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Effect of Climate Variables on Cocoa Black Pod Incidence in Sabah using ARIMAX Model

机译:气候变量对使用ARIMAX模型的Cocoa黑色Pod发病率的影响

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Cocoa black pod disease is one of the major diseases affecting the cocoa production in Malaysia and also around the world. Studies have shown that the climate variables have influenced the cocoa black pod disease incidence and it is important to quantify the black pod disease variation due to the effect of climate variables. Application of time series analysis especially auto-regressive moving average (ARIMA) model has been widely used in economics study and can be used to quantify the effect of climate variables on black pod incidence to forecast the right time to control the incidence. However, ARIMA model does not capture some turning points in cocoa black pod incidence. In order to improve forecasting performance, other explanatory variables such as climate variables should be included into ARIMA model as ARIMAX model. Therefore, this paper is to study the effect of climate variables on the cocoa black pod disease incidence using ARIMAX model. The findings of the study showed ARIMAX model using MA(1) and relative humidity at lag 7 days, RH_(t - 7) gave better R square value compared to ARIMA model using MA(1) which could be used to forecast the black pod incidence to assist the farmers determine timely application of fungicide spraying and culture practices to control the black pod incidence.
机译:可可黑荚疾病是影响马来西亚和世界各地可可产量的主要疾病之一。研究表明,气候变量影响了Cocoa黑色豆荚疾病发病率,并且由于气候变量的效果,量化黑色豆荚疾病变化是重要的。时间序列分析的应用特别是自动回归移动平均(ARIMA)模型已广泛用于经济学研究,可用于量化气候变量对黑色POD的影响预测控制发病率的正确时间。然而,Arima模型不会捕获可可黑色Pod入射中的一些转折点。为了提高预测性能,其他解释性变量如气候变量应包括在Arima模型中作为AriMax模型。因此,本文研究了气候变量对使用ARIMAX模型的Cocoa黑色荚疾病发病率的影响。该研究的发现显示了使用MA(1)的ARIMAX模型,并且滞后7天的相对湿度,与使用MA(1)的ARIMA模型相比,RH_(T-7)与ARIMA模型相比,可以用于预测黑色豆荚协助农民的发病率决定及时应用杀菌剂喷涂和培养实践来控制黑色荚的发病率。

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