The accurate prediction of these indicators can significantly enhance farm economic efficiency and can provide a basis for futureproductionstrategies. Currently, there is a lack of research on the application ofmachinelearning(ML) models to predicteggproductionrate andeggweight in broiler breeders.
This study suggests a mixed approach to predict the optimal age of hens for peakeggproductionby using mixed linear regression (MLR) models and throughmachinelearningtechniques. The primary objective is to enhance the accuracy and reliability of age prediction using real-worldeggproductiondata. The dataset collected from the National Root Crop Research Institute (NRCRI) chicken farm in ...
Predictingeggproductionis a complex challenge due to the multiple variables involved, such as temperature, nutrition, and environmental conditions.Machinelearningmodels have proven effective in forecastingeggpro-duction, enabling the analysis of large datasets and the identification of complex patterns influencingproduction[3].
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Moving forward, it's essential to keep these visual contexts in mind when discussing Machine Learning In Egg Production.
Defectiveeggs(eggswith abnormal exterior quality and size, Figure 1) can reduce theeggquality/food safety and market value of laying henproduction, especially in cage-free houses where flooreggsare more common. To improveeggquality, automated grading and defect detection systems have been developed usingmachinevision and image processing. Automatedeggmeasurement systems are also ...
AbstractEggproductionrate andeggweight are core indicators for evaluating theproductionperformance of broiler breeders. The accurate prediction of these indicators can significantly enhance farm economic efficiency and can provide a basis for futureproductionstrategies. Currently, there is a lack of research on the application ofmachinelearning(ML) models to predicteggproduction...
