Judul: Prediction of moisture, protein and carbohydrate content of sorghum by using near infrared (nir) method
Abstrak: Sorghum is local resources that can be used as a substitution of corn on feed. Moisture, protein and carbohydrate contents of sorghum can be predicted using near infrared method. The aim of this research was to apply NIR method to analyze moisture, protein and carbohydrate contents of sorghum. The calibration methods that used in this research are principal component regression (PCR) and partial least square (PLS). Some data treatments are applied on absorbance and reflectance spectrum. They are smooth average 3 points, normalization between 0-1, second derivative Savitzky-Golay 9 points, combination of smooth average 3 points and second derivative Savitzky-Golay 9 points, and combination of smooth average 3 points, normalization between 0-1, and second derivative Savitzky-Golay 9 points. PLS method with absorbance data and combination of smooth average 3 points, normalization between 0-1, and second derivative Savitzky-Golay 9 points is the best calibration method and data treatment to predict moisture content of sorghum. The best calibration method to predict protein content is PLS with absorbance data and second derivative Savitzky-Golay 9 points data treatment. PLS method with absorbance data and second derivative Savitzky-Golay is the best calibration method and data treatment to predict carbohydrate content. Standard error of prediction (SEP) and coefficient of variability (CV) respectively were 0.005% and 0.04% for moisture content prediction, 0.01% and 0.18% for protein content prediction, 0.01% and 0.02% for carbohydrate content prediction.
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Judul: Aplikasi Teknologi Near Infrared untuk Pendugaan Viabilitas Benih Padi (Oryza sativa) Varietas Ciherang
Abstrak: 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.
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Judul: Embriogenesis ikan buta (Astyanax fasciatus)
Abstrak: Ikan buta Astyanax fasciatus adalah spesies ikan unik dari famili Characidae yang menempati perairan dalam gua di Wilayah La Cueva Chica-San Luis Potasi-Mexico. Ikan ini memiliki mata yang tereduksi (Blind Cavefish) dan warna kulit merah muda, pucat serta mengkilap.
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