R. D., and S. Charlebois. 2007. “The Importance of Marketing Boards in Canada: A Twenty-first Century Perspective.” British Food Journal 109 ( 2 ): 119–144. doi: https://doi.org/10.1108/00070700710725491 .   Web of Science ® Google Scholar
• Tan, K., K. Lee, A. Mohamed, and S. Bhatia. 2009. “Palm Oil: Addressing Issues and Towards Sustainable Development.” Renewable and Sustainable Energy Reviews 13 ( 2 ): 420–427. doi: https://doi.org/10.1016/j.rser.2007.10.001 .   Web of Science ® Google Scholar
• Tellström, R., I.-B. Gustafsson, and L. Mossberg. 2006. “Consuming Heritage: The Use of Local Food Culture in Branding.” Place Branding 2 ( 2 ): 130–143. doi: https://doi.org/10.1057/palgrave.pb.5990051 .   Google Scholar
• Thorning, T. K., A. Raben, T. Tholstrup, S. S. Soedamah-Muthu, I. Givens, and A. Astrup. 2016. “Milk and Dairy Products: Good or Bad for Human Health? An Assessment of the Totality of Scientific Evidence.” Food & Nutrition Research 60 ( 1 ): 32527. doi: https://doi.org/10.3402/fnr.v60.32527 .   PubMed Web of Science ® Google Scholar
• Trubek, A. B. 2008. The Taste of Place: A Cultural Journey into Terroir . Vol. 20. Berkeley, CA: Univ of California Press.   Google Scholar
• Tuck, C., E. Ly, A. Bogatyrev, I. Costetsou, P. Gibson, J. Barrett, and J. Muir. 2018. “Fermentable Short Chain Carbohydrate (FODMAP) Content of Common Plant-based Foods and Processed Foods Suitable for Vegetarian- and Vegan-based Eating Patterns.” Journal of Human Nutrition and Dietetics 31 ( 3 ): 422–435. doi: https://doi.org/10.1111/jhn.12546 .   PubMed Web of Science ® Google Scholar
• Tucker, C. A. 2014. “The Significance of Sensory Appeal for Reduced Meat Consumption.” Appetite 81 : 168–179. doi: https://doi.org/10.1016/j.appet.2014.06.022 .   PubMed Web of Science ® Google Scholar
• Tuomisto, H. L., P. F. Scheelbeek, Z. Chalabi, R. Green, R. D. Smith, A. Haines, and A. D. Dangour. 2017. “Effects of Environmental Change on Agriculture, Nutrition and Health: A Framework with A Focus on Fruits and Vegetables.” Wellcome Open Research 2: 1–31.   Google Scholar
• Valenze, D. 2011. Milk: A Local and Global History . Ann Arbor, MI: Yale University Press.   Google Scholar
• Van Der Weele, C., and J. Tramper. 2014. “Cultured Meat: Every Village Its Own Factory?” Trends in Biotechnology 32 ( 6 ): 294–296. doi: https://doi.org/10.1016/j.tibtech.2014.04.009 .   PubMed Web of Science ® Google Scholar
• Verbeke, W., P. Sans, and E. J. Van Loo. 2015. “Challenges and Prospects for Consumer Acceptance of Cultured Meat.” Journal of Integrative Agriculture 14 ( 2 ): 285–294. doi: https://doi.org/10.1016/S2095-3119(14)60884-4 .   Web of Science ® Google Scholar
• Watson, E. 2018. “Perfect Day Raises $24.7m In Series A Round to Commercialize Animal-free Dairy Ingredients.” Food Navigator USA . https://www.foodnavigator-usa.com/Article/2018/02/27/Perfect-Day-raises-24.7m-in-Series-A-round-to-commercialize-animal-free-dairy-ingredients   Google Scholar
• Wilks, M., and C. J. Phillips. 2017. “Attitudes to in Vitro Meat: A Survey of Potential Consumers in the United States.” PloS One 12 ( 2 ): e0171904. doi: https://doi.org/10.1371/journal.pone.0171904 .   PubMed Web of Science ® Google Scholar
• Wisconsin State Farmer. 2018. “PETA Campaigns against Dairy Pride Act.” Wisconsin State Farmer . https://www.wisfarmer.com/story/news/2018/06/06/peta-campaigns-against-dairy-pride-act/676041002/   Google Scholar
• Woods, M. 2011. Rural. New York: Routledge.   Google Scholar
• Back to Top

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations. Articles with the Crossref icon will open in a new tab.

• People also read
• Recommended articles

To cite this article:

Download citation, your download is now in progress and you may close this window.

• Choose new content alerts to be informed about new research of interest to you
• Easy remote access to your institution's subscriptions on any device, from any location
• Save your searches and schedule alerts to send you new results
• Export your search results into a .csv file to support your research

Login or register to access this feature

Register now or learn more

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• ADVERTISEMENT FEATURE Advertiser retains sole responsibility for the content of this article

How innovative research is improving dairy products

Produced by

Research in China is aimed at making dairy products moresustainable and enhancing their nutritional value. Credit: alvarez/E+/Getty

Dairy products are an important source of essential nutrients — such as protein, calcium and vitamins — and for many people are integral to a balanced diet. Though dairy products have been enjoyed for millennia, researchers in China now want to enhance their nutritional value and taste, improve their quality and meet changing needs of consumers.

It’s important to stimulate innovation throughout the industry,” says Fazheng Ren, a dairy scientist and member of the Chinese Academy of Engineering in Beijing, and also chair of the steering committee of science and technology for the National Centre of Technology Innovation for Dairy (NCTID).

One company leading the charge on dairy research is Yili Group, Asia’s biggest dairy corporation. Yili has 15 innovation centres across the world, employing more than 600 researchers. The company owns more than 100 proprietary technologies and has 4,348 patents covering a multitude of dairy innovations.

Far-reaching partnership

In 2022, Yili partnered with the government of the Inner Mongolia Autonomous Region of China to establish the NCTID. Based in the capital of Hohhot, NCTID was designed with a grand vision to pool resources and minds across more than 100 companies, universities and research institutes, bringing together more than 1,000 researchers and experts.

“In the past, almost every dairy company did research on its own. You can imagine the amount of duplicated research,” says food scientist and engineer, Jian He, who is the general manager of both the NCTID and Yili’s Innovation Centre.

Soon after its founding, the NCTID got to work and identified 20 research fields and 76 research directions aimed at achieving five strategic goals: high-yield dairy cattle breeding; low-carbon farming; high-value ingredients; innovative process and equipment; and the elevation of industry standards.

Probiotic preservation

One of many innovative topics that has emerged from the collaborative initiative is encapsulation, a technology to preserve probiotics in dairy products.

Dairy products are good carriers for probiotics, which are bacteria intended to health benefits when they are consumed via foods and supplements. The carbohydrates, proteins and fats in dairy products provide nutrients and protection to these bacteria as they pass through the gut.

However, probiotic bacteria can only remain viable in dairy products under specific conditions. For example, they can easily be lost when products are not kept cold.

“They have a low tolerance for heat and are sensitive to pressure applied during processing and handling,” says He.

One common method used by food scientists to preserve and protect probiotics is encapsulation. By packaging them up within a carrier material, they can be protected from degradation. NCTID researchers have developed an approach to encapsulate probiotic bacteria by using a complex water-in-oil-in-water (W/O/W) emulsion with a novel stabilizer.

Probiotic bacteria are protected within a water-in-oil-in-water encapsulating shell.

With the goal of helping preserve bacteria at room temperature, NCTID researchers, led by He, developed a new formulation for an encapsulating shell.

A two-film, and three-phase W/O/W emulsion — formed by dispersing water droplets covered by oil into water again — offers multilayer protection. Whey protein concentrate (WPC) and small quantities of pectin (a soluble fibre found in fruits) are then added to stabilize the emulsion.

The researchers tested the emulsion, using a common probiotic bacterium, Lacticaseibacillus rhamnosus , and found that the formulation results in an encapsulation efficiency of nearly 80%. Furthermore, they found that the bacteria were more likely to survive under stimulated conditions of pasteurization, gastrointestinal digestion and also storage at 4 °C for 28 days 1 .

“This technology creates a comfortable water-insulating microenvironment for probiotics and makes them much more resistant to heat, gastric acid and other mechanical forces,” explains He.

The company is now investigating the application of this technology to versions of its yoghurt, milk, milk-based beverages and other products which are stored at room temperature rather than in a refrigerator, He adds.

Dairy cattle breeding

Another important research goal of the NCTID is the breeding of improved, highly productive dairy cattle, and for this they are turning to technologies related to stem cells and gene editing.

Researchers are using IVF and gene editing to breed cattle with desired traits.

“We are working to improve the Holstein breeds of dairy cattle, which have outstanding milk production,” says Xihe Li, executive director of dairy breeding technology at the Dairy Breeding and Farming Technology Research Centre of the NCTID.

Li’s research team have developed ‘bovine expanded potential stem cells’ (bEPSCs), which they hope to modify with gene editing to produce cattle that are more productive and disease resistant 2 .

The researchers first selected high-quality cows and bulls to produce pre-implantation embryos, then used the inner cell mass — a mass of cells within the blastocyst in early development of an embryo — to produce bEPSCs. These stem cells have a high level of pluripotency, which means they can differentiate into many cell types.

“We are researching the application of gene editing to modify bEPSCs and get the desired genetic traits we are looking for in cattle,” says Li.

Li is also heading up other innovative initiatives, including establishing a big data platform for dairy cattle breeding and the use of artificial intelligence to monitor the health status of dairy cattle.

A synergistic future

Many of the new technologies developed via NCTID initiatives have already been applied to Yili’s products. For example, directed enzymatic digestion of milk fats technology, which uses specific enzymes to break down milk fat, has aided improvements to flavour and texture in Yili’s cheese and other products.

To meet the needs of consumers in different parts of the world, Yili has also been developing technologies to identify and evaluate local probiotic strains and has been developing lactose-free products for people who are lactose intolerant.

The National Centre of Technology Innovation for Dairy, in Hohhot, Inner Mongolia, was founded to foster dairy innovation in China.

To further globalize its research initiatives, the NCTID has now set up research centres at Wageningen University, in The Netherlands, and Lincoln University in New Zealand. In 2023, it also collaborated with AgResearch, a leading agricultural research institute in New Zealand, to launch the China–New Zealand Dairy Development Centre, which is working to support sustainable development of the dairy industry in both countries.

These types of collaborations with international enterprises and research institutions will make global innovation resources more accessible to NCTID members and partners, argues He.

“By joining forces between research and industry, we can create more innovative dairy products that will benefit public health,” adds Ren.

Contact us:

www.yili.com/en

National Centre of Technology Innovation for Dairy (NCTID)

www.nctid.cn

Liang, Z. et al. Int. J. Biol. Macromol 232 , 123477 (2023).

Article   PubMed   Google Scholar  

Zhao, L. et al. PNAS 118 (15), e2018505118 (2021).

Download references

Related Articles

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Dairy Technology

In subject area: Agricultural and Biological Sciences

Dairy husbandry involves the production of milk at the farm level, whereas dairy technology involves the conversion of milk to stable, wholesome, and sensorially desirable products.

From: Encyclopedia of Dairy Sciences (Second Edition) , 2011

Chapters and Articles

You might find these chapters and articles relevant to this topic.

P.F. Fox , in Encyclopedia of Dairy Sciences (Third Edition) , 2016

Society of Dairy Technology (UK)

Founded in 1943, the Society of Dairy Technology (SDT) is dedicated to the advancement of dairy science and technology to the mutual benefit of milk producers, dairy processors, food retailers and consumers. The SDT operates principally in the United Kingdom and the Republic of Ireland, but has members from other European countries and further afield. The history and highlights of the SDT are described in commemorative booklets published by the society to mark the 50th and 60th anniversaries in 1993 and 2003, respectively.

The SDT, in conjunction with Blackwell Publishing, publishes the International Journal of Dairy Technology (previously the Journal of the Society of Dairy Technology ) and a series of technological monographs, which have been revised recently. It also organizes formal meetings, symposia and conferences on scientific/technological matters related to the dairy industry and facilitates technological training and education in appropriate subjects. The SDT is an active member of the International Dairy Federation.

The society recognizes the work of its members in promoting the advancement of dairy technology and best practice in the industry by promoting prizes and awards to scientists and technologists working in the dairy field.

In Encyclopedia of Dairy Sciences (Third Edition) , 2022

Milk production and dairy science and technology have been popular research subjects since the early 20th century and are the subjects of a voluminous literature, including several textbooks on Dairy Chemistry, Dairy Microbiology, and Dairy Technology . The Encyclopedia of Dairy Sciences , first published in 2003 and now in its third edition, has become established as an authoritative compilation of this vast literature and has proven valuable to farmers, industry personnel, students, and researchers seeking a succinct introduction to the vast corpus of literature on dairy farming and milk processing. This third edition contains 516 articles covering the broad area of Dairy Science and Technology (Dairy Husbandry, Milk Production, Dairy Chemistry, Dairy Microbiology, Dairy Technology, Nutrition) and I hope it will prove as useful and become as respected as did earlier editions.

P.F. Fox , in Encyclopedia of Dairy Sciences (Third Edition) , 2022

Introduction

The developments in dairy technology described in the preceding article were made possible by advances in the chemistry of milk and its products, and many of the new processes and products were subject to defects or changes, which required chemical investigation. The technological and economic success of dairy processing operations depends on chemical analysis. The first part of this article will trace the development of methods for the chemical analysis of milk and dairy products while the second part will describe the isolation and characterization of the principal constituents of milk.

Hubert Roginski , ... Patrick F. Fox Editors , in Encyclopedia of Dairy Sciences , 2002

The science and practice of milk production (dairy farming) and processing ( dairy technology ), along with food regulations and dairy industry economics, constitute an integrated system that aims to ensure a sufficient supply of dairy products that are both nutritious and safe for human consumption.

NUCLEOSIDES AND NUCLEOTIDES IN MILK

D. Martin , ... D. Tait , in Encyclopedia of Dairy Sciences (Second Edition) , 2011

DAIRY EDUCATION | Dairy Technology . DAIRY FARM MANAGEMENT SYSTEMS | Goats ; DAIRY FARM MANAGEMENT SYSTEMS | Sheep . DEHYDRATED DAIRY PRODUCTS | Milk Powder: Types and Manufacture . MILK | Human Milk .

MILESTONE ACHIEVEMENTS IN DAIRY SCIENCE RESEARCH AND THEIR CURRENT AND FUTURE INDUSTRIAL APPLICATIONS

F.W. Bodyfelt , ... S.A. Rankin , in International Dairy Journal , 2008

The cost of operating duplicate curricula in both Dairy Processing (specialized) and Food Science and Technology (more generic) was all too obvious: too duplicative, too expensive, and an excess burden on University budgets. Hence, merging “ dairy technology ” into a broader curriculum of “food science [and technology]” became many a University's financial “survival mechanism”.

Other Relevant Societies

Although not devoted primarily to the dairy industry, there are several societies that have a major impact on dairy science and technology, some via a dedicated section. The following are, perhaps, the principal among such societies.

The Institute of Food Technology (IFT), probably the oldest society for general food science and technology (established in 1939), is based in the United States and Canada but has members throughout the world (total membership, ∼40   000); it has a strong role in dairy science and technology. The corresponding British institute is the Institute of Food Science and Technology, which has a lesser impact on dairy science and technology than the IFT. Many other countries have national institutes of food science and/or technology that have some impact on the local and perhaps the international dairy industry. As dairy science had evolved from chemistry, it is not surprising that chemical and biochemical societies play significant roles in the chemical aspects of dairy science, especially the American Chemical Society and the Royal Society for Chemistry. Microbiological societies generally are important in certain aspects of dairy science, especially the Society for General Microbiology, the Society for Applied Microbiology, and the societies related to public health. The British Association for Animal Science is active in dairy cattle husbandry and to a lesser extent in other aspects of dairy technology . Nutrition is an increasingly important aspect of dairy science, and the British Society for Nutrition and the American Society of Nutrition are particularly important.

R. Marsili , in Encyclopedia of Dairy Sciences (Third Edition) , 2022

Enzymes Exogenous to Milk in Dairy Technology : Proteinases ; Gas chromatography ; Lipolysis and Hydrolytic Rancidity ; Liquid Chromatography ; Packaging of Milk and Dairy Products: Labeling of Dairy Products ; Psychrotrophic Bacteria: Pseudomonas spp. ; Sensory Evaluation ; Yogurt: Role of Starter Culture ; Yogurt: Types and Manufacture

Technology transfer of some Moroccan traditional dairy products (lben, jben and smen) to small industrial scale

N Benkerroum , A.Y Tamime , in Food Microbiology , 2004

During the past five decades, scientific and technological progress, especially in the field of biotechnology, has lead to an accelerated industrialization of many food fermentations including dairy products. Currently, the industrialization of yoghurt, various types of cheeses including Gruyere, Emmental, Roquefort and Feta, and fermented milks such as Kefir and Buttermilk are well established; the following publications are recommended for further reading regarding aspects of dairy technology ( Robinson and Tamime, 1991 ; Fox, 1993 ; Kosikowski and Mistry, 1997 ; Law, 1997, 1999 ; Pisecky, 1997 ; Robinson and Wilbey, 1998 ; Early, 1998 ; Cheryan, 1998 ; Tamime and Robinson, 1999 ; APV, 2000 ; Tamime and Law, 2001 ). Such technologies use highly mechanized equipment and advanced automation for large-scale operations to ensure product safety, quality and standards so that the product(s) can be marketed internationally. Therefore, the transfer of these technologies is only possible for big companies and multi-national enterprises in developed countries that are able to make heavy investments.

Invited Review: Current state of wearable precision dairy technologies in disease detection*

E.A. Eckelkamp PAS , in Applied Animal Science , 2019

The primary objective of this review article is to provide insight into the role of wearable precision dairy technologies (WPDT) in detection of lameness, mastitis, metabolic disorders, and metritis.

This review is separated into 3 sections: overview of technology development; WPDT behavioral variables linked to disease; and WPDT detection of disease and disorders. Through Web of Science, Google Scholar, and SPAC (Searchable Proceedings of Animal Conferences, ADSA), 99 publications were identified that discuss WPDT that can be used for disease detection and associated similar abnormal behaviors.

Precision dairy technology is the real-time monitoring of animals through behavior monitoring, milk constituents, milk yield, video analysis, record analysis, and physiological monitoring. Technologies can be wearable, incorporated into the milking system, stand alone, or part of the management software. Real-time monitoring has the potential to improve individual cow management and overall farm efficiency. Wearable precision dairy technologies reside on or within the cow for some amount of time. These WPDT currently can measure an individual cow’s time spent at the feed bunk, rumination time, eating time, lying time, standing time, walking time, activity, lying-to-standing transitions, temperature, and rumen pH and provide a cow’s location. Recently, WPDT marketed for estrus detection were adapted for disease detection.

Conclusions and Applications

Potential does exist for WPDT disease detection. Technologies can identify changes in behavior associated with disease or disorders, although no technologies currently provide disease-specific alerts. Future studies should focus on incorporating multiple behavior, physiological, and herd records with machine-learning techniques to create timely, disease-specific alerts.

Related terms:

• Beta-Galactosidase
• Oligosaccharide
• Food Engineering
• Dairy Science
• Dairy Product
• Milk Protein

Dairy Processing: Advanced Research to Applications

• © 2020
• Jagrani Minj 0 ,
• Aparna Sudhakaran V 1 ,
• Anuradha Kumari 2

Department of Food Science and Technology, Nebraska Innovation Campus (NIC), University of Nebraska, Lincoln, USA

You can also search for this editor in PubMed   Google Scholar

Department of Dairy Microbiology, College of Dairy Science and Technology, Kerala Veterinary and Animal Sciences University, Thrissur, India

Dairy chemistry, guru angad dev veterinary and animal sciences university, ludhiana, india.

• Covers the basic facts and technologies involved in dairy processing
• Gives a comprehensive discussion on research methodology and application
• Discusses the problems associated with dairy processing from an economic perceptive

19k Accesses

32 Citations

1 Altmetric

This is a preview of subscription content, log in via an institution to check access.

Access this book

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime
• Available as EPUB and PDF
• Read on any device
• Instant download
• Own it forever
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

About this book

This book focuses on advanced research and technologies in dairy processing, one of the most important branches of the food industry. It addresses various topics, ranging from the basics of dairy technology to the opportunities and challenges in the industry. Following an introduction to dairy processing, the book takes readers through various aspects of dairy engineering, such as dairy-based peptides, novel milk products and bio-fortification. It also describes the essential role of microorganisms in the industry and ways to detect them, as well as the use of prebiotics, and food safety. Lastly, the book examines the challenges faced, especially in terms of maintaining quality across the supply chain. 

Covering all significant areas of dairy science and processing, this interesting and informative book is a valuable resource for post-graduate students, research scholars and industry experts.

Similar content being viewed by others

Emerging Technologies in Dairy Processing: Present Status and Future Potential

Diverse Role of Enzymes in Food and Dairy Industry

Dairy Products

• Dairy Technology
• Dairy Microbiology
• Dairy Chemistry
• Dairy Engineering
• Dairy Economics

Table of contents (17 chapters)

Front matter, basic facts about dairy processing and technologies.

• Aparna Sudhakaran V, Jagrani Minj

Non-thermal Processing of Dairy Foods

• K. G. Rashmi, Aswin S. Warrier

Dairy Engineering: A Keystone to the Dairy Industry

• Kesha D. Vankar

Advances in Dairy Engineering Research Across the Globe

• Aswin S. Warrier

Significance of Fortification of Beneficial Natural Ingredients in Milk and Milk Products

• Jagrani Minj, Sonam Dogra

Multifunctional Aspects of Probiotics and Prebiotics in Health Management: An Overview

• Kamna Saini, Jagrani Minj

Research-Based Biofunctional Aspects of Milk Protein-Derived Bioactive Peptides

• Suvartan Ranvir, Nancy Awasti, Pranali Nikam, Neelima Sharma

Whey: Importance and Techno-functional Applications

• Rita Mehla, Anuradha Kumari, Jyotika Dhankhar, Mitul Bumbadiya, Anuj Tyagi

Overcoming the Quality Challenges Across the Supply Chain

• C. H. Aysha, S. Athira

Application of Research Methodologies in Dairy Chemistry

• Anuradha Kumari, Niraj Kumar Singh, Sonika Choudhary, Dev Priya, Arpna Sharma

Approaches for Detection of Dairy Microorganisms: An Update

• Aparna Sudhakaran V, Santosh Anand

The Role of Yeast and Molds in Dairy Industry: An Update

• Nancy Awasti, Santosh Anand

Dairy Industry: Hurdles Ahead in an Economic Perspective

• Denny Franco, Bulbul G. Nagrale

Novel Milk and Milk Products: Consumer Perceptions

• Anuradha Kumari, Himanshi Solanki, Aparna Sudhakaran V

Novel Dairy-Based Drinks: Changing Scenario

• Swathi P. Anand, Nancy Awasti

Extending the Horizons of Dairying to the Common Man: An Indian Perspective

• Aiswarya S. Panicker, M. Misha Madhavan, Himanshi Solanki

Correction to: Dairy Processing: Advanced Research to Applications

• Jagrani Minj, Aparna Sudhakaran V, Anuradha Kumari

Editors and Affiliations

Jagrani Minj

Aparna Sudhakaran V

Anuradha Kumari

About the editors

Jagrani Minj, PhD  (Dairy Microbiology), is currently a Postdoctoral Research Scholar at the Department of Food Science and Technology, University of Nebraska Lincoln, NE, USA. She worked as a research associate and as a senior officer in the dairy industry for 9 months and 10 months, respectively. She has published a number of research papers, book chapters and technical articles. She has also received best oral presentation awards at conference. She holds a B. Tech. (Dairy Technology), and M. Tech. and PhD (Dairy Microbiology). During her professional career, she has received various prestigious fellowships, including an Indian Council of Agricultural Research-Junior Research Fellowship (ICAR-JRF), University Grant Commission-Rajiv Gandhi National Fellowship (UGC-RGNF), an institutional fellowship, and currently has a National Overseas Scholarship for her postdoctoral research work.

Aparna Sudhakaran V., PhD  (Dairy Microbiology), is an Assistant Professor of Dairy Microbiology at Kerala Veterinary and Animal Sciences University at the College of Dairy Science and Technology, Kerala, India. She has 6 years’ experience of teaching dairy microbiology at undergraduate and postgraduate levels. She is the recipient of numerous academic awards, including Gold Medal for B.Tech., Divisional Topper for M.Tech. and PhD; AIR-1 in the Entrance Examinations for PG and PhD; Fellowships like the DST-INSPIRE Fellowship, ICAR Senior Research Fellowship, ICAR Junior Research Fellowship and KAU Merit Scholarship. She also received the ICAR-sponsored ‘Best Teacher Award’ from the institution in 2016-17, as well as a ‘Young Investigator Award’ from the Probiotic Association of India (2018), best paper award for an article published in Indian Dairyman (2012), and 4 awards for best poster/oral paper presented at professional conferences.

Anuradha Kumari, PhD  (Dairy Chemistry), is an Assistant Professor of Dairy Chemistryat Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India. She holds a B. Tech (Dairy Technology), and M.Tech. and P.h D (Dairy Chemistry). She worked as a Senior Research Fellow for a year, and worked in the dairy industry for 10 months. Her research interests include functional foods, detection of artificial sweeteners, use of food by-products and product development. She has published more than 11 papers in leading national and international journals, as well as review articles, book chapters and popular-science articles, and she has also attended 8 international and national conferences. She is an editorial board member of various national and international research journals. She received an award for the best poster at a national conference.

Bibliographic Information

Book Title : Dairy Processing: Advanced Research to Applications

Editors : Jagrani Minj, Aparna Sudhakaran V, Anuradha Kumari

DOI : https://doi.org/10.1007/978-981-15-2608-4

Publisher : Springer Singapore

eBook Packages : Chemistry and Materials Science , Chemistry and Material Science (R0)

Copyright Information : Springer Nature Singapore Pte Ltd. 2020

Hardcover ISBN : 978-981-15-2607-7 Published: 11 April 2020

Softcover ISBN : 978-981-15-2610-7 Published: 11 April 2021

eBook ISBN : 978-981-15-2608-4 Published: 10 April 2020

Edition Number : 1

Number of Pages : XIX, 350

Number of Illustrations : 11 b/w illustrations, 15 illustrations in colour

Topics : Food Science , Biomedical Engineering/Biotechnology , Food Microbiology

• Publish with us

Policies and ethics

• Find a journal
• Track your research

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

The PMC website is updating on October 15, 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Sensors (Basel)
• PMC10458494

Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation

This technical note critically evaluates the transformative potential of Artificial Intelligence (AI) and sensor technologies in the swiftly evolving dairy livestock export industry. We focus on the novel application of the Internet of Things (IoT) in long-distance livestock transportation, particularly in livestock enumeration and identification for precise traceability. Technological advancements in identifying behavioral patterns in ‘shy feeder’ cows and real-time weight monitoring enhance the accuracy of long-haul livestock transportation. These innovations offer benefits such as improved animal welfare standards, reduced supply chain inaccuracies, and increased operational productivity, expanding market access and enhancing global competitiveness. However, these technologies present challenges, including individual animal customization, economic analysis, data security, privacy, technological adaptability, training, stakeholder engagement, and sustainability concerns. These challenges intertwine with broader ethical considerations around animal treatment, data misuse, and the environmental impacts. By providing a strategic framework for successful technology integration, we emphasize the importance of continuous adaptation and learning. This note underscores the potential of AI, IoT, and sensor technologies to shape the future of the dairy livestock export industry, contributing to a more sustainable and efficient global dairy sector.

1. Introduction

The dairy sector, a cornerstone of global economies, grapples with challenges such as disease control, animal welfare, and supply chain inefficiencies [ 1 ]. If unresolved, these issues could limit productivity and sustainability. The advent of Artificial Intelligence (AI) and advanced sensor technology is instigating paradigm shifts in traditional sectors, including the dairy livestock export industry [ 2 ]. These technologies promise to redefine the sector’s landscape [ 3 ] by promoting humane, efficient, and sustainable practices.

Exporting dairy livestock involves logistical and welfare challenges. Livestock are exposed to various stresses during long shipping durations, potentially compromising their health. Accurate livestock counting and ensuring there is sufficient feed during transit are major challenges. Given the increasing global demand for dairy products and livestock for breeding, it is imperative to improve livestock export procedures.

Precision digital livestock farming, underpinned by AI and sensor technology, offers innovative solutions to persisting issues in the dairy livestock export industry. These disruptive technologies facilitate real-time monitoring, proactive intervention, and data-driven decision making, promising enhanced animal welfare, productivity, and streamlined supply chain operations [ 4 , 5 ].

Traditional practices often falter in managing animals ( Figure 1 ), struggling to meet their nutritional needs due to a lack of assertiveness (shy feeders) in reaching feeding troughs in group feeding scenarios [ 6 , 7 , 8 ]. This behavioral pattern adversely impacts their health and productivity, leading to undernutrition, weight loss, decreased productivity, increased disease susceptibility, and, potentially, a shortened lifespan [ 9 , 10 ]. Current management methods have proven inadequate, underscoring the need for fresh approaches.

The livestock management process: traditional vs. AI and sensor-technology-powered.

Tracking individual animal weights, a crucial parameter of health and performance [ 11 , 12 ], along with accurate cattle counting during the export process [ 13 , 14 ], remains laborious, time consuming, and error prone when using conventional methods. These inaccuracies can lead to supply chain discrepancies, inducing financial losses and logistical complications.

Emerging AI and sensor technology bring forth a beacon of hope [ 15 , 16 ]. By enabling real-time monitoring and data analytics, they can address these concerns, thereby enhancing operational efficiency and animal welfare, crucial elements for the long-term sustainability of the dairy livestock export industry [ 17 ].

AI and sensor technology can automate the tracking of individual animal feeding behaviors [ 18 , 19 ], including their time spent near feeding troughs, feeding frequency, and intake [ 20 ]. These data, once analyzed using AI algorithms, can facilitate early interventions. Furthermore, these technologies assist in monitoring feeding behaviors—vital for livestock management—as they provide insights into animals’ health, productivity, and overall wellbeing. Systems typically employing RFID tags or smart collars can automate this process, offering real-time data [ 20 ]. These systems track proximity to feeding troughs, feeding frequency [ 21 ], and duration. Analyzing these data can alert farmers of anomalies, enabling early health issue detection [ 22 , 23 ], and aid in optimizing feed management, thereby enhancing productivity and sustainability.

This technical note aims to contribute to the evolution of a more sustainable, efficient, and humane dairy livestock export industry through a focused exploration of the Internet of Things (IoT), sensor, and Artificial Intelligence (AI) technologies. Central to our investigation are three key applications: managing feeding behaviors, automating livestock weight tracking, and improving cattle counting accuracy during transportation and traceability.

We delve into the broader implications of these technologies within the dairy livestock export sector. Our analysis encompasses the potential for advancements in animal welfare, operational efficiency, and market access and competitiveness. Concurrently, we address the challenges emerging from the adoption of these cutting-edge technologies, including data security, privacy, infrastructure demands, sensor data reliability, interpretability of AI insights, ethical considerations, and cost implications.

Subsequently, this note outlines a strategic roadmap for the seamless incorporation of these technologies, offering insights into the future trajectory of the sector. Ultimately, this note seeks to serve as a valuable resource for stakeholders within the dairy livestock export industry, enabling informed decision making and fostering innovation.

2. Application of AI and Sensor Technology in Livestock Management

Artificial Intelligence (AI) and sensor technologies are propelling industries into the future, and the dairy livestock export industry is no exception. As a sector steeped in tradition, this industry is beginning to feel the transformative impact of these advanced technologies ( Figure 2 ). AI and sensor technologies are not only changing the way farmers and exporters operate but also shaping the future trajectory of the industry.

Impact of AI and sensor technology on livestock welfare and productivity.

In any livestock population, certain animals stand out due to their lack of assertiveness in reaching feeding troughs, especially in group feeding scenarios. These animals, colloquially referred to as ‘shy feeders’, exhibit a lower food intake [ 15 ]. This behavior significantly impacts their health and productivity, often leading to undernutrition, weight loss, decreased productivity, a heightened susceptibility to diseases, and, in some instances, a reduced lifespan [ 16 , 17 ]. Shy feeder cows, those that eat less when in a group, can be at risk during the shipping process as they may not get enough nutrition.

Given these repercussions, the identification and effective management of shy feeders become pivotal. Historically, this issue has been addressed through manual observation and intervention, which is both time consuming and labor intensive, and not always accurate or timely. However, with the advent of AI and sensor technology, the management of shy feeders is poised for a significant shift. AI can be used to analyze behavioral patterns of livestock through video and motion sensors. This can help in identifying shy feeder cows and modifying the feeding strategies accordingly.

The role of monitoring feeding via AI and sensor technologies offers innovative solutions ( Table 1 ) to the challenges in livestock management, including identifying and managing animals with feeding difficulties [ 20 ]. These technologies automate the tracking of individual animal feeding behaviors, including their time spent near feeding troughs, feeding frequency, and intake. These data, when analyzed using AI algorithms, can assist in identifying animals with feeding difficulties, thereby facilitating early interventions [ 20 , 21 ].

Key applications of Artificial Intelligence and sensor technology in livestock management.

In addition, the role of monitoring feeding behaviors in livestock management provides invaluable insights into animals’ health, productivity, and overall wellbeing. AI and sensor-based systems revolutionize this aspect by offering real-time, automated monitoring capabilities [ 20 ]. These systems employ technologies such as RFID tags or smart collars to track various parameters, converting raw data into meaningful insights about the animals’ feeding behaviors [ 22 , 23 ]. By addressing long-standing challenges such as the optimization of feeding behavior, these technologies can significantly enhance animal welfare, streamline supply chain operations, and boost the dairy livestock export industry’s productivity and profitability [ 24 , 25 ].

Within the sphere of livestock management, the weight of an animal serves as a vital health and productivity barometer. Traditional methods of weight collection in livestock farming rely heavily on manual weighing, a labor-intensive, time-consuming, and error-prone process. AI and sensor technology emerge as game changers in this landscape, fostering an environment for automated data capture in livestock farming [ 25 , 26 ].

The use of AI and sensor technology provides revolutionary solutions ( Table 2 ) for streamlining operations in the livestock supply chain, from counting and tracking animals to predicting and optimizing the logistical routes [ 27 , 28 ]. RFID technology offers transformative potential in the field of automated cattle counting, a critical factor in disease control, inventory management, animal movement tracking, productivity enhancement, and livestock enterprise profitability [ 27 , 29 , 30 ]. Moreover, sensor technologies and AI algorithms, through real-time monitoring and predictive analytics, provide vital insights into every stage of the supply chain. Sensors tracking feed as well as water consumption, for instance, can signal potential health risks, prompting AI algorithms to forecast possible disease outbreaks and recommend preventative measures [ 31 , 32 ].

Impact of AI and sensor technology on supply chain management in livestock industry.

AI and sensor technology also extend their impact to market access and development in the livestock export industry. The traceability offered by RFID and AI technology can meet the stringent safety and quality standards of import markets, bolstering a country’s access to these markets [ 33 ]. Furthermore, AI can analyze sensor-generated data from various supply chain stages to discern valuable insights about market trends, consumer preferences, and price fluctuations, aiding strategic planning and market expansion efforts.

Overall, AI and sensor technologies offer boundless opportunities for operational efficiency, animal welfare enhancement, traceability assurance, and market access expansion in the livestock export industry. The onus now lies on livestock enterprises, policymakers, and researchers to foster an environment conducive to harnessing the potential of these technologies, bringing us closer to a future where every element of the livestock supply chain operates as a cog in a well-oiled machine, powered by AI and sensor technology.

3. Future Perspectives: AI and Sensor Technology in Livestock Management

3.1. identifying opportunities and overcoming challenges.

As we delve into the future of livestock management especially from a practical industry perspective, it is evident that the role of Artificial Intelligence (AI) and sensor technology is increasingly vital. Cutting-edge innovations such as sophisticated machine learning algorithms, expansive big data analytics, widespread Internet of Things (IoT) connectivity, and drone technology herald a new era in the realm of livestock farming.

Machine learning, for instance, has the potential to fine tune predictive analytics, delivering even more accurate and timely insights into animal health, productivity, and potential supply chain issues. The proliferation of IoT devices could facilitate an expansive real-time tracking and monitoring system for livestock, bringing critical data to the fingertips of farmers and industry stakeholders.

Nonetheless, these advancements come hand in hand with substantial challenges ( Figure 3 ). A key concern is the enormous volume of data generated by these technologies. While the depth of big data is invaluable, it necessitates substantial storage, processing capabilities, and advanced analytics tools to convert it into actionable intelligence [ 34 ]. Further, integrating these sophisticated technologies into current livestock management systems can prove complex, disruptive, and capital intensive, necessitating significant technical know-how.

The roadmap to a sustainable and competitive livestock industry with AI and sensor technology.

The issue of data privacy and security also looms large. With vast amounts of data collected and shared, there are legitimate apprehensions regarding the security and potential misuse of this information [ 35 ]. A heavy reliance on technology simultaneously heightens the risk of cyber-attacks, with potential repercussions for the entire livestock management system.

These challenges call for a well-rounded, strategic response [ 36 ]. Technological solutions such as robust data encryption, cloud storage, and improved analytical tools can help manage and secure the data avalanche. Concurrently, there is a pressing need to establish comprehensive regulatory frameworks to safeguard privacy rights and prevent data misuse.

3.2. Navigating towards a Sustainable and Competitive Livestock Sector

AI and sensor technology represent pivotal tools for steering the livestock industry towards a more sustainable and competitive future. By optimizing resource use, boosting productivity, and improving animal welfare, these technologies can catalyze a livestock industry that is economically robust, environmentally benign, and socially responsible.

For example, precise monitoring of animal health can mitigate the reliance on antibiotics, addressing a critical environmental and public health issue. Similarly, the efficient management of feed and water resources not only curtails costs but also minimizes waste and environmental degradation. Further, enhanced supply chain efficiency can strengthen competitiveness by reducing losses, elevating product quality, and ensuring punctual delivery. As the global demand for livestock products escalates, these efficiencies could provide a decisive advantage in the highly competitive international market.

Yet, realizing this vision necessitates a collaborative effort from all stakeholders. It requires a continuous investment in technology development and deployment, supportive policies, and robust public–private partnerships. Above all, it mandates a paradigm shift: technology must be perceived not merely as an instrument for augmenting productivity but as an indispensable tool for achieving sustainability and resilience.

3.3. Applied Informatics for Dairy Livestock Export: Overcoming Big Data Challenges for Real-Time Analytics and Sustainable Practices

In the swiftly transforming world of dairy livestock export, the quest for proficient analytics capable of a dynamic and automated processing of the temporal–spatial distribution of animals in real time has surfaced as a crucial necessity. This necessity stems from the increasing demand for efficiency, transparency, and sustainability in the livestock industry, driven by both market forces and societal expectations. The capacity to precisely track and forecast the movement and behavior of livestock in real time can dramatically augment operational efficiency, animal welfare, and overall productivity. It can also provide valuable insights into the health and well-being of the animals, thereby contributing to improved animal welfare standards and more sustainable farming practices.

However, the road to achieving this level of sophistication in livestock management analytics is laden with hurdles. The most formidable of these challenges are scalability and robustness. The enormous volume of data generated in real time from a myriad of sources, including GPS trackers, RFID tags, machine vision system cameras, and IoT sensors, can be daunting. This ‘big data’ scenario calls for scalable solutions that can efficiently process and analyze data on a colossal scale without compromising speed or accuracy.

The challenge of scalability is not just about handling large volumes of data, but also about integrating and making sense of diverse types of data. For instance, GPS data can provide information about the location and movement of animals, while data from IoT sensors can provide insights into their health status and environmental conditions. Integrating these diverse data sources and extracting meaningful insights from them requires sophisticated data processing and analytics capabilities.

Furthermore, the analytics solutions must exhibit robustness to deliver reliable predictions and insights in real time, under fluctuating conditions and potential system anomalies. This requires not only robust algorithms but also robust data infrastructure and data management practices. For instance, data quality issues, such as missing or erroneous data, can significantly impact the accuracy and reliability of analytics results. Therefore, robust data cleaning and data quality management practices are essential.

Traditional statistical techniques and machine learning approaches, such as decision trees or random forests, have been utilized in the past to analyze livestock data. While these methods have their merits, they may fall short in handling the complexity and scale of real-time, big data scenarios in the livestock export industry. These techniques often grapple with high-dimensional data and may not provide the level of accuracy required for real-time decision making.

In light of these limitations, there is a burgeoning consensus in the agrifood domain that advanced machine learning and deep learning approaches could be the panacea to these challenges. Deep learning, a subset of machine learning inspired by the structure and function of the human brain, has demonstrated remarkable success in handling high-dimensional data and delivering accurate predictions in various fields, including image recognition, natural language processing, and autonomous vehicles.

In the context of dairy livestock export, deep learning models could be trained to recognize patterns and make predictions based on a multitude of factors, including the spatial–temporal distribution of animals, their health status, environmental conditions, and market trends. These models could potentially provide more accurate and timely insights, enabling farmers and exporters to make better-informed decisions, optimize their operations, and ultimately, enhance the sustainability and profitability of their enterprises. However, the adoption of deep learning in the agrifood sector is not without its challenges. These include the need for large amounts of labeled training data, the complexity of model development and tuning, and the interpretability of model predictions. The need for large amounts of labeled training data can be particularly challenging, as it requires significant time and effort to collect and label data. Moreover, the complexity of model development and tuning requires specialized skills and expertise, which may not be readily available in the agrifood sector.

Moreover, the successful integration of deep learning models into the livestock management workflow would require significant investment in infrastructure, skills development, and change management. This includes not only the physical infrastructure for data storage and processing but also the software infrastructure for data management, model development, and deployment. Skills development is another critical aspect, as it requires the training and upskilling of staff to effectively use and manage the advanced analytics solutions. Change management, on the other hand, involves managing the organizational changes associated with the adoption of new technologies and practices.

In addition to these challenges, the interpretability of model predictions is another critical issue. Deep learning models, often referred to as ‘black boxes’, can make highly accurate predictions but may not provide clear explanations for their predictions. This lack of interpretability can be a significant barrier to the adoption of deep learning in the agrifood sector, where decision makers often need to understand the reasons behind the predictions to make informed decisions. Despite these challenges, the potential benefits of adopting advanced analytics and deep learning in dairy livestock export are immense. These benefits extend beyond improved operational efficiency and productivity to include enhanced animal welfare, more sustainable farming practices, and increased competitiveness in the global market. By providing real-time, accurate, and actionable insights, advanced analytics can enable farmers and exporters to make better-informed decisions, optimize their operations, and respond more effectively to market trends and changes.

Moreover, by improving the tracking and monitoring of animal health and welfare, advanced analytics can contribute to higher standards of animal welfare and more ethical farming practices. This, in turn, can enhance the reputation and brand value of dairy livestock exporters, making them more attractive to consumers and investors who value sustainability and animal welfare.

While the path towards advanced analytics in dairy livestock export is challenging, the potential benefits in terms of improved efficiency, animal welfare, and profitability make it a journey worth undertaking. As researchers, developers, and industry stakeholders continue to explore and innovate in this space, the future of dairy livestock export looks set to be increasingly data driven, intelligent, and sustainable. The journey towards this future will require not only technological innovation but also a collaboration and partnership among various stakeholders, including farmers, exporters, technology providers, researchers, and policymakers. By working together, these stakeholders can overcome the challenges and unlock the full potential of advanced analytics in dairy livestock export.

4. The Intersection of Sensor Technologies and Artificial Intelligence: A Closer Look

Sensor technologies and AI form a critical intersection in modern livestock management. Sensors provide a way to collect real-time data from livestock. The vast amounts of data collected can be overwhelming and seemingly chaotic, which is where AI steps in, decoding these massive data sets, identifying patterns, and providing actionable insights [ 37 ].

4.1. Sensor Technologies

Sensor technologies can be categorized into two types: wearable devices and environment-based sensors. Wearable sensors are devices attached directly to the animal. They may track physiological parameters (e.g., heart rate, body temperature), behavioral traits (e.g., feeding patterns, movement), and other relevant indicators of an animal’s health and welfare [ 38 ].

Environment-based sensors, on the other hand, monitor the conditions around the animals. These could include video cameras, thermal imaging sensors, accelerometers, load cells in feeding stations, and drones, among others. They can provide a wealth of information about the environment and how animals interact with it [ 39 ].

The application of sensor technologies in livestock management has opened new avenues for the in-depth monitoring of animals in ways that were previously impossible. However, there are challenges such as the durability of wearable devices, potential discomfort or injury to the animal, ensuring the devices stay on the animals, and the cost and complexity of installing and maintaining environment-based sensors [ 40 ].

4.2. Artificial Intelligence

AI is a broad field that encompasses machine learning, deep learning, computer vision, and more. It provides the capability to analyze and interpret the massive data sets collected by sensors. AI’s ability to ‘learn’ from data and make predictions makes it a powerful tool for decoding the vast array of livestock data [ 41 , 42 ].

In the context of dairy livestock export, AI can be used for a variety of applications. It can identify patterns in livestock behavior and physiological parameters to detect illness, stress, or discomfort. It can analyze patterns in feeding behavior to identify shy feeders and adjust the feeding strategies. It can recognize and count individual animals in video footage, and it can use data on feeding behaviors and physiological parameters to optimize the feeding schedules and portions. However, AI also poses challenges. Developing accurate AI algorithms requires substantial amounts of high-quality training data. There are also ethical considerations associated with AI, such as privacy concerns and the potential for the misuse of data [ 43 ].

4.3. Integration of Multiple Sensor Modalities

One of the future directions in this area is the integration of multiple sensor modalities for the comprehensive monitoring of animal health. A single sensor can only provide a limited perspective. For instance, a wearable device may monitor heart rate, but it might not be able to provide insights into the environmental factors influencing the animal’s stress levels. By integrating data from wearable sensors, environmental sensors, and video data, a more holistic understanding of the animal’s condition can be obtained [ 44 ].

4.4. Advancements in AI Algorithms

Advancements in AI algorithms will also play a significant role in the future of dairy livestock export. Current AI models, such as machine learning and deep learning algorithms, are already powerful tools for analyzing livestock data. However, these models could be further improved. For instance, developing algorithms that can analyze multiple types of data (e.g., physiological data, environmental data, video data) simultaneously could provide more comprehensive and accurate insights [ 45 ].

4.5. Customization and Individual Animal Approach

As with any technology application, one size does not fit all. Dairy cattle have individual differences in their behavior, physiology, and response to environmental stressors. These differences need to be taken into account when designing and implementing sensor and AI systems. For example, the optimal position and type of wearable sensor might vary depending on the size, breed, and behavior of the cow. AI algorithms also need to be designed to account for the individual differences between cows [ 46 , 47 ].

4.6. Technological Adaptation and Training

The implementation of sensor technologies and AI systems in the dairy livestock export sector requires adequate training for staff. Staff must be trained to install and maintain the technologies, interpret the data generated, and take the appropriate actions based on the insights provided by AI. Additionally, the dairy cattle must adapt to the new technologies, particularly the wearable devices. Proper training and adaptation are crucial for the successful implementation of these technologies [ 48 ].

4.7. Stakeholder Engagement and Consumer Perception

The use of sensor technologies and AI in dairy livestock export has implications beyond the farm gate. Stakeholders, including consumers, have increasingly high expectations for animal welfare, environmental sustainability, and food safety. The use of these technologies can help meet these expectations by improving animal welfare and reducing the environmental impacts. However, there is also a need to effectively communicate with stakeholders about the use of these technologies to avoid misconceptions and ensure that they are accepted [ 49 ].

4.8. Data Security and Privacy

With the rise of sensor technologies and AI, vast amounts of data are being collected and analyzed. This presents significant challenges in terms of data security and privacy. Ensuring the secure storage and transmission of data is crucial to prevent unauthorized access and the misuse of data. Regulations and best practices need to be developed and implemented to ensure data security and privacy [ 50 , 51 , 52 ].

4.9. Economic Considerations

While sensor technologies and AI offer many benefits, they also come with costs. The initial investment in the hardware, software, and training can be substantial. There are also ongoing costs for maintenance and data management. Therefore, careful economic analysis is necessary to ensure the benefits outweigh the costs. This includes not only the direct economic benefits but also indirect benefits such as improved animal welfare, reduced environmental impacts, and enhanced public perception [ 53 , 54 , 55 ].

4.10. Ensuring Animal Comfort and Welfare

While wearable devices offer valuable data on an individual animal’s health and well-being, it is vital to ensure that these devices do not compromise the comfort or welfare of the animals. Sensor devices should be designed and fitted in a way that minimizes the potential discomfort, injury, or stress for the animals. Regular checks are needed to ensure the devices remain in the correct position and are not causing any harm to the animals. It is also essential to consider the potential stress associated with introducing new technologies and to manage this process carefully to minimize stress for the animals [ 56 , 57 , 58 ].

4.11. Technology Integration and Interoperability

Given the variety of sensor technologies and AI applications that can be used in dairy livestock export, there is a need to ensure these technologies can be integrated and can operate together seamlessly. This includes not only the integration of different types of sensor data but also the interoperability of different AI algorithms. Developing standardized protocols for data collection, storage, and analysis can help ensure the smooth integration and interoperability of these technologies [ 59 , 60 , 61 ].

4.12. Continual Monitoring and Evaluation

Finally, as sensor technologies and AI are implemented in the dairy livestock export process, it is crucial to continually monitor and evaluate their effectiveness. This includes not only tracking their performance in terms of improving animal health and welfare, but also assessing their impact on operational efficiency, economic outcomes, and environmental sustainability. Regular evaluations can help identify any issues or areas for improvement and ensure that the technologies are providing the maximum number of benefits [ 62 , 63 , 64 , 65 ].

Despite significant advances in sensor and Artificial Intelligence (AI) technologies, their adoption within the livestock export sector remains in the early stages. Numerous studies have been conducted to explore the potential of these technologies in enhancing the efficiency and safety of livestock export, but their translation from research and development to practical implementation is still a work in progress.

There are several reasons for this lag in adoption. One of the main challenges is the practical application of technology. Many technologies that function well in controlled lab conditions might struggle in the dynamic and complex real-world scenarios of livestock export. Livestock export operations present varying environmental conditions, which could significantly impact the performance of sensors and AI tools.

Economic factors also play a significant role. The cost of integrating new technology in these operations can be high, and many businesses may hesitate to make such investments unless they are sure of the economic benefits. Technologies that require substantial changes in operational routines or significant capital investments could be especially challenging to implement.

Regulatory hurdles may also slow the adoption of new technologies. Depending on the country and the specific regulations of the livestock industry, gaining approval for the use of certain technologies can be a lengthy and complex process.

Furthermore, resistance from end users can also be a barrier. Established practices are often hard to change, and new technologies that disrupt these practices may not be readily accepted. In such cases, proper training and education about the benefits and usage of these new technologies are crucial for their successful integration.

While there is no shortage of promising research on the use of sensor and AI technologies in livestock export, several challenges still need to be addressed for these technologies to be widely adopted and effectively employed in real-life situations.

4.13. Challenges Associated with the Use of Sensors and IoT

Data security and privacy: The use of sensors and AI can lead to the collection of a vast amount of data. How these data are stored, processed, and protected can be a significant concern.

Infrastructure requirements: Implementing AI and sensor technology requires significant infrastructure, including data storage and processing facilities, high-speed internet connections, the expertise of highly qualified personnel, and power sources.

Accuracy of sensors: Ensuring that sensors accurately and consistently record data is vital. Inaccurate or inconsistent data can lead to misinformed decisions and subsequent consequences. Malfunctioning sensors could lead to incorrect decisions based on flawed data.

AI interpretation: While AI can process and analyze large volumes of data far more quickly than humans, interpreting that data in a meaningful and useful way can be challenging. An over-reliance on AI without proper understanding could lead to erroneous decisions.

Ethical considerations: There could be ethical concerns around the use of sensor and AI technology in dairy livestock export, particularly if it is perceived as intrusive or causing stress to the animals.

Cost: The cost of implementing and maintaining advanced technologies such as AI and sensors can be high.

We acknowledge the importance of providing comprehensive details on the particular algorithms, including their precision, constraints, and the dependability of related sensor technologies. Nevertheless, it is crucial to emphasize that a significant proportion of these technologies, while developed in academic environments, have yet to be examined or validated in a commercial context within the livestock industry, specifically in the export division.

5. Conclusions

Artificial Intelligence and sensor technology are pioneering a transformational shift in the livestock export industry. These technologies offer innovative solutions to enduring challenges, promising a revolution in livestock management, specifically within the dairy sector. From the automated management of ‘shy feeders’, accurate weight tracking, to efficient cattle enumeration, AI and sensor technologies have the potential to augment productivity, promote animal welfare, and streamline supply chain operations. Yet, this transformational journey is not without significant barriers. The technical complexity, privacy issues, and substantial requirements for capital and expertise present serious challenges that need to be overcome to fully harness these technologies. It thus necessitates a paradigm shift within the livestock export industry from traditional practices to a data-driven, automated operation model. However, the potential impact of these technologies is not limited to operational improvements alone. They also offer the potential for a more sustainable, competitive livestock industry, marrying economic growth with environmental preservation and animal welfare. They envision a future where livestock farming evolves beyond merely being a source of food production to an exemplar of efficiency, sustainability, and humane animal management. As we progress, maintaining a focus on technological innovation, advocating for supportive policy measures, and encouraging robust stakeholder collaborations are key. This review underscores the exciting reality that we are at the brink of a technological revolution in livestock management. The challenge now lies in embracing this change and stepping into a future where AI and sensor technology are integral components of the livestock export industry.

Funding Statement

This research received no external funding.

Conflicts of Interest

The author declares no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

•  We're Hiring!
•  Help Center

Dairy Technology

• Most Cited Papers
• Most Downloaded Papers
• Newest Papers
• Last »
• Dairy Technology &Food Technology Follow Following
• Industrial Food Product Follow Following
• Milk production Follow Following
• Dairy Science and Technology Follow Following
• Dairy Microbiology Follow Following
• Dairy Science Follow Following
• Dairy industry Follow Following
• Drying and Dehydration of Food Follow Following
• Physicochemical Follow Following
• FOOD SAFETY/MICROBIOLOGY Follow Following

Enter the email address you signed up with and we'll email you a reset link.

• Academia.edu Journals
•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024