Journal of Agricultural Machinery Engineering ISSN:2799-8673(Print) 2799-8819(Online) 농업기계공학

The objective of this study was to diagnose the temperature stress of paprika seedlings based on visible/near-infrared (VIS/NIR) hyperspctral image and chlorophyll content data. As the partial least squares (PLS) regression model was applied to the calibration data, seven significant wavelengths of 477, 501, 543, 647, 680, 704, and 751 nm were selected and in the stepwise multiple linear regression (SMLR) model, three wavelengths of 680, 704, and 803 nm were selected. The coefficients of determination of the PLS regression model and SMLR model for validation data were 0.70 and 0.59, respectively. The root mean square deviations of the PLS regression and SMLR model were 6.89 and 8.01, respectively. These results show the potential of VIS/NIR hyperspectral imaging technology with a proper model as a nondestructive method for detecting temperature stress of paprika seedlings.