Literature DB >> 31864744

Symposium review: Real-time continuous decision making using big data on dairy farms.

Victor E Cabrera1, Jorge A Barrientos-Blanco2, Hector Delgado2, Liliana Fadul-Pacheco2.   

Abstract

We are developing a real-time, data-integrated, data-driven, continuous decision-making engine, The Dairy Brain, by applying precision farming, big data analytics, and the Internet of Things. This is a transdisciplinary research and extension project that engages multidisciplinary scientists, dairy farmers, and industry professionals. Dairy farms have embraced large and diverse technological innovations such as sensors and robotic systems, and procured vast amounts of constant data streams, but they have not been able to integrate all this information effectively to improve whole-farm decision making. Consequently, the effects of all this new smart dairy farming are not being fully realized. It is imperative to develop a system that can collect, integrate, manage, and analyze on- and off-farm data in real time for practical and relevant actions. We are using the state-of-the-art database management system from the University of Wisconsin-Madison Center for High Throughput Computing to develop our Agricultural Data Hub that connects and analyzes cow and herd data on a permanent basis. This involves cleaning and normalizing the data as well as allowing data retrieval on demand. We illustrate our Dairy Brain concept with 3 practical applications: (1) nutritional grouping that provides a more accurate diet to lactating cows by automatically allocating cows to pens according to their nutritional requirements aggregating and analyzing data streams from management, feed, Dairy Herd Improvement (DHI), and milking parlor records; (2) early risk detection of clinical mastitis (CM) that identifies first-lactation cows under risk of developing CM by analyzing integrated data from genetic, management, and DHI records; and (3) predicting CM onset that recognizes cows at higher risk of contracting CM, by continuously integrating and analyzing data from management and the milking parlor. We demonstrate with these applications that it is possible to develop integrated continuous decision-support tools that could potentially reduce diet costs by $99/cow per yr and that it is possible to provide a new dimension for monitoring health events by identifying cows at higher risk of CM and by detecting 90% of CM cases a few milkings before disease onset. We are securely advancing toward our overarching goal of developing our Dairy Brain. This is an ongoing innovative project that is anticipated to transform how dairy farms operate.
Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Dairy Brain; artificial intelligence; continuous data integration; decision-making tools; optimization; simulation

Year:  2019        PMID: 31864744     DOI: 10.3168/jds.2019-17145

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  8 in total

1.  Hyperketonemia Predictions Provide an On-Farm Management Tool with Epidemiological Insights.

Authors:  Ryan S Pralle; Joel D Amdall; Robert H Fourdraine; Garrett R Oetzel; Heather M White
Journal:  Animals (Basel)       Date:  2021-04-30       Impact factor: 2.752

2.  A Preliminary Investigation of Social Network Analysis Applied to Dairy Cow Behavior in Automatic Milking System Environments.

Authors:  Liliana Fadul-Pacheco; Michael Liou; Douglas J Reinemann; Victor E Cabrera
Journal:  Animals (Basel)       Date:  2021-04-24       Impact factor: 2.752

3.  Application of an Electronic Nose and HS-SPME/GC-MS to Determine Volatile Organic Compounds in Fresh Mexican Cheese.

Authors:  Héctor Aarón Lee-Rangel; German David Mendoza-Martinez; Lorena Diaz de León-Martínez; Alejandro Enrique Relling; Anayeli Vazquez-Valladolid; Monika Palacios-Martínez; Pedro Abel Hernández-García; Alfonso Juventino Chay-Canul; Rogelio Flores-Ramirez; José Alejandro Roque-Jiménez
Journal:  Foods       Date:  2022-06-25

4.  Database Oriented Big Data Analysis Engine Based on Deep Learning.

Authors:  Xiaoran Shang
Journal:  Comput Intell Neurosci       Date:  2022-08-31

5.  AI Based Digital Twin Model for Cattle Caring.

Authors:  Xue Han; Zihuai Lin; Cameron Clark; Branka Vucetic; Sabrina Lomax
Journal:  Sensors (Basel)       Date:  2022-09-20       Impact factor: 3.847

6.  Milk Source Identification and Milk Quality Estimation Using an Electronic Nose and Machine Learning Techniques.

Authors:  Fanglin Mu; Yu Gu; Jie Zhang; Lei Zhang
Journal:  Sensors (Basel)       Date:  2020-07-30       Impact factor: 3.576

Review 7.  Historical Evolution of Cattle Management and Herd Health of Dairy Farms in OECD Countries.

Authors:  Ivo Medeiros; Aitor Fernandez-Novo; Susana Astiz; João Simões
Journal:  Vet Sci       Date:  2022-03-09

8.  Addressing Data Bottlenecks in the Dairy Farm Industry.

Authors:  Liliana Fadul-Pacheco; Steven R Wangen; Tadeu Eder da Silva; Victor E Cabrera
Journal:  Animals (Basel)       Date:  2022-03-12       Impact factor: 2.752

  8 in total

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