Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
Document title: Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment
Journal: Scientia agricola
Database: PERIÓDICA
System number: 000357870
ISSN: 0103-9016
Authors: 1
1
1
2
Institutions: 1Chinese Academy of Sciences, Institute of Soil and Water Conservation, Yangling, Shaanxi. China
2Chinese Academy of Sciences, Wuhan Botanical Garden, Wuhan, Hubei. China
Year:
Season: Sep-Oct
Volumen: 69
Number: 5
Country: Brasil
Language: Inglés
Document type: Artículo
Approach: Experimental, analítico
English abstract Effects of meteorological variables on crop production can be evaluated using various models. We have evaluated the ability of the Hybrid-Maize model to simulate growth, development and grain yield of maize (Zea mays L.) cultivated on the Loess Plateau, China, and applied it to assess effects of meteorological variations on the performance of maize under rain-fed and irrigated conditions. The model was calibrated and evaluated with data obtained from field experiments performed in 2007 and 2008, then applied to yield determinants using daily weather data for 2005-2009, in simulations under both rain-fed and irrigated conditions. The model accurately simulated Leaf Area Index , biomass, and soil water data from the field experiments in both years, with normalized percentage root mean square errors < 25 %. Gr.Y and yield components were also accurately simulated, with prediction deviations ranging from -2.3 % to 22.0 % for both years. According to the simulations, the maize potential productivity averaged 9.7 t ha–1 under rain-fed conditions and 11.53 t ha–1 under irrigated conditions, and the average rain-fed yield was 1.83 t ha–1 less than the average potential yield with irrigation. Soil moisture status analysis demonstrated that substantial potential yield may have been lost due to water stress under rain-fed conditions
Disciplines: Matemáticas,
Agrociencias
Keyword: Matemáticas aplicadas,
Gramíneas,
Modelos biológicos,
Maíz,
Híbridos,
Productividad,
Variables meteorológicas,
Zonas semiáridas,
China
Keyword: Mathematics,
Agricultural sciences,
Applied mathematics,
Gramineae,
Biological models,
Maize,
Hybrids,
Productivity,
Meteorological variables,
Semiarid zones,
China
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