Scientia Agricultura Sinica ›› 2024, Vol. 57 ›› Issue (4): 627-637.doi: 10.3864/j.issn.0578-1752.2024.04.001

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

Genome-Wide Association Studies for Canopy Activity Related Traits and Its Genetic Effects on Yield-Related Traits

LI FaJi1(), CHENG DunGong1, YU XiaoCong2, WEN WeiE3, LIU JinDong4, ZHAI ShengNan1, LIU AiFeng1, GUO Jun1, CAO XinYou1, LIU Cheng1, SONG JianMin1, LIU JianJun1, LI HaoSheng1()   

  1. 1 Crop Research Institute, Shandong Academy of Agricultural Sciences/National Engineering Research Center of Wheat and Maize/Key Laboratory of Wheat Biology and Genetics and Breeding in Northern Huang-Huai River Plain, Ministry of Agriculture and Rural Affairs/Shandong Technology Innovation Center of Wheat/Jinan Key Laboratory of Wheat Genetic Improvement, Jinan 250100
    2 College of Agricultral and Biological Engineering (College of Tree Peony), Heze University, Heze 274015, Shandong
    3 Department of Cell Biology, Zunyi Medical University, Zunyi 563099, Guizhou
    4 Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081
  • Received:2023-07-17 Accepted:2023-09-12 Online:2024-02-16 Published:2024-02-20
  • Contact: LI HaoSheng

RichHTML

31

PDF

132

Abstract:

【Objective】Canopy activity is an important indicator of wheat growth and development. Identification the loci for canopy activity related traits and their relationships with grain yield (GY) related traits can provide theoretical support for the dissection of genetic structure of yield trait and assisted wheat breeding.【Method】A total of 166 wheat varieties originating from both domestic and international sources were planted in Anyang of Henan province and Suixi of Anhui province in cropping seasons. With the integrated physical map containing 326 570 SNP markers from the wheat 90K and 660K chips, genome-wide association studies for normalized difference vegetation index at seedling stage (NDVI-S) and 10 days after flowering (NDVI-10), and chlorophyll content in flag leaf at 10 days after flowering (Chl-10) were carried out. The results were compared with the previous study for GY related traits using the same material. 【Result】Analysis of variance (ANOVA) showed highly significant effects (P<0.01) of genotypes, environments and genotype×environment interactions on NDVI-S, NDVI-10 and Chl-10, with broad-sense heritabilities (h2 b) of 0.81, 0.81 and 0.91, respectively. Thirteen, 12 and 15 loci were detected to be significantly correlated with NDVI-S, NDVI-10 and Chl-10, respectively, among which 12, 11 and 12 were new, and five loci were associated with two or more traits. The number of favorable alleles for NDVI-S, NDVI-10 and Chl-10 ranged from 4 to 11, 3 to 11 and 4 to 12, respectively, in the 166 wheat varieties, and the phenotypic values increased with the accumulation of favorable alleles. NDVI-S showed significant (P<0.01) and positive correlations with thousand-kernel weight, kernel length and kernel width. Chl-10 was significant positively correlated with GY and flag leaf width (P<0.01), whereas significant negatively correlated with spike number per unit area, plant height and uppermost internode length (P<0.01). Seven pleiotropic loci were detected co-related with both GY and canopy activity related traits.【Conclusion】NDVI-S can be directly used for selection of yield traits. The stable and pleiotropic loci detected in this study can be used for marker-assisted selection.

Key words: Triticum aestivum, canopy activity, grain yield, normalized difference vegetation index, chlorophyll content, genome- wide association studies

Table 1

Analysis of variance and broad-sense heritabilities (h2 b) for canopy activity related traits"

性状
Trait		 均方值Mean square 遗传力
h2 b
基因型
Genotype (G)		 环境
Environment (E)		 重复
Replicate		 基因型×环境
G×E		 误差
Error
NDVI-S 0.003** 0.047** 0.003** 0.001** 0.001 0.81
NDVI-10 0.009** 0.048** 0.001 0.002** 0.001 0.81
Chl-10 74.25** 1212.76** 26.24** 7.47** 1.64 0.91

Fig. 1

Frequency distribution histogram for the BLUE values of NDVI-S, NDVI-10 and Chl-10"

Table 2

Mean, standard deviation (SD), and range of canopy activity related traits in 166 wheat varietie"

性状 Trait 环境 Environment 平均值 Mean 标准差 SD 范围 Range 变异系数 CV
NDVI-S E1 0.20 0.013 0.17-0.24 0.056
E2 0.18 0.018 0.15-0.25 0.072
E3 0.21 0.021 0.14-0.27 0.079
E4 0.20 0.023 0.11-0.26 0.087
E5 0.20 0.015 0.15-0.24 0.063
NDVI-10 E1 0.75 0.028 0.66-0.80 0.035
E2 0.76 0.027 0.66-0.84 0.032
E3 0.75 0.046 0.63-0.87 0.053
E4 0.74 0.040 0.58-0.83 0.048
E5 0.75 0.026 0.68-0.82 0.032
Chl-10 E1 54 2.6 46-61 0.043
E2 53 2.8 45-59 0.047
E3 53 2.8 45-60 0.047
E4 50 3.1 43-57 0.055
E5 53 2.5 46-59 0.042

Fig. 2

Manhattan (left) and quantile-quantile (right) plots for the BLUE values of NDVI-S、NDVI-10 and Chl-10"

Table 3

Loci for canopy activity related traits in the diverse panel of wheat varieties and comparisons with previous studies"

性状
Trait		 标记a
Marker		 染色体
Chr.		 物理位置b
Physical position (bp)		 环境
Environment		 SNPc P
 贡献率
R2 (%)		 QTL/标记/基因d
QTL/marker/gene
苗期归一化
植被指数
NDVI-S		 AX-109973814 1A 553879787-556989408 E1/E4/E5 A/G 3.76E-04-9.45E-04 7.2-8.8
AX-89581383 2A 31905918-31954704 E1/E5 C/T 1.92E-04-9.38E-04 7.3-8.9
AX-95099338 2B 794345863-794501909 E2/E3/E5 C/T 2.30E-05-9.94E-04 6.9-12.5
AX-108780837 3B 800187839-803762562 E2/E3/E4/E5 G/T 2.37E-04-9.92E-04 6.9-9.8
AX-111488372 4A 688477376-692653638 E1/E4/E5 C/T 4.42E-04-9.97E-04 7.0-8.5
AX-108817291 4B 32178420-42912748 E1/E3/E4/E5 A/G 4.67E-05-9.70E-04 7.0-11.1
AX-109416328 5A 511336844-516799817 E3/E4/E5 C/T 7.41E-05-9.99E-04 7.0-10.5
AX-108827844 5B 584820626-587603152 E1/E2/E5 C/T 2.25E-05-9.21E-04 7.0-11.7
AX-95010007 5D 479879394-483521914 E2/E4/E5 C/T 1.02E-04-7.72E-04 7.7-10.0
AX-108871828 6B 705307814-705307884 E1/E5 A/G 2.65E-04-6.98E-04 7.6-8.8 QNDVI-S.caas-6BL[24]
AX-110399902 7A 511044701-514432331 E2/E4/E5 A/C 1.14E-04-9.79E-04 6.9-10.0
AX-109353477 7B 53647905-59320644 E1/E4/E5 C/T 9.49E-06-9.99E-04 6.8-13.5
AX-111483621 7B 700393032-704402945 E2/E3/E5 G/T 1.81E-04-9.82E-04 7.1-9.2
花后10 d归一
化植被指数NDVI-10		 AX-89581383 2A 31905918-31958182 E2/E3/E5 C/T 5.03E-06-9.14E-04 7.9-11.4
AX-110065934 3A 20031674-24754209 E1/E2/E4/E5 C/T 1.28E-05-9.82E-04 7.3-13.7
AX-111066255 4A 3156028-4485378 E3/E4/E5 G/T 3.83E-05-9.39E-04 7.1-12.1
IWB9838 5A 444529778-444893234 E1/E4/E5 A/G 1.26E-04-7.27E-04 7.7-9.4 QNDVI-10.caas-5AL [24]
AX-111085648 5A 509652100-509992242 E2/E3/E4 A/G 6.29E-04-9.85E-04 7.5-8.6
AX-110413050 5A 538001880-540914319 E2/E3/E4/E5 G/T 3.99E-05-9.99E-04 7.0-11.5
AX-110910427 5B 416212499-420974307 E1/E2/E5 A/G 3.33E-05-9.95E-04 7.2-11.7
AX-108831704 5B 571816645-572547249 E2/E4/E5 A/G 8.35E-05-6.95E-04 8.0-10.4
AX-110458337 5D 512761945-515042348 E2/E3/E5 C/T 8.47E-05-5.92E-04 8.1-11.3
IWA497 7A 515006880-517518517 E1/E4/E5 A/G 2.26E-05-9.29E-04 7.1-11.7
IWA5912 7A 674272175-674276806 E1/E2/E5 A/G 3.94E-05-7.05E-04 7.4-10.8
AX-111094331 7B 720812571-725728459 E2/E4/E5 A/G 2.86E-07-9.10E-04 6.7-18.5
花后10 d旗叶
叶绿素含量
Chl-10		 AX-89478051 1A 10746438-11665198 E1/E3/E4/E5 C/T 1.15E-04-8.89E-04 7.3-9.8
AX-110019816 1A 572240419-574819040 E2/E3/E4/E5 A/G 2.21E-04-6.48E-04 7.7-8.8
AX-109271027 1B 14147203-14149354 E1/E3/E4/E5 C/T 3.72E-05-9.09E-04 7.4-10.5
IWB34618 1B 39590913-41642839 E1/E2/E3/E4/E5 C/T 1.49E-05-9.73E-04 6.9-11.7
AX-110906318 1B 464709853-465687627 E3/E4/E5 A/G 2.36E-05-9.71E-04 6.6-9.3
AX-111696227 1B 562234252-563750279 E3/E4/E5 G/T 6.29E-06-9.62E-04 6.8-13.9
AX-111592648 2B 670837387-674035196 E1/E2/E3/E4/E5 C/T 5.71E-05-8.91E-04 6.8-10.1
AX-108767341 2D 79064947-79552104 E1/E2/E3/E4/E5 A/C 4.79E-05-8.80E-04 6.9-11.0 QChl-A.caas-2DS[11]
AX-111709018 4A 3126102-3126172 E1/E2/E5 C/T 5.19E-04-9.10E-04 6.8-7.7
AX-109356891 4A 688401664-690885158 E1/E2/E3/E5 C/G 3.89E-04-9.72E-04 6.4-8.4
AX-110921829 4A 726314392-729886306 E1/E2/E3/E4/E5 C/T 1.74E-04-9.42E-04 6.8-9.7
IWB31092 5A 510096358-514153660 E1/E2/E3/E4/E5 A/G 1.33E-05-9.76E-04 6.5-12.1 IWB21197[21]
AX-111078602 5B 576574518-576574588 E3/E4/E5 C/T 4.38E-04-4.82E-04 7.7-8.1
AX-110462661 6A 26782691-26782761 E1/E2/E4/E5 C/T 2.28E-04-9.14E-04 7.1-9.8 QChl-10.caas-6AS[11];
QChl-6A[20]; Qchl-saw-6A[22]
AX-110587099 7A 6330314-12989016 E1/E2/E3/E4/E5 C/T 8.19E-05-9.97E-04 6.7-10.3

Fig. 3

Effects of the number of alleles for increasing phenotypic values of NDVI-S, NDVI-10 and Chl-10"

Table 4

Correlation analysis between canopy activity related traits and grain yield related traits in our previous study[25] in the diverse panel of wheat varieties"

性状Trait NDVI-S NDVI-10 Chl-10
产量GY -0.001 0.170* 0.405**
每平方米穗数SN -0.052 0.154* -0.367**
穗粒数KNS -0.034 -0.190* 0.220**
千粒重TKW 0.370** 0.082 0.290**
粒长KL 0.293** 0.148 0.037
粒宽KW 0.321** 0.035 0.245**
穗长SL -0.002 -0.211** 0.071
穗干重SDW 0.312** -0.179* 0.346**
抽穗期HD -0.237** 0.142 0.159*
株高PH 0.243** -0.287** -0.381**
穗下节长UIL 0.209** -0.249** -0.362**
旗叶长FLL 0.231** -0.034 -0.291**
旗叶宽FLW -0.092 0.091 0.514**

Table 5

Pleiotropic loci for both canopy activity related traits in the present study and grain yield related traits in our previous study[25] in the diverse panel of wheat varieties"

染色体
Chr.		 物理位置
Physical interval (bp)		 冠层活性相关性状显著性位点
Significant loci for canopy activity related traits		 产量相关性状显著性位点
Significant loci for grain yield related traits
1A 8291180-11950637 AX-89478051 (Chl-10) IWB6999 (KW); AX-109621606 (FLL)
2A 27328522-31954704 AX-89581383 (NDVI-S; NDVI-10) AX-94546135 (GY); AX-111037158 (KW; HD); AX-110988136 (PH)
5A 509652100-516799817 AX-109416328 (NDVI-S); AX-111085648 (NDVI-10); IWB31092 (Chl-10) AX-109367907 (SL)
5A 538001880-547648338 AX-110413050 (NDVI-10) AX-110919697 (SL); AX-110675353 (PH)
5B 571816645-587603152 AX-108827844 (NDVI-S); AX-108831704 (NDVI-10); AX-111078602 (Chl-10) AX-110995303 (GY); AX-110971192 (SL); AX-108921249 (PH)
6B 696641914-709221403 AX-108871828 (NDVI-S) AX-95260682 (SN); AX-109820966 (KW); AX-109459603 (FLL)
7A 511044701-517518517 AX-110399902 (NDVI-S); IWA497 (NDVI-10) AX-110127979 (GY); AX-109921812 (HD)
[1]
FREEMAN K W, RAUN W R, JOHNSON G V, MULLEN R W, STONE M L, SOLIE J B. Late-season prediction of wheat grain yield and grain protein. Communications in Soil Science and Plant Analysis, 2003, 34(13/14): 1837-1852.

doi: 10.1081/CSS-120023219
[2]
BABAR M A, REYNOLDS M P, VAN GINKEL M, KLATT A R, RAUN W R, STONE M L. Spectral reflectance indices as a potential indirect selection criteria for wheat yield under irrigation. Crop Science, 2006, 46(2): 578-588.

doi: 10.2135/cropsci2005.0059
[3]
BABAR M A, REYNOLDS M P, VAN GINKEL M, KLATT A R, RAUN W R, STONE M L. Spectral reflectance to estimate genetic variation for in-season biomass, leaf chlorophyll, and canopy temperature in wheat. Crop Science, 2006, 46(3): 1046-1057.

doi: 10.2135/cropsci2005.0211
[4]
HAZRATKULOVA S, SHARMA R C, ALIKULOV S, ISLOMOV S, YULDASHEV T, ZIYAEV Z, KHALIKULOV Z, ZIYADULLAEV Z, TUROK J. Analysis of genotypic variation for normalized difference vegetation index and its relationship with grain yield in winter wheat under terminal heat stress. Plant Breeding, 2012, 131(6): 716-721.

doi: 10.1111/pbr.2012.131.issue-6
[5]
XIAO Y G, QIAN Z G, WU K, LIU J D, XIA X C, JI W Q, HE Z H. Genetic gains in grain yield and physiological traits of winter wheat in Shandong province, China, from 1969 to 2006. Crop Science, 2012, 52: 44-56.

doi: 10.2135/cropsci2011.05.0246
[6]
GAO F M, MA D Y, YIN G H, RASHEED A, DONG Y, XIAO Y G, XIA X C, WU X X, HE Z H.Genetic progress in grain yield and physiological traits in Chinese wheat cultivars of southern yellow and Huai valley since 1950. Crop Science, 2017, 57(2): 760-773.

doi: 10.2135/cropsci2016.05.0362
[7]
HASSAN M A, YANG M J, RASHEED A, YANG G J, REYNOLDS M, XIA X C, XIAO Y G, HE Z H. A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform. Plant Science, 2019, 282: 95-103.

doi: S0168-9452(17)31020-8 pmid: 31003615
[8]
李龙, 彭智, 毛新国, 王景一, 昌小平, 柳玉平, 景蕊莲. 小麦高密度遗传图谱构建及抗旱相关生理性状的遗传解析. 植物遗传资源学报, 2018, 19(3): 531-538.

doi: 10.13430/j.cnki.jpgr.2018.03.019
LI L, PENG Z, MAO X G, WANG J Y, CHANG X P, LIU Y P, JING R L. Genetic map construction and genetic dissection of drought- tolerant related physiological traits in wheat. Journal of Plant Genetic Resources, 2018, 19(3): 531-538. (in Chinese)
[9]
AVENSON T J, CRUZ J A, KANAZAWA A, KRAMER D M.Regulating the proton budget of higher plant photosynthesis. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(27): 9709-9713.
[10]
EL-FEKI W M, BYRNE P, REID S, HALEY S. Mapping quantitative trait loci for bread making quality and agronomic traits in winter wheat under different soil moisture levels[D]. Fort Collins: Colorado State University, 2010.
[11]
GAO F M, WEN W E, LIU J D, RASHEED A, YIN G H, XIA X C, WU X X, HE Z H. Genome-wide linkage mapping of QTL for yield components, plant height and yield-related physiological traits in the Chinese wheat cross Zhou 8425B/Chinese Spring. Frontiers in Plant Science, 2015, 6: 1099.

doi: 10.3389/fpls.2015.01099 pmid: 26734019
[12]
SHI S K, AZAM F I, LI H H, CHANG X P, LI B Y, JING R L. Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes. Euphytica, 2017, 213(11): 246.

doi: 10.1007/s10681-017-2002-5
[13]
ZHANG K P, FANG Z J, LIANG Y, TIAN J C. Genetic dissection of chlorophyll content at different growth stages in common wheat. Journal of Genetics, 2009, 88(2): 183-189.

doi: 10.1007/s12041-009-0026-x pmid: 19700856
[14]
GENC Y, OLDACH K, VERBYLA A P, LOTT G, HASSAN M, TESTER M, WALLWORK H, MCDONALD G K. Sodium exclusion QTL associated with improved seedling growth in bread wheat under salinity stress. Theoretical and Applied Genetics, 2010, 121(5): 877-894.

doi: 10.1007/s00122-010-1357-y pmid: 20490443
[15]
KUMAR S, SEHGAL S K, KUMAR U, VARA PRASAD P V, JOSHI A K, GILL B S. Genomic characterization of drought tolerance-related traits in spring wheat. Euphytica, 2012, 186(1): 265-276.

doi: 10.1007/s10681-012-0675-3
[16]
JIA H Y, WAN H S, YANG S H, ZHANG Z Z, KONG Z X, XUE S L, ZHANG L X, MA Z Q. Genetic dissection of yield-related traits in a recombinant inbred line population created using a key breeding parent in China’s wheat breeding. Theoretical and Applied Genetics, 2013, 126(8): 2123-2139.

doi: 10.1007/s00122-013-2123-8
[17]
TALUKDER S K, ALI BABAR M, VIJAYALAKSHMI K, POLAND J, PRASAD P V V, BOWDEN R, FRITZ A. Mapping QTL for the traits associated with heat tolerance in wheat (Triticum aestivum L.). BMC Genetics, 2014, 15(1): 97.

doi: 10.1186/s12863-014-0097-4
[18]
XU Y F, LI S S, LI L H, MA F F, FU X Y, SHI Z L, XU H X, MA P T, AN D G. QTL mapping for yield and photosynthetic related traits under different water regimes in wheat. Molecular Breeding, 2017, 37(3): 34.

doi: 10.1007/s11032-016-0583-7
[19]
BHUSAL N, SHARMA P, SAREEN S, SARIAL A K. Mapping QTLs for chlorophyll content and chlorophyll fluorescence in wheat under heat stress. Biologia Plantarum, 2018, 62(4): 721-731.

doi: 10.1007/s10535-018-0811-6
[20]
HASSAN F S C, SOLOUKI M, ALI FAKHERI B, NEZHAD N M, MASOUDI B. Mapping QTLs for physiological and biochemical traits related to grain yield under control and terminal heat stress conditions in bread wheat (Triticum aestivum L.). Physiology and Molecular Biology of Plants, 2018, 24(6): 1231-1243.

doi: 10.1007/s12298-018-0590-8
[21]
LIU Y X, WANG R, HU Y G, CHEN J L. Genome-wide linkage mapping of quantitative trait loci for late-season physiological and agronomic traits in spring wheat under irrigated conditions. Agronomy, 2018, 8(5): 60.

doi: 10.3390/agronomy8050060
[22]
杨斌, 乔玲, 赵佳佳, 武棒棒, 温宏伟, 张树伟, 郑兴卫, 郑军. 小麦旗叶叶绿素含量的QTL定位及验证. 作物学报, 2023, 49(3): 744-754.

doi: 10.3724/SP.J.1006.2023.21018
YANG B, QIAO L, ZHAO J J, WU B B, WEN H W, ZHANG S W, ZHENG X W, ZHENG J. QTL mapping and validation of chlorophyll content of flag leaves in wheat (Triticum aestivum L.). Acta Agronomica Sinica, 2023, 49(3): 744-754. (in Chinese)

doi: 10.3724/SP.J.1006.2023.21018
[23]
LI F J, WEN W E, HE Z H, LIU J D, JIN H, CAO S H, GENG H W, YAN J, ZHANG P Z, WAN Y X, XIA X C. Genome-wide linkage mapping of yield related traits in three Chinese bread wheat populations using high-density SNP markers. Theoretical and Applied Genetics, 2018, 131(19): 1903-1924.

doi: 10.1007/s00122-018-3122-6
[24]
LI F J, WEN W E, LIU J D, ZHAI S N, CAO X Y, LIU C, CHENG D G, GUO J, ZI Y, HAN R, WANG X L, LIU A F, SONG J M, LIU J J, LI H S, XIA X C. Genome-wide linkage mapping for canopy activity related traits using three RIL populations in bread wheat. Euphytica, 2021, 217(4): 1-16.

doi: 10.1007/s10681-020-02732-5
[25]
LI F J, WEN W E, LIU J D, ZHANG Y, CAO S H, HE Z H, RASHEED A, JIN H, ZHANG C, YAN J, ZHANG P Z, WAN Y X, XIA X C. Genetic architecture of grain yield in bread wheat based on genome-wide association studies. BMC Plant Biology, 2019, 19(1): 168.

doi: 10.1186/s12870-019-1781-3 pmid: 31035920
[26]
LI H H, YE G Y, WANG J K. A modified algorithm for the improvement of composite interval mapping. Genetics, 2007, 175(1): 361-374.

doi: 10.1534/genetics.106.066811 pmid: 17110476
[27]
NYQUIST W E, BAKER R J. Estimation of heritability and prediction of selection response in plant populations. Critical Reviews in Plant Sciences, 1991, 10(3): 235-322.

doi: 10.1080/07352689109382313
[28]
HOLLAND J, NYQUIST W, CERVANTES-MARTÍNEZ C T. Estimating and interpreting heritability for plant breeding: An update. Plant Breeding Reviews, 2010, 22: 9-112.
[29]
INTERNATIONAL WHEAT GENOME SEQUENCING CONSORTIUM (IWGSC). A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome. Science, 2014, 345(6194): 1251788.

doi: 10.1126/science.1251788
[30]
PRITCHARD J K, STEPHENS M, ROSENBERG N A, DONNELLY P. Association mapping in structured populations. The American Journal of Human Genetics, 2000, 67(1): 170-181.

doi: 10.1086/302959
[31]
BELLUNDAGI A, SINGH G P, PRABHU K V, ARORA A, JAIN N, RAMYA P, SINGH A M, SINGH P K, AHLAWAT A. Early ground cover and other physiological traits as efficient selection criteria for grain yield under moisture deficit stress conditions in wheat (Triticum aestivum L.). Indian Journal of Plant Physiology, 2013, 18(3): 277-281.

doi: 10.1007/s40502-013-0047-6
[32]
SUN C W, DONG Z D, ZHAO L, REN Y, ZHANG N, CHEN F. The Wheat 660K SNP array demonstrates great potential for marker- assisted selection in polyploid wheat. Plant Biotechnology Journal, 2020, 18(6): 1354-1360.

doi: 10.1111/pbi.v18.6
[1] ZHAO KaiNan, DING Hao, LIU AKang, JIANG ZongHao, CHEN GuangZhou, FENG Bo, WANG ZongShuai, LI HuaWei, SI JiSheng, ZHANG Bin, BI XiangJun, LI Yong, LI ShengDong, WANG FaHong. Nitrogen Fertilizer Reduction and Postponing for Improving Plant Photosynthetic Physiological Characteristics to Increase Wheat- Maize and Annual Yield and Economic Return [J]. Scientia Agricultura Sinica, 2024, 57(5): 868-884.
[2] DONG ErWei, WANG Yuan, WANG JinSong, LIU QiuXia, HUANG XiaoLei, JIAO XiaoYan. Effects of Nitrogen Fertilization Levels on Grain Yield, Plant Nitrogen Utilization Characteristics and Grain Quality of Foxtail Millet [J]. Scientia Agricultura Sinica, 2024, 57(2): 306-318.
[3] BAI Bin, ZHANG HuaiZhi, DU JiuYuan, ZHANG XiaoYang, HE Rui, WU Ling, ZHANG Zhe, ZHANG YaoHui, CAO ShiQin, LIU ZhiYong. Current Situation and Strategy of Stripe Rust Resistance Genes Untilization in Winter Wheat Cultivars of Northwestern Oversummering Region for Puccinia striiformis f. sp. tritici in China [J]. Scientia Agricultura Sinica, 2024, 57(1): 4-17.
[4] ZHANG Xu, HAN JinYu, LI ChenChen, ZHANG DanDan, WU QiMeng, LIU ShengJie, JIAO HanXuan, HUANG Shuo, LI ChunLian, WANG ChangFa, ZENG QingDong, KANG ZhenSheng, HAN DeJun, WU JianHui. Identification of Adult Plant Stripe Rust Resistance Candidate Genes of YrZ501-2BL by Gene Association and Transciptome Analysis in Wheat (Triticum aestivum L.) [J]. Scientia Agricultura Sinica, 2023, 56(8): 1429-1443.
[5] DONG JiZi, CHEN LinQu, GUO HaoRu, ZHANG MengYu, LIU ZhiXiao, HAN Lei, TIAN ZhaoSaShuang, XU NingHao, GUO QingJie, HUANG ZhenJie, YANG AoYu, ZHAO ChunHua, WU YongZhen, SUN Han, QIN Ran, CUI Fa. Analysis of Genetic and Breeding Selection Effects of A Major QTL-qSl-2D for Wheat Spike Length [J]. Scientia Agricultura Sinica, 2023, 56(20): 3917-3930.
[6] LI Yi, LU JianXin, CAO Peng, ZHOU DengWen, LIU JiMin, TIAN PingPing, CAI MingLi, CAO CouGui, YANG TeWu. Critical Lowest Temperature for the Safe Heading of Various Types of Late-Season Rice Cultivars and the Safe Dates for Their Full Heading in Different Double-Season Rice Cropping Regions of Hubei Province [J]. Scientia Agricultura Sinica, 2023, 56(17): 3302-3316.
[7] ZHANG WenXia, LI Pan, YIN Wen, CHEN GuiPing, FAN ZhiLong, HU FaLong, FAN Hong, HE Wei. Effects of Multiple Green Manure After Wheat Combined with Different Levels of Nitrogen Fertilization on Wheat Yield, Grain Quality, and Nitrogen Utilization [J]. Scientia Agricultura Sinica, 2023, 56(17): 3317-3330.
[8] MU XinYuan, LÜ ShanShan, LU LiangTao, LIU TianXue, LI ShuYan, XUE ChangYing, WANG HongWei, ZHAO Xia, XIA LaiKun, TANG BaoJun. Effects of Tassel Sizes on Post-Flowering Dry Matter Accumulation and Yield of Different Maize Varieties Under High Temperature Stress During Pollination [J]. Scientia Agricultura Sinica, 2023, 56(15): 2880-2894.
[9] GUO XinHu, MA Jing, LI ZhongFeng, CHU JinPeng, XU HaiCheng, JIA DianYong, DAI XingLong, HE MingRong. Effects of Cultivation Modes on Soil Physicochemical Properties and Nitrogen Balance in Wheat Fields Under Long-Term Positioning Conditions [J]. Scientia Agricultura Sinica, 2023, 56(12): 2262-2273.
[10] WU JinZhi, HUANG XiuLi, HOU YuanQuan, TIAN WenZhong, LI JunHong, ZHANG Jie, LI Fang, LÜ JunJie, YAO YuQing, FU GuoZhan, HUANG Ming, LI YouJun. Effects of Ridge and Furrow Planting Patterns on Crop Productivity and Soil Nitrate-N Accumulation in Dryland Summer Maize and Winter Wheat Rotation System [J]. Scientia Agricultura Sinica, 2023, 56(11): 2078-2091.
[11] WANG HaoLin,MA Yue,LI YongHua,LI Chao,ZHAO MingQin,YUAN AiJing,QIU WeiHong,HE Gang,SHI Mei,WANG ZhaoHui. Optimal Management of Phosphorus Fertilization Based on the Yield and Grain Manganese Concentration of Wheat [J]. Scientia Agricultura Sinica, 2022, 55(9): 1800-1810.
[12] GUI RunFei, WANG ZaiMan, PAN ShengGang, ZHANG MingHua, TANG XiangRu, MO ZhaoWen. Effects of Nitrogen-Reducing Side Deep Application of Liquid Fertilizer at Tillering Stage on Yield and Nitrogen Utilization of Fragrant Rice [J]. Scientia Agricultura Sinica, 2022, 55(8): 1529-1545.
[13] ZHAO Ling, ZHANG Yong, WEI XiaoDong, LIANG WenHua, ZHAO ChunFang, ZHOU LiHui, YAO Shu, WANG CaiLin, ZHANG YaDong. Mapping of QTLs for Chlorophyll Content in Flag Leaves of Rice on High-Density Bin Map [J]. Scientia Agricultura Sinica, 2022, 55(5): 825-836.
[14] LI Gang, BAI Yang, JIA ZiYing, MA ZhengYang, ZHANG XiangChi, LI ChunYan, LI Cheng. Phosphorus Altered the Response of Ionomics and Metabolomics to Drought Stress in Wheat Seedlings [J]. Scientia Agricultura Sinica, 2022, 55(2): 280-294.
[15] WANG ChuHan,LIU Fei,GAO JianYong,ZHANG HuiFang,XIE YingHe,CAO HanBing,XIE JunYu. The Variation Characteristics of Soil Organic Carbon Component Content Under Nitrogen Reduction and Film Mulching [J]. Scientia Agricultura Sinica, 2022, 55(19): 3779-3790.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备09089781号-30
Copyright 2018 © Editorial office of Scientia Agricultura Sinica
Tel: 86-010-82106279    E-mail: zgnykx@mail.caas.net.cn
Supported by Beijing Magtech Co.Ltd