我国西北内陆棉花品种生态区划分与试验环境评价

乔银桃; 孙世贤; 赵素琴; 杨晓妮; 许乃银

doi:10.12357/cjea.20220012

我国西北内陆棉花品种生态区划分与试验环境评价

doi: 10.12357/cjea.20220012

乔银桃^{1, 2,},
孙世贤³,
赵素琴⁴,
杨晓妮²,
许乃银^2, ,

1.
江苏大学农业工程学院　镇江　212001
2.
江苏省农业科学院经济作物研究所　南京　210014
3.
全国农业技术推广服务中心　北京　100125
4.
新疆维吾尔自治区种业发展中心　乌鲁木齐　830006

基金项目: 国家农业技术试验示范与服务支持项目(0120662912003)资助

详细信息

作者简介:
乔银桃，主要研究方向为农业生态学。E-mail: qiaoytao@163.com

通讯作者:
许乃银, 主要从事棉花品种区域试验和生态适应性模型研究。E-mail: naiyin@126.com

中图分类号: S562.03
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出版历程
- 收稿日期: 2021-12-15
- 录用日期: 2022-02-09
- 网络出版日期: 2022-03-01
- 刊出日期: 2022-08-01

Cotton mega-environment investigation and test environment evaluation for the national cotton variety trials in the northwest inland cotton production region

QIAO Yintao^{1, 2
,},
SUN Shixian³,
ZHAO Suqin⁴,
YANG Xiaoni²,
XU Naiyin^{2
, ,}

1.
School of Agricultural Engineering, Jiangsu University, Zhenjiang 212001, China
2.
Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
3.
National Extension and Service Center of Agricultural Technology, Beijing 100125, China
4.
Xinjiang Uygur Autonomous Region Seed Industry Development Center, Urumqi 830006, China

Funds: This work was supported by the National Agricultural Technology Demonstration and Service Supporting Project of China (0120662912003).

More Information

Corresponding author: E-mail: naiyin@126.com

摘要

摘要: 在农作物多环境品种试验中基因型与环境互作(GE)现象是普遍存在的, 品种生态区划分和试验环境评价与选择是提高品种选择效率的有效方法。西北内陆棉区是我国目前最重要的主产棉区, 探索该棉区棉花品种生态区划分和品种试验环境科学评价与选择, 有利于试验环境资源的合理利用和棉花品种试验效率的提升。本研究基于2011—2020年西北内陆棉区国家棉花品种区域试验产量数据, 采用LG双标图和GGE双标图方法探索了试验环境间的相关性模式, 并对各试验环境的代表性、鉴别力和理想指数进行了综合评价。结果表明: 1) LG双标图揭示了西北内陆早熟棉区除乌苏外的沙湾、五家渠、奎屯、石河子、敦煌、博乐和精河等试点均属于同一品种生态区; 南疆早中熟棉区除麦盖提外的巴州、阿拉尔、莎车、库车、拜城、库尔勒和图木舒克等试点属于同一品种生态区。2)各试验环境的鉴别力差异不显著, 而早熟棉区的乌苏试点和早中熟棉区的麦盖提点的代表性及理想指数显著差于其余试点, 其他试点间的差异不显著。3)早熟棉区各试验环境依据理想指数的综合优劣排序为沙湾>精河>五家渠>敦煌>博乐>石河子>奎屯>乌苏, 早中熟棉区各试验环境的理想指数综合优劣排序为巴州>图木舒克>阿拉尔>库尔勒>莎车>拜城>库车>麦盖提。可见, 乌苏和麦盖提点在品种试验方案优化中应当考虑更换, 以提高试验的总体效率。本研究充分展示了LG双标图和GGE双标图在区域试验环境评价中的应用效果, 为西北内陆棉区棉花品种试验方案优化提供了理论依据, 也可为其他作物和其他目标区域的类似研究提供参考。
- 棉花 /
- 西北内陆棉区 /
- GGE双标图 /
- LG双标图 /
- 试验环境 /
- 品种生态区
Abstract: Plant breeding has played a key role in increasing agricultural productivity and meeting the increasing needs of the world, while the prevalence of genotype-by-environment interaction (GE) in multi-year, multi-location variety trials impedes variety selection and application efficiency. The Northwest Inland Cotton Production Region (NICPR) is currently the most important cotton-growing region, occupying more than 80% of the total cotton acreage in China. Therefore, mega-environment (ME) investigation and test environment evaluation are beneficial for the rational utilization of experimental resources and the improvement of the efficiency of cotton variety trials conducted in the NICPR. The objective of the present study was to demonstrate the application efficiency of the existing genotype main effect plus GE (GGE) biplot and a newly proposed location grouping (LG) biplot in exploring ME and comprehensively evaluating test environments using identification ability, representativeness, and desirability index based on the lint cotton yield of national cotton variety trials in the NICPR from 2011 to 2020. (1) The LG biplot revealed that the majority of test environments, including Shawan, Wujiaqu, Kuytun, Shihezi, Dunhuang, Bole and Jinghe, belonged to the same ME and suitably represented the targeting early-maturing cotton production region, while the test environment Usu was delineated out as an outlier of the early-maturing cotton ME. The test environment Makit in the medium-early maturing ME was also identified as an outlier in the southern Xinjiang cotton growing region, while the other test environments covering Bazhou, Alaer, Shache, Kuqa, Baicheng, Korla, and Tumxuk were all positively correlated and suitably represented the medium-early maturing ME. (2) The differences in identification ability among all test environments were not significant at P>5% level. The representativeness and desirability of Usu and Markit displayed significant differences from other test locations in the same ME, while the differences among other test locations were not significant. (3) According to the desirability index, the comprehensive ordination of the test environments in the early maturing cotton region was ranked as Shawan > Jinghe > Wujiaqu > Dunhuang > Bole > Shihezi > Kuytun > Usu. Similarly, on the basis of the desirability index, the ordination of test locations in the medium-early maturing cotton region was listed as Bazhou > Tumxuk > Alaer > Korla > Shache > Baicheng > Kuqa > Makit. It was clear that Usu and Makit should be removed from cotton variety trial scheme optimization for test efficiency improvement. The results of the study not only presented the highly efficient function of LG and GGE biplots in test environment evaluation in cotton variety trials in the NICPR and provided a theoretical basis for the optimization of the cotton regional trial schemes in Northwest Inland, but they also set a good example for future application in similar studies on other crops for other target crop growing regions.
- Cotton /
- Northwest inland cotton production region (NICPR) /
- GGE biplot /
- LG biplot /
- Test environment /
- Mega-environment

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图 1 2011—2020年西北内陆棉区早熟组(a)和早中熟组(b)棉花品种区域试验的LG双标图

试点图标由各年份试验的平均坐标表示。例如“USU”坐标是2011—2020年期间乌苏点8年试验的平均值; 连接乌苏(USU)的数字表示年份, 如USU-15表示乌苏点2015年的试验结果。试点名称详见表1。

Figure 1. Location-grouping (LG) biplots of the early-maturing group (a) and medium-early maturing group (b) of cotton variety trials in the Northwest Inland cotton production region in 2011−2020

The placement of a location is determined by the mean coordinates of all trials conducted at the locations. For example, the placement of “USU” is determined by the placements of the eight trials conducted at Usu during 2011−2020; date linked with it is the trail year, for example, USU-15 is the trial in Usu in 2015. See Table 1 for the detailed names of the locations.

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图 2 2013年西北内陆棉区早中熟组棉花区试点“鉴别力与代表性”GGE双标图

带*号前缀蓝色图标, 如*Hcm9和*Zms49等为参试品种名称; 红色字母带前缀“+”号的图标为试点名称, 如+Makit和+Alaer等, 试点名称详见表1。Marks in blue prefixed with asterisk are tested varieties, such as *Hcm9 and *Zms49. Marks in red prefixed with plus sign “+” are the test locations, such as +Makit, +Alaer, et al, which are shown in Table 1.

Figure 2. “Discrimination and representativeness” view of the GGE biplot for the medium-early maturing cotton trial dataset in the Northwest Inland cotton production region in 2013

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表 1 2011—2020年西北内陆国家棉花品种区域试验环境的地理因子

Table 1. Geographical factors of trial environments in the national cotton variety trials in the Northwest Inland cotton production region in 2011−2020

棉区 Cotton growing region	试验环境 Trial environment	经度 Longitude	纬度 Latitude	海拔 Altitude (m)	土壤类型 Soil type	试验年限 Test years
早熟棉区 Early-maturing cotton region	博乐 Bole	83°50′	44°57′	501	沙壤土 Sandy loam	7 (2014—2020)
	敦煌 Dunhuang	94°42′	40°11′	1139	灌淤土 Cumulated irrigated soil	9 (2011—2018, 2020)
	精河 Jinghe	82°57′	44°39′	320	沙壤土 Sandy loam	8 (2011—2016, 2018—2019)
	沙湾 Shawan	85°35′	44°50′	457	沙壤土 Sandy loam	10 (2011—2020)
	五家渠 Wujiaqu	87°34′	44°10′	552	灰漠土 Desert grey soil	10 (2011—2020)
	奎屯 Kuytun	84°54′	44°26′	461	黏壤土 Clay loam	10 (2011—2020)
	石河子 Shihezi	86°20′	44°20′	443	草甸土 Meadow soil	10 (2011—2020)
	乌苏 Usu	84°19′	44°25′	479	沙壤土 Sandy loam	9 (2011—2019)
早中熟棉区 Medium-early maturing cotton region	阿拉尔 Alaer	82°40′	41°30′	1011	沙壤土 Sandy loam	9 (2011—2014, 2016—2020)
	图木舒克 Tumxuk	79°10′	39°90′	1098	沙壤土 Sandy loam	10 (2011—2020)
	巴州 Bazhou	86°70′	41°44′	1500	草甸土 Meadow soil	10 (2011—2020)
	库车 Kuqa	82°54′	41°21′	1099	沙壤土 Sandy loam	10 (2011—2020)
	莎车 Shache	77°20′	38°40′	1236	沙壤土 Sandy loam	10 (2011—2020)
	麦盖提 Makit	77°70′	38°90′	1180	灌淤土 Cumulated irrigated soil	7 (2011—2016, 2018)
	拜城 Baicheng	81°53′	41°48′	1240	沙壤土 Sandy loam	9 (2012—2020)
	库尔勒 Korla	86°16′	41°20′	936	沙壤土 Sandy loam	6 (2014, 2016—2020)

下载: 导出CSV

表 2 2011—2020年西北内陆棉区早熟组棉花品种皮棉产量的试验环境间相关系数

Table 2. Average Pearson correlation coefficients among test locations across tested genotypes based on the lint yield data of the early-maturing cotton variety trials in the Northwest Inland cotton production region in 2011−2020

试验环境 Test location	博乐 Bole	敦煌 Dunhuang	精河 Jinghe	奎屯 Kuytun	沙湾 Shawan	石河子 Shihezi	乌苏 Usu	五家渠 Wujiaqu	平均值 Average
博乐 Bole	1.000								0.265a
敦煌 Dunhuang	0.424	1.000							0.266a
精河 Jinghe	0.317	0.297	1.000						0.336a
奎屯 Kuytun	0.205	0.240	0.356	1.000					0.221a
沙湾 Shawan	0.296	0.267	0.425	0.272	1.000				0.351a
石河子 Shihezi	0.431	0.269	0.370	0.138	0.414	1.000			0.275a
乌苏 Usu	−0.042	0.052	0.084	0.102	0.278	−0.021	1.000		0.084b
五家渠 Wujiaqu	0.217	0.351	0.488	0.244	0.486	0.360	0.088	1.000	0.322a
“平均值”列数据后不同小写字母表示P<0.05水平差异显著。Different lowercase letters in the “Average” column mean significant differences at P<0.05 level.

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表 3 2011—2020年西北内陆棉区早中熟组棉花品种试验环境间平均相关系数矩阵

Table 3. Average Pearson correlation coefficients among test locations across tested genotypes based on the lint yield data of the medium-early maturing cotton variety trials in the Northwest Inland cotton production region in 2011−2020

试验环境 Test location	阿拉尔 Alaer	巴州 Bazhou	拜城 Baicheng	库车 Kuqa	库尔勒 Korla	麦盖提 Makit	莎车 Shache	图木舒克 Tumxuk	平均值 Average
阿拉尔 Alaer	1.000								0.352a
巴州 Bazhou	0.293	1.000							0.274a
拜城 Baicheng	0.490	0.300	1.000						0.348a
库车 Kuqa	0.355	0.363	0.491	1.000					0.342a
库尔勒 Korla	0.295	0.356	0.304	0.305	1.000				0.283a
麦盖提 Makit	0.135	−0.147	0.062	−0.236	−0.048	1.000			−0.035b
莎车 Shache	0.351	0.249	0.308	0.377	0.319	0.124	1.000		0.314a
图木舒克 Tumxuk	0.469	0.394	0.463	0.450	0.370	−0.239	0.436	1.000	0.352a
“平均值”列数据后不同小写字母表示P<0.05水平差异显著。Different lowercase letters in the “Average” column mean significant differences at P<0.05 level.

下载: 导出CSV

表 4 2013年西北内陆棉区早中熟组国家棉花品种区域试验环境评价参数

Table 4. Standardized trial location evaluation parameters based on “discrimination and representativeness” GGE biplot for the medium-early maturing cotton trial dataset in the Northwest Inland national cotton production region in 2013

试验环境 Test location	鉴别力 Discriminating ability	代表性 Representativeness	理想指数 Desirability index
阿拉尔 Alaer	0.893	0.479	0.428
拜城 Baicheng	0.583	0.903	0.526
巴州 Bazhou	1.052	0.938	0.987
库车 Kuqa	1.267	0.938	1.188
麦盖提 Makit	1.435	0.411	0.590
莎车 Shache	1.331	0.999	1.330
图木舒克 Tumxuk	1.279	0.998	1.276

下载: 导出CSV

表 5 2011—2020年西北内陆棉区国家棉花品种区域试验环境综合评价参数

Table 5. Standardized trial location evaluation parameters based on “discrimination and representativeness” GGE biplot for the Northwest Inland national cotton variety trials from 2011 to 2020

棉区 Cotton production region	试验环境 Test location	鉴别力 Discriminating ability	代表性 Representativeness	理想指数 Desirability index
早熟棉区 Early-maturing cotton production region	博乐 Bole	0.882±0.10a	0.725±0.05ab	0.654±0.09ab
	敦煌 Dunhuang	0.923±0.03a	0.711±0.11ab	0.667±0.11ab
	精河 Jinghe	0.814±0.02a	0.882±0.06a	0.723±0.06ab
	奎屯 Kuytun	0.907±0.02a	0.619±0.18ab	0.582±0.16ab
	沙湾 Shawan	0.837±0.07a	0.877±0.04a	0.731±0.07a
	石河子 Shihezi	0.851±0.02a	0.729±0.1ab	0.622±0.09ab
	乌苏 Usu	0.800±0.08a	0.484±0.17b	0.422±0.14b
	五家渠 Wujiaqu	0.857±0.07a	0.831±0.06a	0.704±0.08ab
早中熟棉区 Medium-early maturing cotton production region	阿拉尔 Alaer	0.820±0.08a	0.851±0.06a	0.704±0.09a
	拜城 Baicheng	0.920±0.03a	0.711±0.08a	0.657±0.08a
	巴州 Bazhou	0.817±0.03a	0.924±0.02a	0.757±0.03a
	库尔勒 Korla	0.815±0.11a	0.805±0.08a	0.684±0.12a
	库车 Kuqa	0.872±0.03a	0.696±0.15a	0.627±0.13a
	麦盖提 Makit	0.939±0.02a	0.105±0.12b	0.109±0.11b
	莎车 Shache	0.835±0.07a	0.804±0.06a	0.683±0.08a
	图木舒克 Tumxuk	0.817±0.07a	0.862±0.07a	0.705±0.08a
同列数据后同一棉区不同小写字母表示P<0.05水平差异显著。Different lowercase letters for the same cotton production region in the same column mean significant differences among different trail environments at P<0.05 level.

下载: 导出CSV

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