Use of adobe photoshop for body measurements of crossbred beef cows and prediction of body weight after regression analysis - Nilchuen, P.; Yaigat, T.; Tungtrakoolsub, P. (International Journal of Agricultural Technology, 2021)
A total of 160 crossbred beef cows in Thailand were recorded using a digital weighing scale and their body condition score (BCS) categorized to be thin, moderate, and fat. All cows were photographed with a mobile phone camera and the images were analyzed for chest depth (CD) and body length (BL) using Adobe Photoshop software. The average actual BW was 423.99 ± 84.66 kg. The best models to predict actual BW from CD, BL and BCS were as follows: thin, BW = 5.69(CD) + 4.19 (BL) - 463.82; moderate, BW= 16.16(CD) + 1.06(BL) - 606.42 and fat, BW = 5.21(CD) + 4.52(BL) - 426.39, with an adjusted R2 of 0.8749 and a root mean square error (RMSE) of 30.06 corresponding to 7.09% of the mean actual BW. The difference between actual BW and BW predicted from the simple linear regression models was not significant (P> 0.05). The correlation coefficients were 0.938. Results indicated that body measurement (CD and BL) extracted from images using Adobe Photoshop combined with BCS in the regression equations that developed in this study can accurately predict the BW of crossbred beef cows. The method is proved to beviable, rapid, and not involves in physical contact with the animal’s body