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Assessing the potential of photogrammetry to monitor feed intake of dairy cows

Published online by Cambridge University Press:  18 February 2019

Victor Bloch
Affiliation:
Precision Livestock Farming Lab, Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, Rishon LeZion 7505101, Israel
Harel Levit
Affiliation:
Precision Livestock Farming Lab, Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, Rishon LeZion 7505101, Israel
Ilan Halachmi*
Affiliation:
Precision Livestock Farming Lab, Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, Rishon LeZion 7505101, Israel
*
Authors for correspondence: Ilan Halachmi, Email: [email protected]

Abstract

We address the hypothesis that individual cow feed intake can be measured in commercial farms through the use of a photogrammetry method. Feed intake and feed efficiency have a significant economic value for the farmer. A common method for measuring feed mass in research is a feed mass weighing system, which is excessively expensive for commercial farms. However, feed mass can be estimated by its volume, which can be measured by photogrammetry. Photogrammetry applies cameras along the feed-lane, photographing the feed before and after the cow visits the feed-lane, and calculating the feed volume. In this study, the precision of estimating feed mass by its volume was tested by comparing measured mass and calculated volume of feed heaps. The following principal factors had an impact on the precision of this method: camera quality, lighting conditions, image resolution, number of images, and feed density. Under laboratory conditions, the feed mass estimation error was 0·483 kg for heaps up to 7 kg, while in the cowshed the estimation error was 1·32 kg for up to 40 kg. A complementary experiment showed that the natural feed compressibility causes about 85% of uncertainty in the mass estimation error.

Type
Research Article
Copyright
Copyright © Hannah Dairy Research Foundation 2019 

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