Modeling the Influence of Certain Weather Parameters on Oil Palm Production in Peninsular Malaysia

: Oil palm is one of the most important crops in Malaysia. Lately, the production of oil palm has been reduced due to a variety of factors, including the weather and climate. Temperature, wind speed, relative humidity, sunshine, and rainfall distribution all have an impact on palm tree growth and development, which in turn has an impact on oil palm production. This paper aims to investigate the effects of some weather elements (temperature, wind speed, relative humidity, sunshine, and rainfall) on oil palm production in Peninsular Malaysia. Data were analyzed using the Statistical Package for Social Sciences (SPSS 20.0 version), with descriptive statistics, and multiple linear regression (MLR). The MLR model determined the strength of the relationship between oil palm yield (dependent variable) and the changing variables of temperature, sunshine, wind speed, relative humidity, and rainfall (independent variables). The findings revealed that temperature, wind speed, relative humidity, sunshine, and rainfall have a low impact on oil palm production and yield turnover. The R2 value of 0.202 shows that the independent variables explained only 20.2% of the fluctuation in palm oil production. The study recommends working within an integrated approach involving scientific research, planting, improving variety, improving regional academic leadership, and engaging private and public stakeholders, emphasized collaborative efforts with researchers in consumer countries, and strengthening the capacity of growers to best agroecological practices.

evaporates more quickly, so the impacts of dry periods become more intense [41]. The average monthly temperature eight months prior to harvest of 27.83°C led to low FFB yield [42][43]. Wind speed is found to have an impact on oil palm cultivation [44]. The total sunshine hours is not the only site-specific factor for oil palm production [45]. The simultaneous availability of soil moisture also plays an important role in determining the effective sunshine hour for maximising FFB yield [46]. Direct sunlight boosts palm productivity. The lower incidence of cloud cover over much of Southeast Asia is thought to be one of the reasons why oil palm yields are mostly higher than in West Africa [47][48]. Photoperiod response regulates oil palm flowering [49]. In 2014, 2015, and 2016, the palm oil yield dropped by 0.3%, 1.9%, and 17%, respectively, to 3.84, 3.78, and 3.21 t ha -1 , compared to the previous year's record of 3.84, 3.78, and 3.21 t ha -1 . The decrease in palm oil yield has been attributed to a decrease in FFB yield in recent years [50][51].
With oil palm producing accounting fthe highest agricultural yield in Malaysia, research into the effects of climatic element on oil palm cultivation does not receive the same level of attention as that cereal crops. As a result, this study seeks to investigate the most recent trends of climatic elements in Peninsualr Malaysia, as well as the effects of these climatic elements on oil palm cultivation. The study also makes some recommendations to improve oil palm cultivation in Malaysia.

The Study Area
Peninsular Malaysia is geographically located on latitude 1 0 and 7 0 north and between 99 0 and 105 0 east. The region occupied a total land area of 132,000 km 2 and mainly composed the highlands, floodplains, and coastal zones. overall, the Peninsular, has a warm and humid tropical climate throughout the year, with temperature ranges from 25 0 C to 32 0 C. The region is characterized by two monsoon seasons: the southwest monsoon from May to September and the northeast monsoon from November to March, which is associated with high rainfall [52][53]. The region records annual rainfall of 2000-4000 mm [54]

Method
Secondary data was used for the purpose of this study. Data on oil palm yield in Malaysia between 1990-2020 was obtained from the Malaysian Palm Oil Board (MPOB). Climate historical data, particularly average annual temperature and rainfall, sunshine, relative humidity and wind speed were also downloaded from the climate-knowledge portal of the World Bank, and National Aeronautics and Space Administration (NASA) in July, 2021.

Data Analysis
Multiple linear regression, an extension of simple linear regression used where there is more than one independent variable was employed by the study. The model was adopted because the independent variable was interval scale. The independent variables should be mostly interval or scale level variables, but multiple regression can also have dichotomous independent variables called dummy variables. In this study, the independent variables refer to relative humidity (%), wind speed (m/s), mean rainfall Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 11 August 2021 doi:10.20944/preprints202108.0266.v1 (mm), mean temperature ( 0 C) and sunshine/solar radiation (MJ/m^2/day). The dependent variable is the yield of oil palm. In regression analysis, assumptions need to be considered as the samples are normally distributed and uncorrelated with the other variables. There is a linear relationship between the independent variables and the dependent variable and no multicollinearity issues. As a result, this study analyzed bivariate correlation to examine the linear relationship and continued to examine the Variance Inflation Factor (VIF) and tolerance to confirm the presence of multicollinearity.
The values of tolerance must be less than 5 and tolerance values greater than 0.2 [55].
The multiple linear regression equation is follow as: The yield of oil palm are influenced by relative humidity, wind speed, mean rainfall, mean temp and sunshine/solar radiation. For multiple linear regression, the coefficient is estimated similar to simple linear regression. For this case of study, the proposed model would be: Yield tonne (Y) = β0 + B1RelativeH + B2WindS + B3Rainfall + B4Temp + B3SolarR + ɛ

Results and Discussion
The mean yield was 18.719 tonne per hectare, 87.120% of relative humidity, and the mean wind speed was 0.502 m/s. In addition, the mean rainfall was 243.967 mm, 26.010 mean temperature, and 35.659 was the mean of solar radiation. The analysis indicates the histogram was symmetrical, explained to the normal distribution, and met the following regression analysis assumption.  The linear relationship conducted using bivariate correlation. A linear relationship of sunshine/solar radiation has a significant and inverse relationship with temperature from the analysis. In addition, the relative humidity, wind speed, rainfall, temperature, and sunshine were not significant to yield.  influence the yield of oil palm such as farm management, soil characteritics, type of seed among others. This is consistent with study conducted at various locations in Malaysia.
Shafiq [56] found that climatic elements has less impact on oil palm production and determination of Fresh Fruit Bunch yield.

Conclusions
The study conclude that climatic elements are had no significant effect in oil palm production. The mode indicating that 20.2% of the variability in monthly oil palm yield was represented by the regression equation. Future research will most likely include the delineation of climatic regions using statistical analysis of Malaysia's monthly grided data set using various climatic indices. It will be useful to further explore the relationship between oil palm yield, climatic and cultural factors aside. This will give the oil palm growers insight into the agricultural practices suitable for oil palm production.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to [the data generated from different sources].