A simulation model for the dynamics of rice growth and development: Part II—The competition with weeds for nitrogen and light

Graf, B.; Gutiérrez, A. P.; Rakotobe, O.; Zahner, P.; Delucchi, V.

doi:10.1016/0308-521x(90)90100-5

Cited by 86 publications

(43 citation statements)

References 6 publications

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“…One key study (Deen et al, 2003) compared four of the best known of the interspecies competition versions of these simulation models, ALMANAC (Kiniry et al, 1992;Wallace, 1995Wallace, , 1997Debaeke et al 1997;Kiniry et al, 2005), APSIM (Carberry et al, 1996;McCown et al, 1996;Probert et al, 1998;Robertson et al, 2001;Keating et al, 2003;Grenz et al, 2006), CROPSIM (Chikoye et al, 1996;Hunt and Pararajasingham, 1995;Deen et al, 2001), and INTERCOM (Kropff and Van Laar, 1993;Weaver et al, 1994;Kropff et al, 1984;Lindquist and Kropff, 1996) and concluded that simple competition algorithms are capable of accounting for the majority of the competition response. Other examples include SOYWEED (Wilkerson et al, 1990;Wiles and Wilkerson, 1991), an extension of the crop growth model SOYGRO (Jones et al, 1988), as well as other models of competition in corn/maize (Zea mays L.) (Ball and Shaffer, 1993), barley (Hordeum vulgare L.) (Dunan et al, 1994), rice (Oryza sativa L.) (Graf et al, 1990;Graf and Hill, 1992) and wheat (Triticum aestivum L.) Beyschlag et al, 1990). Over time, these styles of models have continued to develop (e.g.…”

Section: How Has Crop-weed Competition Been Modelled?mentioning

confidence: 99%

Modelling crop-weed competition: Why, what, how and what lies ahead?

Renton

Chauhan

2017

Crop Protection

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Section: How Has Crop-weed Competition Been Modelled?mentioning

confidence: 99%

Modelling crop-weed competition: Why, what, how and what lies ahead?

Renton

Chauhan

2017

Crop Protection

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“…Several models have been used to describe and predict N uptake by two general approaches (e.g., Baldwin et al 1973;ten Berge et al 1994ten Berge et al , 1997Graf et al 1990;Hasegawa and Horie 1996;Jeuffroy et al 2002;Kropff 1993;Lindquist 2001a;Nye and Tinker 1977;Sinclair and Muchow 1995). The first approach comes from solute transport theory, in which nutrient uptake is determined primarily by the predicted solute concentration at the root surface (Baldwin et al 1973;Nye and Tinker 1977).…”

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Comparative Nitrogen Uptake and Distribution in Corn and Velvetleaf (Abutilon theophrasti)

et al. 2007

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Weeds compete with crops for light, soil water, and nutrients. Nitrogen (N) is the primary limiting soil nutrient. Forecasting the effects of N on growth, development, and interplant competition requires accurate prediction of N uptake and distribution within plants. Field studies were conducted in 1999 and 2000 to determine the effects of variable N addition on monoculture corn and velvetleaf N uptake, the relationship between plant N concentration ([N]) and total biomass, the fraction of N partitioned to leaves, and predicted N uptake and leaf N content. Cumulative N uptake of both species was generally greater in 2000 than in 1999 and tended to increase with increasing N addition. Corn and velvetleaf [N] declined with increasing biomass in both years in a predictable manner. The fraction of N partitioned to corn and velvetleaf leaves varied with thermal time from emergence but was not influenced by year, N addition, or weed density. With the use of the [N]–biomass relationship to forecast N demand, cumulative corn N uptake was accurately predicted for three of four treatments in 1999 but was underpredicted in 2000. Velvetleaf N uptake was accurately predicted in all treatments in both years. Leaf N content (NL, g N m−2leaf) was predicted by the fraction of N partitioned to leaves, predicted N uptake, and observed leaf area index for each species. Average deviations between predicted and observed corn NLwere < 88 and 12% of the observed values in 1999 and 2000, respectively. Velvetleaf NLwas less well predicted, with average deviations ranging from 39 to 248% of the observed values. Results of this research indicate that N uptake in corn and velvetleaf was driven primarily by biomass accumulation. Overall, the approaches outlined in this paper provide reasonable predictions of corn and velvetleaf N uptake and distribution in aboveground tissues.

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“…Growth of each species is expressed at the population rather than individual plant level, Le. in kg dry matter ha 1 , and the model runs from either sowing or émergence until crop or weed maturity with a time step of 1 d. The approach used in this model to describe light interception and distribution among the competing species, based on Spitters and Aerts (1983), has been followed in many other models (Graf et al 1990b;Kiniry et al 1992;. The light profile within the canopy is calculated as a function of leaf area index, plant height, the vertical distribution of leaf area, and the light extinction coefficient of each species.…”

Section: Examples Of Simulation Models Of Crop-weed Competitionmentioning

confidence: 99%

“…To date, it has been validated with data from only one site and year (Table 1). Graf et al (1990a) constructed a growth model for irrigated rice {Oryza sativa L) in monoculture, and then expanded it to include compétition with multiple weed species for light and nitrogen (Graf et al 1990b). Their model was parameterized and tested with field experiments involving natural populations of mixed weed species.…”

Section: Examples Of Simulation Models Of Crop-weed Competitionmentioning

confidence: 99%

Simulation of crop-weed competition : Models and their applications

Weaver¹

2005

phyto

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Competition between crops and weeds is a complex phenomenon. Comprehensive, process-oriented simulation models which treat competition in a mechanistic rather than an empirical fashion, can offer insight into relationships among competition, crop and weed density, relative time of emergence, various morphological and physiological traits, and resource levels. They can also be used for prediction as part of a Systems approach to weed management. This paper reviews the features of a number of recent simulation models of crop-weed competition, the species for which they have been parameterized, and their applications. To date, these models have been used primarily to predict crop yield losses due to weed competition. Their ability to simulate weed seed production in response to the environment has not been exploited. The next step is to link simulation models of crop-weed competition to weed population dynamics models, in order to improve our ability to predict the effect of various weed management strategies over time. Advantages and drawbacks of a modeling approach to weed management problems are discussed.

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A simulation model for the dynamics of rice growth and development: Part II—The competition with weeds for nitrogen and light

Cited by 86 publications

References 6 publications

Modelling crop-weed competition: Why, what, how and what lies ahead?

Modelling crop-weed competition: Why, what, how and what lies ahead?

Comparative Nitrogen Uptake and Distribution in Corn and Velvetleaf (Abutilon theophrasti)

Simulation of crop-weed competition : Models and their applications

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