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

Abstract

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.

Growing degree-days: one equation, two interpretations

“…If we assume a phyllochron, or rate of leaf appearance, of 105 GDD leafp McMaster et al, 1992a), then a difference of about 2.4 leaves would be predicted based on the difference between methods. In simulation models such as MODWht (Rickman et al, 1995) and SHOOTGRO (McMaster et al, 1992a;Wilhelm et al, 1993), or conceptual models of development (e.g., Klepper et al, 19841, where phenological development is closely integrated using the phyllochron, errors of 2.4 leaves are significant in predicting the timing of events, canopy development, and other processes.…”

“…The GDD approach is often used in crop models (e.g., Baker and Landivar, 199 1;Kiniry and Bonhomme, 1991;Rickman et al, 1995;Weir et al, 1984;Wilhelm et al, 1993;Williams et a]., 1989). Both methods of calculating GDD are used in crop models, and to be certain of the method used, one must examine the code because documentation is usually not clear.…”

Irrigation and Culm Contribution to Yield and Yield Components of Winter Wheat

“…Kernel growth can be affected in various ways by irrigation. For example, irrigation should increase leaf longevity, thus prolonging leaf area duration into grain filling (Wilhelm et al, 1993), increasing the duration and rate of grain filling (Frank et al, 1987;McMaster and Smika, 1988;Singh et al, 1984;Sionit et al, 1980), and increasing peduncle elongation and storage of photoassimilates in the internode tissue (Ape1 and Natr, 1976; Rawson and Evans, 1971). The 1988 results clearly show that irrigation at anthesis increased kernel weight, but an effect on grain set was less evident.…”

Putting genes into genetic coefficients

“…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.…”