Accurate non-destructive prediction of peach fruit internal quality and physiological maturity with a single scan using near infrared spectroscopy

The development of precise and reliable near infrared spectroscopy (NIRS)-based non-destructive tools to assess physicochemical properties of fleshy fruit has been challenging. A novel crop load × fruit developmental stage protocol for multivariate NIRS-based prediction models calibration to non-destructively assess peach internal quality and maturity was followed. Regression statistics of the prediction models highlighted that dry matter content (DMC, R² = 0.98, RMSEP = 0.41%), soluble solids concentration (SSC, R² = 0.96, RMSEP = 0.58%) and index of absorbance difference (I_AD, R² = 0.96, RMSEP = 0.08) could be estimated accurately with a single scan during fruit growth and development. Thus, the impact of preharvest factors such as crop load and canopy position on peach quality and maturity was evaluated. Large-scale field validation showed that heavier crop loads reduced peach quality (DMC, SSC) and delayed maturity (I_AD) and upper canopy position advanced both mainly in the moderate crop loads. This calibration protocol can enhance NIRS adaptation across tree fruit supply chain.