Scientia Agricultura Sinica ›› 2026, Vol. 59 ›› Issue (3): 499-514.doi: 10.3864/j.issn.0578-1752.2026.03.003

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

Genome-Wide Association Study and Candidate Gene Identification for Thousand Grain Weight in Winter Wheat

WANG YongSheng1,2(), NIU Li1,2, WANG ChangJie1,2, MA LiHua1,2, LIAN XiaoXiao1, MENG YaXiong1,2, MA XiaoLe1,2, YAO LiRong1,2, ZHANG Hong1,2, YANG Ke1,2, LI BaoChun2,3, WANG HuaJun1,2, SI ErJing1,2(), WANG JunCheng1,2()   

  1. 1 College of Agronomy, Gansu Agricultural University, Lanzhou 730070
    2 State Key Laboratory of Aridland Crop Science, Lanzhou 730070
    3 College of Life Science and Technology, Gansu Agricultural University, Lanzhou 730070
  • Received:2025-07-31 Accepted:2025-09-15 Online:2026-02-01 Published:2026-01-31
  • Contact: SI ErJing, WANG JunCheng

Abstract:

【Objective】Thousand-grain weight (TGW), a key determinant of final wheat yield, is of great importance for genetic dissection. Precise identification of stable loci and key candidate genes controlling TGW provides theoretical foundations and genetic resources for marker-assisted breeding of high-TGW and high-yield wheat varieties. 【Method】A total of 291 wheat accessions from diverse origins were genotyped using a 100K SNP array. TGW phenotypic data collected over two consecutive years and their best linear unbiased predictions (BLUPs) were analyzed using a genome-wide association study (GWAS) based on a mixed linear model (MLM) incorporating both population structure (P) and kinship (K). Significant loci were further subjected to haplotype analysis. 【Result】TGW showed broad variation across years and BLUP values (mean: 38.24-38.82 g; coefficient of variation: 17.62%-19.93%). The correlation between years was 0.88 (P<0.01), and correlations with BLUP values reached 0.97 (P<0.01). Phenotypic data displayed normal distributions under different environments, meeting the basic requirements for GWAS. A total of 19 SNPs significantly associated with TGW were detected on chromosomes 3B, 5A, and 7A, explaining 6.85%-9.68% of the phenotypic variation; 16 of them were repeatedly detected across multiple environments, indicating stability. Haplotype analysis at locus 7A_145980808 revealed four haplotypes (Hap1-Hap4), of which Hap4 was associated with high TGW (P<0.01) and Hap2 with low TGW (P<0.01). The frequencies of Hap1-Hap4 were 72.36%, 14.55%, 8.73%, and 4.36%, respectively. Domestic accessions were enriched for Hap3 (95.83%) and Hap4 (83.33%), with Hap4 predominantly distributed in the Northwestern winter wheat region, especially in germplasm from Gansu. Candidate gene mining within 3.6 Mb regions flanking significant loci on chromosomes 3B, 5A, and 7A identified 95 genes, among which four were highlighted based on gene annotation and expression profiles. 【Conclusion】GWAS identified 16 stable SNP loci significantly associated with TGW, four distinct haplotypes, and four key candidate genes. These genes are mainly involved in carbohydrate synthesis and transport, cell wall polysaccharide assembly, protein homeostasis, and transcriptional regulation of starch biosynthesis, providing valuable targets for molecular breeding of high-yield wheat.

Key words: wheat, thousand-grain weight, SNP markers, GWAS, haplotype, candidate genes

Table 1

Statistical analysis of thousand-grain weight of 291 winter wheat varieties"

环境
Environment
最大值
Max (g)
最小值
Min (g)
平均值
Average (g)
标准差
SD (%)
峰度
Kurtosis
偏度
Skewness
变异系数
Coefficient of variation (%)
相关系数 Correlation coefficient
E1 E2
E1 57.44 20.26 38.39 7.25 -0.48 0.13 18.87
E2 57.10 19.12 38.82 7.70 -0.62 0.01 19.83 0.88**
E3 56.07 21.90 38.61 6.80 -0.55 0.09 17.62 0.97** 0.97**

Fig. 1

Distribution map of thousand-grain weight of wheat A: 2022-2023 environment; B: 2023-2024 environment; C: BLUP value in a joint environment"

Fig. 2

Heat map of the spatial distribution of molecular marker density in the whole chromosome set of wheat"

Table 2

Distribution of 100K SNP microarray markers on each chromosome in the wheat genome"

染色体 Chromosome 染色体长度 Chromosome length (Mb) 标记数目 Number 标记密度 Density (markers/Mb)
1A 597.39 12892 21.58
1B 699.10 10645 15.23
1D 498.58 5626 11.28
2A 787.40 14438 18.34
2B 812.47 15453 19.02
2D 655.52 6628 10.11
3A 753.13 8471 11.25
3B 851.47 14238 16.72
3D 618.91 3861 6.24
4A 753.69 10308 13.68
4B 673.37 7616 11.31
4D 517.87 2190 4.23
5A 713.16 10341 14.50
5B 714.75 13228 18.51
5D 569.44 4150 7.29
6A 622.46 9200 14.78
6B 730.93 12594 17.23
6D 495.25 3986 8.05
7A 744.23 11698 15.72
7B 763.26 12149 15.92
7D 642.35 5546 8.63
A基因组A genome 4971.46 77348 15.56
B基因组B genome 5245.35 85923 16.38
D基因组D genome 3997.92 31987 8.00
总计Total 14214.73 195285 13.74

Fig. 3

Kinship analysis of 291 winter wheat germplasms A: Frequency distribution map of kinship coefficient; B: Kinship coefficient heat map"

Fig. 4

Population structure analysis of 291 winter wheat materials A: NJ evolutionary tree of the population; B: Principal component analysis; C: ΔK value of the population; D: Population structure diagram"

Fig. 5

Linkage disequilibrium analysis of 291 winter wheat materials"

Fig. 6

Manhattan diagram and Q-Q diagram of thousand-grain weight of wheat A: Environment 2022-2023; B: Environment 2023-2024; C: BLUP value in a joint environment"

Table 3

Significant loci of thousand-grain weight under mixed linear model"

环境Environment 标记 Marker 染色体 Chr. 位置 Position (bp) 显著性阈值 -log10(P) 贡献率 R2 (%)
E1/E3 3B_143949526 3B 143949526 4.58-4.62 8.25-8.36
E2/E3 5A_579847898 5A 579847898 4.83-4.92 7.91-8.06
E2/E3 5A_579848522 5A 579848522 4.60-4.74 7.50-7.76
E2/E3 5A_579921639 5A 579921639 4.48-4.76 7.30-7.80
E2/E3 5A_579921681 5A 579921681 4.20-4.44 6.85-7.27
E2/E3 5A_579921718 5A 579921718 4.35-4.55 7.22-7.64
E2/E3 5A_579955478 5A 579955478 4.24-4.76 6.91-7.79
E2/E3 7A_148378633 7A 148378633 4.55-5.59 7.69-9.68

Fig. 7

Haplotype analysis on chromosome 7A A: LD block corresponding to the 7A_145980808 locus; B: Four haplotypes formed by different allelic combinations within the block; C: Thousand-grain weight differences among materials carrying different haplotypes"

Fig. 8

Distribution frequency of four haplotypes and source regions of Hap4 A: Distribution frequency of four haplotypes; B: Source regions of Hap4"

Table 4

Prediction and annotation of important candidate genes for thousand-grain weight in wheat"

候选基因
Candidate genes
染色体位置
Chromosome location
(bp)
基因注释或编码蛋白
Gene annotation or coding proteins
拟南芥同源基因
Homologs in Arabidopsis thaliana
TraesCS3B03G0336700 3B: 128948207-128950128 赤霉素3-β-羟化酶2 Gibberellin 3-beta-hydroxylase 2 AT1G15550
TraesCS3B03G0338300 3B: 130257382-130258484 β-淀粉酶 Beta-amylase AT4G36780
TraesCS3B03G0339200 3B: 130646139-130648627 F-box家族蛋白 F-box family protein AT2G03560
TraesCS3B03G0343000 3B: 132089715-132091559 糖基转移酶 Glycosyltransferase AT3G53150
TraesCS3B03G0343900 3B: 132904195-132906317 糖基转移酶 Glycosyltransferase AT3G53150
TraesCS3B03G0344400 3B: 132999447-133000637 糖基转移酶 Glycosyltransferase AT2G36750
TraesCS3B03G0345400 3B: 133381587-133383648 F-box家族蛋白 F-box family protein AT4G00755
TraesCS3B03G0345500 3B: 133384475-133386349 糖基转移酶 Glycosyltransferase AT2G36800
TraesCS3B03G0346600 3B: 133818631-133823762 硼转运蛋白 Boron transporter AT1G15460
TraesCS5A03G0902700 5A: 574194918-574199874 bHLH转录因子 Basic helix-loop-helix transcription factor AT2G20180
TraesCS5A03G0903300 5A: 574399521-574400834 F-box家族蛋白 F-box family protein AT3G48880
TraesCS5A03G0903400 5A: 574482068-574485628 转运蛋白相关家族蛋白 Transporter-related family protein AT3G13050
TraesCS5A03G0903600 5A: 574488360-574493061 转运蛋白相关家族蛋白 Transporter-related family protein AT3G13050
TraesCS5A03G0904700 5A: 575322960-575329017 生长素管化蛋白 Auxin canalization protein AT3G22810
TraesCS5A03G0912000 5A: 578061853-578067290 bHLH转录因子 Basic helix-loop-helix transcription factor AT5G43650
TraesCS5A03G0912200 5A: 578446505-578449774 WRKY转录因子 WRKY transcription factor AT2G30590
TraesCS7A03G0440800 7A: 146025353-146026920 NAC结构域蛋白 NAC domain protein AT5G18270

Fig. 9

Expression heat map of important candidate genes for thousand-grain weight in wheat"

Fig. 10

Expression analysis of key candidate genes at 20 days after flowering in wheat varieties with different thousand grain weights"

[1]
KOTULA L, ZAHRA N, FAROOQ M, SHABALA S, SIDDIQUE K H M. Making wheat salt tolerant: What is missing. The Crop Journal, 2024, 12(5): 1299-1308.

doi: 10.1016/j.cj.2024.01.005
[2]
魏益民. 中国小麦的起源、传播及进化. 麦类作物学报, 2021, 41(3): 305-309.
WEI Y M. Origin, spread and evolution of wheat in China. Journal of Triticeae Crops, 2021, 41(3): 305-309. (in Chinese)
[3]
董一帆, 任毅, 程宇坤, 王睿, 张志辉, 时晓磊, 耿洪伟. 冬小麦籽粒主要品质性状的全基因组关联分析. 中国农业科学, 2023, 56(11): 2047-2063. doi: 10.3864/j.issn.0578-1752.2023.11.002.
DONG Y F, REN Y, CHENG Y K, WANG R, ZHANG Z H, SHI X L, GENG H W. Genome-wide association study of grain main quality related traits in winter wheat. Scientia Agricultura Sinica, 2023, 56(11): 2047-2063. doi: 10.3864/j.issn.0578-1752.2023.11.002. (in Chinese)
[4]
XIN F, ZHU T, WEI S W, HAN Y C, ZHAO Y, ZHANG D Z, MA L J, DING Q. QTL mapping of kernel traits and validation of a major QTL for kernel length-width ratio using SNP and bulked segregant analysis in wheat. Scientific Reports, 2020, 10: 25.

doi: 10.1038/s41598-019-56979-7 pmid: 31913328
[5]
WANG X B, GUAN P F, XIN M M, WANG Y F, CHEN X Y, ZHAO A J, LIU M S, LI H X, ZHANG M Y, LU L H, et al. Genome-wide association study identifies QTL for thousand grain weight in winter wheat under normal- and late-sown stressed environments. Theoretical and Applied Genetics, 2021, 134(1): 143-157.

doi: 10.1007/s00122-020-03687-w pmid: 33030571
[6]
TRICKER P J, ELHABTI A, SCHMIDT J, FLEURY D. The physiological and genetic basis of combined drought and heat tolerance in wheat. Journal of Experimental Botany, 2018, 69(13): 3195-3210.

doi: 10.1093/jxb/ery081 pmid: 29562265
[7]
BRINTON J, UAUY C. A reductionist approach to dissecting grain weight and yield in wheat. Journal of Integrative Plant Biology, 2019, 61(3): 337-358.

doi: 10.1111/jipb.12741
[8]
QUAN X Y, LIU J D, ZHANG N, XIE C J, LI H M, XIA X C, HE W X, QIN Y X. Genome-wide association study uncover the genetic architecture of salt tolerance-related traits in common wheat (Triticum aestivum L.). Frontiers in Genetics, 2021, 12: 663941.

doi: 10.3389/fgene.2021.663941
[9]
SAHITO J H, ZHANG H, GISHKORI Z G N, MA C H, WANG Z H, DING D, ZHANG X H, TANG J H. Advancements and prospects of genome-wide association studies (GWAS) in maize. International Journal of Molecular Sciences, 2024, 25(3): 1918.

doi: 10.3390/ijms25031918
[10]
TAO R R, DING J F, LI C Y, ZHU X K, GUO W S, ZHU M. Evaluating and screening of agro-physiological indices for salinity stress tolerance in wheat at the seedling stage. Frontiers in Plant Science, 2021, 12: 646175.

doi: 10.3389/fpls.2021.646175
[11]
HONG Y, ZHANG M N, ZHU J, ZHANG Y H, LV C, GUO B J, WANG F F, XU R G. Genome-wide association studies reveal novel loci for grain size in two-rowed barley (Hordeum vulgare L.). Theoretical and Applied Genetics, 2024, 137(3): 58.

doi: 10.1007/s00122-024-04562-8
[12]
NIU M R, TIAN K W, CHEN Q, YANG C Y, ZHANG M C, SUN S Y, WANG X L. A multi-trait GWAS-based genetic association network controlling soybean architecture and seed traits. Frontiers in Plant Science, 2023, 14: 1302359.

doi: 10.3389/fpls.2023.1302359
[13]
MUHAMMAD A, HU W C, LI Z Y, LI J G, XIE G S, WANG J B, WANG L Q. Appraising the genetic architecture of kernel traits in hexaploid wheat using GWAS. International Journal of Molecular Sciences, 2020, 21(16): 5649.

doi: 10.3390/ijms21165649
[14]
YU H T, HAO Y C, LI M Y, DONG L H, CHE N X, WANG L J, SONG S, LIU Y N, KONG L R, SHI S B. Genetic architecture and candidate gene identification for grain size in bread wheat by GWAS. Frontiers in Plant Science, 2022, 13: 1072904.

doi: 10.3389/fpls.2022.1072904
[15]
席甜甜, 吴倩, 杨建光, 马新, 陈彦竹, 李煜, 王军卫, 马守才. 337份小麦品种籽粒相关性状的全基因组关联分析. 麦类作物学报, 2024, 44(5): 547-558.
XI T T, WU Q, YANG J G, MA X, CHEN Y Z, LI Y, WANG J W, MA S C. Genome-wide association studies of 337 wheat varieties for grain-related traits. Journal of Triticeae Crops, 2024, 44(5): 547-558. (in Chinese)
[16]
TAN C, GUO X J, DONG H X, LI M L, CHEN Q, CHENG M P, PU Z E, YUAN Z W, WANG J R. Meta-QTL mapping for wheat thousand kernel weight. Frontiers in Plant Science, 2024, 15: 1499055.

doi: 10.3389/fpls.2024.1499055
[17]
AHMED H G M, ZENG Y W, KHAN M A, RASHID M A R, AMEEN M, AKREM A, SAEED A. Genome-wide association mapping of bread wheat genotypes using yield and grain morphology- related traits under different environments. Frontiers in Genetics, 2022, 13: 1008024.

doi: 10.3389/fgene.2022.1008024
[18]
鲁宗辉, 司二静, 叶霈颖, 汪军成, 姚立蓉, 马小乐, 李葆春, 王化俊, 尚勋武, 孟亚雄. 大麦籽粒β-葡聚糖含量的全基因组关联分析及候选基因预测. 作物学报, 2024, 50(10): 2483-2492.

doi: 10.3724/SP.J.1006.2024.31084
LU Z H, SI E J, YE P Y, WANG J C, YAO L R, MA X L, LI B C, WANG H J, SHANG X W, MENG Y X. Genome-wide association analysis and candidate genes prediction of β-glucan content in barley grains. Acta Agronomica Sinica, 2024, 50(10): 2483-2492. (in Chinese)

doi: 10.3724/SP.J.1006.2024.31084
[19]
LI Y L, LIU J X. StructureSelector: A web-based software to select and visualize the optimal number of clusters using multiple methods. Molecular Ecology Resources, 2018, 18(1): 176-177.

doi: 10.1111/men.2018.18.issue-1
[20]
ZHANG C, DONG S S, XU J Y, HE W M, YANG T L. PopLDdecay: A fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics, 2019, 35(10): 1786-1788.

doi: 10.1093/bioinformatics/bty875 pmid: 30321304
[21]
BARRETT J C, FRY B, MALLER J, DALY M J. Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics, 2005, 21(2): 263-265.

doi: 10.1093/bioinformatics/bth457 pmid: 15297300
[22]
张泽源, 李玥, 赵文莎, 顾晶晶, 张傲琰, 张海龙, 宋鹏博, 吴建辉, 张传量, 宋全昊, 等. 小麦粒重相关性状的QTL定位及分子标记的开发. 中国农业科学, 2023, 56(21): 4137-4149. doi: 10.3864/j.issn.0578-1752.2023.21.001.
ZHANG Z Y, LI Y, ZHAO W S, GU J J, ZHANG A Y, ZHANG H L, SONG P B, WU J H, ZHANG C L, SONG Q H, et al. QTL mapping and molecular marker development of traits related to grain weight in wheat. Scientia Agricultura Sinica, 2023, 56(21): 4137-4149. doi: 10.3864/j.issn.0578-1752.2023.21.001. (in Chinese)
[23]
WANG Y Q, HAO C Y, ZHENG J, GE H M, ZHOU Y, MA Z Q, ZHANG X Y. A haplotype block associated with thousand-kernel weight on chromosome 5DS in common wheat (Triticum aestivum L.). Journal of Integrative Plant Biology, 2015, 57(8): 662-672.

doi: 10.1111/jipb.v57.8
[24]
MENG D Y, BATOOL A, XUAN Y Z, PAN R Q, ZHANG N, ZHANG W, ZHI L Y, REN X L, LI W Q, LI J J, et al. Fine mapping and validation of a stable QTL for thousand-kernel weight in wheat (Triticum aestivum L.). The Crop Journal, 2023, 11(5): 1491-1500.

doi: 10.1016/j.cj.2023.03.007
[25]
周淼平, 张鹏, 杨学明, 张平平, 宋桂成, 何漪. 扬麦158/西风重组自交系群体千粒重QTL的初步定位. 江苏农业学报, 2025, 41(1): 1-8.
ZHOU M P, ZHANG P, YANG X M, ZHANG P P, SONG G C, HE Y. Preliminary QTL mapping for thousand kernel weight in Yangmai 158/Xifeng recombinant inbred line population. Jiangsu Journal of Agricultural Sciences, 2025, 41(1): 1-8. (in Chinese)
[26]
HUANG F, LI X S, DU X Y, LI S C, LI N N, Y J, ZOU S K, ZHANG Q, WANG L N, NI Z F, et al. SNP-based identification of QTLs for thousand-grain weight and related traits in wheat 8762/Keyi 5214 DH lines. Journal of Integrative Agriculture, 2023, 22(10): 2949-2960.

doi: 10.1016/j.jia.2023.03.004
[27]
TAFURI A, PIRONA R, FRICANO A, GASSER M, MAZZUCOTELLI E, MARET E, CAGLIANI L R, RAVAGLIA S, CONSONNI R, THOMAS A, et al. Integrated GWAS and metabolomic analyses identified metabolic pathways and candidate genes involved in free asparagine accumulation in durum wheat grain. Food Chemistry, 2025, 484: 144393.

doi: 10.1016/j.foodchem.2025.144393
[28]
JAEGLE B, VOICHEK Y, HAUPT M, SOTIROPOULOS A G, GAUTHIER K, HEUBERGER M, JUNG E, HERREN G, WIDRIG V, LEBER R, et al. K-mer-based GWAS in a wheat collection reveals novel and diverse sources of powdery mildew resistance. Genome Biology, 2025, 26(1): 172.

doi: 10.1186/s13059-025-03645-z pmid: 40533797
[29]
LIU D Z, LU S, TIAN R M, ZHANG X B, DONG Q F, REN H, CHEN L, HU Y G. Mining genomic regions associated with stomatal traits and their candidate genes in bread wheat through genome-wide association study (GWAS). Theoretical and Applied Genetics, 2025, 138(1): 20.

doi: 10.1007/s00122-024-04814-7 pmid: 39774685
[30]
DIFABACHEW Y F, FRISCH M, LANGSTROFF A L, STAHL A, WITTKOP B, SNOWDON R J, KOCH M, KIRCHHOFF M, CSELÉNYI L, WOLF M, et al. Genomic prediction with haplotype blocks in wheat. Frontiers in Plant Science, 2023, 14: 1168547.

doi: 10.3389/fpls.2023.1168547
[31]
BRINTON J, RAMIREZ-GONZALEZ R H, SIMMONDS J, WINGEN L, ORFORD S, GRIFFITHS S, HABERER G, SPANNAGL M, WALKOWIAK S, POZNIAK C, et al. A haplotype-led approach to increase the precision of wheat breeding. Communications Biology, 2020, 3: 712.

doi: 10.1038/s42003-020-01413-2 pmid: 33239669
[32]
KUMAR SAINI D, HEIN N T, SOMAYANDA I, BHEEMANAHALLI R, OSTMEYER T, KRISHNA JAGADISH S V. Genetic mapping and haplotype analysis identify novel candidate genes for high night temperature tolerance in winter wheat. The Plant Genome, 2025, 18(3): e70075.

doi: 10.1002/tpg2.v18.3
[33]
THALMANN M, COIRO M, MEIER T, WICKER T, ZEEMAN S C, SANTELIA D. The evolution of functional complexity within the β-amylase gene family in land plants. BMC Evolutionary Biology, 2019, 19(1): 66.

doi: 10.1186/s12862-019-1395-2 pmid: 30819112
[34]
CHEN J W, WATSON-LAZOWSKI A, KAMBLE N U, VICKERS M, SEUNG D. Gene expression profile of the developing endosperm in durum wheat provides insight into starch biosynthesis. BMC Plant Biology, 2023, 23(1): 363.

doi: 10.1186/s12870-023-04369-7 pmid: 37460981
[35]
HOFER G, WIESER S, BOGDOS M K, GATTINGER P, NAKAMURA R, EBISAWA M, MÄKELÄ M, PAPADOPOULOS N, VALENTA R, KELLER W. Three-dimensional structure of the wheat β-amylase Tri a 17, a clinically relevant food allergen. Allergy, 2019, 74(5): 1009-1013.

doi: 10.1111/all.13696 pmid: 30515829
[36]
ZABOTINA O A, ZHANG N, WEERTS R. Polysaccharide biosynthesis: Glycosyltransferases and their complexes. Frontiers in Plant Science, 2021, 12: 625307.

doi: 10.3389/fpls.2021.625307
[37]
FANUEL M, ROPARTZ D, GUILLON F, SAULNIER L, ROGNIAUX H. Distribution of cell wall hemicelluloses in the wheat grain endosperm: A 3D perspective. Planta, 2018, 248(6): 1505-1513.

doi: 10.1007/s00425-018-2980-0 pmid: 30140977
[38]
SULIMAN M, CHATEIGNER-BOUTIN A L, FRANCIN-ALLAMI M, PARTIER A, BOUCHET B, SALSE J, PONT C, MARION J, ROGNIAUX H, TESSIER D, et al. Identification of glycosyltransferases involved in cell wall synthesis of wheat endosperm. Journal of Proteomics, 2013, 78: 508-521.

doi: 10.1016/j.jprot.2012.10.021
[39]
ABD-HAMID N A, AHMAD-FAUZI M I, ZAINAL Z, ISMAIL I. Diverse and dynamic roles of F-box proteins in plant biology. Planta, 2020, 251(3): 68.

doi: 10.1007/s00425-020-03356-8
[40]
SLAFER G A, FOULKES M J, REYNOLDS M P, MURCHIE E H, CARMO-SILVA E, FLAVELL R, GWYN J, SAWKINS M, GRIFFITHS S. A ‘wiring diagram’ for sink strength traits impacting wheat yield potential. Journal of Experimental Botany, 2023, 74(1): 40-71.

doi: 10.1093/jxb/erac410
[41]
TILLETT B J, HALE C O, MARTIN J M, GIROUX M J. Genes impacting grain weight and number in wheat (Triticum aestivum L. ssp. aestivum). Plants, 2022, 11(13): 1772.

doi: 10.3390/plants11131772
[42]
WANG H P, CHEN W Q, XU Z Y, CHEN M F, YU D Q. Functions of WRKYs in plant growth and development. Trends in Plant Science, 2023, 28(6): 630-645.

doi: 10.1016/j.tplants.2022.12.012 pmid: 36628655
[43]
GASPARIS S, MIŁOSZEWSKI M M. Genetic basis of grain size and weight in rice, wheat, and barley. International Journal of Molecular Sciences, 2023, 24(23): 16921.

doi: 10.3390/ijms242316921
[1] LI XinYi, LI JiaNing, YANG WenPing, XIA Qing, HUO YingRui, HAO ShiHang, HUANG TingMiao, REN YongKang, CHEN Jie, GAO ZhiQiang, YANG ZhenPing. Effects of Post-Anthesis Foliar Zinc Application on Zinc Nutrition in Colored-Grain Wheat [J]. Scientia Agricultura Sinica, 2026, 59(3): 515-527.
[2] XIAN QingLin, XIAO JianKe, GAO AQing, GAO LiChuang, LIU Yang. Effects of Planting Patterns Combined with Soil Moisture Measurement and Supplementary Irrigation on the Yield and Water Use Efficiency of Winter Wheat [J]. Scientia Agricultura Sinica, 2026, 59(3): 589-601.
[3] ZHANG ZhiYong, TAN ShiChao, XIONG ShuPing, MA XinMing, WEI YiHao, WANG XiaoChun. Effects of Annual Water and Nitrogen Optimization on Yield and Nitrogen Migration of Wheat-Maize Rotation System in Irrigation Area of Northern Henan [J]. Scientia Agricultura Sinica, 2026, 59(2): 336-353.
[4] LÜ XuDong, SUN ShiYuan, LI YaNan, LIU YuLong, WANG YanQun, FU Xin, ZHANG JiaYing, NING Peng, PENG ZhengPing. Effects of Intelligent Mechanized Layered Fertilization on Root-Soil Nutrient Distribution and Yield in Wheat Fields [J]. Scientia Agricultura Sinica, 2026, 59(1): 129-146.
[5] LU Hao, ZHANG MingLong, HAN Mei, YAN QingBiao, LI ZhengPeng, YIN Wen, FAN ZhiLong, HU FaLong, CHAI Qiang. Green Manure Returning via Sheep Digest with Nitrogen Fertilizer Reduction are Beneficial to Improve Wheat Yield and Soil Quality at Qinghai-Tibet Plateau [J]. Scientia Agricultura Sinica, 2026, 59(1): 147-160.
[6] YE MeiJin, CHEN JiaTing, ZHOU JieGuang, YIN Li, HU XinRong, LAN YuXin, CHEN Bin, SU LongXing, LIU JiaJun, LIU TianChao, LI XiaoYu, MA Jian. Identification, Validation and Genetic Effect Analysis of Major QTL for Spike Density in Wheat [J]. Scientia Agricultura Sinica, 2026, 59(1): 17-28.
[7] PU LiXia, ZHANG JiaRui, YE JianPing, HUANG XiuLan, FAN GaoQiong, YANG HongKun. The Combined Effects of 16, 17-Dihydro Gibberellin A5 and Straw Mulching on Tillering and Grain Yield of Dryland Wheat [J]. Scientia Agricultura Sinica, 2025, 58(9): 1735-1748.
[8] LI YunLi, DIAO DengChao, LIU YaRui, SUN YuChen, MENG XiangYu, WU ChenFang, WANG Yu, WU JianHui, LI ChunLian, ZENG QingDong, HAN DeJun, ZHENG WeiJun. Genome-Wide Association Study of Heat Tolerance at Seedling Stage in A Wheat Natural Population [J]. Scientia Agricultura Sinica, 2025, 58(9): 1663-1683.
[9] WU Yu, QU XiangRu, YANG Dan, WU Qin, CHEN GuoYue, JIANG QianTao, WEI YuMing, XU Qiang. Widespread Non-Targeted Metabolomics Reveals Metabolites of Chloroplasts in Wheat Responses to Stripe Rust [J]. Scientia Agricultura Sinica, 2025, 58(7): 1333-1343.
[10] YIN Bo, YU AiZhong, WANG PengFei, YANG XueHui, WANG YuLong, SHANG YongPan, ZHANG DongLing, LIU YaLong, LI Yue, WANG Feng. Effects of Green Manure Returning Combined with Nitrogen Fertilizer Reduction on Hydrothermal Characteristics of Wheat Field and Grain Yield in Oasis Irrigation Area [J]. Scientia Agricultura Sinica, 2025, 58(7): 1366-1380.
[11] PAN LiYuan, WANG YongJun, LI HaiJun, HOU Fu, LI Jing, LI LiLi, SUN SuYang. Screening Regulatory Genes Related to Wheat Grain Protein Accumulation Based on Transcriptome and WGCNA Analysis [J]. Scientia Agricultura Sinica, 2025, 58(6): 1065-1082.
[12] TANG Yu, LEI BiXin, WANG ChuanWei, YAN XuanTao, WANG Hao, ZHENG Jie, ZHANG WenJing, MA ShangYu, HUANG ZhengLai, FAN YongHui. Response Mechanism of Anthocyanin Accumulation in Colored Wheat to Post-Anthesis High Temperature Stress [J]. Scientia Agricultura Sinica, 2025, 58(6): 1083-1101.
[13] ZHANG HongCheng, XING ZhiPeng, ZHANG RuiHong, SHAN Xiang, XI XiaoBo, CHENG Shuang, WENG WenAn, HU Qun, CUI PeiYuan, WEI HaiYan. Characteristics and Technical Approaches of Integrated Unmanned High-Yield Cultivation of Wheat [J]. Scientia Agricultura Sinica, 2025, 58(5): 864-876.
[14] ZHANG Ling, CAO Lei, CAI Cheng, YAN XinYi, XIANG BoCai, AI Jia, ZHAN XinYang, SONG YouHong, ZHU YuLei. Changes in Seed Vigor and Physiological Index of Winter Wheat Under Natural Aging Condition [J]. Scientia Agricultura Sinica, 2025, 58(5): 877-889.
[15] SHE WenTing, SUN RuiQing, DANG HaiYan, LI WenHu, ZHANG Feng, TIAN Yi, XU JunFeng, DING YuLan, WANG ZhaoHui. Sulfur Concentration and Distribution in Wheat Grain Sampled from Farmers’ Fields in Main Wheat Production Regions of China and Its Affecting Factors [J]. Scientia Agricultura Sinica, 2025, 58(5): 956-974.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!