Visual detection on posture transformation characteristics of sows in late gestation based on Libra R-CNN

Posture transformation characteristics of sows in late gestation can be used as intuitive indicators to predict sow delivery time. To reduce the imbalance in posture distribution and insignificant differences between coherent sow postures in late gestation, a model based on Libra R-CNN was proposed to recognise the sow postures. Libra R-CNN is a simple but effective framework that incorporates intersection over union (IoU)-balanced sam-pling, a balanced feature pyramid, and balanced L1 loss, aiming to balance learning for object detection. The model used here realised the recognition of sow postures: lateral, sternum, sitting, and standing. Experimental results revealed close relationships between the two basic characteristics ('ratio of express nesting behaviour' and 'frequency of postural transformation') and delivery time. The mean average precision values for IoU 1/4 0.5 (mAP0.5) of Libra R-CNN on the validation and test sets from the sow posture sample library were 0.97 and 0.96, whilst the AP value of various postures was balanced. From 16 to 4 h before sow farrowing, the values of the two basic characteristics were significantly increased and lasted for a long time, and started to decrease rapidly 4 h before farrowing. Heat stress caused sow agitation but decreased nesting behaviour before parturition. The Pearson correlation coefficients of 15 features constructed based on the two characteristics and delivery time were all above 0.6. Therefore, Libra R-CNN realised the detection of sow posture and the two basic characteristics can be used as effective indicators for the automated prediction of sow delivery time.(c) 2022 IAgrE. Published by Elsevier Ltd. All rights reserved.

Automated summary

The posture transformation characteristics of sows in late gestation can be used to predict sow delivery time. A model based on Libra R-CNN was used to recognize sow postures. The study found close relationships between the posture characteristics and delivery time.