Impact of El Niño on Oil Palm Yield in Malaysia

Abstract

Oil palm crop yield is sensitive to heat and drought. Therefore, El Niño events affect oil palm production, resulting in price fluctuations of crude palm oil due to global supply shortage. This study developed a new Fresh Fruit Bunch Index (FFBI) model based on the monthly oil palm fresh fruit bunch (FFB) yield data, which correlates directly with the Oceanic Niño Index (ONI) to model the impact of past El Niño events in Malaysia in terms of production and economic losses. FFBI is derived from Malaysian monthly FFB yields from January 1986 to July 2021 in the same way ONI is derived from monthly sea surface temperatures (SST). With FFBI model, the Malaysian oil palm yields are better correlated with ONI and have higher predictive ability. The descriptive and inferential statistical assessments show that the newly proposed FFBI time series model (adjusted R-squared = 0.9312 and residual median = 0.0051) has a better monthly oil palm yield predictive ability than the FFB model (adjusted R-squared = 0.8274 and residual median = 0.0077). The FFBI model also revealed an oil palm under yield concern of the Malaysian oil palm industry in the next thirty-month forecasted period from July 2021 to December 2023.

Oil Palm Yield Prediction Across Blocks Using Multi-Source Data and Machine Learning

“…Notably, the precipitation collected from CHIRPS dropped precipitously to 170 mm and the land surface temperature was the highest (35°C) in 2015 and 2016 as a result of the very severe El Niño that caused the drought. Possibly, the oil palm yields remained low in the next few years due to the heat stress from the recent very severe El Niño that caused the drought to occur and failed to recover (Khor et al 2021;Ahmed et al 2021). In order to ascertain the results, further verification between ground-based rainfall and temperature and satellite-derived climatic variables will be undertaken.…”

“…leaf area index, foliar and soil nutrients, and tree height) are typically inconsistent and can lead to statistical error and bias (Awal et al 2010;Shamshiri et al 2018). Several studies show that climate and agronomic aspects are the main elements in predicting oil palm yield (Chapman et al 2018;Hilal et al 2021;Ahmed et al 2021;Khor et al 2021). Such weather data is crucial in estimating oil palm yield because temperature increases of 1 °C, 2 °C, 3 °C and 4 °C reduce oil palm production by 10% to 41% (Sakar et al 2020).…”

Indonesia’s Natural Rubber Productivity and Technically Specified Natural Rubber 20 Export: The Effect of El Nino Southern Oscillation

“…-13.54 -12.85 8.43 15.58 13.27 30.95 9.64 -19.80 -20.55 0.34 -3.86 0.70 0.69 2009 Strong EN -9.20 -11.04 -11.92 -12.54 -11.36 -12.47 -10.17 -6.52 -6.21 -5.53 -9.80 -4.46 -9 5.67 10.08 12.18 6.88 -4.51 -14.97 -6.60 11.39 8.43 -0.35 2.87 -7.18 1.99 2014Weak EN -1.87 -1.60 -1.31 -1.42 -2.09 -2.84 -2.39 -1.33 -4.97 -5.13 -4.46 -4.10 -2.79 2015 EN -0.31 -0.47 -0.96 -0.22 -1.57 -1.36 -0.09 -0.29 -10.52 -8.23 -6.73 -9.57 -3.36 2019 Normal -4.07 -4.48 -5.13 -5.75 -2.51 -4.34 -3.80 -4.34 -8.67 -8.46 -7.87 -7.83 -5.61 Note In contrast, El Nino, lowering rainfall, could decrease natural rubber productivity, as demonstrated by the 2015 El Nino (Saputra, Stevanus, & Cahyo, 2016). To compare these results to another critical and valuable commodity, lower yield due to El Nino also occurring in palm oil plantations (e.g., Azlan et al, 2016;Khor et al, 2021;Oettli, Behera, & Yamagata, 2018;Stiegler et al, 2019). Khor et al (2021) computed that the opportunity losses because of El Nino, beginning from 1986 (excluding 2018, 2019), were around USD 9.55 billion, while Oettli et al (2018) discovered that La Nina was favorable for improving profit.…”

“…To compare these results to another critical and valuable commodity, lower yield due to El Nino also occurring in palm oil plantations (e.g., Azlan et al, 2016;Khor et al, 2021;Oettli, Behera, & Yamagata, 2018;Stiegler et al, 2019). Khor et al (2021) computed that the opportunity losses because of El Nino, beginning from 1986 (excluding 2018, 2019), were around USD 9.55 billion, while Oettli et al (2018) discovered that La Nina was favorable for improving profit. These results are consistent with Selvaraju (2003), examining the impact of ENSO on food grain production, uncovering that total food grain production increased from normal during La Nina.…”

Impact Comparison of El Niño and Ageing Crops on Malaysian Oil Palm Yield

“…The current downward trend in Malaysian oil palm production was forecast by an oil palm predictive model in our past study [ 26 ]; however, the reason for the under-yield performance was not explored in the earlier stage of our research. The model predicted monthly oil palm yields and matched closely with the 15 most recent months (July 2021 to September 2022) of reported data in Malaysia.…”