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Invited review: Big Data in precision dairy farming
C Lokhorst1, R M de Mol1, C Kamphuis1
11Wageningen Livestock Research,PO Box 338,6700AH Wageningen,The Netherlands.
Animal : an International Journal of Animal Bioscience
|January 12, 2019
Summary
Big Data is a key research area in precision dairy farming, but its full potential remains untapped. Future advancements require integrating multiple data characteristics and sources for better decision-making.
Area of Science:
- Scientific research on Big Data applications in precision dairy farming.
- Analysis of Big Data characteristics and data analytics methods.
Background:
- Understanding Big Data's role in precision dairy farming is crucial to manage expectations.
- A review of scientific literature was conducted to assess Big Data's current impact.
Purpose of the Study:
- To provide scientific background on Big Data in precision dairy farming.
- To determine if Big Data has surpassed the peak of inflated expectations.
Main Methods:
- A conceptual model and literature search in Scopus identified 1442 papers.
- 142 papers were analyzed based on precision dairy farming classes, Big Data-V categories, and data analytics.
- Analysis focused on object of interest (animal, farm, network), data characteristics, and analysis methods.
Main Results:
- The animal sublevel dominated research (83%), with a focus on dairy farm topics (58%).
- Volume (59%) and Variety (37%) were the most analyzed Big Data characteristics; Velocity was absent.
- Supervised learning (87%) and time-series data (61%) were prevalent in dairy farming research.
Conclusions:
- Big Data is a significant research topic in precision dairy farming, but its full potential is not yet realized.
- Integrating diverse Big Data characteristics (Volume, Variety) and sources (animal, farm, chain) is essential for operational and strategic decision-making.
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