Binary mixtures of waxy wheat and conventional wheat as measured by NIR reflectance

被引:12
作者
Delwiche, Stephen R. [1 ]
Graybosch, Robert A. [2 ]
机构
[1] USDA ARS, Beltsville Agr Res Ctr, Food Qual Lab, Beltsville, MD 20705 USA
[2] Univ Nebraska, USDA ARS, Dept Agron, Lincoln, NE 68583 USA
关键词
Waxy wheat; Quantification; Mixture; Amylose; Near infrared spectroscopy; AMYLOSE; IDENTIFICATION; STARCH; PROTEINS; QUALITY; FLOURS;
D O I
10.1016/j.talanta.2015.08.063
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Waxy wheat contains very low concentration (generally <2%) of amylose in endosperm starch, in contrast to conventional wheat whose starch is typically 20% amylose, with the balance being the branched macromolecule, amylopectin. With the release of a commercial hard winter waxy wheat cultivar in the United States, the grain trade, milling, and processing industries seek to have a rapid technique to ensure the purity of identity preserved waxy wheat lots. Near infrared (NIR) reflectance spectroscopy, a technique widely used in the cereals industry for proximate analysis, is a logical candidate for measuring contamination level and thus is the subject of this study. Two sets of wheat samples, harvested, prepared and scanned one year apart, were used to evaluate the NIR concept. One year consisted of nine pairs of conventional:waxy preparations, with each preparation consisting of 29 binary mixtures ranging in conventional wheat fraction (by weight) of 0-100% (261 spectral samples). The second year was prepared in the same fashion, with 12 preparations, thus producing 348 spectral samples. One year's samples were controlled for protein content and moisture level between pair components in order to avoid the basis for the conventional wheat fraction models being caused by something other than spectral differences attributed to waxy and nonwaxy endosperm. Likewise the second year was controlled by selection of conventional wheat for mixture preparation based on either protein content or cluster analysis of principal components of candidate spectra. Partial least squares regression, one and two-term linear regression, and support vector machine regression models were examined. Validation statistics arising from sets within the same year or across years were remarkably similar, as were those among the three regression types. A single wavelength on second derivative transformed spectra, namely 2290 nm, was effective at estimating the mixture level by weight, with standard errors of performance in the 6-9% range. Thus, NIR spectroscopy may be used for measuring conventional hard wheat 'contamination' in waxy wheat at mixture levels above 10% w/w. Published by Elsevier B.V.
引用
收藏
页码:496 / 506
页数:11
相关论文
共 50 条
  • [41] Endosperm and amyloplast development in waxy wheat cultivars
    Liu, Juan
    Zhu, Yuangang
    Yang, Kaibo
    Song, Jian
    Xu, Tisen
    Dai, Zhongmin
    PROTOPLASMA, 2023, 261 (2) : 197 - 212
  • [42] Waxy wheat as a functional food for human consumption
    Fujita, Shuzo
    Kumagai, Takako
    Yanagimachi, Mashimi
    Sakuraba, Suguru
    Sanpei, Ryuichi
    Yamoto, Mika
    Tohara, Haruka
    JOURNAL OF CEREAL SCIENCE, 2012, 55 (03) : 361 - 365
  • [43] Endosperm and amyloplast development in waxy wheat cultivars
    Juan Liu
    Yuangang Zhu
    Kaibo Yang
    Jian Song
    Tisen Xu
    Zhongmin Dai
    Protoplasma, 2024, 261 : 197 - 212
  • [44] Effects of germination on nutritional composition of waxy wheat
    Pham Van Hung
    Maeda, Tomoko
    Yamamoto, Syota
    Morita, Naofumi
    JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, 2012, 92 (03) : 667 - 672
  • [47] Effects of Waxy Wheat Flour and Water on Frozen Dough and Bread Properties
    Yi, Jinhee
    Kerr, William L.
    Johnson, Jerry W.
    JOURNAL OF FOOD SCIENCE, 2009, 74 (05) : E278 - E284
  • [48] Registration of ten soft red winter waxy wheat germplasm lines
    Ma, Fengyun
    Sturbaum, Anne
    Baik, Byung-Kee
    JOURNAL OF PLANT REGISTRATIONS, 2022, 16 (01) : 147 - 151
  • [49] Comparison of Endosperm Amyloplast Development and Degradation in Waxy and Non-waxy Wheat
    Yu, H.
    Yang, Y.
    Chen, X. Y.
    Lin, G. X.
    Sheng, J. Y.
    Nie, J. Y.
    Wang, Q. J.
    Zhang, E. J.
    Yu, X. R.
    Wang, Z.
    Xiong, F.
    CEREAL RESEARCH COMMUNICATIONS, 2018, 46 (02) : 333 - 343
  • [50] Extraction and identification of internal granule proteins from waxy wheat starch
    Wang, Shujun
    Hassani, Mohammad E.
    Crossett, Ben
    Copeland, Les
    STARCH-STARKE, 2013, 65 (1-2): : 186 - 190