Detection of the quality of juicy peach during storage by visible/near infrared spectroscopy

Abstract

In order to study the changes of internal quality of peach (juicy peach) during storage and further discuss the feasibility of predicting the quality of peach through visible /near infrared spectroscopy (VIS/NIR). Firstly, the spectra of peach in two storage conditions were collected with the fruit quality dynamic detection equipment, and its soluble solid content (SSC), firmness and weight were measured. Then, partial least squares discrimination analysis (PLS-DA) was used to develop the classification model of peach, and the accuracy was higher than 90 %. Finally, partial least squares (PLS) regression combined with preprocessing methods was used to develop the models of SSC and firmness. Uninformative variable elimination (UVE) and competitive adaptive reweighted sampling (CARS) were also used to optimize the model to obtain the optimal prediction models. The results showed that CARS-PLS models of peach at the room temperature were the optimal, with prediction correlation coefficient (Rp) at 0.819, and the root mean square error of prediction (RMSEP) at 0.841°Brix. The Rp and RMSEP of firmness were 0.811 and 0.912 N, respectively. In cold storage, the PLS model of SSC processed by CARS was the optimal with the Rp of 0.828 and RMSEP of 0.816°Brix. The Rp and RMSEP of the optimal firmness model were 0.785 and 1.188 N, respectively. This study on the quality of peach can better analyze the quality change of peach during storage, and has certain value for guiding the storage of peach and subsequent related research.