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首页> 外文期刊>Agricultural Research >Near-Infrared Reflectance Spectroscopy for Protein Content in Soybean Flour and Screening of Germplasm Across Different Countries
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Near-Infrared Reflectance Spectroscopy for Protein Content in Soybean Flour and Screening of Germplasm Across Different Countries

机译:豆粕中蛋白质含量的近红外反射光谱法和不同国家的种质筛选

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Maintaining high protein content in soybean seeds is critical in view of the premium offered for protein content in soymeal in international market. Besides, quality of several soy-based products depends upon crude protein content of the initial raw material used. Determination of protein content in soybean seeds through wet chemistry involves use of chemicals and is time-consuming and labour-intensive. In the present investigation, a calibration model for determination of protein content in ground soyflour using non-destructive method of near-infrared reflectance spectroscopy (NIRs) was developed. A set of samples with wide variation in protein content as measured through wet chemistry were scanned by NIRs between 1100 and 2100 nm at 2-nm interval.High determination coefficient (R2) and low values for root-mean-square error as well as standard error of prediction of cross-validation confirmed the utility of model for prediction of future samples. For external validation, a set of genotypes from different genetic background were tested and were predicted with good accuracy. Lower values of standard error of calibration and prediction were observed than reported previously for whole seeds. Subsequently, 1210 soybean accessions from 18 countries were screened through NIRS. Average protein content of soybean accessions from different countries varied significantly. Genotypes identified for high protein content from different countries may be used for development of genotypes containing further highprotein content.
机译:鉴于国际市场上豆粕中蛋白质含量较高,维持大豆种子中高蛋白质含量至关重要。此外,几种大豆制品的质量取决于所用初始原料的粗蛋白含量。通过湿化学法测定大豆种子中的蛋白质含量需要使用化学物质,既费时又费力。在本研究中,开发了使用近红外反射光谱法(NIR)的非破坏性方法测定地面豆粉中蛋白质含量的校准模型。通过1100到2100 nm之间的NIR以2 nm的间隔扫描通过湿化学法测量的一组蛋白质含量差异较大的样品。高测定系数(R2)和低均方根误差值以及标准品交叉验证预测的误差证实了该模型可用于未来样本的预测。为了进行外部验证,测试了一组来自不同遗传背景的基因型,并预测了它们的准确性。观察到的标定和预测的标准误差值比以前对整粒种子的报道要低。随后,通过NIRS筛选了来自18个国家的1210份大豆种质。不同国家大豆品种的平均蛋白质含量差异很大。来自不同国家的高蛋白含量的基因型可用于开发进一步高蛋白含量的基因型。

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