甘蓝型油菜脂肪酸组分近红外分析模型构建

对一批芥酸含量接近0、油酸含量在60％～80％的高油酸油菜脂肪酸组分建立近红外分析模型,旨在提高近红外模型用于高油酸油菜的预测性能,为高油酸育种提供快速品种选择手段.169份油菜样品扫描近红外光谱,采用气相色谱法测定脂肪酸组分含量,结合定标技术进行近红外建模.结果显示:油酸、亚油酸、亚麻酸的建模效果较好,定标相关系数RSQ分别为0.957、0.922、0.891,交叉检验和外部检验都具有较高的相关系数(1-VR,RSQ)和较低的标准差(SECV,SEP):1-VR分别为0.8926、0.8542、0.8008;RSQ分别为0.926、0.867、0.855;SECV分别为1.8638、1.5288、0.8672;SEP分别为1.540、1.506、0.725.所建模型可用于油菜高油酸育种早期材料的快速筛选,用于育种实践.

Establishment of near infrared analytic model for major fatty acids content of Brassica napus L.

In order to improve the prediction performance of NIR model for high oleic acid rapeseed and provide a rapid selection method for high oleic acid breeding, we established NIR model of fatty acids content based on a group of high oleic acid rapeseed, which the erucic acid content was 0 approximately, while the oleic acid content ranged from 60% to 80%. The near infrared model was generated based on the near infrared spectrum data from a set of 169 rapeseed samples, the analysis of the fatty acid content determined by gas chromatography and the combination of calibration technology. The results showed that the oleic acid, linoleic acid and linolenic acid presented a better modeling effect, the RSQ (calibration correlation coefficient) were 0.957,0.922,0.891. The cross-validation and external validation exhibited higher correlation coefficient (1-VR: 0.8926, 0.8542, 0.8008; RSQ: 0.926, 0.867, 0.855) and lower standard deviation (SECV: 1.8638, 1.5288, 0.8672; SEP: 1.540, 1.506, 0.725) respectively. It concludes that the model can be used for rapidly screening early material of high oleic acid breeding, and can be applied in the practice of breeding.