Evaluation of Two Maize Models for Nine U.S. Locations

Abstract

Crop models can be evaluated based on accuracy in simulating several years' yields for one location or on accuracy in simulating long‐term mean yields for several locations. Our objective was to see how the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) model and a new version of CERES‐Maize (Crop‐Environment Resource Synthesis) simulate grain yield of rainfed maize (Zea mays L.). We tested the models at one county in each of nine states: Minnesota, New York, Iowa, Illinois, Nebraska, Missouri, Kansas, Louisiana, and Texas (MN, NY, IA, IL, NE, MO, KS, LA, and TX). Simulated grain yields were compared with grain yields reported by the National Agricultural Statistical Service (NASS) for 1983 to 1992. In each county we chose a soil commonly used in maize production, and we used measured weather data. Mean simulated grain yield for each county was always within 5% of the mean measured grain yield for the location. Within locations, measured grain yield was regressed on simulated grain yields and tested to see if the slope was significantly different from 1.0 and if the y‐intercept was significantly different from 0.0, both at the 95% confidence level. Only at MN, NY, and NE for ALMANAC and at MN, NY, and TX for CERES was slope significantly different from 1.0 or intercept significantly different from 0.0. The CVs of simulated grain yields were similar to the those of measured yields at most sites. Also, both models were appropriate for predicting an individual year's yield for most counties. Values for plant parameters, such as heat units for development and the harvest index, and values for soil parameters describing soil water‐holding capacity offer users reasonable inputs for simulating maize grain yield over a wide range of locations.

The potassium paradox: Implications for soil fertility, crop production and human health

“…Initial recoveries were three-to fivefold higher for non-exchangeable than exchangeable K, followed by a gradual decline toward a stable level of 240-300 kg ha − 1 , with approximately 3000 kg ha − 1 as the cumulative recovery of non-exchangeable K. The resilient behavior of soil K is further revealed, in that 4 years of crop K removal had no consistent effect on soil concentrations of exchangeable, non-exchangeable or total K, implicating the mineral fraction as an important source of buffering. These findings are to be expected, considering what has long been known about the availability and dynamics of non-exchangeable and mineral K, based on chemical extraction 19,[85][86][87] (see also supplemental references [22] and [27][28][29][30] for the online version of the paper), exhaustive cropping 81,86,88,89 (see supplemental references [8], [15] and [16] for the online version of the paper) and electrodialysis 83,90 .…”

“…In the case of the unfertilized (NA-series) subplots, crop K removal was intensified by the harvest of corn or oats stover until 1967, estimated at 331 kg K ha − 1 for continuous corn, 310 kg K ha − 1 for the corn-oats rotation, and 256 kg K ha − 1 for the corn-oatshay rotation. To account for K removal in these residues, a harvest index of 0.5 was assumed for both crops [29][30][31][32] , and a K concentration of 13.5 (corn) or 15 (oats) kg Mg − 1 of dry matter 33 .…”

A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US

“…The harvest index (HI) varies little for each crop species, except under extreme stress conditions [56]. The HI of corn is 0.53, as measured by experiments in nine US locations [57]. The soybean HI is 0.42 based on reported regression equations [56,58].…”

Efeito da radiação solar e temperatura na definição do número de grãos em milho

“…Enquanto alguns autores (Kiniry et al, 1997) constataram relação linear entre número de grãos por planta e a taxa de crescimento da planta, outros (Andrade et al, 1999) não encontraram esse mesmo comportamento entre essas duas variáveis. Tais diferenças são explicadas pelo efeito diferenciado na partição de biomassa e na duração do período crítico de determinação do número de grãos (Andrade et al, 1999).…”