Welcome to Acta Agronomica Sinica，

Acta Agron Sin ›› 2011, Vol. 37 ›› Issue (03): 389-396.doi: 10.3724/SP.J.1006.2011.00389

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

Genetic Effects and Diagnosis of Premature Senescence of Leaf in Upland Cotton

HAO Jun-Jie1,LIU Huan-Min1,MA Qi-Xiang1,CUI Xiao-Wei1,YU Ji-Wen2,JIA Xin-He3,GAO Jun-Shan4   

  1. 1 Plant Protection Institute, Henan Academy of Agricultural Sciences / Henan Key Laboratory for Control of Crop Diseases and Insect Pests, Zhengzhou 450002, China; 2 China Cotton Research Institute, Chinese Academy of Agricultural Sciences, Anyang 455000, China; 3 Zhengzhou Institute of Agriculture and Forestry Sciences, Zhengzhou 450002, China; 4 Kaifeng Academy of Agriculture and Forestry Sciences, Kaifeng 475004, China
  • Received:2010-06-11 Revised:2010-12-06 Online:2011-03-12 Published:2011-01-17

PDF

1354

Cited

6

Abstract: Premature senescence of cotton has been occurring on an increasing scale in China, directly influencing both yield and fiber quality. The most effective way avoiding premature senescence is to obtain stay-green variety in breeding programs. Moreover, plant breeders demand a simple and efficient diagnosis method, and farther understand the genetic basis of premature senescence in cotton. The objective of this paper was to discuss the quick measurement harmless to plant, and to analyze the genetic effects for leaf premature senescence in upland cotton. The SPAD readings of the fourth leaf from the top were measured at the flowering day and also each five days after flowering in nine cotton varieties (lines). The SPAD readings at 35 days after flowering (DAF) were decreasing in premature  senescence cotton varieties (lines). Therefore, the SPAD difference between 35 DAF and the flowering day was calculated as an indicator of the reduction in chlorophyll content; the greater the rate of reduction, the earlier the senescence, and vice versa. The degree of leaf premature senescence was expressed by the reduction of SPAD or the scale of the green-area in generations (P1, F1, P2, F2, BC1, and BC2) of the 33B×CJ463 cross. Generation mean analyses were conducted to explain the inheritance of leaf premature senescence. The results showed the relative importance of additive effects controlling leaf premature senescence. The estimated minimum number of genes controlling leaf premature senescence was an additive major allele at least with relatively high heritability, suggesting the early selection for late-senescence varieties (lines) was effective in the offspring. The relationships between premature senescence and leaf area per plant were different in the different segregating generations. In a few words, the results of genetic analysis and the relationships between premature senescence and leaf area measured by the reduction of SPAD and the scale of the green-area were relatively consistent.

Key words: Cotton, SPAD reading, Leaf premature senescence, Genetic effects

[1]Diaz C, Purdy S, Christ A, Morot-Gaudry J F, Wingler A, Masclaux-Daubresse C. Characterization of markers to determine the extent and variability of leaf senescence in Arabidopsis. A metabolic profiling approach. Plant Physiol, 2005, 138: 898–908
[2]Sadras V O, Echarte L, Andrade F H. Profiles of leaf senescence during reproductive growth of sunflower and maize. Ann Bot, 2000, 85: 187–195
[3]Brevedan R E, Egli D B. Short periods of water stress during seed filling, leaf senescence, and yield of soybean. Crop Sci, 2003, 43: 2083–2088
[4]Jiang G H, He Y Q, Xu C G, Li X H, Zhang Q. The genetic basis of stay-green in rice analyzed in a population of doubled haploid lines derived from an indica by japonica cross. Theor Appl Genet, 2004, 108: 688–698
[5]Abdelkhalik A F, Shishido R, Nomura K, Ikehashi H. QTL-based analysis of leaf senescence in an indica/japonica hybrid in rice (Oryza sativa L.). Theor Appl Genet, 2005, 110: 1226–1235
[6]Borrell A K, Hammer G L, Douglas A C L. Does maintaining green leaf area in sorghum improve yield under drought? I. Leaf growth and senescence. Crop Sci, 2000, 40: 1026–1037
[7]Thomas H, Howarth C J. Five ways to stay green. J Exp Bot, 2000, 51: 329–337
[8]Yu S-X(喻树迅), Song M-Z(宋美珍), Fan S-L(范术丽), Yuan R-H(原日红). Studies on biochemical assistant breeding technology of earliness without premature senescence of the short-season upland cotton. Sci Agric Sin (中国农业科学), 2005, 38(4): 664–670 (in Chinese with English abstract)
[9]Song M-Z(宋美珍), Yu S-X(喻树迅), Fan S-L(范术丽), Yuan R-H(原日红), Huang Z-M(黄祯茂). Genetic analysis is of biochemical traits in short season upland cotton with no premature senescence. Acta Bot Boreali-Occident Sin (西北植物学报), 2005, 25(5): 903–910 (in Chinese with English abstract)
[10]Perez-Perez J M, Serrano-Cartagena J, Micol J L. Genetic analysis of natural variations in the architecture of Arabidopsis thaliana vegetative leaves. Genetics, 2002, 162: 893–915
[11]Waghmare V N, Rong J K, Rogers C J, Pierce G J, Wendel J F, Paterson A H. Genetic mapping of a cross between Gossypium hirsutum (cotton) and the Hawaiian endemic, Gossypium tomentosum. Theor Appl Genet, 2005, 111: 665–676
[12]Hao J J, Yu S X, Dong Z D, Fan S L, Ma Q X, Song M Z, Yu J W. Quantitative inheritance of leaf morphological traits in upland cotton. J Agric Sci, 2008, 146: 561–569
[13]Cavalli L L. Analysis of Linkage Quantitative Inheritance. In: Reevea E C R, Waddington C H, eds. Quantitative Inheritance, London: HMSO, 1952. pp 135–144
[14]Mather K, Jinks J L. Biometrical Genetics, 3rd edn. London: Chapman and Hall, 1982
[15]Gusmini G, Wehner T C, Donaghy S B. SASQuant: a SAS software program to estimate genetic effects and heritabilities of quantitative traits in populations consisting of 6 related generations. J Heredity, 2007, 98: 345–350
[16]Wright S. Evolution and the Genetics of Populations. Chicago: University of Chicago Press, 1968
[17]Lander R. The minimum number of genes contributing to quantitative variation between and within populations. Genetics, 1981, 99: 541–553
[18]Robinson D C, Comstock R E, Harvery P H. Genetic variances in open pollinated corn. Genetics, 1955, 40: 45–60
[19]Wright P R. Premature senescence of cotton (Gossypium hirsutum L.): predominantly a potassium disorder caused by an imbalance of source and sink. Plant Soil, 1999, 211: 231–239
[20]Yu H(鱼欢), Wu H-S(邬华松), Wang Z-J(王之杰). Evaluation of SPAD and Dualex for in-season corn nitrogen status estimation. Acta Agron Sin (作物学报), 2010, 36(5): 840−847 (in Chinese with English abstract)
[21]Qu W-Q(屈卫群), Wang S-H(王绍华), Chen B-L(陈兵林), Wang Y-H(王友华), Zhou Z-G(周治国). SPAD Value of cotton leaves on main stem and nitrogen diagnosis for cotton growth. Acta Agron Sin (作物学报), 2007, 33(6): 1010–1017 (in Chinese with English abstract)
[22]Yu S X, Song M Z, Fan S L, Wang W, Yuan R H. Biochemical genetics of shot-season cotton cultivars that express early maturity without senescence. J Integr Plant Biol, 2005, 47: 334–342
[23]Dong H, Niu Y, Li W, Zhang D. Effects of cotton rootstock on endogenous cytokinins and abscisic acid in xylem sap and leaves in relation to leaf senescence. J Exp Bot, 2008, 59: 1295–1304
[24]Hallauer A R, Miranda J B. Quantitative genetics in maize breeding. 2nd ed. Ames (IA): Iowa State University Press, 1988
[25]Zalapa J E, Staub J E, Mccreight J D. Generation means analysis of plant architectural traits and fruit yield in melon. Plant Breed, 2006, 125: 482–487
[26]Kerby T A, Buxton D R. Effect of leaf shape and plant population on rate of fruiting position appearance in cotton. Agron J, 1978, 70: 535–538
[27]Pettigrew W T, Heitholt J J, Vaughn K C. Gas exchange differences and comparative anatomy among cotton leaf-type isolines. Crop Sci, 1993, 33: 1295–1299
[1] ZHOU Jing-Yuan, KONG Xiang-Qiang, ZHANG Yan-Jun, LI Xue-Yuan, ZHANG Dong-Mei, DONG He-Zhong. Mechanism and technology of stand establishment improvements through regulating the apical hook formation and hypocotyl growth during seed germination and emergence in cotton [J]. Acta Agronomica Sinica, 2022, 48(5): 1051-1058.
[2] SUN Si-Min, HAN Bei, CHEN Lin, SUN Wei-Nan, ZHANG Xian-Long, YANG Xi-Yan. Root system architecture analysis and genome-wide association study of root system architecture related traits in cotton [J]. Acta Agronomica Sinica, 2022, 48(5): 1081-1090.
[3] YAN Xiao-Yu, GUO Wen-Jun, QIN Du-Lin, WANG Shuang-Lei, NIE Jun-Jun, ZHAO Na, QI Jie, SONG Xian-Liang, MAO Li-Li, SUN Xue-Zhen. Effects of cotton stubble return and subsoiling on dry matter accumulation, nutrient uptake, and yield of cotton in coastal saline-alkali soil [J]. Acta Agronomica Sinica, 2022, 48(5): 1235-1247.
[4] ZHENG Shu-Feng, LIU Xiao-Ling, WANG Wei, XU Dao-Qing, KAN Hua-Chun, CHEN Min, LI Shu-Ying. On the green and light-simplified and mechanized cultivation of cotton in a cotton-based double cropping system [J]. Acta Agronomica Sinica, 2022, 48(3): 541-552.
[5] ZHANG Yan-Bo, WANG Yuan, FENG Gan-Yu, DUAN Hui-Rong, LIU Hai-Ying. QTLs analysis of oil and three main fatty acid contents in cottonseeds [J]. Acta Agronomica Sinica, 2022, 48(2): 380-395.
[6] ZHANG Te, WANG Mi-Feng, ZHAO Qiang. Effects of DPC and nitrogen fertilizer through drip irrigation on growth and yield in cotton [J]. Acta Agronomica Sinica, 2022, 48(2): 396-409.
[7] ER Chen, LIN Tao, XIA Wen, ZHANG Hao, XU Gao-Yu, TANG Qiu-Xiang. Coupling effects of irrigation and nitrogen levels on yield, water distribution and nitrate nitrogen residue of machine-harvested cotton [J]. Acta Agronomica Sinica, 2022, 48(2): 497-510.
[8] ZHAO Wen-Qing, XU Wen-Zheng, YANG Liu-Yan, LIU Yu, ZHOU Zhi-Guo, WANG You-Hua. Different response of cotton leaves to heat stress is closely related to the night starch degradation [J]. Acta Agronomica Sinica, 2021, 47(9): 1680-1689.
[9] YUE Dan-Dan, HAN Bei, Abid Ullah, ZHANG Xian-Long, YANG Xi-Yan. Fungi diversity analysis of rhizosphere under drought conditions in cotton [J]. Acta Agronomica Sinica, 2021, 47(9): 1806-1815.
[10] ZENG Zi-Jun, ZENG Yu, YAN Lei, CHENG Jin, JIANG Cun-Cang. Effects of boron deficiency/toxicity on the growth and proline metabolism of cotton seedlings [J]. Acta Agronomica Sinica, 2021, 47(8): 1616-1623.
[11] GAO Lu, XU Wen-Liang. GhP4H2 encoding a prolyl-4-hydroxylase is involved in regulating cotton fiber development [J]. Acta Agronomica Sinica, 2021, 47(7): 1239-1247.
[12] MA Huan-Huan, FANG Qi-Di, DING Yuan-Hao, CHI Hua-Bin, ZHANG Xian-Long, MIN Ling. GhMADS7 positively regulates petal development in cotton [J]. Acta Agronomica Sinica, 2021, 47(5): 814-826.
[13] XU Nai-Yin, ZHAO Su-Qin, ZHANG Fang, FU Xiao-Qiong, YANG Xiao-Ni, QIAO Yin-Tao, SUN Shi-Xian. Retrospective evaluation of cotton varieties nationally registered for the Northwest Inland cotton growing regions based on GYT biplot analysis [J]. Acta Agronomica Sinica, 2021, 47(4): 660-671.
[14] ZHOU Guan-Tong, LEI Jian-Feng, DAI Pei-Hong, LIU Chao, LI Yue, LIU Xiao-Dong. Efficient screening system of effective sgRNA for cotton CRISPR/Cas9 gene editing [J]. Acta Agronomica Sinica, 2021, 47(3): 427-437.
[15] HAN Bei, WANG Xu-Wen, LI Bao-Qi, YU Yu, TIAN Qin, YANG Xi-Yan. Association analysis of drought tolerance traits of upland cotton accessions (Gossypium hirsutum L.) [J]. Acta Agronomica Sinica, 2021, 47(3): 438-450.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Add: No. 80 Xueyuan South Rd, Beijing 100081, P. R. China E-mail: zwxb301@caas.cn
Supported by Beijing Magtech Co.Ltd