August  2004, 4(3): 777-788. doi: 10.3934/dcdsb.2004.4.777

The mathematical method of studying the reproduction structure of weeds and its application to Bromus sterilis


Danish Institute of Agricultural Sciences, Department of Agricultural Engineering, Research Centre BygholmPostboks 536, 8700 Horsens, Denmark


Department of Crop Protection Research Center, Flakkebjerg, DK-4200 Slagelse, Denmark


Key Laboratory for ecosystem models and their application, The State Ethnic Affairs Commission of PRC, The Second North-West University for Nationalities, Yinchuan, 750021, China, China

Received  September 2002 Revised  December 2003 Published  May 2004

This article discusses the structure of weed reproduction incorporating the application of a mathematical model. This mathematical methodology enables the construction, testing and application of distribution models for the analysis of the structure of weed reproduction and weed ecology. The mathematical model was applied, at the individual level, to the weed species, Bromus sterilis. The application of this method, to the weed under competition, resulted in an analysis of the overall reproduction structure of the weed which follows approximately Gaussian distribution patterns and an analysis of the shoots in the weed plant which follow approximately Sigmoid distribution patterns. It was also discovered that the application of the mathematical distribution models, when applied under specific conditions could, effectively estimate the seed production and total number of shoots in a weed plant. On the average, a weed plant has 3 shoots, with each shoot measuring 90cm in height and being composed of 21 spikelets. Besides the estimations of the total shoots and seed production within the experimental field, one may also apply these mathematical distribution models to estimate the germination rate of the species within the experimental field in following years.
Citation: Svend Christensen, Preben Klarskov Hansen, Guozheng Qi, Jihuai Wang. The mathematical method of studying the reproduction structure of weeds and its application to Bromus sterilis. Discrete & Continuous Dynamical Systems - B, 2004, 4 (3) : 777-788. doi: 10.3934/dcdsb.2004.4.777

Benoît Perthame, P. E. Souganidis. Front propagation for a jump process model arising in spacial ecology. Discrete & Continuous Dynamical Systems - A, 2005, 13 (5) : 1235-1246. doi: 10.3934/dcds.2005.13.1235


Robert Stephen Cantrell, Chris Cosner, William F. Fagan. The implications of model formulation when transitioning from spatial to landscape ecology. Mathematical Biosciences & Engineering, 2012, 9 (1) : 27-60. doi: 10.3934/mbe.2012.9.27


Kamaldeen Okuneye, Ahmed Abdelrazec, Abba B. Gumel. Mathematical analysis of a weather-driven model for the population ecology of mosquitoes. Mathematical Biosciences & Engineering, 2018, 15 (1) : 57-93. doi: 10.3934/mbe.2018003


Erika Asano, Louis J. Gross, Suzanne Lenhart, Leslie A. Real. Optimal control of vaccine distribution in a rabies metapopulation model. Mathematical Biosciences & Engineering, 2008, 5 (2) : 219-238. doi: 10.3934/mbe.2008.5.219


Bum Il Hong, Nahmwoo Hahm, Sun-Ho Choi. SIR Rumor spreading model with trust rate distribution. Networks & Heterogeneous Media, 2018, 13 (3) : 515-530. doi: 10.3934/nhm.2018023


Pierre Gabriel, Hugo Martin. Steady distribution of the incremental model for bacteria proliferation. Networks & Heterogeneous Media, 2019, 14 (1) : 149-171. doi: 10.3934/nhm.2019008


Arturo Hidalgo, Lourdes Tello. On a climatological energy balance model with continents distribution. Discrete & Continuous Dynamical Systems - A, 2015, 35 (4) : 1503-1519. doi: 10.3934/dcds.2015.35.1503


Fabio Augusto Milner, Ruijun Zhao. A deterministic model of schistosomiasis with spatial structure. Mathematical Biosciences & Engineering, 2008, 5 (3) : 505-522. doi: 10.3934/mbe.2008.5.505


Anne Devys, Thierry Goudon, Pauline Lafitte. A model describing the growth and the size distribution of multiple metastatic tumors. Discrete & Continuous Dynamical Systems - B, 2009, 12 (4) : 731-767. doi: 10.3934/dcdsb.2009.12.731


Yanan Zhao, Yuguo Lin, Daqing Jiang, Xuerong Mao, Yong Li. Stationary distribution of stochastic SIRS epidemic model with standard incidence. Discrete & Continuous Dynamical Systems - B, 2016, 21 (7) : 2363-2378. doi: 10.3934/dcdsb.2016051


Zhilin Kang, Xingyi Li, Zhongfei Li. Mean-CVaR portfolio selection model with ambiguity in distribution and attitude. Journal of Industrial & Management Optimization, 2019  doi: 10.3934/jimo.2019094


Luca Gerardo-Giorda, Pierre Magal, Shigui Ruan, Ousmane Seydi, Glenn Webb. Preface: Population dynamics in epidemiology and ecology. Discrete & Continuous Dynamical Systems - B, 2020, 25 (6) : ⅰ-ⅱ. doi: 10.3934/dcdsb.2020125


Mariantonia Cotronei, Tomas Sauer. Full rank filters and polynomial reproduction. Communications on Pure & Applied Analysis, 2007, 6 (3) : 667-687. doi: 10.3934/cpaa.2007.6.667


Marzia Bisi, Maria Groppi, Giampiero Spiga. Flame structure from a kinetic model for chemical reactions. Kinetic & Related Models, 2010, 3 (1) : 17-34. doi: 10.3934/krm.2010.3.17


Jacek Banasiak, Eddy Kimba Phongi, MirosŁaw Lachowicz. A singularly perturbed SIS model with age structure. Mathematical Biosciences & Engineering, 2013, 10 (3) : 499-521. doi: 10.3934/mbe.2013.10.499


Torsten Lindström. Discrete models and Fisher's maximum principle in ecology. Conference Publications, 2003, 2003 (Special) : 571-579. doi: 10.3934/proc.2003.2003.571


Li Zu, Daqing Jiang, Donal O'Regan. Persistence and stationary distribution of a stochastic predator-prey model under regime switching. Discrete & Continuous Dynamical Systems - A, 2017, 37 (5) : 2881-2897. doi: 10.3934/dcds.2017124


Rong Liu, Feng-Qin Zhang, Yuming Chen. Optimal contraception control for a nonlinear population model with size structure and a separable mortality. Discrete & Continuous Dynamical Systems - B, 2016, 21 (10) : 3603-3618. doi: 10.3934/dcdsb.2016112


B. D. Craven, Sardar M. N. Islam. An optimal financing model: Implications for existence of optimal capital structure. Journal of Industrial & Management Optimization, 2013, 9 (2) : 431-436. doi: 10.3934/jimo.2013.9.431


Michael L. Frankel, Victor Roytburd. Dynamical structure of one-phase model of solid combustion. Conference Publications, 2005, 2005 (Special) : 287-296. doi: 10.3934/proc.2005.2005.287

2019 Impact Factor: 1.27


  • PDF downloads (29)
  • HTML views (0)
  • Cited by (1)

[Back to Top]