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Mathematical Description of Seedling Emergence of Rice and Echinochloa species as Influenced by Soil burial depth  

Kim Do-Soon (R&D Park, LG Life Sciences Ltd.)
Kwon Yong-Woong (Department of Plant Science, Seoul National University)
Lee Byun-Woo (Department of Plant Science, Seoul National University)
Publication Information
KOREAN JOURNAL OF CROP SCIENCE / v.51, no.4, 2006 , pp. 362-368 More about this Journal
Abstract
A pot experiment was conducted to investigate the effects of soil burial depth on seedling emergences of rice (Oryza sativa) and Echinochloa spp. and to model such effects for mathematical prediction of seedling emergences. When the Gompertz curve was fitted at each soil depth, the parameter C decreased in a logistic form with increasing soil depth, while the parameter M increased in an exponential form and the parameter B appeared to be constant. The Gompertz curve was combined by incorporating the logistic model for the parameter C, the exponential model for the parameter M, and the constant for the parameter B. This combined model well described seedling emergence of rice and Echinochloa species as influenced by soil burial depth and predicted seedling emergence at a given time after sowing and a soil burial depth. Thus, the combined model can be used to simulate seedling emergence of crop sown in different soil depths and weeds present in various soil depths.
Keywords
Echinochloa; emergence; Gompertz curve; modelling; rice (Oryza sativa); soil depth;
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1 Brown, R. F. and P. G. Mayer. 1988. Representing cumulative germination. 2. The use of the Weibull function and other empirically derived functions. Annal. Bot. 61 : 127-138   DOI
2 Gompertz, B. 1825. On the nature of the functions expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philos. Trans., 115 : 513-585   DOI
3 Kim, D. S. 1993. Characterization of emergence and early growth of Echinochloa spp. and rice under the condition of direct-seeding rice culture. MSc thesis, Suwon, Seoul National University
4 King, C. A. and L. R. Oliver. 1994. A model for predicting large crabgrass (Digitaria sanguinalis) emergence as influenced by temperature and water potential. Weed Sci. 42: 561-567
5 Oliver, L. R. 1979. Influence of soybean (Glycine max) planting date on velvetleaf (Abutilon theophrasti) competition. Weed Sci. 27 : 183-188
6 Vleeshouwers, L. M. 1997. Modelling the effect of temperature, soil penetration resistance, burial depth and seed weight on pre-emergence growth of weeds. Annal. Bot. 79 : 553-563   DOI   ScienceOn
7 Kwon, Y. W., B. W. Lee, and D. S. Kim. 1996. Seedling emergence of rice, weedy rice and Echinochloa species sown before wintering and in the early spring. Kor. J. Weed Sci. 16 : 88-89
8 Forcella, F. R. 1993. Seedling emergence model for velvetleaf. Agro. J. 85 : 929-933   DOI   ScienceOn
9 Cussans, G. W., S. Raudonius, P. Brain, and S. Cumberworth. 1996. Effects of depth of seed burial and soil aggregate size on seedling emergence of Alopecurus myosuroides, Galium aparine, Stellaria media and wheat (Triticum aestivum L.). Weed Res. 36 : 133-142   DOI
10 Norris, R. F. 1992. Case history for weed competition/population ecology: barnyardgrass (Echinochloa crus-galli) in sugar beets (Beta vulgaris). Weed Tech. 6 : 220-227   DOI
11 Myers, M. W., W. S. Curran, M. J. VanGessel, D. D. Calvin, D. A. Mortensen, B. A. Majek, H. D. Karsten, and G. W. Roth. 2004. Predicting weed emergence for eight annual in the northeastern United States. Weed Sci. 52 : 913-919   DOI   ScienceOn
12 Ekeleme, F., F. Forcella, D. W. Archer, D. Chikoye, and I. O. Akobundu. 2004. Simulation of shoot emergence pattern of cogograss (Imperata cylindrical) in the humid tropics. Weed Sci. 52 : 961-967   DOI   ScienceOn
13 Forcella, F. R., L. Benech-Arnold, R. Sanchez, and C. M. Ghersa. 2000. Modeling seedling emergence. Field Crops Res. 67: 123-139   DOI   ScienceOn
14 Prostko, E. P., H. I. Wu, and J. M. Chandler. 1998. Modeling seedling johnsongrass (Sorghum halepense) emergence as influenced by temperature and burial depth. Weed Sci. 46: 549-554
15 Holm, L., D. Pucknette, J. Pnacho, and J. Herberger. 1977. The World's Worst Weeds: Distribution and biology. Univ. Hawaii Press, Honolulu, USA
16 Lapp, M. S. and W. P. Skoropad. 1976. A mathematical model of conodial germination and appressorial formation for Colletotrichum graminicola. Can. J. Bot. 54 : 2239-2242   DOI
17 Genstat 5 Committee. 1997. Genstat 5 Release 4.1: Reference Manual Supplement to Genstat 5 Committee (1993) Genstat 5 Reference Manual Release 3. Oxford, UK: Numerical Algorithms Group
18 Kropff, M. J. 1988. Modelling the effects of weeds on crop production. Weed Res. 28 : 465-471   DOI
19 Kwon, Y. W., D. S. Kim, and S. W. Park. 1996. Effect of soil temperature on the emergence-speed of rice and bamyardgrasses under dry direct-seeding condition. Kor. J. Weed Sci. 16 : 81-87
20 Weaver, S. E., C. S. Tan, and P. Brain. 1988. Effect of temperature and soil moisture on time of emergence of tomatoes and four weed species. Can. J. Plant Sci. 68 : 877-886   DOI
21 Prostko, E. P., H. I. Wu, J. M. Chandler, and S. A. Senseman. 1997. Modeling weed emergence as influenced by burial depth using the Fermi-Dirac distribution function. Weed Sci. 45 : 242-248