Estimating the amino acid composition in milled rice by near-infrared reflectance spectroscopy

被引:134
|
作者
Wu, JGG [1 ]
Shi, CH
Zhang, XM
机构
[1] Zhejiang Univ, Coll Agr & Biotechnol, Dept Agron, Hangzhou 310029, Peoples R China
[2] Zhejiang Acad Agr Sci, Crop Res Inst, Hangzhou 310021, Peoples R China
关键词
rice; amino acid; near-infrared reflectance spectroscopy (NIRS); nutritional quality;
D O I
10.1016/S0378-4290(02)00006-0
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
This study was conducted to develop near-infrared reflectance spectroscopy (NIRS) equations to predict the amino acid and nitrogen content of milled rice powder. The samples were scanned by NIRS and analyzed for amino acid composition and total nitrogen by HCl hydrolysis-HPLC methodology and Kjeldahl method, respectively. The NIRS equations of 15 different amino acids, except for cystine, methionine and histidine, showed high coefficients of determination (RSQ = 84.8-97.5%) and low standard errors in calibration (SEC) with 3 g samples for NIBS scanning, while the calibration models of cystine and histidine could explain less variation (RSQ with 77.7 and 65.0%). Calibration for methionine was not suitable to estimate methionine because of its very low RSQ (10.2%). The equations for total amino acids and nitrogen also showed high RSQ and lower SEC, respectively. Furthermore, calibration equations developed with only about 500 mg samples showed similar accuracy and reliability to those with the full cup by using the same calibration set. The equations developed for relative contents of total amino acids did not show good, effective calibration and cross-validation. Only eight different amino acids can be predicted using the equations because their RSQs of calibration were higher than 50.6% (50.6-73.9%). The others cannot be estimated with confidence by their relative contents due to lower RSQ in calibration. Moreover, their relative contents can be calculated from their absolute contents estimated by NIRS calibration. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:1 / 7
页数:7
相关论文
共 50 条
  • [31] Study on developing calibration models of fat acid composition in intact rapeseed by near infrared reflectance spectroscopy
    Wu, JG
    Shi, CH
    Zhang, HZ
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26 (02) : 259 - 262
  • [32] Application of near-infrared reflectance spectroscopy to evaluate the lutein and β-carotene in Chinese kale
    Chen, Xinjuan
    Wu, Jianguo
    Zhou, Shengjun
    Yang, Yuejian
    Ni, Xiaolei
    Yang, Jing
    Zhu, Zhujun
    Shi, Chunhai
    JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2009, 22 (02) : 148 - 153
  • [33] Detection of fraud in high-quality rice by near-infrared spectroscopy
    Liu, Yachao
    Li, Yongyu
    Peng, Yankun
    Yang, Yanming
    Wang, Qi
    JOURNAL OF FOOD SCIENCE, 2020, 85 (09) : 2773 - 2782
  • [34] Near-infrared, mid-infrared or combined diffuse reflectance spectroscopy for assessing soil fertility in rice fields in sub-Saharan Africa
    Johnson, Jean-Martial
    Vandamme, Elke
    Senthilkumar, Kalimuthu
    Sila, Andrew
    Shepherd, Keith D.
    Saito, Kazuki
    GEODERMA, 2019, 354
  • [35] Dynamic monitoring of fatty acid value in rice storage based on a portable near-infrared spectroscopy system
    Jiang, Hui
    Liu, Tong
    Chen, Quansheng
    SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2020, 240 (240)
  • [36] Quantifying species composition in root mixtures using two methods: near-infrared reflectance spectroscopy and plant wax markers
    Roumet, C
    Picon-Cochard, C
    Dawson, LA
    Joffre, R
    Mayes, R
    Blanchard, A
    Brewer, MJ
    NEW PHYTOLOGIST, 2006, 170 (03) : 631 - 638
  • [37] Prediction of the nutritional composition of the crop contents of free-living scarlet macaw chicks by near-infrared reflectance spectroscopy
    Cornejo, Juan
    Taylor, Ryan
    Sliffe, Thomas
    Bailey, Christopher A.
    Brightsmith, Donald J.
    WILDLIFE RESEARCH, 2012, 39 (03) : 230 - 233
  • [38] Multi-parameter analysis of corn using near-infrared reflectance spectroscopy and chemometrics
    Samuel, P. Praveen
    Chinnu, T.
    Lakshmanan, Madan Kumar
    MATERIALS TODAY-PROCEEDINGS, 2015, 2 (03) : 949 - 953
  • [39] Near-Infrared Reflectance Spectroscopy is a Rapid, Cost-Effective Predictor of Seagrass Nutrients
    Ivan R. Lawler
    Lemnuel Aragones
    Nils Berding
    Helene Marsh
    William Foley
    Journal of Chemical Ecology, 2006, 32 : 1353 - 1365
  • [40] Determination of Nitrogen Concentration in Fresh Pear Leaves by Visible/Near-Infrared Reflectance Spectroscopy
    Wang Jie
    Zhao Hua-bing
    Shen Chang-wei
    Chen Qiao-wei
    Dong Cai-xia
    Xu Yang-chun
    AGRONOMY JOURNAL, 2014, 106 (05) : 1867 - 1872