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中文摘要: 针对油菜芽期耐旱鉴定,提出了用近红外反射光谱技术(NIR法)预测油菜吸胀24 h电导率、PEG模拟干旱条件下的相对发芽率、相对鲜重和鲜重耐旱指数等4个芽期耐旱相关性状的方法。以采集的49份不同耐旱水平甘蓝型油菜近红外光谱数据为基础,采用偏最小二乘法和多元回归算法建立了最优定标模型,并获得较高的决定系数(0.71~0.86)和较低的标准误差(1~15.65)。验证集评估结果表明,NIR法与室内鉴定法测定油菜4个芽期耐旱相关性状显著差异,且具有极显著的相关关系(决定系数0.72~0.89)。研究表明,近红外光谱技术用于油菜芽期耐旱性鉴定是可行的,可用于耐旱育种早代选择。
Abstract:Using infrared reflectance spectroscopy (NIR), the study evaluated drought resistance by four parameters including the electric conductivity after 24 h imbibitions, relative germination rate, relative seedling fresh weight and drought tolerant index with PEG treatment. Based on the 49 collected data of different drought tolerance in rapeseed with NIR, and using partial least square algorithm and multiple regression method, we established optimal calibration model, with a higher determination of 0.71~0.98 and lower standard error of 1~15.65. The results indicated no significant difference but a remarkable correlation between the two treatments, with the R2 of 0.72~0.89. The results suggest that NIR was feasible to identify the drought tolerance in rapeseed, which could be used in screening drought tolerance germplasm.
keywords: Brassica napus L. near infrared reflectance (NIR) spectroscopy drought tolerance identification electric conductivity PEG treatment
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基金项目:安徽省自然科学基金(1308085MC45);国家支撑计划(2010BAD01B04)
Author Name | Affiliation |
ZHU Zong-he1, ZHENG Wen-yin1, ZHOU Ke-jin1, ZHANG Xue-kun2 |
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