| 基于非线性主成分分析的北方粳稻苗期耐盐碱性综合评价 |
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| 引用本文： | 刘梦红,李逸,李红宇,林晓影,翟立楠,赵海成,侯宇欣,刘丽华,钱永德.基于非线性主成分分析的北方粳稻苗期耐盐碱性综合评价[J].南方农业学报,2022,53(12):3380-3388. |
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| 作者姓名： | 刘梦红 李逸 李红宇 林晓影 翟立楠 赵海成 侯宇欣 刘丽华 钱永德 |
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| 作者单位： | 1 黑龙江八一农垦大学农学院, 黑龙江大庆 163319;2 农业农村部东北平原农业绿色低碳重点实验室, 黑龙江大庆 163319;3 黑龙江八一农垦大学黑龙江省现代农业栽培技术与作物种质改良重点实验室, 黑龙江大庆 163319;4 黑龙江省八五四农场, 黑龙江鸡西 158100 |
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| 基金项目： | 黑龙江省重点研发计划项目（GA21B002） |
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| 摘 要： | 【目的】通过鉴定北方粳稻种质资源的苗期耐盐碱性并筛选耐盐碱性鉴定的适宜指标，为北方粳稻耐盐碱育种和栽培提供参考。【方法】采用非线性对数主成分评价法，对水稻苗期进行盐碱胁迫，以水稻苗期的13个性状为指标，从形态特征、物质积累、生理特性对56份北方粳稻种质资源进行耐盐碱性综合评价。【结果】利用对数主成分分析将13项指标的耐盐碱系数转化为5个相互独立的综合指标，累积贡献率达86.368%。根据耐盐碱综合评价值Sf将56份材料分成5类，分别为极强耐盐碱型、强耐盐碱型、中耐盐碱型、盐碱中敏感型和盐碱敏感型。龙粳29、NF13G280、长白9号、龙粳46属极强耐盐碱型，占总材料数的7.1%。灰色关联分析结果表明，株高、百株地上鲜重、百株地上干重3个指标的耐盐系数与耐盐碱综合评价值的关联系数大于0.5，可作为苗期耐盐碱性筛选的指标。【结论】从56份北方粳稻种质资源中筛选出龙粳29、NF13G280、长白9号和龙粳46等4份极强耐盐碱种质材料，从13个指标中筛选出株高、百株地上鲜重、百株地上干重作为苗期耐盐碱性筛选的指标，该统计方法适宜作为北方粳稻苗期耐盐碱筛选模型。
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| 关 键 词： | 北方粳稻 水稻 对数主成分分析 耐盐碱性 |
| 收稿时间： | 2022-08-11 |
Comprehensive evaluation of northern japonica rice saline-alkaline tolerance at seedling stage based on nonlinear principal component analysis |
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| LIU Meng-hong,LI Yi,LI Hong-yu,LIN Xiao-ying,ZHAI Li-nan,ZHAO Hai-cheng,HOU Yu-xin,LIU Li-hua,QIAN Yong-de.Comprehensive evaluation of northern japonica rice saline-alkaline tolerance at seedling stage based on nonlinear principal component analysis[J].Journal of Southern Agriculture,2022,53(12):3380-3388. |
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| Authors: | LIU Meng-hong LI Yi LI Hong-yu LIN Xiao-ying ZHAI Li-nan ZHAO Hai-cheng HOU Yu-xin LIU Li-hua QIAN Yong-de |
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| Affiliation: | 1 College of Agriculture, Heilongjiang Bayi Agricultural University, Daqing, Heilongjiang 163319, China;2 Key Laboratory of Low-carbon Green Agriculture in Northeastern China, Ministry of Agriculture and Rural Affairs, Daqing, Heilongjiang 163319, China;3 Heilongjiang Provincial Key Laboratory of Modern Agricultural Cultivation and Crop Germplasm Improvement, Heilongjiang Bayi Agricultural University, Daqing, Heilongjiang 163319, China;4 Heilongjiang Bawusi Farm, Jixi, Heilongjiang 158100, China |
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| Abstract: | 【Objective】 To identify saline-alkaline tolerance during seedling stage of northern japonica rice germplasm resources and screen suitable indicators for salinity tolerance identification, so as to provide reference for the breeding and cultivation of saline-alkaline-tolerant northern japonica rice.【Method】 The non-linear logarithmic principal component evaluation method was used to evaluate the saline-alkaline stress of rice seedlings, and saline-alkaline tolerance of 56 northern japonica rice germplasm resources were comprehensively evaluated for in terms of morphological characteristics, material accumulation and physiological traits taking 13 traits of rice seedlings as indicators.【Result】 The logarithmic principal component analysis was used to transform the saline-alkaline tolerance coefficients of the 13 indicators into 5 mutually independent comprehensive indicators with a cumulative contribution of 86.368%. The 56 materials were classified into 5 categories according to the comprehensive evaluation value of saline-alkaline tolerance Sf:extremely saline-alkaline tolerant, strongly saline-alkaline tolerant, mediumly saline-alkaline tolerant, mediumly saline-alkaline-sensitive and saline-alkaline-sensitive. LJ29, NF13G280, CB9 and LJ46 were extremely saline-alkaline-tole-rant, accounting for 7.1% of the total number of materials. The plant height(PH), above-ground part fresh weight per 100 plants(FWS) and above-ground part dry weight per 100 plants(DWS) were selected by gray correlation analysis as indicators for classifying saline-alkaline tolerance at seedling stage of the rice since the correlation coefficient between saline-alkaline tolerance coefficient and comprehensive value of saline-alkaline tolerance was greater than 0.5.【Conclusion】 Four extremely saline-alkaline tolerant materials, LJ29, NF13G280, CB9 and LJ46 are selected from the 56 northen japonica rice germplasm materials. Three suitable indicators for classifying saline-alkaline tolerance at seedling stage of the rice, plant height, above-ground part fresh weight per 100 plants and above-ground part dry weight per 100 plants are selected from 13 indicators, this statistical method is appropriate for classifying saline-alkaline tolerance of northern japonica rice at seedling stage. |
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