近红外光谱技术快速预测大豆氨基酸

为探索近红外光谱技术在大豆氨基酸测试中的应用,寻找一种快速的检测方法,以167份大豆Glycine max(L.)Merr.]种子为材料,采用傅里叶变换近红外光谱技术(FT-NIRS)对经高效液相色谱法(HPLC)分析的18种氨基酸含量进行模拟。结果显示:天冬氨酸(R2CV=0.85)、谷氨酸(R2CV=0.86)、丝氨酸(R2CV=0.82)、甘氨酸(R2CV=0.89)、酪氨酸(R2CV=0.83)、苯丙氨酸(R2CV=0.78)、异亮氨酸(R2CV=0.86)和色氨酸(R2CV=0.81)及15种氨基酸总和(R2CV=0.82)可利用FT-NIRS准确预测;苏氨酸、精氨酸、丙氨酸、缬氨酸、亮氨酸和胱氨酸检测模型有一定的参考价值,可用来进行相对含量的估测;而对组氨酸、赖氨酸、脯氨酸和蛋氨酸的预测不准确。本研究进一步证明,利用FT-NIRS技术预测大豆主要氨基酸组分是稳定可行的。

The Prediction of Nondestructive Measurement of Amino Acids Composition

To establish a rapid, efficient and low-cost method of applying Fourier-Transform Near-Infrared Reflectance Spectroscopy (FT-NIRS) to detecting amino acids in soybean, we selected 167 representative soybean flour samples from a large original population and utilized FT-NIRS to predict the contents (which were analyzed by HPLC) of eighteen amino acid species. According to the data we obtained, aspartate (R2CV = 0.85), glutamate (R2CV = 0.86), serine (R2CV = 0.82), glycine (R2CV = 0.89), tyrosine (R2CV = 0.83), phenylalanine (R2CV = 0.78), isoleucine (R2CV = 0.86), ryptophane (R2CV = 0.81) and the total amino acids content (R2CV = 0.82) can be detected by FT-NIRS accurately; the detected models of threonine, arginine, alanine, valine, leucine, and cystine are valuable as references and can be used to estimate the relative contents; the content prediction of histidine, lysine, proline and methionine is inaccurate. This study has further demonstrated the stability and feasibility of using FT-NIRS to detect the major amino acid components in soybean.