Yield responses of two maize cultivars following short periods of water stress at tasseling

Soriano, A.; Ginzo, H. D.

doi:10.1016/0002-1571(75)90010-2

Cited by 9 publications

(3 citation statements)

References 12 publications

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“…Values for HI reported for temperate regions usually were between 0.46 and 0.58 and the mean was 0.52 (Kiniry et a!., 1997). While severe drought treatments have been shown to reduce maize HI to as low as 0.27 to 0.31 (Sobriano and Ginzo, 1975;Griffin, 1980;Costa eta!., 1988), use of such a low value for plant stress in this study caused greater errors in grain yield simulation by ALMANAC. For sorghum, the simulated HI value was 0.45, based on the results of Prihar and Stewart (1990).…”

Section: Almanacmentioning

confidence: 70%

Maize and Sorghum Simulation in Diverse Texas Environments

Kiniry

Bockholt

1998

Agronomy Journal

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Crop models for decision making should accurately simulate grain yields across a wide range of soils and climate regimes. This study was designed to evaluate two models' ability to simulate plot grain yields under diverse weather conditions and soils in Texas. The objective was to compare measured grain yields of maize (Zea mays L.) and sorghum [Sorghum bicolor (L.) Moench] with grain yields simulated by the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) model and to compare measured maize yields with grain yields simulated by a new version of the CERES‐Maize (Crop‐Environment Resource Synthesis) model. Using yield performance trials, both models were tested for their ability to simulate the mean yield for five years at each location and their ability to describe year‐to‐year variability in measured yields. Both models were tested at nine locations for maize and ALMANAC was tested at eight locations for sorghum. Model inputs included parameters for the soil type, planting dates, planting rates, and locally measured weather data. Mean simulated grain yield for each site was within 10% of the mean measured grain yield for all cases, except for CERES at Thrall, where mean simulated yield was 13% lower than mean measured yield. When the models did not account for a significant amount of the year‐to‐year variability in measured grain yield at a site, it was usually due to the narrow range of measured grain yields. The soils, weather, and crop parameter data sets developed here can be useful starting points for deriving data at similar sites, giving model users examples of realistic input data.

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Section: Almanacmentioning

confidence: 70%

Maize and Sorghum Simulation in Diverse Texas Environments

Kiniry

Bockholt

1998

Agronomy Journal

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“…Five days of severe drought during this interval reduces HI to a crop‐specific minimum. This minimum for maize was set to 0.30, based on results of Sobriano and Ginzo (1975), Griffin (1980), and Costa et al (1988) Because ALMANAC requires the minimum HI to be less than potential HI, minimum HI for sorghum was 0.44 to allow only minimal decreases.…”

Section: Data Setsmentioning

confidence: 99%

Maize and Sorghum Simulations with CERES‐Maize, SORKAM, and ALMANAC under Water‐Limiting Conditions

Xie

Kiniry

Nedbalek³

et al. 2001

Agronomy Journal

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While crop models often are tested against long‐term mean grain yields, models for aiding decision making must accurately simulate grain yields in extreme climatic conditions. In this study, we evaluated the ability of a general crop model (ALMANAC) and two crop‐specific models (CERES‐Maize and SORKAM) to simulate maize (Zea mays L.) and sorghum [Sorghum bicolor (L.) Moench] grain yields in a dry growing season at several sites in Texas. The root mean square deviation values were 0.36 Mg ha−1 for sorghum with ALMANAC, 0.71 for sorghum with SORKAM, 0.56 for maize with ALMANAC, and 0.83 for maize with CERES‐Maize. For maize, values for coefficient of determination (r2) between measured and simulated grain yields were 0.95 for ALMANAC and 0.88 for CERES‐Maize. For sorghum, r2 values were 0.86 for ALMANAC and 0.45 for SORKAM. ALMANAC and SORKAM should be useful tools to simulate dryland sorghum in drought, as indicated by their root mean square deviation values of <0.8 Mg ha−1. The mean errors for irrigated maize were 2.0% for CERES and 6.2% for ALMANAC. For dryland maize, mean errors were 6.2% for ALMANAC and −2.2% for CERES. In CERES, simulated leaf area index (LAI) and kernel weight appeared to be overly sensitive to drought stress. Further study on the response of LAI and kernel weight to drought in CERES would be valuable. The soil, weather, and crop parameter data sets developed for this study could be useful guidelines for model applications in similar climatic regions and on similar soils.

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“…The second example illustrates how our population based approach can be used to analyze differences in genotype response to environmental conditions that inhibit plant growth during flowering. Genotypic differences in silking patterns and yield performance under source limited conditions around flowering have been well documented (Moss and Stinson, 1961;Woolley et al, 1962;Buren et al, 1974;Soriano and Ginzo, 1975;Bruce et al, 2002). The physiological mechanism(s) underlying these differences in stress tolerance, however, remain…”

Section: Sensitivity Analysismentioning

confidence: 99%

Managing maize pollen dispersal and out-crossing

Astini

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Coupling Time to Silking With Plant Growth Rate in Maize 108 I would like to recognize and gratefully thank many people who helped me achieve this project. Primary and principal, to my family, Pilar and friends, who provided essential emotional support and encouragement. Additionally, I would like to extend personal thanks to Mark Westgate for his patience, guidance and support during this project. The committee members have also provided important input and assistance, my appreciation to Susana Goggi, Raymond Arritt and Lance Gibson. Thanks to Horan BioProduction Inc. and Syngenta Seeds Inc., for providing me the opportunity of working on their fields.

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Yield responses of two maize cultivars following short periods of water stress at tasseling

Cited by 9 publications

References 12 publications

Maize and Sorghum Simulation in Diverse Texas Environments

Maize and Sorghum Simulation in Diverse Texas Environments

Maize and Sorghum Simulations with CERES‐Maize, SORKAM, and ALMANAC under Water‐Limiting Conditions

Managing maize pollen dispersal and out-crossing

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