Prediction of milk yield using visual images of cows through deep learning.
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Abstract
The broad objective of the study was to determine, through deep learning, the predictability of
milk yield from a cow's image data. The data size of 1238 image pairs (the side-view images
and the rear-view images) from 743 Holstein cows within their first or second parity and the
cows’ corresponding first lactation 305-day milk yield values were used to train a deep
learning model. The data was first split into the training and testing data at the ratio of 80:20,
respectively. The training data was then augmented four times more, then again split into
training and validation data at the ratio of 80:20, respectively.
Three principal analyses were done, i.e. the prediction of milk yield using rear-view images
only, the prediction of milk yield using the side-view images only and the prediction of milk
yield using a merge of the side-view and rear-view images (the combined-view images). In all
three analyses, poor predictions were observed, i.e. R2 values of 0.32 for the model using the
side-view image, 0.30 for the model using the rear-view images and 0.38 for the model using
combined side and rear images. The mean absolute errors were 1146.4 kg, 1148.3 kg and
1112.9 kg for the side-view, the rear-view and the combined-view models, respectively. The
root mean square error values were 1460.7 kg, 1480.5 kg and 1401.2 kg and the mean absolute
error percentages were 17.6, 17.3 and 17.0 % for the side-view, rear-view and combined-view
models, respectively.
Hypotheses tests were also done to check whether there was any difference between these
three prediction models. There was no significant difference in performance between all the
prediction models (p>0.05), i.e. the side-view model, the rear-view model and the combinedview
model. It was concluded that predicting 305-day milk yield of Holstein cows using either
view has the same level of accuracy and no additional benefits are derived from using both the
rear and the side views.
Keywords: Computer vision; deep learning; linear conformation traits; 305-day milk yield;
side-view images; rear-view images; combined-view images; Holstein cows.
Description
Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.