HARNESSING HYPERSPECTRAL IMAGING AND ML FOR EARLY PREDICTION OF CHICK EMBRYO SEX AND EMBRYONIC MORTALITY FOR NEXT GENERATION POULTRY INDUSTRY

The primary objective of the proposed research is to use machine learning (ML)-driven hyperspectral imaging for the early prediction of chick embryo sex and embryonic mortality. The specific objectives are to: (1) Optimize and develop ML models for detecting chick embryo sex and embryonic mortality at early incubation and (2) Identify some important bands from 400-1700 nm to design a multispectral real-time system.