摘要
籽仁蔗糖含量是影响花生食味品质的重要因素。为了建立花生籽仁中蔗糖含量的高效检测技术,本研究采集了149份花生籽仁的近红外光谱,结合化学法测定籽仁蔗糖含量,采用偏最小二乘法(PLS)构建花生籽仁蔗糖含量近红外预测群体模型。结果显示,预测模型的决定系数(R^(2))为0.898,校正标准偏差(SEC)为0.253,20份外部验证材料的预测值和化学值的R^(2)为0.873,预测模型具有较高的可信度,运用该模型筛选徐花17号诱变群体,从1965份M;单株籽仁中获得4分的突变体。本研究为优质食味花生种质资源的筛选和品种选育奠定了基础。
The sucrose content of seed kernel is an important factor affecting the edible quality of peanut(Arachis hypogaea L.).In order to establish an efficient technology for detecting sucrose content of peanut kernel,near infrared spectrum of a total of 149 peanut kernel samples were collected in this study,and the sucrose content of each sample was determined by chemical methods.A near-infrared calibration model of peanut seed sucrose content was established by partial least square(PLS)method.The results showed that the coefficient of determination(R^(2))was 0.898 and the squared error of calibration(SEC)was 0.253.The coefficient of determination between the predicted values and chemically tested values were 0.873 with 20 external samples,indicating that the model could be used to predict the sucrose content of peanut seeds very well.Using this model,four mutants with sucrose content higher than 6.00%were selected among 1965 EMS-induced M;individuals derived from Xuhua 17.This study laid the foundation for selecting germplasm resources and developing peanut varieties with good eating quality.
作者
卞能飞
童飞
巩佳莉
孙东雷
沈一
王幸
邢兴华
王晓军
BIAN Nengfei;TONG Fei;GONG Jiali;SUN Donglei;SHEN Yi;WANG Xing;XING Xinghua;WANG Xiaojun(Xuzhou Institute of Agricultural Sciences of the Xuhuai District,Xuzhou,Jiangsu 221131;Institute of Industrial Crops,Jiangsu Academy of Agricultural Sciences,Nanjing,Jiangsu 210014)
出处
《核农学报》
CAS
CSCD
北大核心
2022年第2期251-258,共8页
Journal of Nuclear Agricultural Sciences
基金
财政部和农业农村部:国家现代农业产业技术体系(CARS-13)
江苏省农业科技自主创新资金[cx(18)2015]
徐州市科技项目(KC19114)
亚夫科技服务项目[KF(20)1005]。
关键词
花生
蔗糖含量
近红外模型
突变体
peanut
sucrose content
near infrared model
mutant
