The moisture content of persimmons during drying was monitored by hyperspectral imaging technology. All persimmons were dried using a hot-air dryer at 40 °C and divided into seven groups according to drying time: semi-dried persimmons (Cont), 1 day (DP-1), 2 days (DP-2), 3 days (DP-3), 4 days (DP-4), 5 days (DP-5), and 6 days (DP-6). Shortwave infrared hyperspectral spectra and moisture content of all persimmons were analyzed to develop a prediction model using partial least squares regression. There were obvious absorption bands: two at approximately 971 nm and 1452 nm were due to water absorption related to O–H stretching of the second and first overtones, respectively. The R-squared value of the optimal calibration model was 0.9673, and the accuracy of the moisture content measurement was 95%. These results indicate that hyperspectral imaging technology can be used to predict and monitor the moisture content of dried persimmons during drying.

通过高光谱成像技术监测柿子在干燥过程中的水分含量。所有柿子均用40℃热风干燥机烘干，按干燥时间分为七组：半干柿子（Cont）、1天（DP-1）、2天（DP-2）、3天(DP-3)、4 天 (DP-4)、5 天 (DP-5) 和 6 天 (DP-6)。分析了所有柿子的短波红外高光谱和水分含量，以使用偏最小二乘回归建立预测模型。有明显的吸收带：大约 971 nm 和 1452 nm 处的两个分别是由于与第二和第一泛音的 O-H 拉伸相关的吸水。最优校准模型的R平方值为0.9673，水分含量测量精度为95%。