Short communication: Measuring feed volume and weight by machine vision

A. N. Shelley, D. L. Lau, A. E. Stone, J. M. Bewley

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Individual dairy cow feed intake is closely related to the health and productive output of each cow, with healthy cows generally eating more feed than unhealthy cows. Incorporating the use of an automated system to monitor feed consumption for each cow may be beneficial for dairy farm management. This study examined the use of an inexpensive 3-dimensional video camera to measure feed volume, from which we derived feed weight. Proof-of-concept testing was conducted to determine the effectiveness and capability of the machine vision feed-scanning system and its possible use in feed intake monitoring. Such systems are ideal because they do not impede the workflow of the farm or interrupt feeding behavior. This is an improvement over existing systems that are labor and cost intensive. Our conducted experiments involve measuring feed volume at known weights, up to 22.68 kg, with the resulting volume and weight values analyzed by means of linear and quadratic least squares t-test regression analysis. The effects of feed positioning in the bin and near-range sensor limitations were also examined. The results showed that an estimation of feed weight from 3-dimensional scan of volume measurements could be made to within 0.5 kg of the physically measured feed weight using a digital scale. Future efforts will focus on extending this work to active bunks with multiple cows eating throughout the day and testing total mixed rations of varied composition.

Original languageEnglish
Pages (from-to)386-391
Number of pages6
JournalJournal of Dairy Science
Volume99
Issue number1
DOIs
StatePublished - Jan 1 2016

Bibliographical note

Funding Information:
The authors acknowledge financial support from the Kentucky Science and Engineering Foundation .

Publisher Copyright:
© 2016 American Dairy Science Association.

Keywords

  • Feed intake
  • Machine vision
  • Precision dairy farming
  • Structured light illumination

ASJC Scopus subject areas

  • Food Science
  • Animal Science and Zoology
  • Genetics

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