Simple Regression Modeling on the Number of Fronds Increases with Age on Oil Palm Seedling’s Growth

Sumaryanto, Mirwan Ushada and Endy Suwondo
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Sumaryanto: Department Agro-Industrial Technology, Faculty of Agricultural Technology, Gadjah Mada University. Jl. Flora No.1 Bulaksumur, Yogyakarta 55281, Indonesia Indonesian Oil Palm Research Institute, Jln. BrigjenKatamso, No. 51 Medan 20158, Indonesia
Mirwan Ushada: Department Agro-Industrial Technology, Faculty of Agricultural Technology, Gadjah Mada University. Jl. Flora No.1 Bulaksumur, Yogyakarta 55281, Indonesia
Endy Suwondo: Department Agro-Industrial Technology, Faculty of Agricultural Technology, Gadjah Mada University. Jl. Flora No.1 Bulaksumur, Yogyakarta 55281, Indonesia

International Journal of Research and Innovation in Applied Science, 2023, vol. 8, issue 6, 198-202

Abstract: The productivity of oil palm crops is a crucial factor in the current oil palm plantation industry, considering the prevalent issues and criticisms about the environmental impact of land clearing for oil palm plantations. Given that the productivity of oil palm crops is determined by their quality and growth rate, it is important to study the speed and quality of oil palm crop growth during the early stages, namely seedling growth, where the number of fronds can be measured. This research aims to analyse the number of seedling fronds growing during their 9-month growth period since being transferred from the pre-nursery to the main nursery plantation. The fronds growth observation results of 300 seedlings over nine months are evaluated using the distribution analysis each month, and the growth model in the form of a linear equation is developed using a statistical linear regression method. The correlation coefficients indicate a reasonably significant increase in the number of fronds as the age of the seedlings, with R values = 0.6728, R = 0.8346, and R = 0.9489 for the minimum, the maximum and average number of fronds, respectively. It is concluded that the growth of the number of oil palm fronds can be easily simulated using the developed regression model.

Date: 2023
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