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Use of seasonal climate information to predict coconut production in Sri Lanka by T. S. G. Peiris; J. W. Hansen; Lareef Zubair is a Environmental Science article available to read on EtoBox.

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## Abstract Accurate forecasting of annual national coconut production (ANCP) is important for national agricultural planning and negotiating forward contracts. Climate and the long‐term trends (attributed to ‘technology’) are major factors that determine ANCP. The effect of climate on ANCP of the following year was studied for the seven agro‐ecological regions (AER's) in the principal coconut growing areas for the period 19502002. Climate was studied based on seasons aggregated by the monsoon calendar and by quarters that are consistent with the agricultural calendar. The use of quarterly seasons explained more of the variability of ANCP than the use of monsoon based seasons. January–March rainfall in all AER's and July–September rainfall in the wetter regions are positively correlated with the ANCP (__p__ < 0.005). The technology effect was estimated using a log–linear trend model. The regression model integrates both climate and technology effects developed to predict ANCP with high fidelity (__R__^2^ = 0.94). The climate effect was estimated by regressing production data that had been de‐trended to remove the technology effects with quarterly rainfall in the year prior to harve

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Author

T. S. G. Peiris; J. W. Hansen; Lareef Zubair

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0899-8418)

Published

2007

Language

EN

Field

Environmental Science (Physical Sciences)