Abstract
ABSTRACT The objective of this study was to develop a software based on image processing and computer vision techniques for monitoring the feeding/collective behavior of broilers (Cobb) and validate it based on the results obtained from the visual analysis of an expert. The visual analysis was performed based on the observation and quantification of behaviors in the interval of 10 min at each hour of the day, in the period of 24 hours, totaling 1728 frames/day, for males and females. The software was developed using the Hoshen-Kopelman algorithm, for labeling clusters, which would basically be the grouping of similar pixels. This software is written in the 1999 standard of the C language. After this stage of programming, the Hoshen-Kopelman algorithm identified the birds in the region of interest (feeder and drinker), with removal of the background color to obtain the descriptors, using the same range of visual analysis. Then, the software was validated through linear regression analysis, using the R platform. Based on the correlation analyses, it was found that the coefficient of determination (R2) ranged from 0.74 to 0.97 for all software validation events. The number of broilers in the regions of interest showed R2 above 0.70 for females and above 0.89 for males, which allowed the characterization of the ingestive behavior of broilers by computer vision. Some factors that caused interference in the accuracy of the software were decisive for the result, especially the arrangement of the cameras, uneven lighting, obstruction caused by the lighting system, pendular movement of the feeders and drinker, and shade generated by them. Despite the highlighted interferences, the results allowed us to infer that the software identified and quantified the feeding behavior of broilers in an appropriate manner.
Highlights
The continuous increase in the world population significantly increases the demand for food, in quantity and quality
The objective of this study was to develop a software based on image processing and computer vision techniques for monitoring the feeding/collective behavior of broilers (Cobb) and validate it based on the results obtained from the visual analysis of an expert
The objective of this study was to develop a software based on image processing and computer vision techniques, for monitoring the feeding/collective behavior of broilers, and validate it based on the results obtained from the visual analysis of an expert
Summary
The continuous increase in the world population significantly increases the demand for food, in quantity and quality. Farmers and ranchers, and researchers have devoted considerable efforts to a wide variety of techniques to increase food production, with an emphasis on production efficiency and increased return on investment. In this context, information technology has been heavily exploited in this sector, especially in terms of management and controllers that integrate automatic realtime decision-making support, such as precision agriculture and livestock farming (So-In et al, 2014; Zhang et al, 2002). The behavior is a direct reflection of how the animal is coping with its environment. Video-based behavioral analysis can be very time consuming, and the accuracy and reliability of the result
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