Advancement in measurement and AI-driven predictions of maturity indices in kinnow(Citrus nobilis x Citrus deliciosa ): A comprehensive review

Abstract

Kinnow also known as mandarin are popular fruits worldwide for their refreshing flavor and nutritional benefits. Their quality standards vary globally due to differences in climatic conditions, agronomical practices, mandarin physiology, etc. The fruit maturity indices are region and consumer specific which make traditional methods of maturity predictions a very difficult task which become challenge for producers and researchers. This review provides state-of-art approches on maturity indices of mandarin fruit by understanding its physiological changes including their biotic, abiotic factors, physicochemical parameters and artificial intelligence integration with non-destructive technologies to predict the fruit maturity. It focuses on rapid on-field sensor and camera based systems with different algorithmic models for fruit maturity prediction. The use of AI driven advanced spectrometry, imaging techniques, real time monitoring are crucial for predicting harvest time. It also highlights significant technical challenges and identifies promising areas for future research, offering a valuable insights for growers.