| 花生籽仁含油量近红外模型的构建及其应用 |
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| 引用本文： | 纪红昌,邱晓臣,柳文浩,胡畅丽,孔铭,胡晓辉,黄建斌,杨雪,唐艳艳,张晓军,王晶珊,乔利仙.花生籽仁含油量近红外模型的构建及其应用[J].中国油料作物学报,2022,44(5):1089-1097. |
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| 作者姓名： | 纪红昌 邱晓臣 柳文浩 胡畅丽 孔铭 胡晓辉 黄建斌 杨雪 唐艳艳 张晓军 王晶珊 乔利仙 |
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| 作者单位： | 1.青岛农业大学农学院/山东省花生产业协同创新中心/山东省旱作农业技术重点实验室，山东 青岛，2661092.山东省花生研究所，山东 青岛，266100 |
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| 基金项目： | 青岛市科技惠民示范引导专项重点项目(20-3-4-25-nsh);山东省农业良种工程(2020LZGC001);山东省自然科学基金(ZR2020MC102);农业农村部油料作物生物学与遗传育种重点实验室开放课题(KF2018008) |
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| 摘 要： | 花生(Arachis hypogaea L.)籽仁含油量是花生品质评价的重要指标，建立快速高效的含油量检测方法，对加快高油花生品种选育意义重大。本研究选用高油亲本宇花14(含油量59.32%)与低油亲本LOP215(含油量48.97%)杂交构建的RIL群体为建模材料，使用Thermo公司(美国)生产的Antaris Ⅱ型傅立叶变换近红外光谱分析仪对229份样品籽仁进行光谱采集，随后测定籽仁含油量。利用偏最小二乘法(partial least squares,PLS)构建花生籽仁含油量近红外定标模型，该模型的内部验证均方差(root mean square error of cross validation, RMSECV)为0.885，相关系数R2=0.9147。选用未参与建模的21份花生材料对该模型进行外部验证，模型预测值和化学测定值的决定系数R2=0.9492，表明该模型可适用于花生籽仁含油量检测。利用该模型对宇花14与LOP215杂交后代群体进行筛选，获得含油量超过55%的优良株系21个，含油量低于48%的株系9个，可为花生高低含油量品...
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| 关 键 词： | 花生 籽仁 含油量 近红外模型 RIL群体 |
| 收稿时间： | 2021-08-18 |
Construction and application of near infrared ray model for oil content prediction in peanut kernel |
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| Hong-chang JI,Xiao-chen QIU,Wen-hao LIU,Chang-li HU,Ming KONG,Xiao-hui HU,Jian-bin HUANG,Xue YANG,Yan-yan TANG,Xiao-jun ZHANG,Jing-shan WANG,Li-xian QIAO.Construction and application of near infrared ray model for oil content prediction in peanut kernel[J].Chinese Journal of Oil Crop Sciences,2022,44(5):1089-1097. |
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| Authors: | Hong-chang JI Xiao-chen QIU Wen-hao LIU Chang-li HU Ming KONG Xiao-hui HU Jian-bin HUANG Xue YANG Yan-yan TANG Xiao-jun ZHANG Jing-shan WANG Li-xian QIAO |
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| Institution: | 1.College of Agronomy, Qingdao Agricultural University / Shandong Provincial Peanut Industry Cooperative Innovation Center / Shandong Provincial Dry-land Farming Technology Lab, Qingdao 266109, China2.Shandong Peanut Research Institute, Qingdao 266100, China |
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| Abstract: | Kernel oil content is an important index for peanut quality evaluation. It is of great significance to establish a rapid and efficient oil content detection method for accelerating the breeding of high oil peanut varieties. The RIL population constructed by crossing high oil parent Yuhua 14 with oil content of 59.32% and LOP215 with oil content of 48.97% was used as the modeling material, and the spectra of 229 samples were collected by using Antaris II type fourier transform near infrared spectrometer produced by thermo company （USA）, and then the oil content of seed kernel was determined. The partial least squares （PLS） method was used to construct the near infrared calibration model of peanut kernel oil content. The root mean square error of cross validation （RMSECV） of the model was 0.885, and the correlation coefficient R2=0.9147. Twenty-one peanut materials not involved in the modeling were selected for external validation of the model, and the coefficient of determination of predicted value and chemical determination value of the model R2=0.9492, indicating that the model can be applied to determination of oil content in peanut kernels. Twenty-one lines with oil content more than 55% and 9 lines with oil content less than 48% were obtained by screening from the progeny population of crossing between Yuhua 14 and LOP215, which can provide germplasm materials for breeding high or low oil content peanut varieties. |
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| Keywords: | peanut kernels oil content near infrared ray model RIL population |
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