Scientia Agricultura Sinica ›› 2026, Vol. 59 ›› Issue (20): 4461-4475.doi: 10.3864/j.issn.0578-1752.2026.20.003

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

Genetic Diversity and Genome-Wide Association Study of Amino Acid Content in Soybean Seeds at the R6 Stage

LIU DanDan(), DING WenTao, CHENG QiCan, ZHANG Yu, XING AiShuang, GUO XiangLong, XING Han, GUO Na(), ZHAO JinMing()   

  1. Nanjing Agricultural University/Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs/State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding/Jiangsu Key Laboratory of Soybean Biotechnology and Intelligent Breeding/Jiangsu Zhongshan Biological Breeding Laboratory, Nanjing 210095
  • Received:2026-02-21 Accepted:2026-04-15 Online:2026-10-16 Published:2026-10-21
  • Contact: GUO Na, ZHAO JinMing

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Abstract:

【Objective】This study aimed to dissect the genetic diversity of amino acid contents in soybean seeds at the R6 stage, comprehensively evaluate their nutritional quality, screen elite germplasm resources, and map key genetic loci and candidate genes regulating amino acid accumulation, thereby providing a theoretical basis for molecular breeding in vegetable soybean.【Method】The contents of 17 amino acids in seeds of 133 soybean germplasms at the R6 stage were determined using an automatic amino acid analyzer. A comprehensive evaluation system for amino acid quality was established by integrating principal component analysis (PCA) with the membership function method. The test materials were systematically evaluated, and elite germplasms were screened via cluster analysis. Combined with high-density genotyping data, restricted two-stage multi-locus genome-wide association analysis (RTM-GWAS) was performed to associate the total amino acid content (TAA) and comprehensive evaluation value (F value), aiming to identify significant genetic loci and mine candidate genes. On the basis of the QTL-allele matrix, the breeding potential of hybrid combinations for TAA was predicted in the tested population, and the optimal hybrid combinations were screened out for subsequent breeding application.【Result】The 133 soybean accessions exhibited abundant genetic diversity for amino acid contents. Among the 17 detected amino acids, glutamic acid had the highest content, while methionine and cysteine had the lowest contents. PCA revealed that the cumulative contribution rate of the first three principal components was 95.92%, adequately representing most phenotypic variation of the 17 amino acid traits. Combined with the F value, cluster analysis classified the tested germplasms into three distinct groups, and nine germplasms with superior comprehensive performance were ultimately identified. A total of 55 loci significantly associated with amino acid contents were detected by RTM-GWAS. Among these, 8 loci overlapped with previously reported genomic regions, and 7 were stably detected across two or more environments. Chr.17_3312682 was a stable locus co-localized with both the F value and TAA, with 29 candidate genes annotated in its flanking genomic region. Notably, Glyma.17g044500 encodes a protein with aspartate esterase activity and is highly expressed in seeds, suggesting that it is a key candidate gene regulating amino acid accumulation in soybean seeds at the R6 stage. Based on the QTL-allele matrix, the TAA breeding potential was predicted for all possible cross combinations within the tested population, and the top 10 optimal combinations were identified, with their pure-line progenies projected to achieve the TAA content of 29.36%.【Conclusion】This study systematically elucidated the genetic diversity of amino acid contents in soybean seeds at the R6 stage, established a reliable comprehensive evaluation system for amino acid quality, classified 133 germplasms into three major groups, and identified 9 elite germplasm resources with superior amino acid quality. Furthermore, a stably associated locus (Chr.17_3312682) was identified via RTM-GWAS, and subsequent analysis identified Glyma.17g044500 as the key candidate gene regulating amino acid accumulation in soybean seeds at the R6 stage.

Key words: soybean (Glycine max (L.) Merr.), R6 stage, amino acids, comprehensive evaluation, restricted two-stage multi-locus genome-wide association analysis

Table 1

Descriptive statistics of amino acid contents"

性状
Trait		 2020 2021 遗传多样
性指数
H′		 F值(基因型)
FG
最小值
Min		 最大值
Max		 平均值
Mean		 标准差
SD		 变异系数
CV (%)		 最小值
Min		 最大值
Max		 平均值
Mean		 标准差
SD		 变异系数
CV (%)
天冬氨酸Asp (%) 1.69 3.32 2.47 0.34 13.90 2.03 3.66 2.70 0.32 11.77 2.02 1.92**
苏氨酸Thr (%) 0.55 1.10 0.79 0.12 14.66 0.51 1.11 0.83 0.11 13.22 2.06 2.02**
丝氨酸Ser (%) 0.75 1.46 1.09 0.16 14.42 0.69 1.53 1.14 0.15 13.36 2.00 1.98**
谷氨酸Glu (%) 2.61 4.77 3.68 0.52 14.25 2.36 5.39 3.96 0.56 14.14 2.08 2.03**
甘氨酸Gly (%) 0.61 1.17 0.85 0.12 14.24 0.57 1.19 0.90 0.12 13.04 2.06 1.89**
丙氨酸Ala (%) 0.65 1.37 0.94 0.13 14.28 0.78 1.32 1.04 0.12 11.45 2.03 1.60**
半胱氨酸Cys (%) 0.20 0.47 0.29 0.04 15.03 0.16 0.40 0.27 0.04 15.65 2.08 2.36**
缬氨酸Val (%) 0.66 1.25 0.92 0.13 13.88 0.61 1.26 0.97 0.12 12.69 2.03 1.95**
甲硫氨酸Met (%) 0.16 0.49 0.28 0.05 18.95 0.18 0.38 0.28 0.04 12.68 2.00 1.73**
异亮氨酸Ile (%) 0.63 1.22 0.90 0.14 15.08 0.59 1.25 0.96 0.12 12.95 2.02 1.85**
亮氨酸Leu (%) 1.08 2.10 1.55 0.23 14.54 1.00 2.12 1.63 0.21 13.04 2.03 1.90**
酪氨酸Tyr (%) 0.52 0.98 0.72 0.09 12.80 0.48 0.90 0.72 0.08 11.31 2.03 1.71**
苯丙氨酸Phe (%) 0.78 1.57 1.10 0.16 14.16 0.71 1.42 1.11 0.14 12.73 2.05 1.71**
赖氨酸Lys (%) 0.94 1.93 1.36 0.19 13.84 0.90 1.90 1.44 0.18 12.81 2.00 1.91**
组氨酸His (%) 0.40 0.73 0.56 0.07 13.28 0.47 0.83 0.61 0.07 12.18 2.04 1.76**
精氨酸Arg (%) 1.09 2.32 1.57 0.23 14.77 1.11 2.46 1.68 0.24 14.57 2.04 2.13**
脯氨酸Pro (%) 0.68 1.35 0.98 0.15 14.78 0.61 1.37 1.01 0.14 13.87 2.05 1.97**
总氨基酸TAA (%) 14.35 26.59 20.04 2.77 13.81 13.85 28.44 21.26 2.70 12.70 2.06 1.94**

Fig. 1

Correlation analysis of amino acids ***: P<0.001. The same as below"

Table 2

The eigenvectors of the first three principal components"

指标
Indicators		 主成分 Principal component
PC1 PC2 PC3
X1 (Asp) 0.57 -0.63 0.28
X2 (Thr) -0.02 0.23 -0.06
X3 (Ser) 0.03 0.15 0.16
X4 (Glu) 0.15 0.11 0.22
X5 (Gly) 0.14 0.10 0.01
X6 (Ala) 0.52 -0.23 -0.71
X7 (Cys) -0.27 -0.57 1.49
X8 (Val) -0.04 0.28 -0.20
X9 (Met) -0.22 -0.57 -0.20
X10 (Ile) -0.08 0.22 -0.23
X11 (Leu) -0.06 0.32 -0.13
X12 (Tyr) -0.28 0.45 -0.03
X13 (Phe) -0.51 0.95 -0.36
X14 (Lys) -0.27 0.52 -0.23
X15 (His) 0.40 -0.54 0.12
X16 (Arg) 0.46 -0.51 0.10
X17 (Pro) 0.15 0.08 0.32

Table 3

The correlation analysis between F value and amino acids"

指标Indicators F值F value 指标Indicators F值F value
天冬氨酸Asp 0.97** 异亮氨酸Ile 0.88**
苏氨酸Thr 0.89** 亮氨酸Leu 0.89**
丝氨酸Ser 0.91** 酪氨酸Tyr 0.83**
谷氨酸Glu 0.93** 苯丙氨酸Phe 0.79**
甘氨酸Gly 0.92** 赖氨酸Lys 0.84**
丙氨酸Ala 0.92** 组氨酸His 0.90**
半胱氨酸Cys 0.71** 精氨酸Arg 0.95**
缬氨酸Val 0.89** 脯氨酸Pro 0.92**
甲硫氨酸Met 0.73** 总氨基酸TAA 0.93**

Table 4

Excellent germplasm selected based on the comprehensive evaluation value"

材料编号
Accessions		 综合评价值Comprehensive evaluation value 隶属函数值Membership function value F值
F value		 排名
Rank
PC1 PC2 PC3 u(X1) u(X2) u(X3)
ZDD06803 2.56 4.39 0.65 1.00 0.79 0.74 0.99 1
ZDD00326 2.55 4.52 0.73 0.97 0.91 1.00 0.97 2
ZDD18558 2.55 4.55 0.65 0.96 0.94 0.76 0.96 3
ZDD11575 2.52 4.61 0.67 0.90 0.99 0.83 0.90 4
ZDD17767 2.52 4.41 0.69 0.89 0.81 0.88 0.89 5
ZDD04959 2.52 4.39 0.67 0.88 0.79 0.81 0.88 6
ZDD14228 2.51 4.53 0.68 0.87 0.92 0.85 0.87 7
ZDD14252 2.51 4.27 0.67 0.86 0.68 0.80 0.86 8
ZDD07580 2.50 4.55 0.66 0.85 0.93 0.78 0.85 9

Fig. 2

F value clustering diagram of 133 soybean germplasms"

Fig. 3

Manhattan and QQ plots for amino acid contents in soybean seeds at the R6 stage A: Manhattan plot (Tracks from the inner to outer represent 2020TAA, 2021TAA, Combined-TAA, and F value, respectively); B: Q-Q plot. 2020TAA: Total amino acid content in 2020; 2021TAA: Total amino acid content in 2021; Combined-TAA: Total amino acid content under multi-environment; F value: Comprehensive evaluation value. The same as below"

Table 5

Stable loci significantly associated with the amino acid contents"

标记Marker 染色体Chromosome 位置Position (bp) 表型解释率R2 (%) P值P value 性状Trait
Block_Chr.08_40280597_40371555 8 40280597 6.82 1.48E-07 2020TAA
2.68 3.53E-03 Combined-TAA
Block_Chr.09_3765291_3798028 9 3765291 14.62 9.91E-17 2021TAA
5.08 2.09E-06 Combined-TAA
Chr.10_35011505 10 35011505 1.77 7.97E-04 2020TAA
0.87 2.40E-02 Combined-TAA
Block_Chr.13_37392403_37407538 13 37392403 15.70 2.95E-18 2021TAA
1.46 1.37E-02 Combined-TAA
Chr.16_35161914 16 35161914 7.88 1.40E-10 2020TAA
1.28 6.06E-03 Combined-TAA
Chr.17_3312682 17 3312682 6.53 2.61E-09 2020TAA
4.59 2.84E-07 Combined-TAA
13.48 2.96E-16 F值F value
Chr.18_38254088 18 38254088 3.92 1.54E-06 2020TAA
0.37 1.42E-01 Combined-TAA

Fig. 4

Haplotype analysis of significant loci and tissue-specific expression analysis of candidate genes associated with amino acid contents A: Box plot of total amino acid (TAA) content in soybean accessions carrying distinct Chr.17_3312682-A/G haplotypes; B: Tissue-specific expression heatmap of candidate genes"

Fig. 5

QTL-allele matrix of total amino acid content detected by the RTM-GWAS"

Table 6

The top 10 predicted optimal hybrid combinations"

亲本1 P1 亲本2 P2 TAA含量TAA content (%)
ZDD16743 ZDD18558 29.36
ZDD11575 ZDD16743 29.00
ZDD16743 ZDD00326 28.78
ZDD16743 ZDD06494 28.65
ZDD16743 ZDD14228 28.40
ZDD16743 ZDD03013 28.35
ZDD08228 ZDD18558 28.33
ZDD16771 ZDD16743 28.21
ZDD17574 ZDD16743 28.06
ZDD16743 ZDD09279 27.89
[1]
Wang C C, Lin J Y, Bu Y P, Sun R D, Lu Y, Gai J Y, Xing H, Guo N, Zhao J M. Genome-wide transcriptome analysis reveals key regulatory networks and genes involved in the determination of seed hardness in vegetable soybean[J]. Horticulture Research, 2024, 11(5): uhae084.
[2]
Li X N, Zhang X L, Zhu L M, Bu Y P, Wang X F, Zhang X, Zhou Y, Wang X T, Guo N, Qiu L J, Zhao J M, Xing H. Genome-wide association study of four yield-related traits at the R6 stage in soybean[J]. BMC Genetics, 2019, 20(1): 39.

doi: 10.1186/s12863-019-0737-9 pmid: 30922237
[3]
Herrmann K M, Somerville R L. Amino Acids: Biosynthesis and Genetic Regulation[M]. Reading, Mass: Addison-Wesley Pub. Co., Advanced Book Program, 1983.
[4]
Berry T H, Becker D E, Rasmussen O G, Jensen A H, Norton H W. The limiting amino acids in soybean protein[J]. Journal of Animal Science, 1962, 21(3): 558-561.

doi: 10.2527/jas1962.213558x
[5]
Chen Z J, Zhong W J, Zhou Y H, Ji P C, Wan Y L, Shi S J, Yang Z H, Gong Y Y, Mu F S, Chen S W. Integrative analysis of metabolome and transcriptome reveals the improvements of seed quality in vegetable soybean (Glycine max (L.) Merr.) [J]. Phytochemistry, 2022, 200: 113216.

doi: 10.1016/j.phytochem.2022.113216
[6]
Kumar V, Rani A, Goyal L, Pratap D, Billore S D, Chauhan G S. Evaluation of vegetable-type soybean for sucrose, taste-related amino acids, and isoflavones contents[J]. International Journal of Food Properties, 2011, 14(5): 1142-1151.

doi: 10.1080/10942911003592761
[7]
王伟威, 王兴宇, 魏崃, 于志远, 赵贵兴, 任洪波, 李波, 刘丽君. 中俄大豆品种氨基酸组成特性分析[J]. 大豆科学, 2015(4): 635-638.
Wang W W, Wang X Y, Wei L, Yu Z Y, Zhao G X, Ren H B, Li B, Liu L J. Analysis of amino acid composition characters in Chinese and Russian soybean cultivars[J]. Soybean Science, 2015(4): 635-638. (in Chinese)
[8]
Song J F, Liu C Q, Li D J, Gu Z X. Evaluation of sugar, free amino acid, and organic acid compositions of different varieties of vegetable soybean (Glycine max [L.] Merr) [J]. Industrial Crops and Products, 2013, 50: 743-749.

doi: 10.1016/j.indcrop.2013.08.064
[9]
Lee S, Van K, Sung M, Nelson R, LaMantia J, McHale L K, Rouf Mian M A. Genome-wide association study of seed protein, oil and amino acid contents in soybean from maturity groups I to IV[J]. Theoretical and Applied Genetics, 2019, 132(6): 1639-1659.

doi: 10.1007/s00122-019-03304-5 pmid: 30806741
[10]
张红梅, 熊雅文, 许文静, 张威, 王琼, 刘晓庆, 刘慧, 崔晓艳, 陈新, 陈华涛. 大豆R6期籽粒氨基酸含量的全基因组关联分析[J]. 作物学报, 2023, 49(12): 3277-3288.

doi: 10.3724/SP.J.1006.2023.34031
Zhang H M, Xiong Y W, Xu W J, Zhang W, Wang Q, Liu X Q, Liu H, Cui X Y, Chen X, Chen H T. Genome-wide association study for amino acid content at R6 stage in soybean (Glycine max L.) seed[J]. Acta Agronomica Sinica, 2023, 49(12): 3277-3288. (in Chinese)

doi: 10.3724/SP.J.1006.2023.34031
[11]
Vaughn J N, Nelson R L, Song Q J, Cregan P B, Li Z L. The genetic architecture of seed composition in soybean is refined by genome-wide association scans across multiple populations[J]. G3, 2014, 4(11): 2283-2294.
[12]
Dornbos D L Jr, McDonald M B Jr. Mass and composition of developing soybean seeds at five reproductive growth stages[J]. Crop Science, 1986, 26(3): 624-630.

doi: 10.2135/cropsci1986.0011183X002600030042x
[13]
Yazdi-Samadi B, Rinne R W, Seif R D. Components of developing soybean seeds: Oil, protein, sugars, starch, organic acids, and amino acids[J]. Agronomy Journal, 1977, 69(3): 481-486.

doi: 10.2134/agronj1977.00021962006900030037x
[14]
Saldivar X, Wang Y J, Chen P Y, Hou A F. Changes in chemical composition during soybean seed development[J]. Food Chemistry, 2011, 124(4): 1369-1375.

doi: 10.1016/j.foodchem.2010.07.091
[15]
张秋英, 李彦生, 刘长锴, 田博文, 涂冰洁, 毛健伟. 菜用大豆食用品质关键组分及其积累动态研究[J]. 作物学报, 2015, 41(11): 1692-1700.

doi: 10.3724/SP.J.1006.2015.01692
Zhang Q Y, Li Y S, Liu C K, Tian B W, Tu B J, Mao J W. Key components of eating quality and their dynamic accumulation in vegetable soybean varieties [Glycine max (L.) Merr] [J]. Acta Agronomica Sinica, 2015, 41(11): 1692-1700. (in Chinese)

doi: 10.3724/SP.J.1006.2015.01692
[16]
He J B, Meng S, Zhao T J, Xing G N, Yang S P, Li Y, Guan R Z, Lu J J, Wang Y F, Xia Q J, Yang B, Gai J Y. An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding[J]. Theoretical and Applied Genetics, 2017, 130(11): 2327-2343.

doi: 10.1007/s00122-017-2962-9 pmid: 28828506
[17]
潘丽媛, 贺建波, 赵晋铭, 王吴彬, 邢光南, 喻德跃, 张小燕, 李春燕, 陈受宜, 盖钧镒. RTM-GWAS方法应用于大豆RIL群体百粒重QTL检测的功效[J]. 中国农业科学, 2020, 53(9): 1730-1742. DOI: 10.3864/j.issn.0578-1752.2020.09.004.
Pan L Y, He J B, Zhao J M, Wang W B, Xing G N, Yu D Y, Zhang X Y, Li C Y, Chen S Y, Gai J Y. Detection power of RTM-GWAS applied to 100-seed weight QTL identification in a recombinant inbred lines population of soybean[J]. Scientia Agricultura Sinica, 2020, 53(9): 1730-1742. DOI: 10.3864/j.issn.0578-1752.2020.09.004. (in Chinese)
[18]
Zhang Y H, He J B, Wang H W, Meng S, Xing G N, Li Y, Yang S P, Zhao J M, Zhao T J, Gai J Y. Detecting the QTL-allele system of seed oil traits using multi-locus genome-wide association analysis for population characterization and optimal cross prediction in soybean[J]. Frontiers in Plant Science, 2018, 9: 1793.

doi: 10.3389/fpls.2018.01793 pmid: 30568668
[19]
李曙光, 曹永策, 贺建波, 王吴彬, 邢光南, 杨加银, 赵团结, 盖钧镒. 大豆巢式关联作图群体蛋白质含量的遗传解析[J]. 中国农业科学, 2020, 53(9): 1743-1755. DOI: 10.3864/j.issn.0578-1752.2020.09.005.
Li S G, Cao Y C, He J B, Wang W B, Xing G N, Yang J Y, Zhao T J, Gai J Y. Genetic dissection of protein content in a nested association mapping population of soybean[J]. Scientia Agricultura Sinica, 2020, 53(9): 1743-1755. DOI: 10.3864/j.issn.0578-1752.2020.09.005. (in Chinese)
[20]
邱丽娟, 李英慧, 关荣霞, 刘章雄, 王丽侠, 常汝镇. 大豆核心种质和微核心种质的构建、验证与研究进展[J]. 作物学报, 2009, 35(4): 571-579.
Qiu L J, Li Y H, Guan R X, Liu Z X, Wang L X, Chang R Z. Establishment, representative testing and research progress of soybean core collection and mini core collection[J]. Acta Agronomica Sinica, 2009, 35(4): 571-579. (in Chinese)

doi: 10.3724/SP.J.1006.2009.00571
[21]
Strong W L. Biased richness and evenness relationships within Shannon-Wiener index values[J]. Ecological Indicators, 2016, 67: 703-713.

doi: 10.1016/j.ecolind.2016.03.043
[22]
谢志坚. 农业科学中的模糊数学方法[M]. 武汉: 华中理工大学出版社, 1983: 99-193.
Xie Z J. Fuzzy Mathematics Method in Agricultural Science[M]. Wuhan: Huazhong University of Science and Technology Press, 1983: 99-193. (in Chinese)
[23]
刘鹏鹏, 李江博, 徐红军, 聂迎彬, 韩新年, 孔德真, 桑伟. 新疆冬小麦品种资源蛋白组分及品质的遗传多样性[J]. 中国农业科学, 2025, 58(15): 2948-2959. DOI: 10.3864/j.issn.0578-1752.2025.15.002.
Liu P P, Li J B, Xu H J, Nie Y B, Han X N, Kong D Z, Sang W. Genetic diversity analysis of protein fractions and quality in Xinjiang winter wheat cultivar resources[J]. Scientia Agricultura Sinica, 2025, 58(15): 2948-2959. DOI: 10.3864/j.issn.0578-1752.2025.15.002. (in Chinese)
[24]
贺建波, 刘方东, 王吴彬, 邢光南, 管荣展, 盖钧镒. 限制性两阶段多位点全基因组关联分析法在遗传育种中的应用[J]. 中国农业科学, 2020, 53(9): 1704-1716. DOI: 10.3864/j.issn.0578-1752.2020.09.002.
He J B, Liu F D, Wang W B, Xing G N, Guan R Z, Gai J Y. Restricted two-stage multi-locus genome-wide association analysis and its applications to genetic and breeding studies[J]. Scientia Agricultura Sinica, 2020, 53(9): 1704-1716. DOI: 10.3864/j.issn.0578-1752.2020.09.002. (in Chinese)
[25]
Amir R, Galili G, Cohen H. The metabolic roles of free amino acids during seed development[J]. Plant Science, 2018, 275: 11-18.

doi: S0168-9452(18)30461-8 pmid: 30107877
[26]
李福山, 常汝镇, 舒世珍, 常碧影, 陈志萍, 左江湾. 栽培、野生、半野生大豆蛋白质含量及氨基酸组成的初步分析[J]. 大豆科学, 1986, 5(1): 65-72.
Li F S, Chang R Z, Shu S Z, Chang B Y, Chen Z P, Zuo J W. Protein content and composition of amino acid in cultivated semi-cultivated and wild soybeans[J]. Soybean Science, 1986, 5(1): 65-72. (in Chinese)
[27]
吕景良, 邵荣春, 吴百灵, 张明, 胡传璞, 吴桂荣. 东北地区大豆品种资源氨基酸组成的分析研究[J]. 大豆科学, 1988, 7(3): 193-201.
Lü J L, Shao R C, Wu B L, Zhang M, Hu C P, Wu G R. Study on the amino acid composition of soybean germpiasm in north-east of China[J]. Soybean Science, 1988, 7(3): 193-201. (in Chinese)
[28]
孙铭, 符开欣, 范彦, 张新全, 张成林, 郭志慧, 汪霞, 马啸. 15份多花黑麦草优良引进种质的表型变异分析[J]. 植物遗传资源学报, 2016, 17(4): 655-662.
Sun M, Fu K X, Fan Y, Zhang X Q, Zhang C L, Guo Z H, Wang X, Ma X. Analysis of phenotypic variations in 15 introduced elite germplasm of Lolium multiflorum Lam[J]. Journal of Plant Genetic Resources, 2016, 17(4): 655-662. (in Chinese)
[29]
孟祥勋, 胡明祥. 大豆籽粒蛋白质氨基酸组成成分的相关分析[J]. 大豆科学, 1987, 6(3): 213-219.
Meng X X, Hu M X. An analysis on the relationship between protein and its amino acid in soybean seed[J]. Soybean Science, 1987, 6(3): 213-219. (in Chinese)
[30]
Yuan W J, Huang J, Li H Y, Ma Y J, Gui C J, Huang F, Feng X Z, Yu D Y, Wang H, Kan G Z. Genetic dissection reveals the complex architecture of amino acid composition in soybean seeds[J]. Theoretical and Applied Genetics, 2023, 136(1): 17.

doi: 10.1007/s00122-023-04280-7
[31]
Kim W J, Kang B H, Kang S, Shin S, Chowdhury S, Jeong S C, Choi M S, Park S K, Moon J K, Ryu J, Ha B K. A genome-wide association study of protein, oil, and amino acid content in wild soybean (Glycine soja)[J]. Plants, 2023, 12(8): 1665.

doi: 10.3390/plants12081665
[32]
武晓玲, 梁海媛, 杨峰, 刘卫国, 佘跃辉, 杨文钰. 大豆苗期耐荫性综合评价及其鉴定指标的筛选[J]. 中国农业科学, 2015, 48(13): 2497-2507. DOI: 10.3864/j.issn.0578-1752.2015.13.002.
Wu X L, Liang H Y, Yang F, Liu W G, She Y H, Yang W Y. Comprehensive evaluation and screening identification indexes of shade tolerance at seedling in soybean[J]. Scientia Agricultura Sinica, 2015, 48(13): 2497-2507. DOI: 10.3864/j.issn.0578-1752.2015.13.002. (in Chinese)
[33]
张笛, 袁明, 韩冬伟, 王淑荣, 王振, 孙浩月, 朱治佳, 王连霞, 韩业辉, 王伟. 158份中欧大豆种质资源农艺性状综合评价及分析[J/OL]. 分子植物育种, 2023: 1-9. https://link.cnki.net/urlid/46.1068.s.20230216.1615.027.
Zhang D, Yuan M, Han D W, Wang S R, Wang Z, Sun H Y, Zhu Z J, Wang L X, Han Y H, Wang W. Comprehensive evaluation and analysis of agronomic traits of 158 soybean germplasm resources in Central Europe[J/OL]. Molecular Plant Breeding, 2023: 1-9. https://link.cnki.net/urlid/46.1068.s.20230216.1615.027. (in Chinese)
[34]
李欢, 鄢小青, 杨占烈, 谭金玉, 黎小冰, 陈能刚, 吴荣菊, 陈惠查, 阮仁超. 贵州香禾糯地方稻种资源表型遗传多样性分析与综合评价[J]. 中国农业科学, 2023, 56(11): 2035-2046. DOI: 10.3864/j.issn.0578-1752.2023.11.001.
Li H, Yan X Q, Yang Z L, Tan J Y, Li X B, Chen N G, Wu R J, Chen H C, Ruan R C. Analysis and comprehensive evaluation of phenotype genetic diversity in kam sweet rice germplasm resources in Guizhou[J]. Scientia Agricultura Sinica, 2023, 56(11): 2035-2046. DOI: 10.3864/j.issn.0578-1752.2023.11.001. (in Chinese)
[35]
沈倩, 张思平, 刘瑞华, 刘绍东, 陈静, 葛常伟, 马慧娟, 赵新华, 杨国正, 宋美珍, 庞朝友. 棉花出苗期耐冷综合评价体系的构建及耐冷指标筛选[J]. 中国农业科学, 2022, 55(22): 4342-4355. DOI: 10.3864/j.issn.0578-1752.2022.22.002.
Shen Q, Zhang S P, Liu R H, Liu S D, Chen J, Ge C W, Ma H J, Zhao X H, Yang G Z, Song M Z, Pang C Y. Construction of a comprehensive evaluation system and screening of cold tolerance indicators for cold tolerance of cotton at seedling emergence stage[J]. Scientia Agricultura Sinica, 2022, 55(22): 4342-4355. DOI: 10.3864/j.issn.0578-1752.2022.22.002. (in Chinese)
[36]
杨涛, 黄雅婕, 李生梅, 任丹, 崔进鑫, 庞博, 于爽, 高文伟. 海岛棉种质资源表型性状的遗传多样性分析及综合评价[J]. 中国农业科学, 2021, 54(12): 2499-2509. DOI: 10.3864/j.issn.0578-1752.2021.12.002.
Yang T, Huang Y J, Li S M, Ren D, Cui J X, Pang B, Yu S, Gao W W. Genetic diversity and comprehensive evaluation of phenotypic traits in sea-island cotton germplasm resources[J]. Scientia Agricultura Sinica, 2021, 54(12): 2499-2509. DOI: 10.3864/j.issn.0578-1752.2021.12.002. (in Chinese)
[37]
黎松松, 赖建军, 张红梅, 崔晓艳, 刘晓庆, 陈新, 朱月林, 陈华涛. 江苏鲜食春大豆种质资源表型鉴定及综合评价[J]. 大豆科学, 2022, 41(4): 385-396.
Li S S, Lai J J, Zhang H M, Cui X Y, Liu X Q, Chen X, Zhu Y L, Chen H T. Phenotyping identification and comprehensive evaluation of fresh spring soybean germplasms in Jiangsu Province[J]. Soybean Science, 2022, 41(4): 385-396. (in Chinese)
[38]
石彦国, 单彤彤, 曾剑华, 刘琳琳, 朱秀清. 基于主成分分析和偏最小二乘法的蒸煮大豆食味品质评价[J]. 中国食品学报, 2019, 19(10): 265-277.
Shi Y G, Shan T T, Zeng J H, Liu L L, Zhu X Q. Estimating the eating quality of cooking-soybean based on principal component analysis and partial least squares[J]. Journal of Chinese Institute of Food Science and Technology, 2019, 19(10): 265-277. (in Chinese)
[39]
杜世坤, 赵宝勰, 赵振宁, 高玉芳, 李雨阳, 陈彩霞, 强旭阳. 间作用大豆亲本的相关性、主成分及聚类分析[J]. 分子植物育种, 2022, 20(1): 266-275.
Du S K, Zhao B X, Zhao Z N, Gao Y F, Li Y Y, Chen C X, Qiang X Y. Correlation analysis, principal component analysis and cluster analysis in parent selection of intercropping soybean[J]. Molecular Plant Breeding, 2022, 20(1): 266-275. (in Chinese)
[40]
Liu G Y, Xing H, Diao Y L, Yang X F, Sun D, Wang Q, Qi N, Lin H. Identification of resistance to soybean aphids in early germplasm[J]. Crop Science, 2014, 54(6): 2707-2712.

doi: 10.2135/cropsci2013.11.0735
[41]
Yang J, Liu G Y, Tang J Y, Wang X J, Diao Y L, Su Y, Sun D, Shang J W, Guo Y, Qiu L J. Fine mapping and characterization of an aphid-resistance gene in the soybean Landrace Fangzheng moshidou[J]. Frontiers in Plant Science, 2022, 13: 899212.

doi: 10.3389/fpls.2022.899212
[42]
陈文杰, 梁江, 钟开珍, 韦清源, 汤复跃, 曾维英, 陈渊. 大豆抗花叶病毒材料初步筛选及评价[J]. 大豆科学, 2012, 31(4): 617-620.
Chen W J, Liang J, Zhong K Z, Wei Q Y, Tang F Y, Zeng W Y, Chen Y. Preliminary selection and evaluation for Glycine max resistant to soybean mosaic virus[J]. Soybean Science, 2012, 31(4): 617-620. (in Chinese)
[43]
Zhang T F, Wu T T, Wang L W, Jiang B J, Zhen C X, Yuan S, Hou W S, Wu C X, Han T F, Sun S. A combined linkage and GWAS analysis identifies QTLs linked to soybean seed protein and oil content[J]. International Journal of Molecular Sciences, 2019, 20(23): 5915.

doi: 10.3390/ijms20235915
[44]
段金涛. 大豆蛋白质含量及组分的全基因组关联分析[D]. 雅安: 四川农业大学, 2022.
Duan J T. Genome-wide association analysis of protein content and fractions in soybean[D]. Yaan: Sichuan Agricultural University, 2022. (in Chinese)
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