Abstract
In this study, a multisensory system was built to evaluate the effect of the temperature, humidity, the concentration of carbon dioxide and ammonia on pig weight gain. During the experiment, RGB-based image analysis provided body weight information of 22 pigs over a three-month period. In the experiment, two cameras were set to obtain pictures, and the resulting data showed high correlation. Pearson’s and Spearman’s correlation was calculated between the body weight and the monitored environmental parameters. Results showed that temperature negatively correlates with the body weight, while CO2 and NH3 have a positive correlation. In this study, humidity, random effect, and changes in temperature had slightly negative but not significant correlation with body weight gain. Multiple linear regression showed that temperature and humidity had a significant effect on the body weight gain of the pigs, while the effect of the NH3 was also noticeable. Our results proved that image-analysis-based weight evaluation is a powerful tool in precision livestock farming and that environmental conditions have a significant effect on pigs’ production.
Published Version
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