Accurate simulation of plant growth depends not only on plant parameters, but also on soil parameters. Although there is uncertainty in measured soil parameters and root distributions, their eff ects on simulated plant growth have been much less studied. Th is study evaluates the simulated responses of six crops, wheat (Triticum aestivum L.), maize (Zea mays L.), barley (Hordeum vulgare L.), soybean (Glycine max L. Merr.), peanut (Arachis hypogaea L.), and chickpea (Cicer arietinum L.), under various water and N management to diff erent methods of estimating soil hydraulic properties and soil root growth factor (SRGF) in root zone water quality model (RZWQM2) that contains the decision support system for agrotechnology transfer (DSSAT) Version 4.0 plant growth models. Th e two methods of obtaining the soil water retention curve (SWRC) in RZWQM2 were based on (i) known soil water contents at both 33 and 1500 kPa suctions, or (ii) soil water content at 33 kPa only. Th e two methods of estimating saturated hydraulic conductivity (K sat ) were (i) soil texture class based average K sat or (ii) K sat calculated from eff ective porosity (diff erence between soil water contents at saturation and at 33 kPa). For the six crops, simulation results showed that the soil water balance was aff ected more by K sat than by SWRC, whereas the simulated crop growth was aff ected by both K sat and SWRC. Small variations in the SRGF did not aff ect soil and crop simulations, and SRGF could be estimated with a simple exponential equation.
Water is generally the limiting factor in U.S. Great Plains wheat (Triticum aestivum L.) production. With increasing demands for limited water, improving the efficacy of irrigation is critical. One technique is to irrigate during responsive stages of crop development, but few studies have examined this approach. This 2‐yr study on a Nunn clay loam soil (fine, montmorillonitic, mesic Aridic Argiustoll) was designed to examine the effects of irrigation, based on stage of crop development, on winter wheat yield, yield components (on a plant basis), and specific culm responses. In the first year, the treatments were control (dryland), and irrigation at late jointing. In the second year, the treatments were dryland, irrigation at late jointing, irrigation at anthesis, and irrigation at both late jointing and anthesis. Irrigation at late jointing or anthesis significantly increased grain yield and the most important yield component (spikes per plant), as well as spikelets per plant, number of kernels per plant, and kernel weight per plant. The increased spikes per plant in the irrigation treatments, particularly with late‐jointing irrigation, was due to reduced tiller abortion. Increased yield was primarily due to the contribution of more secondary tillers (T10, T11, T20, T21, T30, and T31) that produced spikes. The contribution of main stems to the total yield decreased from 92% to at most 86% with irrigation, although the dry weight of main‐stem spikes increased with irrigation. The contribution to total yield of the main yield‐producing tillers, Tl and T2, decreased from 20 to 15% and 19 to 15%, respectively, with irrigation. As with main‐stem spikes, irrigation also increased T1 and T2 spike dry weight. Therefore, the production of secondary spikes due to irrigation treatments was not at the expense of main stem or primary tiller spikes. If only one irrigation can be applied, irrigation at late jointing is recommended for central Great Plains conditions, due to its greater effect on tiller survival. This implies that developmental and physiological processes at late jointing are critical in determining final grain yield, and water stress should be avoided at this growth stage.
A modeling approach that assesses impacts of alternative management decisions prior to field implementation would reduce decision-making risk for rangeland and livestock production system managers. However, the accuracy and functionality of models should be verified before they are used as decision-making tools. The goal of this study was to evaluate the functionality of the Great Plains Framework for Agricultural Resource Management (GPFARM) model in simulating forage and cow-calf production in the central Great Plains. The forage production module was tested in shortgrass prairie using April-October monthly biomass values from 2000 through 2002 for warm-season grasses (WSG), cool-season grasses (CSG), shrubs, and forbs. The forage module displayed excellent (99% explained variance) agreement in the 2001 calibration year in tracking growth and senescence trends of WSG and CSG, which constitute the vast majority of the aboveground biomass. Less agreement (35%-39% explained variance) was observed for shrubs and forbs. The model-explained variances of biomass in 2000 and 2002 (verification years) were 80% for WSG, 67% for CSG, 78% for shrubs, and 82% for forbs. Further development is needed to improve predicted plant response to environmental stresses. The cow-calf production module was tested in northern mixed-grass prairie using June-November monthly average cow and calf weights from 1996 through 2001 for March-calving, moderately stocked Hereford pairs. Overall, GPFARM performed well and tracked cow (81% explained variance) and calf (94% explained variance) pre-and postweaning weights. The GPFARM model has functional utility for simulating forage and cow-calf production with satisfactory accuracy at semiarid-temperate sites, such as southeastern Wyoming and northeastern Colorado. Continued development will focus on improving plant response to environmental stresses and testing the model's functionality as a decision support tool for strategic and tactical ranch management. Resumen Una metodología de modelaje que evalú e los impactos de decisiones alternativas de manejo antes de su implementació n en campo reduciría el riesgo de la toma de decisió n para los manejadores del sistema de pastizal y producció n de ganado. Sin embargo, la certeza y funcionalidad de los modelos debe ser verificadas antes de que ellos sean usados como herramientas de toma de decisiones. La meta de este estudio fue evaluar la funcionalidad del modelo ''Marco de las Grandes Planicies para el Manejo de los Recursos Agrícolas''(GPFARM) para simular la producció n de forraje y vaca-becerro en las Grandes Planicies del Centro. El mó dulo de producció n de forraje fue probado en una pradera de zacates cortos usando valores mensuales de Abril a Octubre del 2000 al 2002 de biomasa de zacates de estació n caliente (WSG), zacates de estació n fría (CSG), arbustos y hierbas. En el añ o de calibració n de 2001, el modulo de forraje mostró una excelente concordancia (explicó 99% de la varianza) en el monitoreo de la tendencia de crecimiento y senesce...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.