Nondestructive Prediction of Eggshell Thickness Using NIR Spectroscopy and Machine Learning with Explainable AI

Keyphrases

• Near-infrared Spectroscopy 100%
• Machine Learning 100%
• Partial Least Squares Regression Model 100%
• Eggshell Thickness 100%
• Non-destructive Prediction 100%
• Explainable AI 100%
• Root Mean Square Error of Prediction 66%
• Lipids 33%
• Moisture 33%
• Calibration Model 33%
• Respiration 33%
• K-nearest 33%
• Performance Prediction 33%
• Thickness Determination 33%
• Machine Learning Techniques 33%
• Coefficient of Determination 33%
• Partial Least Squares Regression 33%
• Regression Forest 33%
• Eggshell 33%
• Content Supply 33%
• Explainable Artificial Intelligence 33%
• Regression Calibration 33%
• Competitive Adaptive Reweighted Sampling 33%
• Shapley Additive Explanations 33%
• Full-wavelength 33%
• Support Vector Regression 33%

Material Science

• Near Infrared Spectroscopy 100%
• Explainable Artificial Intelligence 100%
• Coherent Anti-Stokes Raman Spectroscopy 50%

Chemistry

• NIR Spectroscopy 100%
• Coherent Anti-Stokes Raman Spectroscopy 50%
• Lipid 50%