Welcome to Acta Agronomica Sinica,

Acta Agron Sin ›› 2009, Vol. 35 ›› Issue (11): 2101-2106.doi: 10.3724/SP.J.1006.2009.02101


Morphogenesis Model with Relation to Light and Temperature Condition for Above-Ground Organs in Cotton

GUO Yin-Qiao1,2,ZHAO Chuan-De4,ZHU Yan1,LI Cun-Dong2,SUN Hong-Chun2,CAO Wei-Xing1*   

  1. 1Jiangsu Key Laboratory for Information Agricultural,College of Agronomy,Nanjing Agricultural University,Nanjing 210095,China;2College of Agronomy,Agricultural University of Hebei,Baoding 071001,China;3Advanced Technology & Materials Co.,Ltd,Beijing 100081,China
  • Received:2009-05-12 Revised:2009-07-21 Online:2009-11-12 Published:2009-09-10
  • Contact: CAO Wei-Xing,E-mail: caow@njau.edu.cn; Tel: 025-84396565


Due to their complexity in the morphological character of multi-branch cotton, it is hard to simulate the morphogenesis of cotton. The objective of the study was to construct a simulation model with morphological characters based on GDD (growing degree day) and Logistic equation. An experiment for model establishment was conducted using two cultivars (Meimian 33B and Jifeng 908) with three repetitions. The length and width of leaf, the length of petiole, the length and diameter of internode, the height and diameter of boll were determined from three-leaf stage to the stationary length of leaf on main stem. The result was as follows: (1) GDD and IGDD were quantitied through integrating the quantitative connection of every organ of cotton and the relationship of morphological indices to the effective cumulative temperature, the growing degree day and initial growing degree day of every organ in cotton were quantitied. (2) The major influencing factors of temperature and sunlight were quantitied. The temperature and sunshine hours effect factor model was constructed using mathematical modeling method, which can be explained and reflected better by effect factor in practice. (3) According to the pot experiment data in the field of Hebei Agriculture University in 2006, through analyzing the effects of temperature and sunshine hours on morphogenesis formation in cotton, potential length and width of different cotton organs were quantitied. (4) By quantifying relationship of morphogenesis formation to temperature and sunshine hours, an ecological model of cotton morphogenesis was constructed with the rule of “the same similar”. The model is based on GDD and Logistic equation, which can predict the morphologic indices such as the length and width of leaf, the length of petiole, the length and diameter of internode, the height and diameter of boll. The model was validated with independent dataset from experiment in Nanjing in 2006, the results showed that the RMSEs between simulated and observed value for length and width of leaf on main stem, length of petiole on main stem, length and width of internode on main stem, length and width of leaf on sympodial stem, length of petiole on sympodial stem, length and width of internodes on sympodial stem, boll height and diameter was 0.48, 0.65, 0.53, 0.09 0.02, 0.55, 0.28, 0.23, 0.14, 0.17, 0.20, and 0.11 cm, respectively, which indicated that the present model has a good performance in predicting the dynamics of each organ size in cotton growth process.

Key words: Cotton, Morphogenesis formation, Sunlight and temperature ecological model

[1]Room P M, Hanan J S. Virtual cotton: A new tool for research, management and training. Proceedings of the world Cotton Research Conference-1. Challenging the Future. Brisbane, Melbource: CSIRO Australia, 1995. pp 40-44
[2]Marcelis L F M, Heuvelink E, Goudriaan J. Modelling biomass production and yield of horticultural crops: A review. Sci Hort, 1998, 74: 83-111
[3]Fournier C, Andrieu B A. 3D architectural and process-based model of maize development. Ann Bot, 1998, 81: 233-250
[4]Song Y-H(宋有洪), Guo Y(郭焱), Li B-G(李保国), de Reffye P. Virtual maize model II plant morphological constructing based on organ biomass accumulation. Acta Ecol Sin (生态学报), 2003, 23(12): 2579-2586 (in Chinese with English abstract)
[5] de Reffye P, Blaise F, Chemouny S. Calibration of hydraulic growth model on the architecture of cotton plants. Agronomie, 1999, 19: 265-280
[6] Room P M, Hanan J S, Prusinkiewicz P. Virtual plants: New perspectives for pcologists, pathologists and pgricultural scientists. Trends Plant Sci, 1996, 1: 33-38
[7] Hanan J S, Hearn A B. Linking physiological and architectural models of cotton. Agric Syst, 2003, 75: 47-77
[8] Yang J(杨娟), Zhao M(赵明), Pan X-B(潘学标). Visualization of cotton growth based on NURBS and VC++ 6.0. Trans CSAE (农业工程学报), 2006, 22(10): 159-162 (in Chinese with English abstract)
[9] Zhang L-Z(张立桢). A Process-Based Simulation Model for Cotton Growth and Development. PhD Dissertation of Nanjing Agricultural University, 2003 (in Chinese with English abstract)
[10] Zhang W-P(张吴平), Li B-G(李保国). Three-dimensional model simulating development and growth of cotton root system. J Syst Simulat (系统仿真学报), 2006, 18(z1): 283-286 (in Chinese with English abstract)
[11] Buch-Sorlin G H. L-System Model of the Vegetative Growth of Winter Barley. In: Polani D, Kim J, Martinetz T, eds. Fifth German Workshop on Artificial Life. Berlin: Akademische Verlagsgesellschaft Aka Gmbh, 2000. pp 53-64
[12] Zhang Z-G(展志刚), Wang Y-M(王一鸣), de Reffye P. Morphological architecture-based growth model of winter wheat. Trans CSAE (农业工程学报), 2001, 17(5): 6-11 (in Chinese with English abstract)
[13] Chen G-Q(陈国庆). Study on morphogenesis model and virtual system of wheat. MS Dissertation of Shangdong Agricultural University, 2004 (in Chinese with English abstract)
[14] Tan Z-H(谭子辉), Zhu Y(朱艳), Yao X(姚霞), Tian Y-C(田永超), Liu X-J(刘小军), Cao W-X(曹卫星). Modeling spike growth dynamics in winter wheat. J Triticeae Crops (麦类作物学报), 2006, 26(4): 93-97 (in Chinese with English abstract)
[15] Shi C-L(石春林), Jin Z-Q(金之庆), Cao W-X(曹卫星). An elementary study on virtual growth of rice plant. Jiangsu J Agric Sci (江苏农业学报), 2006, 22(2): 105-108 (in Chinese with English abstract)
[16] Chang L-Y(常丽英), Gu D-X(顾东祥), Zhang W-Y(张文宇), Yang J(杨杰), Cao W-X(曹卫星), Zhu Y(朱艳). A simulation model of leaf elongation process in rice. Acta Agron Sin (作物学报), 2008, 34(2): 311-317 (in Chinese with English abstract)
[17] Chang L-Y(常丽英), Tang L(汤亮), Gu D-X(顾东祥), Yang J(杨杰), Cao W-X(曹卫星), Zhu Y(朱艳). A process-based simulation model of leaf sheath and internode elongation dynamics in rice. J Nanjing Agric Univ (南京农业大学学报), 2008, 31(3): 19-25 (in Chinese with English abstract)
[18] Dong Q-X(董乔雪), Wang Y-M(王一鸣), Barczi J F, He C-X(贺超兴). Estimation method for model parameters of tomato morphological architecture by multi-targets plant fitting. Trans CSAE (农业工程学报), 2007, 15(1): 122-126 (in Chinese with English abstract)
[19] Zhang G-J(张光鉴). Theory of Similarity (相似论). Jiangsu: Jiangsu Science and Technology Press, 1992 (in Chinese)
[20] Institute of Cotton of The Chinese Academy of Agricultural Sciences (中国农业科学院棉花研究所主编). Cotton Cultivation in China (中国棉花栽培学). Shanghai: Shanghai Science and Technology Press, 1983 (in Chinese)

Yu Z-W(于振文). Crop Cultivation (for Species) (作物栽培学各论). Beijing: China Agriculture Press, 2003 (in Chinese)
[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.
Full text



No Suggested Reading articles found!