摘要
蛋白质和脂肪含量是影响黑豆营养品质的重要因素。为了建立黑豆中粗蛋白和粗脂肪含量的近红外快速检测模型,采集200份具有代表性的地方黑豆种质资源为研究材料,利用近红外漫反射光谱仪,结合化学法测定黑豆中粗蛋白和粗脂肪含量,并进行统计学分析。结果表明,采用一阶导数+MSC、一阶导数+矢量归一化光谱预处理,分别建立粗蛋白、粗脂肪含量的近红外快速检测模型。该模型的交叉验证决定系数(R^(2))分别为0.907和0.873,误差分别为0.477和0.420,表明模型准确可靠,可代替化学分析法鉴定黑豆粗蛋白和粗脂肪含量。对200份不同产地黑豆种质资源进行分析评价,粗蛋白含量最大值为50.11%,最小值为37.00%,粗脂肪含量最大值为22.62%,最小值为12.06%。最终筛选出79份高蛋白和4份高油黑豆品种资源,为优质黑豆资源的筛选和品种选育奠定了基础。
Protein and fat contents are critical factors influencing the nutritional quality of black soybean.This study aimed to develop a rapid and reliable near-infrared(NIR)model for quantifying these components.The total of 200 representative black soybean germplasm resources from various regions were collected.Their crude protein and crude fat contents were measured using chemical methods and NIR diffuse reflectance spectroscopy.The data were statistically analyzed to build NIR models.Using first-order derivative+MSC and first-order derivative+vector normalization spectral preprocessing methods,two separate models were established for crude protein and crude fat,respectively.The models demonstrated high accuracy,with cross-validation determination coefficients(R^(2))of 0.907 and 0.873,and low errors of 0.477 and 0.420.These models are accurate and reliable,offering a viable alternative to time-consuming chemical analysis for screening black soybeans.An analysis of the 200 germplasm accessions revealed a wide range of variation,with crude protein content ranging from 37.00%to 50.11%and crude fat content from 12.06%to 22.62%.Based on these results,79 high-protein and four high-oil black soybean varieties were identified and selected.This research provides a crucial foundation for the future selection and breeding of high-quality black soybean varieties.
作者
田翔
陈妍
聂萌恩
张海平
Tian Xiang;Chen Yan;Nie Mengʼen;Zhang Haiping(Center for Agricultural Genetic Resources Research,Shanxi Agricultural University,Taiyuan 030031,Shanxi,China;Key Laboratory of Crop Gene Resources and Germplasm Enhancement on Loess Plateau,Ministry of Agriculture and Rural Affairs,Taiyuan 030031,Shanxi,China)
出处
《作物杂志》
北大核心
2025年第5期272-278,共7页
Crops
基金
国家重点研发计划子课题(2021YFD1600601-03)
山西省科技重大专项计划(202201140601025)
山西省现代农业产业技术体系建设专项资金
科技创新2030-重大项目课题(2023ZD0403703)。
