基于GYT双标图分析对黄淮海夏玉米区域试验品种综合评价

doi:10.3724/SP.J.1006.2023.23035

作物学报 ›› 2023, Vol. 49 ›› Issue (5): 1231-1248.doi: 10.3724/SP.J.1006.2023.23035

• 作物遗传育种·种质资源·分子遗传学 • 上一篇下一篇

基于GYT双标图分析对黄淮海夏玉米区域试验品种综合评价

岳海旺¹(), 韩轩², 魏建伟¹, 郑书宏¹, 谢俊良¹, 陈淑萍¹, 彭海成¹, 卜俊周¹^,^*()

¹河北省农林科学院旱作农业研究所/河北省农作物抗旱研究重点实验室, 河北衡水 053333
²河北省农林科学院, 河北石家庄 050031

收稿日期:2022-04-18 接受日期:2022-10-10 出版日期:2023-05-12 网络出版日期:2022-10-26
通讯作者: *卜俊周, E-mail: bujunzhou@126.com
作者简介:岳海旺, E-mail: yanjiu1982@163.com第一联系人：^**同等贡献
基金资助:
河北省重点研发计划项目(20326305D);财政部和农业农村部国家现代农业产业技术体系建设专项(玉米, CARS-02);河北省科技支撑计划(16226323D-X);河北省农林科学院科技创新专项课题;河北省“三三三人才工程”人才培养项目(A202101056);河北省农业科技成果转化资金项目(21626310D)

Comprehensive evaluation of maize hybrids tested in Huang-Huai-Hai summer maize regional trial based on GYT biplot analysis

YUE Hai-Wang¹(), HAN Xuan², WEI Jian-Wei¹, ZHENG Shu-Hong¹, XIE Jun-Liang¹, CHEN Shu-Ping¹, PENG Hai-Cheng¹, BU Jun-Zhou¹^,^*()

¹Dryland Farming Institute, Hebei Academy of Agriculture and Forestry Sciences/Hebei Provincial Key Laboratory of Crops Drought Resistance Research, Hengshui 053000, Hebei, China
²Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang 050031, Hebei, China

Received:2022-04-18 Accepted:2022-10-10 Published:2023-05-12 Published online:2022-10-26
Contact: *E-mail: bujunzhou@126.com
About author:First author contact:^**Contributed equally to this work
Supported by:
Key Research and Development Projects of Hebei Province(20326305D);China Agriculture Research System of MOF and MARA(Maize, CARS-02);Science and Technology Support Program of Hebei Province(16226323D-X);HAAFS Science and Technology Innovation Special Project;“Three-Three-Three Talent Project” Funded Project in Hebei Province(A202101056);Agricultural Science and Technology Achievement Transformation Project of Hebei Province(21626310D)

摘要/Abstract

摘要：

旨在科学准确地对黄淮海夏播玉米区域试验参试品种进行综合评价, 为品种合理布局和区域规划提供理论和实践依据。本研究采用GYT双标图技术对2020—2021年黄淮海夏玉米区域试验22个参试品种的籽粒产量与生育期、收获时籽粒含水量、株高、穗位高、倒伏率、穗长、穗粗、秃尖, 穗粒重和百粒重等农艺性状的组合水平进行综合评价。方差分析表明, 被测农艺性状基因型和环境效应均达到了显著水平(P<0.05), 除穗粗、突尖长度和穗粒重等性状基因型与环境互作效应中无显著差异外, 其余性状基因型与环境互作效应均达到了显著水平。籽粒产量、生育期、收获时籽粒含水量、穗粗、秃尖和百粒重等性状环境效应平方和占总方差平方和最大, 倒伏率的基因型与环境互作效应平方和占总方差平方和最大。农艺性状相关性分析结果表明, 籽粒产量与百粒重、株高、穗位高、穗长、穗粗和生育期呈极显著正相关(P<0.001), 而与突尖长度呈负相关。根据参试品种的理想指数筛选出衡玉868、邯玉1806和宿单908等为产量-性状组合表现优良的品种, 同时也鉴别出陕单685、敦玉291、邯玉17-6601和邯玉573等品种综合表现较差, 对照品种郑单958表现一般。衡玉868较其他参试品种在黄淮海夏玉米区更具有广泛的适应性, 展现出绝对的区域产量优势, 具有广阔的推广前景。与GT双标图相比, GYT双标图显示出前2个主成分解释的变异比例较高、拟合度较好、分析结果可信度较高等优点。本研究运用GYT双标图技术对黄淮海夏玉米参试品种进行品种产量-性状特性分析, 为本区玉米品种综合评价提供借鉴, 也为其他作物品种多性状研究提供了参考。

关键词: GT双标图, GYT双标图, 理想指数, 夏玉米, 产量-性状组合

Abstract:

The objective of this study is to scientifically and accurately conduct a comprehensive evaluation of the tested hybrids participating in the Huang-Huai-Hai summer maize regional trials, and provide theoretical and practical basis for the rational distribution of hybrids and regional planning. GYT biplot analysis was applied to the data of 22 hybrids during 2020?2021 in the Huang-Huai-Hai summer maize regional trials to provide a comprehensive evaluation of the tested hybrids based on grain yield, growth period, grain moisture content at harvest, plant height, ear height, lodging rate, ear length, ear diameter, barren tip length, grain weight per ear, and hundred grain weight. The analysis of variance results showed that the genotype and environment main effects of the evaluated agronomic traits reached significant level at P < 0.05. Genotype and environment interaction effect of other traits had significant level, except for ear diameter, bald tip length, and grain weight per ear, which had no significant difference. The square sum of environmental effect on grain yield, growth period, grain moisture content, ear diameter, bare tip length, 100-seed weight, and the square sum of genotype and environment interaction effect on lodging rate were worth the largest in the square sum of total variance. The results of the correlation analysis showed that grain yield was significantly at P < 0.001 and positively correlated with 100-seed weight, plant height, ear height, ear length, ear diameter, and growth period, but negatively correlated with bald tip length. According to the GYT superiority index, Hengyu 868, Handyu 1806, and Sudan 908 had the best yield-trait combinations. The comprehensive performances of hybrids Shandan 686, Dunyu 291, Hanyu 17-6601, and Hanyu 573 were poor, and the performance of the control hybrid Zhengdan 958 was intermediate. Compared with other tested hybrids, Hengyu 868 had the widest adaptability in the Huang-Huai-Hai summer maize area, indicating outstanding regional yield advantages, and great potential for maize production in the region. Compared with the GT biplot, the GYT biplot showed that the first two principal components explained a higher proportion of variance, a better fit, and a higher reliability of the analysis results. Through GYT biplot analysis, maize hybrids with superior yield-trait combinations were identified, the GYT biplot analysis was a useful analytic tool for graphical evaluation based on multiple traits, and also set up a reference base for comprehensive evaluation of other crops.

Key words: genotype × trait biplot (GT biplot), genotype × yield × trait biplot (GYT biplot), superiority index (SI), summer maize hybrids, yield-trait combination

岳海旺, 韩轩, 魏建伟, 郑书宏, 谢俊良, 陈淑萍, 彭海成, 卜俊周. 基于GYT双标图分析对黄淮海夏玉米区域试验品种综合评价[J]. 作物学报, 2023, 49(5): 1231-1248.

YUE Hai-Wang, HAN Xuan, WEI Jian-Wei, ZHENG Shu-Hong, XIE Jun-Liang, CHEN Shu-Ping, PENG Hai-Cheng, BU Jun-Zhou. Comprehensive evaluation of maize hybrids tested in Huang-Huai-Hai summer maize regional trial based on GYT biplot analysis[J]. Acta Agronomica Sinica, 2023, 49(5): 1231-1248.

图/表 16

表1

参试品种信息"

品种名称 Hybrid name	品种缩写 Hybrid abbreviation	试验年份 Year	来源 Origin
敦玉286 Dunyu 286	DY286	2020	甘肃省敦煌种业集团股份有限公司 Gansu Dunhuang Seed Industry Group Co., Ltd.
敦玉291 Dunyu 291	DY291	2020	甘肃省敦煌种业集团股份有限公司 Gansu Dunhuang Seed Industry Group Co., Ltd.
邯玉1604 Hanyu 1604	HY1604	2020	邯郸市农业科学院 Handan Academy of Agricultural Sciences
邯玉573 HY 573	HY573	2021	邯郸市农业科学院 Handan Academy of Agricultural Sciences
邯玉17-6601 Hanyu 17-6601	HY17-6601	2020−2021	邯郸市农业科学院 Handan Academy of Agricultural Sciences
鲁单719	LD719	2020	山东省农业科学院玉米研究所
Ludan 719	LD719	2020	Maize Research Institute, Shandong Academy of Agricultural Sciences
鲁单0195	LD0195	2020	山东省农业科学院玉米研究所
Ludan 0195	LD0195	2020	Maize Research Institute, Shandong Academy of Agricultural Sciences
君育136	JY136	2020	河南技丰种业集团有限公司
Junyu 136	JY136	2020	Henan Jifeng Seed Industry Group Co., Ltd.
陕单685 Shaandan 685	SD685	2020	陕西荣华农业科技有限公司 Shaanxi Ronghua Agricultural Technology Co., Ltd.
新单96 Xindan 96	XD96	2020	新乡市农业科学院 Xinxiang Academy of Agricultural Sciences
宿单908 Sudan 908	SD908	2020−2021	宿州市农业科学院 Suzhou Academy of Agricultural Sciences
郑单6162	ZD6162	2020	河南省农业科学院粮食作物研究所
Zhengdan 6162	ZD6162	2020	Institute of Cereal Crops, Henan Academy of Agricultural Sciences
郑单958	ZD958	2020−2021	河南省农业科学院粮食作物研究所
Zhengdan 958	ZD958	2020−2021	Institute of Cereal Crops, Henan Academy of Agricultural Sciences
鲁宁818 Luning 818	LN818	2020	济宁市农业科学研究院 Jining Academy of Agricultural Sciences
漯玉19 Luoyu 19	LY19	2020	漯河市农业科学院 Luohe Academy of Agricultural Sciences
衡玉7182	HY7182	2020	河北省农林科学院旱作农业研究所
Hengyu 7182	HY7182	2020	Dryland Farming Institute, Hebei Academy of Agriculture and Forestry Sciences
衡玉9186 Hengyu 9186	HY9186	2021	河北省农林科学院旱作农业研究所 Dryland Farming Institute, Hebei Academy of Agriculture and Forestry Sciences
衡玉868 Hengyu 868	HY868	2020−2021	河北省农林科学院旱作农业研究所 Dryland Farming Institute, Hebei Academy of Agriculture and Forestry Sciences

表1

表2

试点环境信息"

省份 Province	试点 Testing site	经度 Longitude	纬度 Latitude	海拔 Altitude (m)	年降雨量 Annual rainfall (mm)	年份 Year
安徽Anhui	阜南Funan	115°55′	32°68′	34	824	2020-2021
安徽Anhui	宿州Suzhou	117°11′	33°60′	29	865	2020-2021
安徽Anhui	濉溪Suixi	116°84′	33°45′	31	902	2020-2021
河北Hebei	藁城Gaocheng	114°85′	38°02′	59	494	2020-2021
河北Hebei	邯郸Handan	114°54′	36°63′	55	515	2020-2021
河北Hebei	深州Shenzhou	115°56′	38°01′	28	482	2020-2021
省份 Province	试点 Testing site	经度 Longitude	纬度 Latitude	海拔 Altitude (m)	年降雨量 Annual rainfall (mm)	年份 Year
河北Hebei	武强Wuqiang	115°98′	38°06′	18	556	2020-2021
河北Hebei	鸡泽Jize	114°75′	37°03′	38	490	2020-2021
河北Hebei	高阳Gaoyang	115°79′	38°68′	12	342	2020-2021
河北Hebei	靳庄Jinzhuang	114°66′	38°01′	52	485	2020-2021
河北Hebei	内丘Neiqiu	114°34′	37°29′	149	531	2020-2021
河北Hebei	晋州Jinzhou	115°07′	38°02′	43	412	2020-2021
河南Henan	鹤壁Hebi	114°28′	35°74′	88	727	2020
河南Henan	辉县Huixian	113°80′	35°46′	95	589	2020-2021
河南Henan	临颍Linying	113°93′	33°83′	62	716	2020-2021
河南Henan	洛阳Luoyang	112°46′	34°61′	140	803	2020-2021
河南Henan	孟州Mengzhou	112°79′	34°91′	115	557	2020-2021
河南Henan	南阳Nanyang	112°52′	32°99′	131	875	2020-2021
河南Henan	西华Xihua	114°53′	33°76′	52	624	2020-2021
河南Henan	荥阳Xingyang	113°38′	34°79′	144	655	2020-2021
河南Henan	原阳Yuanyang	113°97′	35°05′	78	529	2020-2021
河南Henan	驻马店Zhumadian	114°02′	33°01′	84	702	2020-2021
河南Henan	柘城Zhecheng	115°12′	33°58′	46	781	2020-2021
湖北Hubei	襄阳Xiangyang	112°12′	32°01′	70	878	2020-2021
湖北Hubei	宜城Yicheng	112°30′	31°69′	120	862	2020-2021
江苏Jiangsu	丰县Fengxian	116°43′	34°70′	42	630	2020-2021
江苏Jiangsu	睢宁Suining	117°94′	33°91′	23	916	2021
山东Shandong	昌邑Changyi	119°42′	36°70′	33	562	2020-2021
山东Shandong	茌平Chiping	116°14′	36°34′	31	570	2020-2021
山东Shandong	德州Dezhou	116°36′	37°43′	23	547	2020-2021
山东Shandong	寒亭Hanting	119°20′	36°77′	20	622	2020-2021
山东Shandong	济宁Jining	116°54′	35°37′	38	693	2020-2021
山东Shandong	莱州Laizhou	119°95′	37°17′	56	614	2020-2021
山东Shandong	聊城Liaocheng	115°99′	36°46′	37	540	2020-2021
山东Shandong	泰安Tai’an	117°09′	36°20′	167	763	2020-2021
山东Shandong	章丘Zhangqiu	117°52′	36°68′	143	633	2020-2021
山东Shandong	宁津Ningjin	116°78′	37°72′	23	721	2020-2021
山东Shandong	郓城Yuncheng	115°75′	35°44′	48	694	2020-2021
山西Shanxi	新绛Xinjiang	111°01′	35°03′	439	460	2020-2021
山西Shanxi	盐湖Yanhu	110°89′	35°01′	369	487	2020-2021
陕西Shaanxi	杨凌Yangling	108°08′	34°27′	465	631	2020-2021
陕西Shaanxi	渭南Weinan	109°78′	34°95′	405	465	2020-2021

表2

附表1

附表2

表3

表4

图1

图2

图3

附表3

2020年参试品种标准化后的GYT数据和理性指数"

品种名称 Genotype name	产量×生育期 Y×GP	产量×株高 Y×PH	产量×穗位高 Y×EH	产量×倒伏率 Y×LR	产量×含水量 Y× GMC	产量×穗长 Y×EL	产量×穗粗 Y×ED	产量×秃尖长度 Y× BTL	产量×穗粒重 Y× GWE	产量×百粒重 Y×HSW	理想指数 Superiority index
敦玉286 Dunyu 286	0	0.45	0.39	1.37	−0.34	0.35	−0.56	−0.60	−0.16	−0.09	0.00
敦玉291 Dunyu 291	−0.20	−0.53	−0.47	−0.32	0.20	−0.59	−0.22	0.06	−0.39	−0.45	−0.29
邯玉1604 Hanyu 1604	0.86	1.41	0.84	1.95	0.33	0.69	0.97	−0.05	1.03	0.76	0.88
邯玉17-6601 Hanyu 17-6601	−0.13	1.05	0.23	−0.59	−0.43	0.78	−0.38	0.63	−0.12	0.01	0.11
衡玉7182 Hengyu 7182	0.60	−0.43	−1.18	−0.63	0.57	−0.17	0.96	1.02	0.60	1.04	0.24
衡玉868 Hengyu 868	0.66	0.73	0.56	1.86	1.13	1.15	0.66	0.66	1.00	0.69	0.91
君育136 Junyu 136	0.81	−0.45	0.61	−1.10	0.94	0.62	0.89	0.30	0.55	1.02	0.42
鲁单0195 Ludan 0195	−0.69	−0.39	−0.46	−0.27	−0.77	−0.29	−0.66	2.03	−0.80	−0.40	−0.27
鲁单719 Ludan 719	0.19	0.73	0.10	−0.51	0.12	−0.17	0.56	−1.38	0.62	−0.04	0.02
鲁宁818 Luning 818	0.65	0.40	0.71	−0.42	0.67	1.18	0.39	0.05	0.57	0.36	0.46
鲁宁19 Luning 19	0.19	−0.97	−0.75	−1.15	0.18	−0.36	0.30	−1.05	0.04	1.33	−0.22
陕单685 Shandan 685	−3.40	−2.69	−2.98	−1.10	−3.25	−3.06	−3.19	−0.77	−3.17	−3.02	−2.66
宿单908 Sudan 908	0.11	0.02	0.77	0.13	0.51	0.16	−0.12	0.20	−0.14	−0.40	0.12
新单96 Xindan 96	0.17	0.39	0.26	−0.04	0.37	0.50	0.47	−1.13	0.70	−0.12	0.16
郑单6162 Zhengdan 6162	0.17	0.94	0.85	0.84	−0.03	−0.14	−0.03	1.37	0.03	−0.52	0.35
郑单958 Zhengdan 958	−0.30	−0.66	0.50	−0.04	−0.21	−0.66	−0.05	−1.33	−0.38	−0.17	−0.33
平均 Mean	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
标准差Standard Deviation	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0

附表3

附表4

表5

表6

图4

图5

图6

参考文献 36

[1]	王克如, 李璐璐, 鲁镇胜, 高尚, 王浥州, 黄兆福, 谢瑞芝, 明博, 侯鹏, 薛军, 张镇涛, 侯梁宇, 李少昆. 黄淮海夏玉米机械化粒收质量及其主要影响因素. 农业工程学报, 2021, 37(7): 1-7.
	Wang K R, Li L L, Lu Z S, Gao S, Wang Y Z, Huang Z F, Xie R Z, Ming B, Hou P, Xue J, Zhang Z T, Hou L Y, Li S K. Mechanized grain harvesting quality of summer maize and its major influencing factors in Huanghuaihai region of China. Trans CSAE, 2021, 37(7): 1-7. (in Chinese with English abstract)
[2]	徐田军, 张勇, 赵久然, 王荣焕, 吕天放, 刘月娥, 蔡万涛, 刘宏伟, 陈传永, 王元东. 宜机收籽粒玉米品种冠层结构、光合及灌浆脱水特性. 作物学报, 2022, 48: 1526-1536. doi: 10.3724/SP.J.1006.2022.13036
	Xu T J, Zhang Y, Zhao J R, Wang R H, Lyu T F, Liu Y E, Cai W T, Liu H W, Chen C Y, Wang Y D. Canopy structure, photosynthesis, grain filling, and dehydration characteristics of maize varieties suitable for grain mechanical harvesting. Acta Agron Sin, 2022, 48: 1526-1536. (in Chinese with English abstract) doi: 10.3724/SP.J.1006.2022.13036
[3]	De Leon N, Jannink J L, Edwards J W, Kaeppler S M. Introduction to a special issue on genotype by environment interaction. Crop Sci, 2016, 56: 2081-2089. doi: 10.2135/cropsci2016.07.0002in
[4]	Malik W A, Forkman J, Piepho H P. Testing multiplicative terms in AMMI and GGE models for multienvironment trials with replicates. Theor Appl Genet, 2019, 132: 2087-2096. doi: 10.1007/s00122-019-03339-8 pmid: 30982926
[5]	Yue H W, Gauch H G, Wei J W, Xie J L, Chen S P, Peng H C, Bu J Z, Jiang X W. Genotype by environment interaction analysis for grain yield and yield components of summer maize hybrids across the Huanghuaihai region in China. Agriculture, 2022, 12: 602. doi: 10.3390/agriculture12050602
[6]	严威凯. 品种选育与评价的原理和方法评述. 作物学报, 2022, 48: 2137-2154. doi: 10.3724/SP.J.1006.2022.11105
	Yan W K. A critical review on the principles and procedures for cultivar development and evaluation. Acta Agron Sin, 2022, 48: 2137-2154. (in Chinese with English abstract) doi: 10.3724/SP.J.1006.2022.11105
[7]	朱亚利, 王晨光, 杨梅, 郑学慧, 赵成凤, 张仁和. 不同熟期玉米不同粒位籽粒灌浆和脱水特性对密度的响应. 作物学报, 2021, 47: 507-519. doi: 10.3724/SP.J.1006.2021.03024
	Zhu Y L, Wang C G, Yang M, Zheng X H, Zhao C F, Zhang R H. Response of grain filling and dehydration characteristics of kernels located in different ear positions in the different maturity maize hybrids to plant density. Acta Agron Sin, 2021, 47: 507-519. (in Chinese with English abstract) doi: 10.3724/SP.J.1006.2021.03024
[8]	Yue H W, Wang Y B, Wei J W, Meng Q M, Yang B L. Chen S P, Peng H C, Xie J L, Jiang X W. Effects of genotype-by- environment interaction on the main agronomic traits of maize hybrids. Appl Ecol Environ Res, 2020, 18: 1437-1458. doi: 10.15666/aeer
[9]	徐田军, 吕天放, 赵久然, 王荣焕, 邢锦丰, 张勇, 蔡万涛, 刘月娥, 刘秀芝, 陈传永, 王元东, 刘春阁. 不同播期条件下黄淮海区主推夏播玉米品种籽粒灌浆特性. 作物学报, 2021, 47: 566-574. doi: 10.3724/SP.J.1006.2021.03023
	Xu T J, Lyu T F, Zhao J R, Wang R H, Xing J F, Zhang Y, Cai W T, Liu Y E, Liu X Z, Chen C Y, Wang Y D, Liu C G. Grain filling characteristics of summer maize varieties under different sowing dates in the Huang-Huai-Hai region. Acta Agron Sin, 2021, 47: 566-574. (in Chinese with English abstract)
[10]	李少昆. 我国玉米机械粒收质量影响因素及粒收技术的发展方向. 石河子大学学报(自然科学版), 2017, 35: 265-272.
	Li S K. Factors affecting the quality of maize grain mechanical harvest and the development trend of grain harvest technology. J Shihezi Univ (Nat Sci Edn), 2017, 35: 265-272. (in Chinese with English abstract)
[11]	Kendal E. Comparing durum wheat cultivars by genotype × yield × trait and genotype × trait biplot method. Chil J Agric Res, 2019, 79: 512-522. doi: 10.4067/S0718-58392019000400512
[12]	Karahan T, Akgün I. Selection of barley (Hordeum vulgare) genotypes by GYT (genotype × yield × trait) biplot technique and its comparison with GT (genotype × trait). Appl Ecol Environ Res, 18: 1347-1359. doi: 10.15666/aeer
[13]	Al-Naggar A M M, Shafik M M, Musa R Y M. Genetic diversity based on morphological traits of 19 maize genotypes using principal component analysis and GT biplot. Annu Res Rev Biol, 2020, 35: 68-85.
[14]	Yan W K, Frégeau-Reid J. Genotype by yield × trait (GYT) biplot: a novel approach for genotype selection based on multiple traits. Sci Rep, 2018, 8: 8242. doi: 10.1038/s41598-018-26688-8
[15]	Gouveia B T, Barrios S C L, Do Valle C B, Gomes R D C, Machado W K R, Bueno Filho J S D S, Nunes J A R. Selection strategies for increasing the yield of high nutritional value leaf mass in Urochloa hybrids. Euphytica, 2020, 216: 38. doi: 10.1007/s10681-020-2574-3
[16]	Woyann L G, Meira D, Zdziarski A D, Matei G, Milioli A S, Rosa A C, Benin G. Multiple-trait selection of soybean for biodiesel production in Brazil. Ind Crop Prod, 2019, 140: 111721. doi: 10.1016/j.indcrop.2019.111721
[17]	Mohammadi R. Genotype by yield × trait biplot for genotype evaluation and trait profiles in durum wheat. Cereal Res Commun, 2019, 47: 541-551. doi: 10.1556/0806.47.2019.32
[18]	NY/T 1209- 2020. 农作物品种试验与信息化技术规程:玉米. 北京: 中国农业出版社, 2020.
	NY/T 1209- 2020. Regulations for the Variety Tests and Information of Field Crop:Maize (Zea mays L.). Beijing: China Agriculture Press, 2020. (in Chinese)
[19]	Yan W, Wu H X. Application of GGE biplot analysis to evaluate genotype (G), environment (E), and G × E interaction on Pinus radiata: a case study. New Zealand J For Sci, 2008, 38: 132-142.
[20]	Pourdad S S, Moghaddam M J. Study on seed yield stability of sunflower inbred lines through GGE biplot. Helia, 2013, 36: 19-28. doi: 10.2298/HEL1358019P
[21]	叶夕苗, 程鑫, 安聪聪, 袁剑龙, 余斌, 文国宏, 李高峰, 程李香, 王玉萍, 张峰. 马铃薯产量组分的基因型与环境互作及稳定性. 作物学报, 2020, 46: 354-364. doi: 10.3724/SP.J.1006.2020.94089
	Ye X M, Cheng X, An C C, Yuan J L, Yu B, Wen G H, Li G F, Cheng L X, Wang Y P, Zhang F. Genotype × environment interaction and stability of yield components for potato lines. Acta Agron Sin, 2020, 46: 354-364. (in Chinese with English abstract) doi: 10.3724/SP.J.1006.2020.94089
[22]	Rakshit S, Ganapathy K N, Gomashe S S, Rathore A, Ghorade R B, Kumar M V, Patil J V. GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi- location data. Euphytica, 2012, 185: 465-479. doi: 10.1007/s10681-012-0648-6
[23]	Tang Q Y, Zhang C X. Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research. Insect Sci, 2013, 20: 254-260. doi: 10.1111/j.1744-7917.2012.01519.x
[24]	岳海旺, 魏建伟, 谢俊良, 姚文影, 曹红梅, 陈淑萍, 彭海成, 卜俊周. 基因型和环境互作对黄淮海夏玉米品种籽粒产量的影响. 中国农业大学学报, 2022, 27(4): 31-43.
	Yue H W, Wei J W, Xie J L, Yao W Y, Cao H M, Chen S P, Peng H C, Bu J Z. Effect of interaction between genotype and environment on the grain yield of summer maize hybrids in Huanghuaihai region. J China Agric Univ, 2022, 27(4): 31-43. (in Chinese with English abstract)
[25]	岳海旺, 魏建伟, 卜俊周, 陈淑萍, 彭海成, 李春杰, 李媛, 谢俊良, 叶美金. 河北省春播玉米品种产量和主要穗部性状GGE双标图分析. 玉米科学, 2018, 26(4): 28-35.
	Yue H W, Wei J W, Bu J Z, Chen S P, Peng H C, Li C J, Li Y, Xie J L, Ye M J. GGE-biplot analysis of grain yield and main ear characteristics for spring maize in Hebei province. J Maize Sci, 2018, 26(4): 28-35. (in Chinese with English abstract)
[26]	岳海旺, 李春杰, 李媛, 卜俊周, 魏建伟, 彭海成, 陈淑萍, 谢俊良. 河北省春播玉米品种产量稳定性及试点辨别力综合分析. 核农学报, 2018, 32: 1267-1280. doi: 10.11869/j.issn.100-8551.2018.07.1267
	Yue H W, Li C J, Li Y, Bu J Z, Wei J W, Peng H C, Chen S P, Xie J L. Comprehensive analysis of yield stability and testing site discrimination of spring sowing maize variety in Hebei province. J Nucl Agric Sci, 2018, 32: 1267-1280. (in Chinese with English abstract) doi: 10.11869/j.issn.100-8551.2018.07.1267
[27]	Dolatabad S S, Choukan R, Hervan E M, Dehghani H. Biplot analysis for multi-environment trials of maize (Zea mays L.) hybrids in Iran. Crop Pasture Sci, 2010, 61: 700-707. doi: 10.1071/CP09325
[28]	Xu N Y, Fok M, Li J, Yang X N, Yan W K. Optimization of cotton variety registration criteria aided with a genotype-by-trait biplot analysis. Sci Rep, 2017, 7: 17237. doi: 10.1038/s41598-017-17631-4 pmid: 29222523
[29]	Boureima S, Abdoua Y. Genotype by yield × trait combination biplot approach to evaluate sesame genotypes on multiple traits basis. Turk J Field Crops, 2019, 24: 237-244.
[30]	Da Cruz D P, De Oliveira T R A, Gomes A B S, Gravina L M, Rocha R S, Da Costa Jaeggi M E P, Daher R F. Selection of cowpea lines for multiple traits by GYT biplot analysis. J Agric Stud, 2020, 8: 124-137.
[31]	Tsenov N, Gubatov T, Yanchev I. Genotype selection for grain yield and quality based on multiple traits of common wheat (Triticum aestivum L.). Cereal Res Commun, 2021, 49: 119-124. doi: 10.1007/s42976-020-00080-7
[32]	Yue H W, Wei J W, Xie J L, Chen S P, Peng H C, Cao H M, Bu J Z, Jiang X W. A study on genotype-by-environment interaction analysis for agronomic traits of maize genotypes across Huang- Huai-Hai region in China. Phyton-Int J Exp Bot, 2022, 91: 57-81.
[33]	Badu-Apraku B, Bankole F A, Ajayo B S, Fakorede M A B, Akinwale R O, Talabi A O, Ortega-Beltran A. Identification of early and extra-early maturing tropical maize inbred lines resistant to Exserohilum turcicum in sub-Saharan Africa. Crop Prot, 2021, 139: 105386. doi: 10.1016/j.cropro.2020.105386
[34]	Sofi P A, Saba I, Ara A, Rehman K. Comparative efficiency of GY × T approach over GT approach in genotypic selection in multiple trait evaluations: case study of common bean (Phaseolus vulgaris) grown under temperate Himalayan conditions. Agric Res, 2021, 9: 1-9. doi: 10.1007/s40003-019-00403-z
[35]	Yue H W, Jiang X W, Wei J W, Xie J L, Chen S P, Peng H C, Bu J Z. A study on genotype × environment interactions for the multiple traits of maize hybrids in China. Agron J, 2021, 113: 4889-4899. doi: 10.1002/agj2.v113.6
[36]	许乃银, 赵素琴, 张芳, 付小琼, 杨晓妮, 乔银桃, 孙世贤. 基于GYT双标图对西北内陆棉区国审棉花品种的分类评价. 作物学报, 2021, 47: 660-671. doi: 10.3724/SP.J.1006.2021.04135
	Xu N Y, Zhao S Q, Zhang F, Fu X Q, Yang X N, Qiao Y T, Sun S X. Retrospective evaluation of cotton varieties nationally registered for the Northwest Inland cotton growing regions based on GYT biplot analysis. Acta Agron Sin, 2021, 47: 660-671. (in Chinese with English abstract) doi: 10.3724/SP.J.1006.2021.04135

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

品种 Hybrid name	GY (kg hm^-2)	GP (d)	PH (cm)	EH (cm)	LR (%)	GMC (%)	EL (cm)	ED (cm)	BTL (cm)	GWE (g)	HSW (g)
邯玉1604 Hanyu 1604	11065.8	104.0	283	109	2.6	27.2	17.0	5.0	0.9	165.2	32.9
君育136 Junyu 136	10950.8	104.7	241	108	0.1	28.7	17.1	5.0	0.9	158.9	33.4
衡玉7182 Hengyu 7182	10842.3	104.3	245	86	0.5	28.3	16.1	5.1	1.2	161.6	34.1
鲁宁818 Luning 818	10798.2	105.0	265	110	0.7	28.6	18.1	4.9	0.9	160.3	33.1
衡玉868 Hengyu 868	10785.3	105.2	274	109	2.7	29.7	18.1	5.0	1.1	168.7	36.1
鲁单719 Ludan 719	10577.3	104.0	277	105	0.6	28.0	16.5	5.1	0.5	165.0	32.8
敦玉286 Dunyu 286	10564.5	104.8	273	109	2.7	27.0	17.2	4.6	0.7	151.9	33.0
新单96 Xindan 96	10515.9	104.4	273	108	1.1	28.7	17.6	5.1	0.6	167.2	32.4
漯玉19 Luoyu 19	10485.2	104.9	239	94	0.0	28.4	16.3	5.0	0.6	156.4	37.0
郑单6162 Zhengdan 6162	10422.2	105.3	289	116	1.9	28.0	16.7	4.9	1.3	157.6	31.6
宿单908 Sudan 908	10348.5	105.7	268	116	1.2	29.6	17.4	4.9	1.0	156.2	32.1
邯玉17-6601 Hanyu 17-6601	10296.6	104.4	295	108	0.5	27.5	18.4	4.8	1.1	155.5	34.8
敦玉291 Dunyu 291	10213.4	104.8	257	101	0.8	29.1	16.3	4.9	0.9	152.9	32.3
郑单958 Zhengdan 958	10091.1	105.3	257	115	1.1	28.7	16.5	5.0	0.5	155.5	33.6
鲁单0195 Ludan 0195	9898.4	104.3	269	104	0.9	27.9	17.4	4.9	1.6	150.2	35.7
陕单685 Shandan 685	7953.0	104.4	260	86	0.1	28.2	16.0	4.6	0.9	128.8	30.9

品种 Hybrid	GY (kg hm^-2)	GP (d)	PH (cm)	EH (cm)	LR (%)	GMC (%)	EL (cm)	ED (cm)	BTL (cm)	HSW (g)
衡玉868 Hengyu 868	9074.4	107.1	267.9	93.0	0.3	30.9	18.1	4.8	1.4	31.7
宿单908 Sudan 908	8977.5	106.3	260.2	108.2	0.6	29.2	17.0	4.8	0.9	28.8
衡玉9186 Hengyu 9186	8572.2	104.9	243.0	93.4	0.4	25.2	17.3	4.3	0.4	25.7
郑单958 Zhengdan 958	8211.8	106.2	252.8	102.7	2.0	28.8	16.0	4.8	0.6	27.4
邯玉17-6601 Hanyu 17-6601	8195.9	105.9	287.9	99.6	0.3	27.8	17.3	4.6	1.2	28.0
邯玉573 Hanyu 573	8098.8	106.1	290.1	94.9	0.1	27.5	17.7	4.5	1.2	28.7

变异来源 Source of variations	自由度 DF	籽粒产量 Grain yield (kg hm^-2)		生育期 Growth period (d)		株高 Plant height (cm)		穗长 Ear length (cm)		籽粒含水量 Grain moisture content (%)		秃尖 Bare tip length (cm)
变异来源 Source of variations	自由度 DF	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)
基因型Genotype (G)	15	1,401,266.56^**	15.54	161.27^**	1.30	16.23^**	27.36	340.63^**	21.33	324.45^**	0.87	55.38^**	13.31
环境Environment (E)	40	5,849,359.39^**	64.85	11,559.51^**	93.09	16.44^**	27.71	615.92^**	38.56	35,323.17^**	94.47	191.95^**	46.13
互作 GE	600	1,768,956.03^**	19.61	697.17^**	5.61	26.65^**	44.92	640.65^**	40.11	1743.21^**	4.66	168.80^ns	40.56
残差 Residuals	544	968,945.72		544.89		4.65		501.51		1136.71		136.02
总变异 Total	655	9,019,581.99		12,417.95		59.32		1597.20		37,390.82		416.12
变异来源 Source of variations	自由度 DF	倒伏率 Lodging rate (%)		百粒重 Hundred seed weight (g)		穗位高 Ear height (cm)		穗粗 Ear diameter (cm)		穗粒重 Grain weight per ear (g)
变异来源 Source of variations	自由度 DF	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)
基因型Genotype (G)	15	39.98^**	5.41	1749.95^**	12.10	5.52^**	36.41	13.95^**	22.82	53,219.64^**	7.48
环境Environment (E)	40	137.37^**	18.60	9288.23^**	64.25	5.32^**	35.11	30.07^**	49.18	489,725.83^**	68.84
互作 GE	600	561.13^**	75.99	3418.46^**	23.65	4.32^**	28.48	17.12^ns	28.00	168,400.87^**	23.67
残差 Residuals	544	299.16		2217.74		3.13		13.51		141,400.99
总变异 Total	655	738.48		14,456.64		15.16		61.13		711,346.35

变异来源 Source of variations	自由度 DF	籽粒产量 Grain yield (kg hm^-2)		生育期 Growth period (d)		株高 Plant height (cm)		穗长 Ear length (cm)		籽粒含水量 Grain moisture content (%)
变异来源 Source of variations	自由度 DF	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)
基因型Genotype (G)	5	163,431.34^**	3.76	107.79^**	1.73	73,459.78^**	34.58	105.95^**	9.19	740.97^**	13.45
环境Environment (E)	40	3,805,577.11^**	87.66	5836.37^**	93.89	108,081.84^**	50.88	852.20^**	73.95	4265.29^**	77.43
互作 GE	200	372,322.27^**	8.58	272.21^**	4.38	30,867.77^**	14.53	194.19^**	16.85	502.61^**	9.12
残差 Residuals	114	112,318.41		95.35		10,134.95		70.03		183.33
总变异 Total	245	4,341,330.71		6216.37		212,409.39		1152.34		5505.87
变异来源 Source of variations	自由度 DF	秃尖 Bare tip length (cm)		倒伏率 Lodging rate (%)		百粒重 Hundred seed weight (g)		穗位高 Ear height (cm)		穗粗 Ear diameter (cm)
变异来源 Source of variations	自由度 DF	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)	SS	PSS (%)
基因型Genotype (G)	5	32.45^**	18.77	95.00^**	3.68	824.08^**	13.32	7508.64^**	12.25	7.77^**	12.19
环境Environment (E)	40	75.89^**	43.90	896.29^**	34.69	4287.08^**	69.27	44,148.26^**	72.05	50.29^**	78.88
互作 GE	200	64.52^ns	37.33	1592.45^**	61.63	1077.74^**	17.41	9621.09^*	15.70	5.69^ns	8.93
残差 Residuals	114	40.36		73.37		317.12		3973.98		2.51
总变异 Total	245	172.86		2583.74		6188.91		61,277.99		63.76

组合Combination	Y×GP	Y×PH	Y×EH	Y×LR	Y×GMC	Y×EL	Y×ED	Y×BTL	Y×GWE	Y×HSW
产量×生育期Y×GP	1
产量×株高Y×PH	0.749^**	1
产量×穗位高Y×EH	0.797^**	0.823^**	1
产量×倒伏率Y×LR	0.377^ns	0.634^**	0.532*	1
产量×籽粒含水量Y×GMC	0.952^**	0.626^**	0.748^**	0.289^ns	1
产量×穗长Y×EL	0.893^**	0.829^**	0.835^**	0.430^ns	0.847^**	1
产量×穗粗Y×ED	0.953^**	0.653^**	0.686^**	0.259^ns	0.942^**	0.794^**	1
产量×突尖长度Y×BTL	0.150^ns	0.216^ns	0.106^ns	0.161^ns	0.140^ns	0.239^ns	0.084^ns	1
产量×穗粒重Y×GWE	0.963^**	0.783^**	0.755^**	0.397^ns	0.934^**	0.883^**	0.969^**	0.072^ns	1
产量×百粒重Y×HSW	0.901^**	0.502^*	0.544^*	0.151^ns	0.860^**	0.758^**	0.911^**	0.106^ns	0.866^**	1

基于GYT双标图分析对黄淮海夏玉米区域试验品种综合评价

Comprehensive evaluation of maize hybrids tested in Huang-Huai-Hai summer maize regional trial based on GYT biplot analysis

RichHTML

PDF

摘要/Abstract

引用本文

使用本文

图/表 16

参考文献 36

相关文章 15

Metrics

本文评价

推荐阅读 10

关于本刊

在线期刊

作者中心

相关单位

联系我们

品种名称 Genotype name	产量×生育期 Y×GP	产量×株高 Y×PH	产量×穗位高 Y×EH	产量×倒伏率 Y×LR	产量×含水量 Y×GMC	产量×穗长 Y×EL	产量×穗粗 Y×ED	产量×秃尖 Y× BTL	产量×百粒重 Y× HSW	理想指数 Superiority index
邯玉17-6601 Hanyu 17-6601	−0.78	0.63	−0.32	−0.48	−0.55	−0.39	−0.54	0.41	−0.57	−0.29
邯玉573 Hanyu 573	−0.91	0.51	−1.05	−0.79	−0.70	−0.27	−0.99	0.45	−0.30	−0.45
衡玉868 Hanyu 868	1.42	1.00	0.03	−0.40	1.56	1.54	1.33	1.38	1.75	1.07
衡玉9186 Hengyu 9186	−0.11	−1.25	−0.58	−0.31	−1.01	0.12	−0.85	−1.31	−0.84	−0.68
宿单908 Sudan 908	1.04	0.39	1.86	0.00	0.85	0.47	1.11	0.06	0.62	0.71
郑单958 Zhengdan 958	−0.67	−1.28	0.05	1.97	−0.16	−1.47	−0.07	−0.99	−0.66	−0.36
平均Mean	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
标准差Standard Deviation	0.91	0.91	0.91	0.91	0.91	0.91	0.91	0.91	0.91

组合Combination	Y×GP	Y×PH	Y×EH	Y×LR	Y×GMC	Y×EL	Y×ED	Y×BTL	Y×HSW
产量×生育期Y×GP	1
产量×株高Y×PH	0.374^ns	1
产量×穗位高Y×EH	0.642^ns	0.138^ns	1
产量×倒伏率Y×LR	-0.154^ns	-0.648^ns	0.248^ns	1
产量×籽粒含水量Y×GMC	0.878^*	0.529^ns	0.623^ns	0.038^ns	1
产量×穗长Y×EL	0.842^*	0.612^ns	0.237^ns	-0.630^ns	0.665^ns	1
产量×穗粗Y×ED	0.902^*	0.414^ns	0.760^ns	0.125^ns	0.976^**	0.612^ns	1
产量×突尖长度Y×BTL	0.422^ns	0.960^**	0.053	-0.532^ns	0.630^ns	0.634^ns	0.485^ns	1
产量×百粒重Y×HSW	0.877^*	0.673^ns	0.429^ns	-0.247^ns	0.947^**	0.832^*	0.876^*	0.769	1

[1]	张振博, 贾春兰, 任佰朝, 刘鹏, 赵斌, 张吉旺. 氮磷配施对夏玉米产量和叶片衰老特性的影响[J]. 作物学报, 2023, 49(6): 1616-1629.
[2]	李慧, 王旭敏, 刘苗, 刘朋召, 李巧丽, 王小利, 王瑞, 李军. 基于夏玉米产量和氮素利用的水氮减量方案优选[J]. 作物学报, 2023, 49(5): 1292-1304.
[3]	张俊杰, 陈金平, 汤钰镂, 张锐, 曹红章, 王丽娟, 马梦金, 王浩, 王泳超, 郭家萌, KRISHNA SV Jagadish, 杨青华, 邵瑞鑫. 花期前后干旱胁迫对复水后夏玉米光合特性与产量的影响[J]. 作物学报, 2023, 49(5): 1397-1409.
[4]	许乃银, 王扬, 王丹涛, 宁贺佳, 杨晓妮, 乔银桃. 棉花纤维质量指数的构建与WGT双标图分析[J]. 作物学报, 2023, 49(5): 1262-1271.
[5]	刘昕萌, 程乙, 刘玉文, 庞尚水, 叶秀芹, 卜艳霞, 张吉旺, 赵斌, 任佰朝, 任昊, 刘鹏. 黄淮海区域现代夏玉米品种产量与资源利用效率的差异分析[J]. 作物学报, 2023, 49(5): 1363-1371.
[6]	张金鑫, 葛均筑, 马玮, 丁在松, 王新兵, 李从锋, 周宝元, 赵明. 华北平原冬小麦-夏玉米种植体系周年水分高效利用研究进展[J]. 作物学报, 2023, 49(4): 879-892.
[7]	宋杰, 王少祥, 李亮, 黄金苓, 赵斌, 张吉旺, 任佰朝, 刘鹏. 施钾量对夏玉米氮、磷、钾吸收利用和籽粒产量的影响[J]. 作物学报, 2023, 49(2): 539-551.
[8]	刘梦, 张垚, 葛均筑, 周宝元, 吴锡冬, 杨永安, 侯海鹏. 不同降雨年型施氮量与收获期对夏玉米产量及氮肥利用效率的影响[J]. 作物学报, 2023, 49(2): 497-510.
[9]	张振博, 屈馨月, 于宁宁, 任佰朝, 刘鹏, 赵斌, 张吉旺. 施氮量对夏玉米籽粒灌浆特性和内源激素作用的影响[J]. 作物学报, 2022, 48(9): 2366-2376.
[10]	裴丽珍, 陈远学, 张雯雯, 肖华, 张森, 周元, 徐开未. 有机物料还田对夏玉米穗位叶光合性能及氮代谢的影响[J]. 作物学报, 2022, 48(8): 2115-2124.
[11]	陈静, 任佰朝, 赵斌, 刘鹏, 张吉旺. 叶面喷施甜菜碱对不同播期夏玉米产量形成及抗氧化能力的调控[J]. 作物学报, 2022, 48(6): 1502-1515.
[12]	朱亚迪, 王慧琴, 王洪章, 任昊, 吕建华, 赵斌, 张吉旺, 任佰朝, 殷复伟, 刘鹏. 不同夏玉米品种大喇叭口期耐热性评价和鉴定指标筛选[J]. 作物学报, 2022, 48(12): 3130-3143.
[13]	宋杰, 任昊, 赵斌, 张吉旺, 任佰朝, 李亮, 王少祥, 黄金苓, 刘鹏. 施钾量对夏玉米维管组织结构与物质运输性能的影响[J]. 作物学报, 2022, 48(11): 2908-2919.
[14]	张倩, 韩本高, 张博, 盛开, 李岚涛, 王宜伦. 控失尿素减施及不同配比对夏玉米产量及氮肥效率的影响[J]. 作物学报, 2022, 48(1): 180-192.
[15]	李静, 王洪章, 刘鹏, 张吉旺, 赵斌, 任佰朝. 夏玉米不同栽培模式花后叶片光合性能的差异[J]. 作物学报, 2021, 47(7): 1351-1359.