Large-Scale Screening of Intact Tomato Seeds for Viability Using Near Infrared Reflectance Spectroscopy (NIRS)

Near infrared reflectance spectroscopy (NIRS), a non-destructive and rapid analytical method, was used to examine the possibility of replacing a method for the large-scale screening of tomato seed viability. A total of 368 tomato seed samples were used for development and validation of an NIRS calibration model. The accelerating aging method (98 ± 2% R.H., 40 ◦C) was employed for preparation of a calibration set (n = 268) and a validation set (n = 100) with wider seed viability. Among the tomato NIRS calibration models tested, the modified partial least square (MPLS) regression produced the best equation model. Specifically, this model produced a higher RSQ (0.9446) and lower SEC (6.5012) during calibration and a higher 1-VR (0.9194) and lower SECV (7.8264) upon cross-validation compared to the other regression methods (PLS, PCR) tested in this study. Additionally, the SD/SECV was 3.53, which was greater than the criterion point of 3. External validation of this NIRS equation revealed a significant correlation between reference values and NIRS-estimated values based on the coefficient of determination (R2), the standard error of prediction (SEP (C)), and the ratio of performance to deviation (RPD = SD/SEP (C)), which were 0.94, 6.57, and 3.96, respectively. The external validation demonstrated that this model had predictive accuracy in tomato, indicating that it has the potential to replace the germination test.