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Improving Efficiency: Automatic Intelligent Weighing System as a Replacement for Manual Pig Weighing
Gaifeng Hou1, Rui Li1, Mingzhou Tian1
1CAS Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Hunan Research Center of Livestock and Poultry Sciences, South Central Experimental Station of Animal Nutrition and Feed Science in the Ministry of Agriculture, National Engineering Laboratory for Poultry Breeding Pollution Control and Resource Technology, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China.
AIWS accurately predicts pig weights, offering a feasible alternative to manual weighing in large-scale farms. This technology enhances growth curve analysis for growing-finishing pigs.
Area of Science:
- Animal Science
- Agricultural Technology
- Precision Livestock Farming
Background:
- Accurate monitoring of pig body weight is crucial for optimizing growth and management in intensive farming systems.
- Traditional manual weighing is labor-intensive and can be stressful for animals.
- Automated systems offer potential for more efficient and less disruptive weight monitoring.
Purpose of the Study:
- To evaluate the accuracy and effectiveness of an Automated Imaging Weighing System (AIWS) for predicting body weights of growing-finishing pigs.
- To compare the growth curve fitting performance of AIWS-derived data with traditional manual weighing methods.
- To determine the feasibility of AIWS as a replacement for manual weighing in commercial pig production.
Main Methods:
- 106 growing-finishing pigs were weighed using both manual methods and AIWS.
- Accuracy was assessed using Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE).
- Growth curves were fitted using data from both methods, comparing model fit using AIC and BIC values.
Main Results:
- AIWS demonstrated high accuracy with MAE of 3.48 kg, MAPE of 3.71%, and RMSE of 4.43 kg for pigs between 60-120 kg.
- A strong positive correlation (r=0.9410, R²=0.8854, p<0.001) was found between AIWS and manual weight measurements.
- AIWS resulted in lower AIC and BIC values, indicating superior growth curve fitting compared to the manual method, with the Logistic model being the best fit.
Conclusions:
- AIWS provides accurate body weight predictions for growing-finishing pigs in real-world production settings.
- The AIWS method offers superior performance in fitting growth curves compared to traditional manual weighing.
- AIWS is a viable and potentially more efficient alternative to manual weighing for monitoring pig weights (50-120 kg) in large-scale farming operations.
