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中国冬播小麦面粉颗粒度分布及近红外透射光谱测试技术研究
引用本文:CHEN Feng,Nagamine T,张艳,何中虎,王德森,Hisashi Yoshida. 中国冬播小麦面粉颗粒度分布及近红外透射光谱测试技术研究[J]. 作物学报, 2005, 31(3): 302-307
作者姓名:CHEN Feng  Nagamine T  张艳  何中虎  王德森  Hisashi Yoshida
作者单位:中国农业科学院作物育种栽培研究所/ 国家小麦改良中心,北京100081
基金项目:中国科学院资助项目,国家高技术研究发展计划(863计划),国家重点基础研究发展计划(973计划)
摘    要:面粉颗粒度是影响小麦食品加工品质的重要性状。以2001-2002年度来自北部冬麦区、黄淮冬麦区、长江中下游冬麦区和西南冬麦区的256份小麦品种(系)为材料,用激光散射颗粒度分析仪和近红外透射光谱技术对面粉颗粒度进行了研究。结果表明,我国小麦面粉颗粒度分布特点为从北向南,硬质麦分布比例逐渐减少,软质麦分布比例逐

关 键 词:普通小麦  面粉颗粒大小  近红外光谱技术  定标集  预测集
收稿时间:2004-02-19
修稿时间:2004-02-19

Flour Particle Size Distribution in Chinese Winter Wheat and Measurement by Near Infrared Spectroscopy
CHEN Feng,Nagamine T,ZHANG Yan,HE Zhong-Hu,WANG De-Sen,Hisashi Yoshida. Flour Particle Size Distribution in Chinese Winter Wheat and Measurement by Near Infrared Spectroscopy[J]. Acta Agronomica Sinica, 2005, 31(3): 302-307
Authors:CHEN Feng  Nagamine T  ZHANG Yan  HE Zhong-Hu  WANG De-Sen  Hisashi Yoshida
Affiliation:Institute of Crop Breeding and Cultivation/National Wheat Improvement Center, Chinese Academy of Agriculture Sciences, Beijing 100081
Abstract:flour particle size is an important quality parameter which has a significant effect on food processing. The objective of this study is to investigate the distribution of flour particle size in Chinese winter wheat cultivars and the rapid testing method by near infrared transmittance spectroscopy. Total of 256 wheat cultivars and advanced lines from four major wheat regions, i.e., North Winter Region, Yellow Huai Facultative Wheat Region, Middle and Low Yangtze Winter Region, and Southwestern Winter Wheat Region, were grown in Anyang in 2001-2002 season. They were used to measure flour particle size with laser diffraction particle size analyzer and near infrared transmittance spectroscopy (NITS), respectively. According to flour particle size by laser diffraction particle size analyzer, the Chinese winter wheat could be divided into three distinguished types, hard, soft and mixed wheats. It has been found that the hard wheat were dominant in North China, while a high percentage of soft wheat cultivars in South China. The percentage of hard, soft, and mixed wheat were 59.4%, 28.1% and 12.5%, respectively. A determination coefficient of prediction set of 0.92 was observed between flour particle size determined by laser diffraction particle size analyzer and those predicted by NITS. Prediction residual error sum of square (PRESS) and cross validation were adopted to find the optimal number of principal components in developing calibration model. Model was optimized by deleting outlier samples twice and then RSQ of calibration set increased from 0.82 to 0.92 and SEC decreased from 12.75 to 8.54. This model could be used for selection of hardness in wheat breeding program, wheat quality classification and marketing. In addition, we found that the model developed with total samples was a little inferior to those developed with wheat samples from various wheat regions.
Keywords:Common wheat  Flour particle size  Near infrared spectroscopy  Calibration set  Prediction set
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