|Anapalli, Saseendran - COLO. STATE UNIVERSITY|
|Lyon, Drew - UNIV. OF NEBRASKA|
|Felter, D - JOHN DEERE|
|Baltensperger, D - TEXAS A&M UNIVERSITY|
|Hoogenboom, G - UNIV. OF GEORGIA|
Submitted to: Field Crops Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 10, 2009
Publication Date: June 1, 2009
Citation: Anapalli, S.S., Nielsen, D.C., Lyon, D.J., Ma, L., Felter, D.G., Baltensperger, D.D., Hoogenboom, G., Ahuja, L.R. 2009. Modeling Responses of Dryland Spring Triticale, Proso Millet and Foxtail Millet to Initial Soil Water in the High Plains. Field Crops Research 113:48-63. Interpretive Summary: Dryland cropping in semi-arid regions could use water more efficiently if cropping systems employing fallow periods could reduce the frequency of fallow. This could be done through flexible fallow systems in which fallow was avoided in years when sufficient soil water was available at planting to produce a profitable crop. In order to develop a decision support system that will help farmers in making crop choice decisions in flexible fallow systems, crop models need to be developed and tested for short-season fallow replacement crops such as spring triticale, foxtail millet, and proso millet. This study modified two existing crop models (CERES-Wheat and CERES-Sorghum) to simulate development and yield of those three crops. Data were collected on beginning soil water effects on leaf area and biomass development. Effects on seed yield were also measured for proso millet. These data were used to calibrate and validate the modified models. The modified crop modules have the potential to simulate these new crops under a range of varying water availability conditions. Consequently, these models can aid in the development of decision support tools for the season-to-season management of these summer fallow replacement crops under dryland conditions in semi-arid environments.
Technical Abstract: Dryland farming strategies in the High Plains must make efficient use of limited and variable precipitation and stored water in the soil profile for stable and sustainable farm productivity. Current research efforts focus on replacing summer fallow in the region with more profitable and environmentally sustainable spring and summer crops. In the absence of reliable precipitation forecasts for the crop growing season, farmers rely mainly upon knowledge of plant available water (PAW) in the soil profile at planting for making planting decisions. To develop PAW-at-planting based decision support for crop selection, experiments were conducted with spring triticale (X Titicosecale Wittmack), proso millet (Panicum miliaceum L.), and foxtail millet (Setaria italica L. Beauv.) under artificially controlled low, medium, and high PAW levels during 2004 and 2005 at Akron, Colorado, and Sidney, Nebraska. The objectives of this study were to adapt existing simulation models for the simulation of triticale and millet and to evaluate simulations from the adapted models by comparing results with field data collected under varying PAW conditions at planting. The RZWQM2-DSSAT v4.0 with DSSAT v4.0 crop growth modules was used. Specifically, the Cropping System Model (CSM)-CERES-Wheat module was adapted for simulating triticale, and CSM-CERES-Sorghum (v4.0) module was adapted for simulating proso and foxtail millets. To adapt and calibrate the crop modules, data (soil water, LAI, grain yield and biomass) for the highest PAW level treatment for one crop season each for the three crops were used. The models were then evaluated with data from the remaining PAW level treatments. The proso millet module was further tested with four years of data from a crop rotation experiment at Akron from 2003 to 2006. Simulation results indicated that the adapted and calibrated crop modules have the potential to simulate these new crops under a range of varying water availability conditions. Consequently, these models can aid in the development of decision support tools for the season-to-season management of these summer fallow replacement crops under dryland conditions in semi-arid environments.