Prediction of Soluble Solids Content During Storage of Apples with Different Maturity Based on VIS / NIR Spectroscopy

Abstract. The soluble solids content (SSC) is an important quality attribute to measure the eating quality of apples, and the apple SSC during storage period will change with the storage time. In order to increase the value of apple commodities, it is necessary to carry out SSC nondestructive testing on apples during storage. In this paper, we studied the predictability of Vis-Nir (Vis-Nir, 400-1100nm) and Long-Wave Near-Infrared (LWIR, 1100-2200nm) spectra for apple SSC during storage. Apples of different maturity harvested on three dates were stored in a cold store at 0°C (± 1). The SSC and diffuse reflectance data were measured after 0, 30, 80, 150, and 180 days of storage. Partial least squares (PLS) was used to establish the prediction model. The results show that the harvest period model cannot achieve the prediction of apple SSC during storage period, and the accuracy of the fusion model at different maturity storage periods is also poor. The reason is that starch is continuously hydrolyzed to soluble sugar during storage. Therefore, three SSC prediction models for individual maturity storage periods were established. The overall effect of the model is better, and the best one is the high-maturity-LWIR model (Rc = 0.8573, RMSEC = 0.5297, Rp = 0.8417, RMSEP = 0.5669). The overall high maturity of the model is better than medium and low maturity, and LWIR is better than Vis-Nir. This study provides an important theoretical basis for improving the quality of apple industrialization during storage.