| Summary: | The present investigation was carried out to develop a novel, portable and user-friendly method for hands-off measurement of body dimensions and prediction of body weight of the Ghoongroo breed of pigs (aged 30 to 190 days) using a smartphone object measurement app- On 3D CameraMeasure. Prediction of body weight from body dimensions was carried out through various types of regression analyses. This image-based method was compared with the traditional manual measurement method. Almost all the corresponding body dimensions between manual and image-based methods showed a very high and positive correlation (0.842–0.984). The product of body length and heart girth height measured from the images was identified as the best predictors of body weight. A comparison among stepwise regression and regression on one or two body dimensions showed that linear inclusion of more than one predictor did not increase accuracy. When non-linear regression using the product of two image-morphometric traits (Z=body length x heart girth height) was carried out, the R2 (0.98) value increased significantly. This sex and age-independent equation (Y= -6.335 + 0.024 Z, R2= 0.98) derived from the training dataset from an organized farm accurately predicted the body weights of pigs of an independent test population. The correlation coefficient between the actual body weight and the predicted body weight of pigs from the test population was 0.99. It was concluded that the smartphone image-based method could replace the cumbersome and stressful manual method very effectively. The additional advantages of smartphone image measurements are- robustness, accuracy, simplicity, user-friendliness, and true portability.
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