近红外光谱法同时分析油菜9种品质参数的研究

应用近红外光谱技术(NIRS)对油菜种子9种主要品质参数进行了分析研究,并建立了数学模型。内部交叉验证结果表明,油菜种子油酸、亚油酸、亚麻酸、芥酸和饱和脂肪酸的决定系数R2分别为98．97％, 93．02％,86．49％,99．53％和84．78％,均方差分别为2．20,1．12,0．46,1．51和0．29;油菜种子含水量、含油量、硫苷和蛋白质含量的R2分别为99．64％,98．91％,82．46％-98．40％和89．32％,均方差分别为0．23,0．39,2．59- 13．50和0．74。对于含量较小而极差较大的硫苷采用分段建模,可提高分析结果的准确性。外部检验结果表明:各参数近红外预测值和标准方法之间的相关系数高达0．883-0．992;平均相对误差较小,为2．62％-8．19％;t测验差异不显著。研究表明NIRS技术具有检测快速、结果准确、制样简便、无污染和无损伤等优点,已经应用于油菜种子品质分析,并且分析参数还可以扩展。

Determination of quality factors in intact rapeseed by near infrared reflectance spectroscopy (NIRS)

Near infrared reflectance spectroscopy (NIRS) was performed to determin 9 quality factors in intact rapeseed and correlation models were established. The determination coefficients (R2) of most fatty acid content (C18:1.C18:2,C18 : 3,C22:1 and Saturated fatty acid) were estimated to be 98. 97%, 93. 02%,86. 49%,99. 53% and 84. 78% ,and RMSECV to be 2. 20,1.12,0.46,1. 51 and 0. 29,respectively. R2 of water content, oil content, total glucosinolate and protein content were estimated to be 99.64%, 98. 91%,82. 46% -98. 40% and 89. 32%,and RMSECV to be 0. 23,0. 39,2. 59-13. 50 and 0. 74,respectively. Results can be improved by calibrating sectional model for low content and large range total glucosinolate. Correlation coefficient of quality factors in rapeseed was 0. 883 -0. 992 between NIRS and standard methods, and mean relative error was 2. 62% - 8. 19%. Moreover there was no significant difference in student's test. NIRS is a non-destructive,rapid,efficient and pollution-free technique. It is thus concluded that NIRS analysis can be applied to quantitative analysis of quality factors of rapeseed.