玉米籽粒直链淀粉含量的近红外透射光谱无损检测

Whole Kernel Detection:Determination of Amylose Content of Maize with Near-Infrared Transmittance Spectroscopy

以214份玉米样品为材料,利用近红外谷物分析仪对样品进行光谱扫描,并测定直链淀粉含量的参比数据,借助于WinISI软件,采用多种数学处理方法和不同的回归统计方法进行定标曲线的开发,优化得到了玉米籽粒直链淀粉含量测定的近红外定标方程,其中直链淀粉占总淀粉含量及直链淀粉占样品干重两个定标方程的定标标准偏差(SEC)、定标相关系数(RSQ)、交叉验证标准误差(SECV)和检验工作标准误差(SEP)分别为2.3201和1.2064、0.8860和0.8856、2.5896和1.3769、3.368和2.133。通过内部交叉验证和外部交叉验证及对其它的231份自交系、杂交种和高直链淀粉自交系进行预测,结果表明,近红外分析技术具有较高的准确度,能代替常规化学分析方法应用于玉米育种的早代材料直链淀粉含量的筛选,可作为高直链淀粉玉米育种的一种简便快速的无损筛选技术。

Using 214 inbred and hybrid kernel samples of maize as materials, a study was conducted to investigate the whole kernel detection method for measuring amylose content by near - infrared transmittance spectroscopy （NITS）. The samples were scanned by FOSS Infratec 1241 Analyzer. With powerful WinISI calibration maker software, several mathematics treatments to the sample spectra and several different regression methods were adopted to optimize a good calibration equation for determination of amylose content in maize. The standard error of calibration （ SEC）, regression squared （ RSQ ）, standard error of cross - validation （ SECV）, and standard error of prediction （SEP） of calibration selected about the starch amylose content and the grain amylose content are 2. 320 1 and 1. 206 4, 0. 886 0 and 0.885 6, 2. 589 6 and 1. 376 9, 3. 368 and 2. 133, respectively. The method of NITS exhibits high accuracy in prediction tests of cross validation and independent validationl Using the calibration mode to predict the amylose content of other 231 samples, results show its good application value. The NITS detection method could be used for early generation selection in maize breeding program and for quick test of maize quality.