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 x 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, R-2 = 0.98, RMSEP = 0.41%), soluble solids concentration (SSC, R-2 = 0.96, RMSEP = 0.58%) and index of absorbance difference (I-AD, R-2 = 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.

Automated summary

The development of precise and reliable near infrared spectroscopy (NIRS)-based non-destructive tools has been a challenge for assessing the physicochemical properties of fleshy fruit. A novel protocol involving crop load and fruit developmental stage was used to calibrate multivariate NIRS prediction models, accurately estimating peach internal quality and maturity. The study found that preharvest factors such as crop load and canopy position significantly influenced peach quality and maturity, showing the potential for NIRS adaptation across the tree fruit supply chain.