Mechanisms of color change and smart control strategies during carrot drying

This study elucidated coupled surface-interior color evolution mechanisms, examined the interrelationship between external and internal chromatic variations and proposed an intelligent control strategy for carrot drying processes. Four drying techniques—hot air drying (HAD), infrared drying (IRD), microwave vacuum drying (MVD), and freeze drying (FD)—were comparatively analyzed in terms of their effects on surface color, internal browning, and pigment stability. Both enzymatic and non-enzymatic browning were examined by monitoring browning degree (BD), 5-hydroxymethylfurfural (5-HMF) levels, and the activities of polyphenol oxidase (PPO) and peroxidase (POD) throughout the drying stages. Dynamic analyses revealed enzymatic reactions dominated high-moisture stages (MC &gt; 0.6 g/g w.b.), while Maillard reactions prevailed at MC &lt; 0.6 g/g w.b. To enable nondestructive, real-time monitoring, a hybrid detection system integrating near-infrared spectroscopy (NIR) and low-field nuclear magnetic resonance (LF-NMR) was developed. BD prediction models were constructed using partial least squares (PLS), support vector machine (SVM), and back-propagation artificial neural network (BP-ANN) algorithms. Among these, the BP-ANN model exhibited superior predictive performance (<i>R</i>² = 0.9220, RMSE = 0.0128). In the practical application of dry browning control and burn prevention, the browning degrees of carrots were 0.168 and 0.274, respectively, with the efficiency improvements of 28% and 37%. This work provides critical insights into spatiotemporal browning dynamics and demonstrates the viability of AI-driven quality control in industrial drying. First multimodal NIR-LF-NMR sensing platform enabling synchronous analysis of surface-interior browning dynamics.Constructed high-accuracy BP-ANN models for predicting browning degree using fusion spectral–moisture features.Proposed an intelligent MVD control strategy that reduced drying time by 37% while preserving color quality. First multimodal NIR-LF-NMR sensing platform enabling synchronous analysis of surface-interior browning dynamics. Constructed high-accuracy BP-ANN models for predicting browning degree using fusion spectral–moisture features. Proposed an intelligent MVD control strategy that reduced drying time by 37% while preserving color quality.