糙米蛋白质含量与矿质元素含量的相关分析及NIRS模型的建立

Correlation Analysis of Protein Content and Mineral Content in Brown Rice and Establishment of the Math Model for the NIRS Analysis

利用162份不同类型水稻种质,采用微量凯氏定氮法测定蛋白质含量,原子吸收分光光度法(atomic absorption spec-trophotometry,AAS)测定Mg、Ca、Fe、Zn、Cu和Mn等6种矿质元素含量,火焰光度法测定K含量,分光光度法测定P含量。对糙米蛋白质与矿质元素、矿质元素间进行相关分析;并利用测定的蛋白质含量的化学值,采用偏最小二乘法(partial leastsquares,PLS)建立糙米蛋白质预测的校正模型。结果表明,糙米矿质元素含量大小顺序为P>K>Mg>Ca>Zn>Fe>Cu>Mn,蛋白质与P、K、Cu和Mn等矿质元素极显著或显著正相关;通过比较光谱预处理方法在不同谱区的处理效果:采用一阶导数预处理、谱区为11995.7～7498.3/cm和6102～4597.7/cm建立校正模型的检验和预测效果最佳,糙米蛋白质的近红外测定值和化学测定值之间有较高的相关性,其校正决定系数为92.89,外部验证决定系数为89.91;筛选到小黑谷、小红米和紫糯米等高蛋白、富矿质营养的种质材料,可作为富营养稻米品种创新的亲本材料;通过利用蛋白质和矿质元素间的相关性,借助近红外分析技术(Near-infrared Reflectance Spectroscopy,NIRS)辅助测定蛋白质含量,并间接选择富矿质营养水稻种质,聚合高蛋白和富2种以上矿质元素,可能是水稻营养品质育种的一条有效途径。

Using 162 rice samples as materials,the method of semimicro-kjeldahl was employed to determinate the protein content,while atomic absorption spectrophotometry （ASS） was employed to determinate the contents of Ca, Mg, Fe, Zn, Cu, and Mn, colorimetry with phosphate-molybdenum-blue complex was employed to determinate the content of P,and flame photometry was employed to determinate the content of K in brown rice. The relationships of protein content and mineral content, different mineral element contents in brown rice were investigated. The chemo- metrical method of partial least squares gression was used to establish the calibration model of protein content in brown rice. The results showed that the elemental concentrations in brown rice were in turn of P 〉 K 〉 Mg 〉 Ca 〉 Zn 〉 Fe 〉 Cu 〉 Mn. Significant positive correlations were found between protein content and mineral contents, including P, K, Cu,and Mn. In addition,the optimal model was developed by the spectral data pretreatment of the first derivative in 11995.7 -7498.3/era and 6102 -4597.7/cm, by analyzing spectral data pretreatment and light frequency ranges. This model＇s calibration coefficient and validation coefficient were 92.89 and 89.76, respec- tively. The model showed significant correlation and lower error between near-infrared value and true value. The germplasm of rice resource with high protein content and rich mineral contents, such as Xiaoheigu,Xiaohongmi and Zinuomi had been selected. Good calibration equation was successfully developed for protein content and the equa- tion showed satisfactory determination coefficients. Finally, a probably effective way to improve protein content of rice was proposed. Combination of some special characteristics, such as protein content, P, K, Cu, and Mn etc, was one of the effective approaches to increase nutrient of rice. This NIRS-assisted-selection could be a very efficient method to improve protein content and mineral contents in rice breeding programs.