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Big Data Meets the Food Supply: A Network of Cattle Monitoring Systems

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Trends and Advances in Information Systems and Technologies (WorldCIST'18 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 746))

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Abstract

The beef cattle industry generates $78.2 billion of revenues from nearly 100 million head each year in the U.S. alone. Cattle feed efficiency is a measure of animal growth. Animals with better efficiency may grow at the same rate as animals with lower efficiency, but will eat less to do so. This paper introduces a network of sensors in a cattle production operation designed to measure and report feed efficiency to the farmer. The sensors provide data that is used to monitor and control feed rations to the animals and help the farmer make informed decisions regarding animal grouping, control and genetic line building to improve beef stock quality over time. While cattle feed control and monitoring is itself not a new concept, the system described here adds some automated components to enhance and better control the operation that have not yet been done.

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Notes

  1. 1.

    The heritability parameter, h2, estimates the amount of phenotypic diversity due to genetics. It ranges from 0 (no genetic differences) to 1 (100% genetic differences).

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Authors and Affiliations

  1. Kansas State University, Manhattan, KS, 66506, USA

    Michael A. Chilton

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  1. Michael A. Chilton
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Correspondence to Michael A. Chilton .

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Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, Ohio, USA

    Hojjat Adeli

  3. DSI/EEUM, Universidade do Minho, Guimarães, Portugal

    Luís Paulo Reis

  4. DIMES, Universita della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

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Chilton, M.A. (2018). Big Data Meets the Food Supply: A Network of Cattle Monitoring Systems. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 746. Springer, Cham. https://doi.org/10.1007/978-3-319-77712-2_15

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  • DOI: https://doi.org/10.1007/978-3-319-77712-2_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77711-5

  • Online ISBN: 978-3-319-77712-2

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