Akademik Veri Yönetim Sistemi
Türk Tarım - Gıda Bilim ve Teknoloji dergisi, cilt.8, sa.8, ss.1636-1642, 2020 (Hakemli Dergi)
The application of near-infrared reflectance spectroscopy (NIRS) and multivariate analysis fordetermining the seed germination rate of corn genotypes was assessed. Seed samples about 90 grbelong to commercial and local corn varieties at various ages were scanned with FT-NIRS on thereflectance mode from 1000 to 2500 nm wavelength. Filter paper technique showed the seedgermination rates varied between 18-100% depending on the genotypes after 7 days at ±25°C.Partial least squares regression (PLSR) was applied to the reference values corresponding to thespectra. The best statistical results obtained from the pre-treatment combinations of SmoothSavitzky-Golay 9 Points (sg9), MSC full and normalization to unit length (nle). The regressioncoefficient of calibration (R2C) and prediction (R2P) of the created NIRS calibration viachemometric software NIRCal are realized 0.97 and 0.98 respectively for the property of corngermination rate. The standard error of both calibration (SEC) and prediction (SEP) were almostoverlapping (4.17%, 4.61% respectively). The prediction accuracy of the final NIRS model wasquite reasonable with the acceptable root mean standard error of prediction (RMSEP) as 8.88%.According to the residual predictive deviation (RPD) index (4.18), the accuracy of the NIRS modelregarded as in the best category. Therefore, the NIRS model developed here is sufficient to predictthe corn seed germination rate very fast and non-destructively without using any regents.