Abstract
Precision poultry farming technologies include the analysis of images of poultry flocks using cameras. In large-scale waterfowl farming, these can be used to determine the individual weight of poultry flocks. In our research in a real farming environment, we investigated the cameras fixed to the metal support structure of the barn, located above the suspended bird scales. Camera images of the bird on the weighing cell, taken from a top view, were matched to the weight data measured by the scale. The algorithm was trained on training data sets from a part of the database, and the results were validated with the other part of the database (Training: 60% Validation: 20% Testing: 20%). Three data science models were compared, and the random forest method achieved the highest accuracy and reliability. Our results show that the random forest method gave the most reliable results for determining the individual weights of birds. We found that the housing environment had a strong influence on the applicability of the data collection and processing technology. We have presented that by analyzing carefully collected images, it is possible to determine the individual weights of birds and thus provide valuable information on it.
Funder
National Research, Development, and Innovation Fund of Hungary
Óbuda University
Subject
Plant Science,Agronomy and Crop Science,Food Science
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