Optimal growth model of <i>Populus simonii</i> seedling combination based on Logistic and Gompertz models

Ge Huishuo; Song Yuepeng; Su Xuehui; Zhang Deqiang; Zhang Xiaoyu

doi:10.12171/j.1000-1522.20190296

Journal of Beijing Forestry University > 2020 > 42(5): 59-70. > DOI: 10.12171/j.1000-1522.20190296

Ge Huishuo, Song Yuepeng, Su Xuehui, Zhang Deqiang, Zhang Xiaoyu. Optimal growth model of Populus simonii seedling combination based on Logistic and Gompertz models[J]. Journal of Beijing Forestry University, 2020, 42(5): 59-70. DOI: 10.12171/j.1000-1522.20190296

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Optimal growth model of Populus simonii seedling combination based on Logistic and Gompertz models

1.
School of Science, Beijing Forestry University, Beijing 100083, China
2.
School of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
3.
Jiaozuo Agricultural and Forestry Research Institute, Jiaozuo 454001, Henan, China

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Received Date: July 14, 2019
Revised Date: December 29, 2019
Available Online: May 10, 2020
Published Date: June 30, 2020

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Abstract

Abstract

Objective Through the research on the growth regularity and growth model of Populus simonii seedlings, it could provide reference for its growth prediction and scientific seedling raising.
Method Taking P. simonii seedlings in 16 regions of China as the research object, basic data were obtained by means of experimental field investigation and measurement, and the growth rules of plant height were analyzed from the time dimension. We used existed growth equations to select the optimal basic growth model according to the model goodness of fit and evaluation indexes, and constructed optimal growth models suitable for seedling growth in different regions with the basis of the optimal model.
Result (1) The comprehensive optimal basic models of sample plant height in different regions were Logistic equation and Gompertz equation, respectively. The Logistic model’s R² and prediction accuracy were above 0.847 9 and 92.23%, and the Gompertz model ’s R² and prediction accuracy were above 0.891 5 and 92.60%, respectively. (2) On this basis, the combinative optimization model constructed showed a larger F value (α = 0.01) and a higher prediction accuracy for the growth of P. simonii seedlings in 7 regions of China, among which the prediction accuracy of samples in Menyuan County increased by 0.90%, and the sample prediction accuracy of samples in Fuping County and Dulan County increased by 0.37% and 0.34%, respectively. (3) Through combinatorial optimization of model parameters, it was found that samples from 16 regions reached the maximum growth rate in the 17.73th day on average.
Conclusion The growth of P. simonii seedlings was affected by geographical location and climate and other conditions. Establishing models suitable for the growth of seedlings of P. simonii in different regions was conducive to improve the accuracy and applicability of the models, which could not only provide a scientific basis for seedling research, but also lay a foundation for further genome-wide association analysis.
- Populus simonii,
- seedling period,
- combinatorial optimization model,
- growth rhythm,
- significance test

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[1]	Chen J H, Song Y P, Zhang H, et al. Genome-wide analysis of gene expression in response to drought stress in Populus simonii[J]. Plant Molecular Biology Reporter, 2013, 31(4): 946−962. doi: 10.1007/s11105-013-0563-6
[2]	Wei Z Z, Du Q Z, Zhang J F, et al. Genetic diversity and population structure in Chinese indigenous poplar (Populus simonii) populations using microsatellite markers[J]. Plant Molecular Biology Reporter, 2013, 31(3): 620−632. doi: 10.1007/s11105-012-0527-2
[3]	Luquez V, Hall D, Albrectsen B R, et al. Natural phenological variation in aspen (Populus tremula): the SwAsp collection[J]. Tree Genetics & Genomes, 2008, 4(2): 279−292.
[4]	Wei Z Z, Zhao X, Pan W, et al. Phenotypic variation among five provenances of Populus simonii in northern China[J]. Forestry Studies in China, 2011, 13(2): 97−103. doi: 10.1007/s11632-011-0203-x
[5]	Robertson T B. The chemical basis of growth and senescence[J]. Canadian Medical Association Journal, 1924, 14(7): 267−270.
[6]	Maruyama K, Akbar M K, Turk C M. Growth pattern and carcase development in male ducks selected for growth rate[J]. British Poultry Science, 1999, 40(2): 233−239. doi: 10.1080/00071669987656
[7]	Richards F J. A flexible growth fection for empirical use[J]. Journal of Experimental Botany, 1959, 10(2): 290−300. doi: 10.1093/jxb/10.2.290
[8]	Laird A K, Tyler S A, Barton A D. Dynamic of normal growth[J]. Growth, 1965, 29(3): 233−248.
[9]	Paine C E T, Marthews T R, Vogt D R, et al. How to fit nonlinear plant growth models and calculate growth rates: an update for ecologists[J]. Methods in Ecology and Evolution, 2012, 3(2): 245−256. doi: 10.1111/j.2041-210X.2011.00155.x
[10]	林丽平, 徐期瑚, 罗勇, 等. 广东省樟树立木生长规律和生长模型研究[J]. 中南林业科技大学学报, 2018, 38(6):23−29. Lin L P, Xu Q H, Luo Y, et al. Study on the growth laws and models of Cinnamomum camphora in Guangdong Province[J]. Journal of Central South University of Forestry & Technology, 2018, 38(6): 23−29.
[11]	张连翔, 王洪江, 林阳, 等. 小叶杨胸径和树高生长进程的连续性和阶段性定量研究[J]. 河北林果研究, 2010, 25(3):228−231. doi: 10.3969/j.issn.1007-4961.2010.03.002 Zhang L X, Wang H J, Lin Y, et al. A quantitative research on DBH(diameter breast height) and height growth process of Populus simonii Carr.[J]. Hebei Journal of Forestry and Orchard Research, 2010, 25(3): 228−231. doi: 10.3969/j.issn.1007-4961.2010.03.002
[12]	姜鹏, 崔丽红, 秦召文, 等. 小黑杨胸径和树高的生长动态[J]. 西北林学院报, 2013, 28(6):129−133. Jiang P, Cui L H, Qin Z W, et al. Tree height and DBH growth models of Populus simonii × P. nigra[J]. Journal of Northwest Forestry University, 2013, 28(6): 129−133.
[13]	于志民, 康文娟, 涂淑萍. 基于Logistic、Gompertz模型的圆齿野鸦椿幼苗生长模拟与分析[J]. 江西农大学学报, 2017, 39(6):1187−1195. Yu Z M, Kang W J, Tu S P. Simulation of growth curve based on nonlinear models of Logistic and Gompertz for Euscaphis konishii seedling[J]. Acta Agriculturae Universitatis Jiangxiensis, 2017, 39(6): 1187−1195.
[14]	杨柳, 陈艳萍. 一种新的Levenberg-Marquardt算法的收敛性[J]. 计算数学, 2005, 27(1):55−62. doi: 10.3321/j.issn:0254-7791.2005.01.006 Yang L, Chen Y P. On the convergence of a new Levenberg-Marquardt method[J]. Mathematic Numerica Sinica, 2005, 27(1): 55−62. doi: 10.3321/j.issn:0254-7791.2005.01.006
[15]	Yip C Y, Ng K H, Lim H E. The relative predictive ability of forecast weight averaging and model averaging procedure[J]. Economic Computation and Economic Cybernetics Studies and Research, 2012, 6(2): 213−230.

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Optimal growth model of Populus simonii seedling combination based on Logistic and Gompertz models

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