## 3 Palm Oil Background
### Factors Affecting Palm Oil Growth and Quality  
Palm oil forecasting has been critically shown in studies, particularly in early warning of potential problems. The current state of palm oil modelling indicates a lack of knowledge on palm oil growth and the ability to improve the fruit quality [54; 55]; thus, an in-depth analysis is required. It is necessary to examine the heterogeneity of its production to better comprehend and exert control over the emergence of palm oil. An initial step can be taken before establishing predictive modelling to gain insight and understand the factors (environmental factors, phenotypes, and genotypes). This step includes determining the relationships between palm oil and the method used in the growth analysis. An analysis method is essential to gain insight into the factors and inter-relationships in palm oil production. Palm oil analysis provides a comprehensive understanding of the uncertainty and nonlinearity of its forecast. The most common method of analysing the palm oil data is through, for example, using a preprocessing algorithm or feature selection algorithm. However, previous studies only needed the analysis with no attempt at making predictions. Oil palms require light and nutrients such as nitrogen and phosphorus as a starting point for photosynthesis. Temperature and water turbidity are other environmental factors that affect palm oil production. Five environmental parameters facilitate the oil palm stress tolerance [56]: rainfall, temperature, relative humidity, light intensity, and wind speed. The inefficient production of palm oil may occur in low humidity levels, especially in the dry seasons when the watering holes and rivers have dried up. Oil palms may be more stressed during this season, affecting their yields. Humidity concentration in palm oil cultivation can be predicted [57], for example, a study recognised several environmental effects influencing inflorescence abortion and sex determination. These factors include rainfall, monthly rain, sunshine hour, and evapotranspiration, followed by the minimum and maximum temperature [58]. Notably, in various studies, rainfall is positively correlated with crop output but is weakly associated with crop prices [59]. However, a cointegration analysis from 2018 to 2050 reported that rainfall changes affect future and spot prices with different time lags [60]. Furthermore, a study utilised monthly temperature anomalies to successfully predict palm oil yields [61]. Soil type and texture potentially improve the accuracy of forecasts and climate. Malaysian yields of over 30T fruit bunches per hectare were reported on all soil types, excluding shallow ones. This type exhibits issues such as reduced root proliferation, increased sensitivity to drought and flooding, and a higher risk of palms toppling. The most common soil type based on the Asian soil taxonomy is ultisols and oxiols [62; 63]. One study used 14 different soil textures and chemical variables on six palm oil plantations to measure the effects on palm oil and the physicochemical properties of soil [64]. [PERSON] et al. [65] mentioned that palm oil physiological and behavioural adaptations to survive were defined as early tenera hybrid seedling stages. Sandy soils with macropores exhibit low resistance to penetration, producing excellent root growth in length and ramification. Meanwhile, the variability of soil in the water column is recognised as a more effective measurement approach than conventional techniques. Phenotyping is possible at all levels of an organism's organisation, including the subcellular, cellular, tissue, organismic, and agrophotocenosis levels. This approach is used to identify productivity determinants, abiotic stressors, and plantation planning, especially on lands. This list can be extended to include the determining of the critical mechanisms of oil palm's resistance to pathogens [66]. In oil palm phenotyping, the fruit's size, shape, and physiological and biochemical characteristics are considered.