Simulation of shoot vegetative development and growth of unstressed winter wheat

McMaster, Gregory S.; Klepper, Betty; Rickman, R. B.; Wilhelm, Wallace; Willis, W. O.

doi:10.1016/0304-3800(91)90156-u

Cited by 57 publications

(41 citation statements)

References 28 publications

(34 reference statements)

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“…Recent works on germination and epicotile extension [78, 81, 183 1 now make it possible to distinguish two phases in the emergence. This is the case in the SHOOTGRO mode1 of McMaster et al [104], in its derivatives (MODWTH3 of Rickman et al [131]) and in STICS. Such an approach allows the simulated duration of emergence to Vary with the three factors temperature, water status of the soi1 and sowing depth.…”

Section: Discussionmentioning

confidence: 98%

STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn

et al. 1998

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-STICS (Simulateur mulTJdiscplinaire pour les Cultures Standard) is a crop model constructed as a simulation tool capable of working under agricultural conditions. Outputs comprise the production (amount and quality) and the environment. Inputs take into account the climate, the soi1 and the cropping system. STICS is presented as a model exhibiting the following qualities: robustness, an easy access to inputs and an uncomplicated f~~t u r e evolution thanks to a modular (easy adaptation to various types of plant) nature and generic. However, STICS is not an entirely new model since most parts use classic formalisms or stem from existing models. The main simulated processes are the growth, the development of the crop and the water and nitrogenous balance of the soil-crop system. The seven modules of STICSdevelopment, shoot growth, yield components, root growth, water balance, thermal environment and nitrogen balanceare presented in tum with a discussion about the theoretical choices in comparison to other models. These choices should render the model capable of exhibiting the announced qualities in classic environmental contexts. However, because some processes (e.g. ammoniac volatilization, clrought resistance, etc.) are not taken into account, the use of STICS is presently limited to several cropping systems. (

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Section: Discussionmentioning

confidence: 98%

STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn

et al. 1998

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“…Until the advent of molecular markers (Ellis et al, 2002), cultivars could be grouped as being gibberellic acid sensitive or insensitive, but most cultivars were grouped into one of several relative height classes. For example in the SHOOTGRO model (McMaster et al, 1991;Wilhelm et al, 1993;Zalud et al, 2003), a wheat cultivar was considered as tall if its height was greater than 1.3 m, medium tall if its height was 1.1-1.3 m, semidwarf if its height was 0.95-1.1 m, and dwarf if its height was less than 0.95 m tall. These measurements are for wheat grown in optimal height environments, and reductions in height under stressed conditions are treated the same for all height classes.…”

Section: Plant Height Genesmentioning

confidence: 99%

Putting genes into genetic coefficients

Baenziger

McMaster²,

Wilhelm³

et al. 2004

Field Crops Research

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Plant parameters are critical inputs in crop simulation models and allow a general set of algorithms to represent features of specific cultivars. A subset of plant parameters is often referred to as ''genetic coefficients''. However, these genetic coefficients are developed from phenotypic observations, usually have a weak genetic basis, and are at best ''genotypic'' coefficients because they consider the genotype from a very integrative perspective and likely include some impact of environment on the trait or characteristic described. With increased understanding of crop genomes, we believe models can be improved by incorporating genetic coefficients that accurately describe the action of specific genes (within the genome) and therefore better represent the association between gene function and plant phenotype in simulation models. As an example, we discuss how knowledge of height genes in wheat (Triticum aestivum L.) cultivars, along with stronger genetic and environmental response algorithms, could substitute for the phenotypic parameter ''height class'' in the model SHOOTGRO. We also demonstrate how models containing responses based on known genetic variation can be used to identify traits to incorporate into cultivars better adapted to future climate scenarios. It remains for the geneticist, plant breeder, physiologist and modeler to cooperate and communicate with each other so that genetic information and responses with the genotype and environment and their interaction can be described in models and used to develop cultivars better able to exploit future climatic conditions. #

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“…Recently we developed a model (SHOOTGRO 1.0;McMaster et al, 1991) which systematically combined current knowledge of above-ground vegetative development and growth of winter wheat in the absence of environmental stress. SHOOTGRO 1.0 simulates seedling emergence and appearance of tillers, leaves and internodes, based on the accumulation of thermal time [growing degree-days (GDD)], for several cohorts of plants (cohort groupings based on time of seedling emergence).…”

Section: Introductionmentioning

confidence: 99%

“…1). SHOOT-GRO 2.0 modifies and extends SHOOTGRO 1.0 (McMaster et al, 1991). Most modifications relate to the addition of soil N and water budget routines and the addition of response functions for crop development and growth to availability of N and water resources.…”

Section: Introductionmentioning

confidence: 99%

Above-ground vegetative development and growth of winter wheat as influenced by nitrogen and water availability

Wilhelm

McMaster

Rickman

et al. 1993

Ecological Modelling

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Assessing the influence of nitrogen and water availability on development and growth of individual organs of winter wheat (Triticum aestivum L.) is critical in evaluating the response of wheat to environmental conditions. We constructed a simulation model (SHOOTGRO 2.0) of shoot vegetative development and growth from planting to early boot by adding nitrogen and water balances and response functions for seedling emergence, tiller and leaf appearance, leaf and internode growth, and leaf and tiller senescence to the existing wheat development and growth model, SHOOTGRO 1.0. Model inputs include daily maximum and minimum air temperature, rainfall, daily photosynthetically active radiation, soil characteristics necessary to compute soil N and water balances, and several factors describing the cultivar and soil conditions at planting. The model provides information on development and growth characteristics of up to six cohorts of plants within the canopy (cohort groupings are based on time of emergence). The cohort structure allows SHOOTGRO 2.0 to provide output on the frequency of occurrence of plants with specific features (tillers and leaves) within the canopy. The model was constructed so that only water availability limited seedling emergence. Resource availability (nitrogen and water) does not influence time of leaf appearance. Leaf and internode growth, and leaf and tiller senescence processes are limited by the interaction of N and water availability. interaction of N, radiation and water availability. Predicted and observed dates of emergence and appearance of the first tiller had correlation coefficients of 0.98 and 0.93, respectively. However, these events were, on average, predicted 3.2 and 5.2 days later than observed. SHOOTGRO 2.0 generally under-predicted the number of culms per unit land area, partially because the simulation is limited to a maximum of 16 culms/plant. Model output shows that the simulation is sensitive to N and water inputs. The model provides a tool for predicting vegetative development and growth of the winter wheat with individual culms identified and followed from emergence through boot. SHOOTGRO 2.0 can be used in evaluating alternative crop management strategies.

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Simulation of shoot vegetative development and growth of unstressed winter wheat

Cited by 57 publications

References 28 publications

STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn

STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn

Putting genes into genetic coefficients

Above-ground vegetative development and growth of winter wheat as influenced by nitrogen and water availability

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