摘要
应用近红外光谱法以稻谷、糙米、精米、糙米粉和精米粉为扫描材料分别建立了粳稻直链淀粉含量的预测模型。结果表明采用光谱预处理的校正效果比不采用预处理的好,用偏最小二乘法(PLS)获得的粳稻稻谷、糙米、精米、糙米粉、精米粉的回归模型和交叉验证结果为:最优校正决定系数(R2)和交叉检验均方误差(RMSECV)分别为0.8136、2.74,0.8864、2.56,0.8915、2.59,0.9261、2.26,0.9505、1.83,粉碎性样品的误差比整粒样品的误差小。育种实践中,低世代可选用糙米、高世代可选用糙米粉或精米粉作为扫描样本测定稻米直链淀粉含量。
The amylose content prediction models for short -grain rice were established by using near infrared spectroscopy and by scanning rough rice, brown rice, milled rice, brown rice flour, and milled rice flour. Results show that calibration effect by using pre - spectral treatment is better than direct treatment. The regression models derived from the partial least squares （PLS） for rough rice, brown rice, milled rice, brown rice flour, and milled rice flour, and the cross -certification results indicate that absolute error is less by using the flour samples, and the optimal calibration determination coefficient （R^2） and cross- examination mean square errors （RMSECV） are 0.8136, 2.74 ; 0. 8864, 2.56 ; 0. 8915, 2.59 ; 0. 9261,2.26 ; 0. 9505, 1.83 respectively. In terms of a prediction model for amylose content, it is proposed that brown rice can be chosen as a scanning sample when earlier generation selections are carried on, and brown rice flour and milled rice flour can be chosen while higher generation selections are carried on in rice breeding practice.
出处
《中国粮油学报》
EI
CAS
CSCD
北大核心
2007年第3期149-153,共5页
Journal of the Chinese Cereals and Oils Association
基金
浙江省科技攻关项目(011102471
2004C22009
2005D70053
2005C22016)
关键词
近红外光谱法
水稻
直链淀粉含量
快速测定
near infrared spectroscopy, rice, amylose content, rapid analysis
