Big data analytics for empowering milk yield prediction in dairy supply chains

Yan, Wenjing; Chen, X.; Akcan, Orkan; Lim, Jasmine J.; Yang, Di

doi:10.1109/bigdata.2015.7363997

Cited by 18 publications

(8 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An important application of BD/BDA is to improve on-farm decision making, milk yield prediction, milk quality improvement and dairy farm management. In this context, Yan et al (2015) introduced the Milk Yield Prediction and Analysis Tool (PAT), a cost-effective tool that uses BDA to accurately predict milk yield at both individual cow and group levels. This study highlighted the importance of data-driven decision making for small-scale milk producers.…”

Section: Discussion Of Applications Of Dairy 40 Technologies In Milk ...mentioning

confidence: 99%

Birth of dairy 4.0: Opportunities and challenges in adoption of fourth industrial revolution technologies in the production of milk and its derivatives

Hassoun

García-García

Trollman

et al. 2023

Current Research in Food Science

View full text Add to dashboard Cite

Section: Discussion Of Applications Of Dairy 40 Technologies In Milk ...mentioning

confidence: 99%

Birth of dairy 4.0: Opportunities and challenges in adoption of fourth industrial revolution technologies in the production of milk and its derivatives

Hassoun

García-García

Trollman

et al. 2023

Current Research in Food Science

View full text Add to dashboard Cite

“…Research studies depict that the prediction of milk production yields through BDA. The milk yield of cattle is very beneficial in economic terms [73]. Accuracy in forecasts regarding products tends to gather information about the shortage, efficiency, cattle's overall health, etc.…”

Section: Milk and Milk Productsmentioning

confidence: 99%

Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics

et al. 2021

View full text Add to dashboard Cite

The agri-food sector is an endless source of expansion for nourishing a vast population, but there is a considerable need to develop high-standard procedures through intelligent and innovative technologies, such as artificial intelligence (AI) and big data. This paper addresses the research concerning AI and big data analytics in the food industry, including machine learning, artificial neural networks (ANNs), and various algorithms. Logistics, supply chain, marketing, and production patterns are covered along with food sub-sector applications for artificial intelligence techniques. It is found that utilization of AI techniques and the intelligent optimization algorithm also leads to significant process and production management. Thus, digital technologies are a boon for the food industry, where AI and big data have enabled us to achieve optimum results in realtime.

show abstract

“…Forecasting of food production and consumption would help in logistical planning of the existing resources nationwide. A study done by Sharma and Patil (2015), had used a fuzzy inference system to forecast the production and consumption of rice yearly while Yan et al (2015) employed four ML techniques, namely, ANN, support vector machine (SVM), genetic programing (GP), and Gaussian process regression (GPR), to develop a feasible and economical tool to forecast future milk yield at the individual cow and the group level. Evolutionary machine learning (EML) techniques can find solutions to reduce time and cost for both production and transportation.…”

Section: Food Accessibilitymentioning

confidence: 99%

“…Streamlining transport, marketing, and storage facilities can be reached more efficiently and effectively by employing faster or simpler working methods in AI such as ANN, fuzzy logic systems, ML, computer vision and robotics. Forecasting production and consumption would help in making decisions, efficient food distribution and consequently supply chain optimization (Yan et al, 2015;Sethanan and Pitakaso, 2016;Faust et al, 2017;Liu et al, 2019).…”

Section: How Sri Lanka Can Be Benefited From Artificial Intelligence In Achieving Food Securitymentioning

confidence: 99%

Role of artificial intelligence in achieving global food security: a promising technology for future

et al. 2020

View full text Add to dashboard Cite

Rapid growth of population, diminishing natural resources, climate change, shrinking agricultural lands and unstable markets are making the global food systems rather insecure. Therefore, modern agriculture and food systems should be more productive in terms of output, efficient in operation, resilient to climate change and sustainable for the future generations. As a result, the need of a technological transformation is greater than ever before. Being a recent advancement in computer sciences, Artificial Intelligence (AI) has the capacity to address the challenges of this new paradigm. Hence, understanding the importance and applicability of AI in agriculture and food sector could be vital in the journey towards achieving global food security. This review focuses on the AI applications in relation to four pillars of food security (food availability, food accessibility, food utilization and stability) as defined by FAO, in detail. The AI technologies are being applied worldwide in all four pillars of food security even though it has been one of the slower adopted technologies compared to the rest. Nevertheless, it warrants exploring the capabilities of AI and their current impact on the food systems. It is eminent that AI technology has a key role to play in the future agriculture sector. The worldwide AI in agriculture market is expected to reach USD 2,075 million by 2024. Present article reveals how AI technologies could benefit global agriculture and food sector, and examines the ways by which AI can address the prominent issues in Sri Lankan agriculture sector such as labor scarcity, misuse of agrochemicals and inefficient food value chains. Though there are still many challenges and gaps to be addressed at research, policy, administrative and farmer levels, the immense potential of this novel technology should be exploited fast in the journey towards global food security.

show abstract

Big data analytics for empowering milk yield prediction in dairy supply chains

Cited by 18 publications

References 22 publications

Birth of dairy 4.0: Opportunities and challenges in adoption of fourth industrial revolution technologies in the production of milk and its derivatives

Birth of dairy 4.0: Opportunities and challenges in adoption of fourth industrial revolution technologies in the production of milk and its derivatives

Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics

Role of artificial intelligence in achieving global food security: a promising technology for future

Contact Info

Product

Resources

About