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Research Articles

Modelling canopy development, biomass and yield of maize (Zea mays L.) under optimal management

Authors:

J. B. D. A. P. Kumara ,

University of Peradeniya, LK
About J. B. D. A. P.
Postgraduate Institute of Agriculture
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L. D. B. Suriyagoda,

University of Peradeniya, LK
About L. D. B.
Department of Crop Science, Faculty of Agriculture
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W. A. J. M. De Costa,

University of Peradeniya, LK
About W. A. J. M.
Department of Crop Science, Faculty of Agriculture
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M. A. P. W. K. Mallaviarachchi

Field Crops Research and Development Institute, LK
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Abstract

Among upland cereals, Maize (Zea mays L.) is considered as the most important cereal crop in Sri Lanka. Successful expansion of maize cultivation requires knowledge on its yield potential. Conventional agronomic research may require considerable time and physical resources to generate the relevant knowledge whereas simulation modelling would enable prediction of crop responses to varying environment and management conditions with less time and resources. Therefore, the objective of this research was to develop a process-based simulation model to predict the yield potential of maize in different agro-ecological zones of Sri Lanka under recommended crop management. Detailed leaf initiation and expansion data of maize growing at Kundasale (IM3a) in Sri Lanka under recommended crop management practices were used to construct a canopy development sub-model, which is driven by the thermal responses of leaf initiation and expansion. Time-courses of canopy leaf area index estimated based on the canopy development sub-model were used to estimate radiation interception. Biomass production and yield were estimated from intercepted radiation using radiation-use efficiency and harvest index, respectively. Model predictions were compared with independent data collected from field experiments at Peradeniya (WM2b) and Maha-Illuppallama (DL1b). Results were in agreement with actual data of leaf initiation, individual leaf area, leaf area index, above ground biomass and yield with respective Root Mean Square Error (RMSE) values being 0.89, 81.13, 0.45, 0.14 and 0.06, respectively. Simulations predicted that increased growing season temperature decreased the number of days to tasseling and crop maturity by 3.1 and 4.1 days per °C, respectively, which were in agreement with the observed data.

Tropical Agricultural Research Vol. 25 (2): 214 – 227 (2014)

How to Cite:
Published on 23 Nov 2015.
Peer Reviewed

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