Abstract:

Soluble solid content (SSC) is one of the most critical quality indexes of peach. Nondestructive detection of SSC in peaches is mainly realized by visible/near-infrared (VIS/NIR) spectroscopy, but it has some limitations. In this paper, the applications of NIR spectroscopy in the nondestructive detection of peaches under different circumstances were comprehensively explored and analyzed. The modeling and detection methods of different cultivars were analyzed and compared to improve the accuracy of nondestructive detection of SSC in peaches. In this study, three local cultivars of peaches collected from Fenghua were selected as the research object, and the spectral data were acquired for modeling. Firstly, the self-modeling H-100 nondestructive sugar content detector was used to conduct the experiment. The results showed that the root mean square error (RMSE) and R² values of the NIR models established on different cultivars were different, among which the Xinyu model obtained the best results, with RMSE of 0.22 and R² of 0.98. The model based on single cultivars had the best predictive ability to detect the respective cultivar, but it performed worse when detecting other cultivars. The more cultivars of peaches, the larger amount of data, the better the model. The R² of the model based on three cultivars was as high as 0.92. Secondly, Kubota K-SS300, ATAGO PAL-HIKARi 10, and self-modeling H100 were used to detect the same part of three local cultivars of Fenghua peaches, respectively. The correlation analysis was conducted between the values predicted by the nondestructive detectors and those obtained by the destructive ATAGO PAL-1. The results showed that the H100 detector had the highest predictive accuracy for all the cultivars. Next, SSC detection at different depths of mixed cultivars of Fenghua peaches. The results showed that the SSC levels obtained by the H100 device could better reflect the overall quality. In contrast, Kubota K-SS300 and ATAGO PAL-HIKARi 10 could only reflect the SSC levels of the external areas. Finally, the influence of the SSC levels of two peach cultivars on the result of H100 detector under different hardness conditions was explored. The results showed that the decrease in peach hardness would significantly affect the nondestructive detection of SSC in peaches. Therefore, the H100 nondestructive detector combined with the effective prediction model could better avoid the limitations of NIR spectroscopy and provide a reference for the nondestructive detection of SSC in peaches.

Key words: peach, nondestructive testing, brix, model