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Acta Agronomica Sinica ›› 2026, Vol. 52 ›› Issue (5): 1352-1364.doi: 10.3724/SP.J.1006.2026.53086

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Genetic diversity analysis of nationally approved maize varieties in different ecological regions

Yang Yang(), Chang Shi-Hui(), Tian Hong-Li(), Yi Hong-Mei, Wang Lu, Ren Jie, Fan Ya-Ming, Liu Ya-Wei, Wang Feng-Ge*(), Zhao Jiu-Ran*()   

  1. Maize Research Institute, Beijing Academy of Agriculture and Forestry Sciences / Key Laboratory of Crop DNA Fingerprinting Innovation and Utilization of the Ministry of Agriculture and Rural Affairs (Co-construction by Ministry and Province) / Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing 100097, China
  • Received:2025-10-31 Accepted:2026-01-22 Online:2026-05-12 Published:2026-02-05
  • Contact: *Zhao Jiu-Ran, E-mail: maizezhao@126.com; Wang Feng-Ge, E-mail: gege0101@163.com
  • About author:First author contact:**Contributed equally to this work
  • Supported by:
    Biological Breeding-National Science and Technology Major Project(2022ZD04019);Science and Technology Innovation Capacity Building Project of BAAFS(KJCX20230303);Beijing Scholars Program(BSP041)

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Abstract:

Analyzing the genetic diversity of maize varieties approved at the national level across different ecological regions reveals patterns of genetic differentiation among regional germplasms. This provides a theoretical basis for elite germplasm screening and region-specific variety breeding. In this study, 273 nationally approved common maize varieties were analyzed. Sixteen field phenotypic traits and genetic variation parameters based on 40 SSR markers were statistically evaluated. Cluster analysis and association analysis of phenotypic and genotypic data were conducted to explore the relationships among phenotypes, genotypes, and environmental factors in common maize. The results showed significant differences in growth period and regional trial yield across ecological regions, with F values of 2484.95 and 472.83, respectively. Genetic diversity was relatively high in the Xi-Nan spring-sowing region (XN), with a gene diversity index of 0.72. Phenotypic clustering divided 325 variety records into four groups: Group X1 mainly included varieties from the Dong-Hua-Bei (DHB) and Xi-Bei (XB) spring-sowing regions; Group X2 was dominated by varieties from the Bei-Fang (BF) early-maturity spring-sowing region; Group X3 included varieties from the XN region; and Group X4 mostly comprised varieties from the Huang-Huai-Hai (HHH) summer-sowing and Dong-Nan (DN) spring-sowing regions. Phenotypic differentiation among ecological regions followed clear trends: DHB and XB varieties were characterized by medium-late maturity and tall stalks; BF by early maturity and medium short stalks; XN by medium maturity and medium stalks; and HHH and DN by early maturity and medium stalks. Notably, XN, HHH, and DN regions experienced relatively high disease pressure. Principal component analysis (PCA) of phenotypic traits showed that the first two components explained 69.0% of the total variance, with clear group separation, supporting the validity of the phenotypic classifications. Genotypic clustering also divided the 273 varieties into four groups. In Group Y1, the predominant heterosis patterns were Reid × X and Improved Reid × X; in Group Y2, X × Tangsipingtou (Huangzaosi-derived lines); and in Group Y4, Improved Reid × Tangsipingtou. Genotypic PCA demonstrated a cumulative contribution of 57.9% from the first two components, with clear intra-group cohesion and significant inter-group differentiation, confirming the reliability of the genotypic groupings. Association analysis between genotypes and phenotypes revealed a weak correlation, likely due to the design objectives of molecular marker selection. Maize varieties from different ecological regions in China exhibit distinct regional differentiation in field performance and parental heterosis groups, resulting in a well-defined correspondence among ecological zones, trait expression, and genetic background. This pattern reflects region-specific breeding goals that prioritize yield stability and efficient resource utilization.

Key words: maize, nationally approved varieties, ecological regions, phenotypic data, genotypic data, genetic diversity

Fig. 1

Differences in the statistical distribution of phenotypes of nationally approved maize varieties in different ecological regions A-P represent the statistical distribution of growth period, plant height, ear height, number of leaves, anther color, planting density, ear length, hundred kernel weight, grain yield in regional trials, seed capacity, crude fat content, crude protein content, lysine content, crude starch content, stalk rot resistance and ear rot resistance across different ecological regions. The horizontal axis represents ecological regions. BF: Bei-Fang early-maturity spring-sowing region; DHB: Dong-Hua-Bei spring-sowing region; HHH: Huang-Huai-Hai summer-sowing region; XB: Xi-Bei spring-sowing region; XN: Xi-Nan spring-sowing region; DN: Dong-Nan spring-sowing region. In Figures 1-O and 1-P, vertical axis values 1 to 5 represent highly susceptible, susceptible, moderately resistant, resistant, and highly resistant, respectively."

Table 1

Comparison of genetic variation diversity in nationally approved maize varieties across different ecological regions"

生态区
Ecological region		 样本数
Sample number		 基因型总数
Total number of
genotypes		 等位变异总数
Total number of alleles		 基因多样性
Gene
diversity		 杂合度
Heterozygosity
(%)		 多态性信息含量
PIC
北方早熟春播区
Northern early-maturity spring-sowing region		 10 248 219 0.66 68 0.62
东华北春播区
Northeast and North spring-sowing region		 108 672 342 0.63 68 0.59
黄淮海夏播区
Huang-Huai-Hai summer-sowing region		 103 586 325 0.64 69 0.59
西北春播区
Northwest spring-sowing region		 24 337 238 0.61 68 0.57
西南春播区
Southwest spring-sowing region		 25 503 327 0.72 67 0.69
东南春播区
Southeast spring-sowing region		 3 97 133 0.59 72 0.53

Fig. 2

Cluster analysis of phenotypic data of nationally approved maize varieties A: phylogenetic tree based on phenotypic data; B: principal component analysis based on the Euclidean distance matrix. Branch labels from the innermost to the outer circle represent: ecological region (ER), growth period (C1), plant height (C2), ear height (C3), number of leaves (C4), anther color (C5), planting density (C6), ear length (C7), hundred kernel weight (C8), grain yield in regional trials (C9), seed capacity (C10), crude fat content (C11), crude protein content (C12), lysine content (C13), crude starch content (C14), stalk rot resistance (C15), and ear rot resistance (C16). C: circle. Abbreviations are the same as those given in Fig. 1."

Table 2

Summary of the number of variety records grouped by phenotypic clustering in different ecological regions"

生态区
Ecological region		 X1组
Group X1		 X2组
Group X2		 X3组
Group X3		 X4组
Group X4
北方早熟春播区
Northern early-maturity spring-sowing region		 — 9 — 1
东华北春播区
Northeast and North spring-sowing region		 119 — — —
黄淮海夏播区
Huang-Huai-Hai summer-sowing region		 — 4 1 118
西北春播区
Northwest spring-sowing region		 38 — —
西南春播区
Southwest spring-sowing region		 — 1 27 3
东南春播区
Southeast spring-sowing region		 — — — 4

Fig. 3

Cluster analysis of genotypic data of nationally approved maize varieties A: phylogenetic tree based on genotypic data; B: principal component analysis based on Rogers’s 1972 distance matrix. Branch labels from the inner circle to the outer circle are: ecological region (ER), parental heterosis group 1 (PG1), parental heterosis group 2 (PG2); the parental heterosis groups include Tangsipingtou, P group, Reid, Improver Reid, X group, Lancaster, Lvda red cob, Mixed 1 and Mixed 2. Abbreviations are the same as those given in Fig. 1."

Table 3

Summary of the number of varieties grouped by genotypic clustering in different ecological regions"

生态区
Ecological region		 Y1组
Group Y1		 Y2组
Group Y2		 Y3组
Group Y3		 Y4组
Group Y4
北方早熟春播区
Northern early-maturity spring-sowing region		 1 — 9 —
东华北春播区
Northeast and North spring-sowing region		 75 14 18 1
黄淮海夏播区
Huang-Huai-Hai summer-sowing region		 59 20 11 13
西北春播区
Northwest spring-sowing region		 19 3 1 1
西南春播区
Southwest spring-sowing region		 3 — 20 2
东南春播区
Southeast spring-sowing region		 — — 1 2

Fig. 4

Phylogenetic tanglegram of phenotypic versus genotypic data The left side shows the phylogenetic tree based on phenotypic data, and the right side shows the tree based on genotypic data. Groups X1-X4 are phenotypic clustering groups, and groups Y1-Y4 are genotypic clustering groups."

Fig. 5

Correlation between phenotypic and genotypic data GP: growth period; PH: plant height; EH: ear height; LN: number of leaves; AC: anther color; PD: planting density; EL: ear length; HKW: hundred kernel weight; RGY: grain yield in regional trials; SC: seed capacity; CFC: crude fat content; CPC: crude protein content; LC: lysine content; CSC: crude starch content; SRR: stalk rot resistance; ERR: ear rot resistance. P01-P40 represent the 40 SSR markers of genotypic data."

[1] 李少昆, 赵久然, 董树亭, 等. 中国玉米栽培研究进展与展望. 中国农业科学, 2017, 50: 1941-1959.
doi: 10.3864/j.issn.0578-1752.2017.11.001
Li S K, Zhao J R, Dong S T, et al. Advances and prospects of maize cultivation in China. Sci Agric Sin, 2017, 50: 1941-1959 (in Chinese with English abstract).
doi: 10.3864/j.issn.0578-1752.2017.11.001
[2] 杨扬, 王凤格, 赵久然, 等. 中国玉米品种审定现状分析. 中国农业科学, 2014, 47: 4360-4370.
doi: 10.3864/j.issn.0578-1752.2014.22.002
Yang Y, Wang F G, Zhao J R, et al. Analysis of the current situation of accredited maize varieties in China. Sci Agric Sin, 2014, 47: 4360-4370 (in Chinese with English abstract).
[3] Zhao Y, Fang J Q, Gislum R, et al. Genetic diversity analysis of phenotypic and agronomic traits in oat germplasm resources. Front Plant Sci, 2025, 16: 1670684.
doi: 10.3389/fpls.2025.1670684
[4] Chaudhary D, Gore P G, Wankhede D P, et al. Morphological variability and genetic diversity assessment of agronomic traits in cowpea (Vigna unguiculata (L.) Walp.) core collection using multivariate analysis. Genet Resour Crop Evol, 2025, 72: 6027-6042.
doi: 10.1007/s10722-024-02299-3
[5] 孙博微, 邳植, 李胜男, 等. 国外引进甜菜品种的表型性状遗传多样性分析. 植物遗传资源学报, 2026, 27: 351-361.
Sun B W, Pi Z, Li S N, et al. Analysis of phenotypic trait genetic diversity in foreign sugar beet varieties. J Plant Genet Resour, 2026, 27: 351-361 (in Chinese with English abstract).
[6] 张盼, 卢道文, 孙海潮, 等. 近年国审玉米品种品质性状演变及不同生态区间差异分析. 玉米科学, 2025, 33(5): 27-34.
Zhang P, Lu D W, Sun H C, et al. The evolution of quality traits and differences between different regions for maize hybrids recently approved in China. J Maize Sci, 2025, 33(5): 27-34 (in Chinese with English abstract).
[7] 李清超, 张登峰, 杨珊, 等. 326份玉米种质资源多样性分析. 甘肃农业大学学报, 网络首发[2024-07-03], https://kns.cnki.net/KCMS/detail/detail.aspxfilename=GSND20240701001&dbname=CJFD&dbcode=CJFQ.
Li Q C, Zhang D F, Yang S, et al. Diversity analysis of 326 maize germplasm resources. J Gansu Agric Univ,Published online [2024-07-03], https://kns.cnki.net/KCMS/detail/detail.aspxfilename=GSND20240701001&dbname=CJFD&dbcode=CJFQ (in Chinese with English abstract).
[8] 贺乔乔, 周希希, 王业文, 等. 基于SNP和表型性状的籼稻种质资源遗传多样性研究. 中国农业大学学报, 2023, 28(8): 80-93.
He Q Q, Zhou X X, Wang Y W, et al. Genetic diversity of Indica rice germplasm resources based on SNP and phenotypic markers. J China Agric Univ, 2023, 28(8): 80-93 (in Chinese with English abstract).
[9] 杨扬, 仇律雯, 田红丽, 等. 308个糯玉米审定品种SSR标记遗传多样性分析. 植物遗传资源学报, 2022, 23: 169-176.
doi: 10.13430/j.cnki.jpgr.20210629001
Yang Y, Qiu L W, Tian H L, et al. Genetic diversity analysis of 308 waxy maize varieties by SSR markers. J Plant Genet Resour, 2022, 23: 169-176 (in Chinese with English abstract).
[10] 易红梅, 任洁, 王璐, 等. 2014-2019年国家玉米区域试验参试组合DNA指纹检测及遗传多样性分析. 华北农学报, 2020, 35(3): 87-93.
doi: 10.7668/hbnxb.20191055
Yi H M, Ren J, Wang L, et al. DNA fingerprinting and genetic diversity analysis of national maize regional trials in 2014-2019. Acta Agric Boreali-Sin, 2020, 35(3): 87-93 (in Chinese with English abstract).
doi: 10.7668/hbnxb.20191055
[11] Wu M L, Bai Y Y, Huang L W, et al. SSR marker-based genetic diversity and relationship analyses of Stephania tetrandra S. Moore. Plant Mol Biol Report, 2024, 42: 675-687.
[12] Yin J W, Zhao H, Wu X T, et al. SSR marker based analysis for identification and of genetic diversity of non-heading Chinese cabbage varieties. Front Plant Sci, 2023, 14: 1112748.
doi: 10.3389/fpls.2023.1112748
[13] 李婷婷, 郭瑞, 王江浩, 等. 河北省玉米地方种质资源表型多样性分析. 玉米科学, 2025, 33(8): 1-11.
Li T T, Guo R, Wang J H, et al. Phenotypic diversity analysis of maize landrace germplasm in Hebei province. J Maize Sci, 2025, 33(8): 1-11 (in Chinese with English abstract).
[14] 田红丽, 赵紫薇, 杨扬, 等. 290个吉林省审定玉米品种SSR-DNA指纹构建及遗传多样性分析. 作物学报, 2022, 48: 2994-3003.
doi: 10.3724/SP.J.1006.2022.13076
Tian H L, Zhao Z W, Yang Y, et al. Construction of SSR-DNA fingerprints and genetic diversity analysis of 290 maize varieties approved in Jilin province, China. Acta Agron Sin, 2022, 48: 2994-3003 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2022.13076
[15] 薛亚鹏, 辛旭霞, 王若楠, 等. 国内外谷子资源农艺、品质性状差异分析以及遗传多样性研究. 作物学报, 2024, 50: 2468-2482.
doi: 10.3724/SP.J.1006.2024.44041
Xue Y P, Xin X X, Wang R N, et al. Analysis of agronomic, quality traits and genetic diversity of domestic and foreign foxtail millet resources. Acta Agron Sin, 2024, 50: 2468-2482 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2024.44041
[16] 柯会锋, 苏红梅, 孙正文, 等. 棉花现代品种资源产量与纤维品质性状鉴定及分子标记评价. 作物学报, 2024, 50: 280-293.
doi: 10.3724/SP.J.1006.2023.34075
Ke H F, Su H M, Sun Z W, et al. Identification for yield and fiber quality traits and evaluation of molecular markers in modern cotton varieties. Acta Agron Sin, 2024, 50: 280-293 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2023.34075
[17] 周泽宇, 张力科, 王凤格, 等. 国审玉米品种(2014-2017年) SSR指纹图谱. 北京: 中国农业科学技术出版社, 2021. pp 1-369.
Zhou Z Y, Zhang L K, Wang F G, et al. SSR fingerprint maps of maize varieties approved by nation (2014-2017). China Agricultural Science and Technology Press, 2021. pp 1-369 (in Chinese).
[18] 周泽宇, 晋芳, 刘丰泽, 等. 国审玉米品种(2018-2019年) SSR指纹图谱. 北京: 中国农业科学技术出版社, 2021. pp 1-283.
Zhou Z Y, Jin F, Liu F Z, et al. SSR fingerprint maps of maize varieties approved by nation (2018-2019). China Agricultural Science and Technology Press, 2021. pp 1-283 (in Chinese).
[19] Liu K J, Muse S V. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics, 2005, 21: 2128-2129.
doi: 10.1093/bioinformatics/bti282 pmid: 15705655
[20] Subramanian B, Gao S H, Lercher M J, et al. Evolview v3: a webserver for visualization, annotation, and management of phylogenetic trees. Nucleic Acids Res, 2019, 47: W270-W275.
doi: 10.1093/nar/gkz357
[21] 王凤格, 杨扬, 易红梅, 等.中国玉米审定品种标准SSR指纹库的构建. 中国农业科学, 2017, 50: 1-14.
Wang F G, Yang Y, Yi H M, et al. Construction of an SSR-based standard fingerprint database for corn variety authorized in China. Sci Agric Sin, 2017, 50: 1-14 (in Chinese with English abstract).
doi: 10.3864/j.issn.0578-1752.2017.01.001
[22] 杨扬, 田红丽, 易红梅, 等. 基于分子标记技术的玉米品种杂种优势模式鉴定方法. 科学通报, 2025, 70: 3191-3202.
Yang Y, Tian H L, Yi H M, et al. Heterosis pattern detection method of maize single-cross hybrids via molecular marker. Chin Sci Bull, 2025, 70: 3191-3202 (in Chinese with English abstract).
[23] 王晓鸣, 邱丽娟, 景蕊莲, 等. 作物种质资源表型性状鉴定评价: 现状与趋势. 植物遗传资源学报, 2022, 23: 12-20.
Wang X M, Qiu L J, Jing R L, et al. Evaluation on phenotypic traits of crop germplasm: status and development. J Plant Genet Resour, 2022, 23: 12-20 (in Chinese with English abstract).
[24] 杨国航, 孙世贤, 张春原, 等. 东北早熟春玉米区玉米生产现状和发展趋势. 玉米科学, 2007, 15(4): 143-145.
Yang G H, Sun S X, Zhang C Y, et al. Current production status and prospect development of maize in northeast early maturity spring maize area. J Maize Sci, 2007, 15(4): 143-145 (in Chinese with English abstract).
[25] 苗永茂, 李丽君, 王海霞, 等. 西北春玉米组品种试验现状分析. 中国种业, 2021(12): 45-48.
Miao Y M, Li L J, Wang H X, et al. Analysis on the present situation of spring maize variety test in Northwest China. China Seed Ind, 2021(12): 45-48 (in Chinese).
[26] 曹冬梅, 丁明亚, 方继友. 我国北方早熟玉米区高密度、超高密度栽培的品种选择. 农业科技通讯, 2007(12): 56-59.
Cao D M, Ding M Y, Fang J Y. Variety selection of high-density and ultra-high-density cultivation in early-maturing corn areas in northern China. Bull Agric Sci Technol, 2007(12): 56-59 (in Chinese).
[27] 熊志国, 肖春华, 肖强. 西南地区玉米种植现状及应对措施. 四川农业科技, 2024(6): 48-50.
Xiong Z G, Xiao C H, Xiao Q. Present situation and countermeasures of maize planting in southwest China. Sichuan Agric Sci Technol, 2024(6): 48-50 (in Chinese).
[28] 周进宝, 杨国航, 孙世贤, 等. 黄淮海夏播玉米区玉米生产现状和发展趋势. 作物杂志, 2008(2): 4-7.
Zhou J B, Yang G H, Sun S X, et al. Current situation and prospect of maize production in the Huang-Huai-Hai summer maize region. Crops, 2008(2): 4-7 (in Chinese with English abstract).
[29] 王然, 隋冬华, 张冬雪, 等. 利用SSR技术鉴定玉米杂交种乡糯4的种子纯度. 黑龙江农业科学, 2025(3): 7-11.
Wang R, Sui D H, Zhang D X, et al. Identification of seed purity of edible maize hybrid Xiangnuo 4 using SSR technology. Heilongjiang Agric Sci, 2025(3): 7-11 (in Chinese with English abstract).
[30] 郭奕生, 何德银. SSR分子标记在玉米品种真实性鉴定上的应用. 广东农业科学, 2014, 41(12): 12-15.
Guo Y S, He D Y. Application of SSR molecular markers in authenticity identification of maize vatieties. Guangdong Agric Sci, 2014, 41(12): 12-15 (in Chinese with English abstract).
[31] 刘志斋, 吴迅, 刘海利, 等. 基于40个核心SSR标记揭示的820份中国玉米重要自交系的遗传多样性与群体结构. 中国农业科学, 2012, 45: 2107-2138.
doi: 10.3864/j.issn.0578-1752.2012.11.001
Liu Z Z, Wu X, Liu H L, et al. Genetic diversity and population structure of important Chinese maize inbred lines revealed by 40 core simple sequence repeats (SSRs). Sci Agric Sin, 2012, 45: 2107-2138 (in Chinese with English abstract).
[32] Li X R, Zhu C S, Yeh C T, et al. Genic and nongenic contributions to natural variation of quantitative traits in maize. Genome Res, 2012, 22: 2436-2444.
doi: 10.1101/gr.140277.112 pmid: 22701078
[33] 刘丽华, 刘阳娜, 周悦, 等. 基于高效SNP芯片的小麦产量相关性状全基因组关联分析. 麦类作物学报, 2023, 43: 1404-1416.
Liu L H, Liu Y N, Zhou Y, et al. Genome-wide association analysis of wheat yield related traits based on efficient SNP array. J Triticeae Crops, 2023, 43: 1404-1416 (in Chinese with English abstract).
[34] 邱树青, 陆青, 喻辉辉, 等. 水稻全基因组选择育种技术平台构建与应用. 生命科学, 2018, 30: 1120-1128.
Qiu S Q, Lu Q, Yu H H, et al. The development and application of rice whole genome selection breeding platform. Chin Bull Life Sci, 2018, 30: 1120-1128 (in Chinese with English abstract).
[35] 徐翠, 许理文, 葛建镕, 等. 利用高密度SNP芯片定位玉米雄穗分枝数QTL. 植物遗传资源学报, 2022, 23: 832-841.
doi: 10.13430/j.cnki.jpgr.20211223002
Xu C, Xu L W, Ge J R, et al. QTL mapping of the tassel branch number using high-density SNP array in maize. J Plant Genet Resour, 2022, 23: 832-841 (in Chinese with English abstract).
[36] 武炳瑾, 简俊涛, 张德强, 等. 利用90k芯片技术进行小麦穗部性状QTL定位. 作物学报, 2017, 43: 1087-1095.
doi: 10.3724/SP.J.1006.2017.01087
Wu B J, Jian J T, Zhang D Q, et al. QTL mapping for spike traits of wheat using 90k chip technology. Acta Agron Sin, 2017, 43: 1087-1095 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2017.01087
[37] Tian H L, Yang Y, Yi H M, et al. New resources for genetic studies in maize (Zea mays L.): a genome-wide Maize6H-60K single nucleotide polymorphism array and its application. Plant J, 2021, 105: 1113-1122.
doi: 10.1111/tpj.v105.4
[38] Wang Y J, Deng D X, Bian Y L, et al. Genome-wide analysis of primary auxin-responsive Aux/IAA gene family in maize (Zea mays L.). Mol Biol Rep, 2010, 37: 3991-4001.
doi: 10.1007/s11033-010-0058-6
[39] 王艳芳, 李红, 张立军, 等. 春玉米籽粒灌浆期IAA对淀粉积累的作用及其机制的研究. 化学与生物工程, 2006, 23(3): 35-37.
Wang Y F, Li H, Zhang L J, et al. Effect and mechanism of IAA to starch accumulation in grain during grain-filling stage in spring maize. Chem Bioeng, 2006, 23(3): 35-37 (in Chinese with English abstract).
[40] He Z H, Zhong J W, Sun X P, et al. The maize ABA receptors ZmPYL8, 9, and 12 facilitate plant drought resistance. Front Plant Sci, 2018, 9: 422.
doi: 10.3389/fpls.2018.00422 pmid: 29670640
[41] Guo L, Wang X H, Zhao M, et al. Stepwise cis-regulatory changes in ZCN8 contribute to maize flowering-time adaptation. Curr Biol, 2018, 28: 3005-3015.e4.
doi: S0960-9822(18)30928-X pmid: 30220503
[42] 潘光堂, 杨克诚, 高世斌. 发展西南玉米现代生态育种之我见. 作物学报, 2022, 48: 2427-2434.
doi: 10.3724/SP.J.1006.2022.13065
Pan G T, Yang K C, Gao S B. Insights on developing modern corn ecological breeding in southwest China. Acta Agron Sin, 2022, 48: 2427-2434 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2022.13065
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