基于GGE模型的棉花品种生态区划分与试验环境评价
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摘要
棉花的生长发育受到生态环境变化的影响,存在着显著的基因型与环境交互作用,只有充分研究和应用棉花基因型与环境的互作效应,恰当地进行品种生态区划分,并选择目标种植区域内有代表性的试验环境作为育种环境,才能大幅度提高棉花遗传改良效果,并利用品种对环境的特殊适应性,充分发挥植棉区域生态环境的资源优势和品种的生产潜力。本研究利用HA-GGE双标图分析了2000～2010年27组长江流域棉花品种多环境试验中的基因型与环境互作模式,对基于皮棉产量、纤维长度、纤维比强度、马克隆值的单性选择和基于纤维品质选择指数(FSI)以及皮棉产量与纤维品质联合选择指数(ISI)的多目标性状选择条件下长江流域棉区可能存在的品种生态区进行了探索与划分,对试验环境的鉴别力、代表性和理想度进行了综合评价,同时构建了IR-GGE模型和基于GGE主成分得分的理想距离计算公式,以提高品种生态区划分和试验环境评价的准确性、可靠性与高效性。研究提出了长江流域棉区基于产量与纤维品质单性状或多目标性状联合选择的品种生态区划分方案和理想试验环境筛选结论,为以长江流域棉区和品种生态区为目标环境的广泛适应性和特殊适应性品种选择和应用提供科学依据和决策支持。
主要研究结果如下：
1.遗传力校正GGE模型的再校正与应用效果
依据主成分分析的信息比(IR)有效性准则,即选取IR≥1的试验环境主成分参与GGE模型的拟合,并据此构建了IR-GGE模型对HA-GGE双标图拟合效果进行校正,以提高品种生态区划分和品种评价的准确性。基于IR-GGE模型对皮棉产量、纤维长度、纤维比强度、马克隆值、纤维品质选择指数、产量和品质联合选择指数的拟合度分别提高了8.2%、3.1%、6%、6.7%、5.4%和5.4%。
2.基于GGE模型的棉花品种生态区鉴别与划分
基于皮棉产量、纤维长度、纤维比强度、马克隆值、纤维品质选择指数(FSI)以及皮棉产量与纤维品质联合选择指数(ISI)选择应用GGE双标图及其校正版本对长江流域棉区可能存在的品种生态区进行了探索与划分,并用IR-GGE模型进行校正：
(1)基于纤维品质综合选择指数(FSI)可以将目标区域划分为整个长江流域棉区划分为1个主品种生态区包括安庆、武汉、襄阳、岳阳、九江、南阳、黄冈、常德、荆州和南京等10个试验环境,2个小品种生态区包括慈溪、射洪、简阳、南通和盐城。
(2)基于皮棉产量和纤维品质综合选择指数(ISI)可以将目标区域划分为一个综合的主品种生态区和两个小范围的特殊品种生态区。主品种生态区涵盖了长江流域棉花区试的11个试验环境所代表的大部分目标区域,具有西太平洋温带季风气候区的典型气候型和土壤类型,而两个小规模品种生态区是分别位于长江流域棉区最北边霜期较早且晚秋降温快的南襄盆地品种生态区和长江流域棉区最西边的品种熟期较早且种植密度较高的四川盆地品种生态区。
3.基于GGE双标图的试验环境综合评价
本研究分别基于皮棉产量、纤维长度、纤维比强度、马克隆值、纤维品质选择指数、产量与品质联合选择指数等单性状选择或多目标性状同步选择条件下对试验环境的鉴别力、代表性、理想指数、理想距离等指标进行了综合评价：
(1)黄冈、荆州、南京和常德试验环境总体而言是长江流域棉花区域试验的理想试验环境,也是针对全流域广适性品种选择最有效的育种环境,而南襄盆地的襄阳和南阳试验环境对产量选择和产量与品质综合选择不理想、江浙沿海棉区的南通、盐城和慈溪试验环境对纤维品质选择不理想、四川盆地棉区的射洪和简阳试验环境对产量和纤维品质的单性状或多目标性状选择均不理想。
(2)基于产量和品质综合选择指数排名较差的试验环境对产量和纤维品质的综合选择效果效率最低,这可能同样与试验环境所处的地理位置及特殊的气候特征有关。除了与基于纤维品质综合选择指数分析的结果同样的四川盆地棉区“射洪和简阳”外,位于长江流域棉区北缘的“南襄盆地”棉区的南阳和襄阳试验环境也是较差的试验环境,其原因可能与该区域霜期早和晚秋降温快有关。
The formation and development of cotton lint yield and fiber quality traits is strongly affected by multiple ecological environment factors, thus leading to the universal existence of significant genotype by environment interaction. Insight exploration to genotype by environment interaction effect is the basis of megaenvironment investigation and sufficient test environment evaluation and selection for representative test environment as a breeding environment within the target planting region, and thus to greatly improve the cotton genetic improvement and new cultivar selection efficiency. To select and recommend particular varieties to its special adaptive subregions will give rise to full play of the positive interactive effects of ecological resources and varieties'production potential. In this study, the heritability adjusted GGE biplot was adopted to intensively explore the genotype by environment interaction patterns in the datasets of27independent cotton multi-environment cultivar trials in the Yangtze River Valley during2000-2010. The possible existence of megaenvironment in the Yangtze River Valley was investigated based on the selection for single breeding traits (lint yield, fiber length, fiber strength, micronaire), and for multi-traits simultaneous selection index of the fiber quality selection index (FSI) and lint yield plus fiber quality integrated selection index (ISI). In the same time the desirability of test environments was comprehensively evaluated in terms of the discriminating ability, representativeness of the target region and also the desirability index for ideal test environment selection and recommendation. On the basis of the construction of information ratio adjusted GGE model and the responding goodness-of-fit test method, and the establishment of the mathematical formula for ideal distance calculation based on GGE principal component scores, the goodness of fit of GGE model was tested and the test environment evaluation result was revised, and hence after the desirability index was adjusted with the Euclidean distance to the ideal environment to enhance the accuracy, reliability and efficiency of the megaenvironment investigation and test environment evaluation. The conclusion of the ideal test environment selection and megaenvironment investigation scheme in the Yangtze River Valley was proposed out based on single trait or multiple yield and fiber quality trait integrated selection index, in order to provide the theoretical implications and decision-making support for broad adaptive and specific adaptive cultivar selection and application targeting at the whole cotton planting region in the Yangtze River Valley and the megaenvironment within the region as well. The main findings were listed as follows.
1. The readjustment and application effect of the HA-GGE model
In accordance with the effective information ratio judgment criteria of principal component analysis, the principal component scores with IR≥1were entered the GGE model simulation procedure, and thus revised the GGE model simulation goodness of fit. Based on the selection of cotton lint yield, fiber length, fiber strength, micronaire, fiber combined selection index, lint yield plus fiber quality integrated selection index, the goodness of fit of IR-GGE model was improved8.2%,3.1%,6%,6.7%,5.4%and5.4%respectively, in this way the megaenvironment investigation and text environment evaluation efficiency were effectively enhanced.
2. Cotton megaenvironment identification and investigation based on HA-GGE model
Based on GGE model and its information ratio revised version, the possible existence of megaenvironments in the Yangtze River Valley was intensively investigated for the selection of cotton lint yield, fiber length, fiber strength, micronaire, fiber combined selection index(FSI) and lint yield plus fiber quality integrated selection index(ISI).
(1) Based on the fiber quality combined selection, the cotton planting region in the Yangtze River Valley as target region were divided into three distinct megaenvironments: A major complex megaenvironment covering the majority test environments including Anqing, Wuhan, Xiangfan, Yueyang, Jiujiang, Nanyang, Huanggang, Changde, Jinzhou and Nanjing, and two minority megaenvironments covering the test environment Shehong, Yancheng, Nantong Cixi and Jianyang representing for the cotton planting region in Sichuan basin and the coastal region in Jiangsu and Zhejiang province.
(2) Based on the cotton lint yield and fiber quality integrated selection index, the whole cotton growing region in the Yangtze River Valley were divided into two minor megaenvironments, one is located at the inland Nan-Xiang basin bordering with the Yellow River Valley in the north including two locations, the other is at the mountainous basin in west area including two locations too, and a major complex megaenvironment covering the majority eleven locations in the target region, where are of the most traditional climatotype and agrotype around the western Pacific temperate monsoon climate regions.
3. Test environment comprehensive evaluation based on GGE model
Based on GGE biplot and the selection of cotton lint yield, fiber length, fiber strength, micronaire, fiber combined selection index(FSI) and lint yield plus fiber quality integrated selection index(ISI), the test environment was elaborately evaluated as far as its discriminating ability, representativeness, desirability index and the distance to the ideal environment were concerned.
(1) Globally speaking, Huanggang, Jingzhou, Nanjing and Changde were ideal test environments and the most effective breeding environments for cultivar selection targeting at the whole cotton planting region in the Yangtze River Valley, while Xiangfan and Nanyang in Nan-Xiang basin were ineffective test environment in terms of cotton lint yield and lint yield plus fiber quality integrated selection, Nantong, Yancheng and Cixi in Jiangsu and Zhejiang provincial coastal cotton region were less effective for fiber quality selection, Shehong and Jiangyan in Sichuan basin were poor test environments for cotton cultivar selection in neither of lint yield nor fiber quality traits.
(2) Based on the selection of yield plus fiber quality integrated selection index (ISI), the ranking by desirability index of the test environments was relevant to the cultivar comprehensive selection efficiency implementing in the locations, which might be linked to the special geographical position and the climate characteristics. Shehong and Jianyang were located at the mountainous basin in the west area which might implicated its lower efficiency in cultivar selection, while Nanyang and Xiangfan test environment representing for the Nan-Xiang basin region were located in the northern border of the Yangtze River Valley, where frost descents earlier and temperature declines fast in the later autumn might be the reason explaining its poor representativeness to the whole region and less efficiency of cotton lint yield selection.
主要研究结果如下：
1.遗传力校正GGE模型的再校正与应用效果
依据主成分分析的信息比(IR)有效性准则,即选取IR≥1的试验环境主成分参与GGE模型的拟合,并据此构建了IR-GGE模型对HA-GGE双标图拟合效果进行校正,以提高品种生态区划分和品种评价的准确性。基于IR-GGE模型对皮棉产量、纤维长度、纤维比强度、马克隆值、纤维品质选择指数、产量和品质联合选择指数的拟合度分别提高了8.2%、3.1%、6%、6.7%、5.4%和5.4%。
2.基于GGE模型的棉花品种生态区鉴别与划分
基于皮棉产量、纤维长度、纤维比强度、马克隆值、纤维品质选择指数(FSI)以及皮棉产量与纤维品质联合选择指数(ISI)选择应用GGE双标图及其校正版本对长江流域棉区可能存在的品种生态区进行了探索与划分,并用IR-GGE模型进行校正：
(1)基于纤维品质综合选择指数(FSI)可以将目标区域划分为整个长江流域棉区划分为1个主品种生态区包括安庆、武汉、襄阳、岳阳、九江、南阳、黄冈、常德、荆州和南京等10个试验环境,2个小品种生态区包括慈溪、射洪、简阳、南通和盐城。
(2)基于皮棉产量和纤维品质综合选择指数(ISI)可以将目标区域划分为一个综合的主品种生态区和两个小范围的特殊品种生态区。主品种生态区涵盖了长江流域棉花区试的11个试验环境所代表的大部分目标区域,具有西太平洋温带季风气候区的典型气候型和土壤类型,而两个小规模品种生态区是分别位于长江流域棉区最北边霜期较早且晚秋降温快的南襄盆地品种生态区和长江流域棉区最西边的品种熟期较早且种植密度较高的四川盆地品种生态区。
3.基于GGE双标图的试验环境综合评价
本研究分别基于皮棉产量、纤维长度、纤维比强度、马克隆值、纤维品质选择指数、产量与品质联合选择指数等单性状选择或多目标性状同步选择条件下对试验环境的鉴别力、代表性、理想指数、理想距离等指标进行了综合评价：
(1)黄冈、荆州、南京和常德试验环境总体而言是长江流域棉花区域试验的理想试验环境,也是针对全流域广适性品种选择最有效的育种环境,而南襄盆地的襄阳和南阳试验环境对产量选择和产量与品质综合选择不理想、江浙沿海棉区的南通、盐城和慈溪试验环境对纤维品质选择不理想、四川盆地棉区的射洪和简阳试验环境对产量和纤维品质的单性状或多目标性状选择均不理想。
(2)基于产量和品质综合选择指数排名较差的试验环境对产量和纤维品质的综合选择效果效率最低,这可能同样与试验环境所处的地理位置及特殊的气候特征有关。除了与基于纤维品质综合选择指数分析的结果同样的四川盆地棉区“射洪和简阳”外,位于长江流域棉区北缘的“南襄盆地”棉区的南阳和襄阳试验环境也是较差的试验环境,其原因可能与该区域霜期早和晚秋降温快有关。
The formation and development of cotton lint yield and fiber quality traits is strongly affected by multiple ecological environment factors, thus leading to the universal existence of significant genotype by environment interaction. Insight exploration to genotype by environment interaction effect is the basis of megaenvironment investigation and sufficient test environment evaluation and selection for representative test environment as a breeding environment within the target planting region, and thus to greatly improve the cotton genetic improvement and new cultivar selection efficiency. To select and recommend particular varieties to its special adaptive subregions will give rise to full play of the positive interactive effects of ecological resources and varieties'production potential. In this study, the heritability adjusted GGE biplot was adopted to intensively explore the genotype by environment interaction patterns in the datasets of27independent cotton multi-environment cultivar trials in the Yangtze River Valley during2000-2010. The possible existence of megaenvironment in the Yangtze River Valley was investigated based on the selection for single breeding traits (lint yield, fiber length, fiber strength, micronaire), and for multi-traits simultaneous selection index of the fiber quality selection index (FSI) and lint yield plus fiber quality integrated selection index (ISI). In the same time the desirability of test environments was comprehensively evaluated in terms of the discriminating ability, representativeness of the target region and also the desirability index for ideal test environment selection and recommendation. On the basis of the construction of information ratio adjusted GGE model and the responding goodness-of-fit test method, and the establishment of the mathematical formula for ideal distance calculation based on GGE principal component scores, the goodness of fit of GGE model was tested and the test environment evaluation result was revised, and hence after the desirability index was adjusted with the Euclidean distance to the ideal environment to enhance the accuracy, reliability and efficiency of the megaenvironment investigation and test environment evaluation. The conclusion of the ideal test environment selection and megaenvironment investigation scheme in the Yangtze River Valley was proposed out based on single trait or multiple yield and fiber quality trait integrated selection index, in order to provide the theoretical implications and decision-making support for broad adaptive and specific adaptive cultivar selection and application targeting at the whole cotton planting region in the Yangtze River Valley and the megaenvironment within the region as well. The main findings were listed as follows.
1. The readjustment and application effect of the HA-GGE model
In accordance with the effective information ratio judgment criteria of principal component analysis, the principal component scores with IR≥1were entered the GGE model simulation procedure, and thus revised the GGE model simulation goodness of fit. Based on the selection of cotton lint yield, fiber length, fiber strength, micronaire, fiber combined selection index, lint yield plus fiber quality integrated selection index, the goodness of fit of IR-GGE model was improved8.2%,3.1%,6%,6.7%,5.4%and5.4%respectively, in this way the megaenvironment investigation and text environment evaluation efficiency were effectively enhanced.
2. Cotton megaenvironment identification and investigation based on HA-GGE model
Based on GGE model and its information ratio revised version, the possible existence of megaenvironments in the Yangtze River Valley was intensively investigated for the selection of cotton lint yield, fiber length, fiber strength, micronaire, fiber combined selection index(FSI) and lint yield plus fiber quality integrated selection index(ISI).
(1) Based on the fiber quality combined selection, the cotton planting region in the Yangtze River Valley as target region were divided into three distinct megaenvironments: A major complex megaenvironment covering the majority test environments including Anqing, Wuhan, Xiangfan, Yueyang, Jiujiang, Nanyang, Huanggang, Changde, Jinzhou and Nanjing, and two minority megaenvironments covering the test environment Shehong, Yancheng, Nantong Cixi and Jianyang representing for the cotton planting region in Sichuan basin and the coastal region in Jiangsu and Zhejiang province.
(2) Based on the cotton lint yield and fiber quality integrated selection index, the whole cotton growing region in the Yangtze River Valley were divided into two minor megaenvironments, one is located at the inland Nan-Xiang basin bordering with the Yellow River Valley in the north including two locations, the other is at the mountainous basin in west area including two locations too, and a major complex megaenvironment covering the majority eleven locations in the target region, where are of the most traditional climatotype and agrotype around the western Pacific temperate monsoon climate regions.
3. Test environment comprehensive evaluation based on GGE model
Based on GGE biplot and the selection of cotton lint yield, fiber length, fiber strength, micronaire, fiber combined selection index(FSI) and lint yield plus fiber quality integrated selection index(ISI), the test environment was elaborately evaluated as far as its discriminating ability, representativeness, desirability index and the distance to the ideal environment were concerned.
(1) Globally speaking, Huanggang, Jingzhou, Nanjing and Changde were ideal test environments and the most effective breeding environments for cultivar selection targeting at the whole cotton planting region in the Yangtze River Valley, while Xiangfan and Nanyang in Nan-Xiang basin were ineffective test environment in terms of cotton lint yield and lint yield plus fiber quality integrated selection, Nantong, Yancheng and Cixi in Jiangsu and Zhejiang provincial coastal cotton region were less effective for fiber quality selection, Shehong and Jiangyan in Sichuan basin were poor test environments for cotton cultivar selection in neither of lint yield nor fiber quality traits.
(2) Based on the selection of yield plus fiber quality integrated selection index (ISI), the ranking by desirability index of the test environments was relevant to the cultivar comprehensive selection efficiency implementing in the locations, which might be linked to the special geographical position and the climate characteristics. Shehong and Jianyang were located at the mountainous basin in the west area which might implicated its lower efficiency in cultivar selection, while Nanyang and Xiangfan test environment representing for the Nan-Xiang basin region were located in the northern border of the Yangtze River Valley, where frost descents earlier and temperature declines fast in the later autumn might be the reason explaining its poor representativeness to the whole region and less efficiency of cotton lint yield selection.
引文
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