Aplication of Near Infrared to Determine Viability of ‘Ciherang’ Paddy (Oryza sativa) Seed.

Abstract

Near infrared (NIR) spectroscopy in the range of 1000-2500 nm was studied for its ability to predict the seed viability such as germability, vigor index, maximum growth potential and the biochemistry composition such as water content, soluble protein, and free faty acid of the ciherang paddy seed following 0, 2, 4, 6 and 8 days acclerated aging (45oC, RH >90%). A total of 60 sample groups consist of 40 g paddy seed per sample ware used. Fourty samples were used for calibration and 20 samples were used for validation. Artificial neural network (ANN) and partial least squares (PLS) regression methods were used to build the prediction model. The good model should have a low standard error of calibration (SEC), a low standard error of performance (SEP), a high correlation coefficient, a small difference between SEC and SEP and have ratio performance deviation (RPD) higher than 2.5. The result showed that kind of original and pre processing spectra influenced the value of evaluation ANN and PLS model. The structure of ANN also influence the value of evaluation model. The best model to predict germability was 10-5-3 ANN using standard normal variate of reflectan spectra with RPD = 2.2359 and r validation = 0.8947, to predict vigor index was 10-5-1 ANN using 2nd derivative of reflectan spectra with RPD=3.6842 and r validation 0.9645, to predict maximum growth potential was 10-5-1 ANN using 2nd derivative of reflectan spectra with RPD=2.5572 and r validation 0.9204, to predict water content was PLS using absorbant spectra with RPD=9.6028 and r validation 0.9946, to predict soluble protein was 5-5-1 ANN using 2nd derivative of reflectan spectra with RPD=3.9615 and r validation 0.9686, and to predict free faty acid was 10-20-1 ANN model using 2nd derivative of absorbant spectra with RPD=4.0290 and r validation 0.9688.