AI in Dairy Science
hampaign, IL, February 6, 2023—Artificial intelligence (AI; the ability of computers or robots to perform reasoning tasks) is a popular topic today, so many are investigating how it can be used to assist dairy farms. “Artificial Intelligence and Machine Learning in Dairy Production Systems” was the title of the American Registry of Professional Animal Scientists symposium that was held in June 2022 at the annual meeting in Kansas City, Missouri. A new invited review in Applied Animal Science resulted from a presentation that was given at this symposium.
“Our goal was to show the variety of settings in dairy farms where AI is being applied and discuss some strengths and weaknesses of the applications,” said lead author Albert De Vries, PhD (Department of Animal Sciences, University of Florida, Gainesville, FL, USA). De Vries and his coauthors reached this goal be supplying an overview of AI and machine learning (ML), discussing 5 published review articles about ML use in dairy farms, and providing examples of AI applied to animal performance.
The article begins by discussing the broad field of AI, detailing the theory and models currently used and touching on expert systems used in the 1980s and 1990s. Analytics offered by AI include descriptive, predictive, and prescriptive analyses, but the authors state that applications on dairy farms most often involve predictive analytics. “Predictive analytics uses historical data with the aim of understanding future performance through statistical modeling, for example estimating which cows are at risk of disease given their historical data,” said De Vries.
The researchers then cover what findings have been reported in the literature and highlight five reviews that focus on ML applications in dairy or livestock farms. They said that one review reported that most studies they reviewed used tree-based algorithms and an increasing number used neural network algorithms (deep learning), usually focusing on ML and the physiology and health of dairy cows. Another study reviewed articles about ML applications to a wide variety of areas important to dairy farming, although implementation was not recommended because of the limited quantity of data available. The third review that the authors focused on addressed the use of ML for disease detection and quantifying milk production and milk quality, with most articles using decision tree–based algorithms and others using artificial neural network–based, regression-based, or other algorithms. Another survey looked at deep learning and precision cattle farming, found that convolutional neural networks were the most frequently used models, and listed challenges faced. The final review that the authors highlighted studied ML applications for precision livestock farming but concluded that ML is not overly useful yet in precision livestock farming because it is at such an early stage of development.
Caption: Much research has investigated various machine learning applications in the dairy farm. Data derived from sensors are often used in these applications (Credit: iStock.com/Alisovna).
Numerous specific examples of the use of AI in dairy farms are described in the article. “Because of advances in both hardware and software, intelligent use of new big data is possible, fostering improved decision making and processing using robots especially for repetitive manual and computational tasks,” said David K. Beede, PhD, Editor in Chief of Applied Animal Science. The review describes the use of ML for crop yield prediction, disease and estrus detection, prediction of insemination success and onset of calving, estimation of future milk yield and feed intake, employee training, and more. The use of robotics and even virtual reality goggles for dairy cows are mentioned. De Vries said that in the future, “AI will change the dairy sector by enabling improved work environments (all facets including decision making and robots) and removing or minimizing the need for manual human processing of repetitive tasks.”
The article appears in the February issue of Applied Animal Science.
Notes for editors
“Invited Review: Examples and opportunities for artificial intelligence (AI) in dairy farms,” by A. De Vries, N. Bliznyuk, and P. Pinedo (https://doi.org/10.15232/aas.2022-02345), Applied Animal Science, volume 39, issue 1 (February 2023), published by FASS Inc. and Elsevier.
This article is openly available at https://doi.org/10.15232/aas.2022-02345.
Full text of the article is also available to credentialed journalists upon request; contact Brittany Morstatter at +1-217-356-3182 ext. 143 or ARPAS@assochq.org to obtain copies. To schedule an interview with the author(s), please contact Albert De Vries at devries@ufl.edu.
About Applied Animal Science
Applied Animal Science (AAS) is a peer-reviewed scientific journal and the official publication of the American Registry of Professional Animal Scientists (ARPAS). In continuous publication since 1985, AAS is a leading outlet for animal science research and is indexed by Scopus and ESCI (Clarivate’s Emerging Sources Citation Index). The journal welcomes novel manuscripts on applied technology, reviews on the use or application of research-based information on animal agriculture, commentaries on contemporary issues, short communications, and technical notes. Topics that will be considered for publication include (but are not limited to) feed science, farm animal management and production, dairy science, meat science, animal nutrition, reproduction, animal physiology and behavior, disease control and prevention, microbiology, agricultural economics, and environmental issues related to agriculture. Themed special issues also will be considered for publication. www.appliedanimalscience.org
About the American Registry of Professional Animal Scientists (ARPAS)
The American Registry of Professional Animal Scientists (ARPAS) is the organization that provides certification of animal scientists through examination, continuing education, and commitment to a code of ethics. Continual improvement of individual members is catalyzed through publications (including the AAS journal) and by providing information on educational opportunities. ARPAS is affiliated with five professional societies: American Dairy Science Association, American Meat Science Association, American Society of Animal Science, Equine Science Society, and Poultry Science Association. www.arpas.org
About FASS Inc.
Since 1998, FASS has provided shared management services to not-for-profit scientific organizations. With combined membership rosters of more than 10,000 professionals in animal agriculture and other sciences, FASS offers clients services in accounting, membership management, convention and meeting planning, information technology, and scientific publication support. The FASS publications department provides journal management, peer-review support, copyediting, and composition for this journal; the staff includes several BELS-certified (www.bels.org) technical editors and experienced composition staff. www.fass.org
About Elsevier
As a global leader in information and analytics, Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Elsevier does this by facilitating insights and critical decision-making for customers across the global research and health ecosystems.
In everything Elsevier publishes, it upholds the highest standards of quality and integrity. Elsevier brings that same rigor to their information analytics solutions for researchers, health professionals, institutions and funders.
Elsevier employs 8,700 people worldwide. Elsevier has supported the work of our research and health partners for more than 140 years. Growing from its roots in publishing, Elsevier offers knowledge and valuable analytics that help users make breakthroughs and drive societal progress. Digital solutions such as ScienceDirect, Scopus, SciVal, ClinicalKey, and Sherpath support strategic research management, R&D performance, clinical decision support, and health education. Researchers and healthcare professionals rely on over 2,700 digitized journals, including The Lancet and Cell; over 43,000 eBook titles; and iconic reference works, such as Gray's Anatomy. With the Elsevier Foundation and its external Inclusion & Diversity Advisory Board, Elsevier works in partnership with diverse stakeholders to advance inclusion and diversity in science, research, and healthcare in developing countries and around the world.
Elsevier is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. www.elsevier.com
Comments
Post a Comment