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作 者:杨小红[1] 郭玉秋[1] 傅旸[1] 胡洁云[1] 柴宇超[1] 张义荣[1] 李建生[1]
机构地区:[1]中国农业大学国家玉米改良中心,北京市作物遗传育种重点实验室,北京100094
出 处:《光谱学与光谱分析》2009年第1期106-109,共4页Spectroscopy and Spectral Analysis
基 金:国家自然科学基金项目(30571165);农业部“948”项目资助
摘 要:采用傅里叶近红外漫反射光谱技术,结合偏最小二乘法,以294份中选的普通和高油玉米自交系以及高油玉米重组自交系为样品建立了玉米籽粒四种主要脂肪酸(软脂酸、硬脂酸、油酸和亚油酸)含量和含油量的近红外光谱(NIRS)校正模型。其中,油酸、亚油酸和含油量的校正模型质量较高,交叉验证决定系数分别为0.89,0.88和0.91,外部验证决定系数分别为0.86,0.84和0.92,相对分析误差(RSP(C))均大于2.5。软脂酸和硬脂酸的校正模型不够精确,交叉验证决定系数和外部验证决定系数均小于0.80,相对分析误差(RSP(C))均小于2.5。通过实际预测进一步验证了油酸、亚油酸和含油量NIRS模型的准确性和可靠性。这些模型可应用于玉米籽粒脂肪酸含量及油分含量大批量快速测定,对玉米油分的品质育种具有重要意义。The fatty acid concentrations in maize grain were analyzed with a set of 294 samples including normal inbred lines,high-oil inbred lines and high-oil recombinant inbred lines(RIL).The method of partial least squares(PLS) regression with internal cross validation was employed to develop the measuring models of near-infrared reflectance spectroscopy(NIRS) for concentrations of four major fatty acids,palmitic,stearic,oleic and linoleic acids,as well as oil concentration in maize grain.The NIRS models were accurate for oleic acid,linoleic acid and oil concentrations.The determination coefficients of these models in cross validation were 0.89,0.88 and 0.91,respectively;the determination coefficients in external validation were 0.86,0.84 and 0.92,respectively;and the ratio of standard deviation(SD) to root mean square error of validation(RMSEV) in both calibration and external validation sets(RSC(P)) was higher than 2.5.But the models for palmitic and stearic acid concentrations were not accurate enough with determination coefficients in cross validation and external validation lower than 0.80,and RSC(P) lower than 2.5.Further practical validation showed that the predicted results by using NIRS models for oleic acid,linoleic acid and oil concentrations were accurate and reliable,which will be a useful approach to the measurement of a large number of breeding samples during genetic improvement of oil quality and quantity in maize.
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