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NIR Spectroscopy Model Construction and Application for Amino Acid Composition in Rice Grain

Author: ZhangBin
Tutor: WuJianGuo
School: Zhejiang University
Course: Crop Genetics and Breeding
Keywords: Brown rice Milled rice Amino acids Near Infrared Reflectance Spectroscopy Calibration equation
CLC: S511
Type: Master's thesis
Year: 2010
Downloads: 58
Quote: 0
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Abstract


Near infrared spectroscopy is a new physical testing technology developed rapidly in the late 1980s, the technology has a non-polluting, low consumption, non-destructive, can be realized Simultaneous Determination of Multicomponent and fast analysis, have been classified as international or industry standard, widely used in many fields. The purpose of this study was to establish the amino acid content of rice (milled rice and brown rice) NIR calibration model, expand research and milled rice scaling model of amino acid content, in order to improve the applicability and predictive ability of the model, the nutritional quality of rice amino acids detection and rice quality breeding provides a quick and simple method of measuring. Amino acid content in brown rice near infrared calibration equation created and applied research, 279 brown rice and brown rice flour samples were selected from 518 groups in the multi-year, and two different samples (approximately 3 g and 500 mg) near-infrared spectroscopy, scanning, each amino acid content was determined by acid hydrolysis. Selection of mathematical processing (2,8,8,1) / Standard normal variate transformation and detrending (SNV D) the best combination of pretreatment method creates NIR calibration models found based on 3 g spectrum amino acid content of brown rice flour given The best calibration equation based 500mg the brown rice scaling effect slightly worse. Standard error of prediction (SEP) for the cross validation of the calibration equations of the remaining amino acids except cysteine, methionine, and tyrosine, the standard error (SECV), 0.010% -0.063%, 0.011% -0.066%, crosscheck The coefficient of determination (1-VR) and predict the coefficient of determination (R 2 ) were 87.8% -96.0% 83.7% -94.7%, the ratio of the standard deviation, standard error of prediction (SD / SEP) reached 2.421 -4.333. Since the complete decomposition of tryptophan in the acid hydrolysis by alkaline hydrolysis - spectrophotometric determination of tryptophan content of milled rice. Derivative processing (1, 4, 4, 1) and the SNV D spectra preprocessing, combined with MPLS regression method to establish the NIR calibration equation established equation standard error of calibration (SEC: 0.007%), SECV (0.008 %) and SEP (0.007%) lower, the corresponding calibration coefficient of determination (RSQ: 88.4%) ,1-VR (85.0%) and R of 2 (87.1%). Studied the correlation between the milled rice flour spectra with tryptophan content value interpretation load (Loading) of the first three MPLS variable factor. Two groups (P 1 = 220 and P 2 = 225) 445 NIR calibration model for the expansion of the material content of 17 amino acids used for rice research. Explore different modes of data conversion and regression methods of artificial neural network (ANN) calibration algorithm results, optimize and select the best pretreatment methods (1,8,8,1) / (SNV D) Combined with our improved partial least squares (MPLS) and ANN algorithm established milled rice amino acid calibration equations. The results showed that ANN algorithm scaling equation is slightly worse than MPLS method. Choose glutamic acid, phenylalanine and arginine MPLS calibration model to expand research results show that the calibration equation predicted effect of the two groups was significantly better than using only one calibration equation groups; from two The predictive ability of the two groups in the use of the SELECT program to select 189 samples (NH = 0.26), the establishment of the calibration equation scaling effects of the two groups are similar. Application to establish rice rapid analysis of amino acids near infrared screening of \Near-infrared spectroscopy technology can also be developed in this study for the rapid screening of the middle of the rice breeding materials and germplasm evaluation and rice processing industry in quality control of provided favorable detection tools.

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