【摘要】 建立花生籽仁粗蛋白、粗脂肪、油酸、亚油酸含量的近红外光谱快速测定方法。利用波通DA7200型近红外分析仪采集近红外光谱，采用凯氏定氮法、索氏提取法分别测定粗蛋白、粗脂肪的含量，采用气相色谱法测定油酸、亚油酸的相对含量，采用偏最小二乘法，构建花生籽仁主要品质指标含量的近红外预测模型。结果表明，模型对花生籽仁粗蛋白、粗脂肪、油酸、亚油酸含量的决定系数分为0.9270、0.9647、0.9915、0.9915，均方根误差分别为0.8702、0.5631、1.6671、1.4040。经外部验证，独立测试集决定系数分别为0.960 8、0.946 0、0.9605、0.9492。该模型对花生籽仁粗蛋白、粗脂肪、油酸、亚油酸含量的预测准确，可实现花生籽仁主要品质指标的快速、无损测定，提升高品质花生新品种的育种效率。更多还原

【Abstract】 A rapid near-infrared spectroscopy method was established for determination of crude protein, crude fat,oleic acid, and linoleic acid content in peanut kernels. Near infrared spectra of the kernels were collected using a DA7200 near-infrared analyzer. The content of crude protein and crude fat were determined using Kjeldahl nitrogen determination method and Soxhlet extraction method, respectively. The relative content of oleic acid and linoleic acid was determined using gas chromatography. Partial least squares method was used to construct a near-infrared prediction model for the main quality indicators of peanut kernels. The results showed that the determination coefficients of the model for crude protein, crude fat, oleic acid, and linoleic acid content in peanut kernels were 0.927 0,0.9647, 0.9915, and 0.9915 with root mean square errors as 0.8702, 0.5631, 1.6671, and 1.4040, respectively.After external verification, the determination coefficients of the independent test set were 0.9608, 0.9460, 0.9605,and 0.9492, respectively. This model accurately predicted the content of crude protein, crude fat, oleic acid, and linoleic acid in peanut kernels, and achieved rapid and non-destructive determination of the main quality indicators of peanut kernels, which is helpful for improvement of breeding efficiency of high-quality peanut varieties.更多还原