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Influence of Rainfall and Fire Caterpillar on Oil Palm Yield at Tor Gamba Fahmi, Yudi; Kusumawati, Anna; Siregar, Sutan Borohim
Jurnal Biologi Tropis Vol. 26 No. 3 (2026): in Progress
Publisher : Biology Education Study Program, Faculty of Teacher Training and Education, University of Mataram, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbt.v26i3.12224

Abstract

As a strategic plantation commodity, oil palm (Elaeis guineensis Jacq.) plays a crucial role in supporting Indonesia's national economy, yet its productivity is strongly influenced by climatic variability and pest pressure, particularly fire caterpillar (Limacodidae) attacks that damage foliage and reduce photosynthetic capacity. This study aimed to analyze the relationships between annual rainfall, fire caterpillar attack intensity, and fresh fruit bunch (FFB) productivity at PT Perkebunan Nusantara III Tor Gamba I Plantation over a five-year period (2012–2016; n = 5 annual observations). A quantitative observational-correlational design was applied using secondary archival data on rainfall (mm/year), pest attack intensity (mean larvae per frond), and FFB yield (kg/ha/year). Pearson correlation and paired T-tests were conducted at a 5% significance level (df = 3; T-table = 2.78). Rainfall showed a very strong positive correlation with FFB productivity (r = 0.95; T-count = 9.34) and a very strong negative correlation with fire caterpillar attack intensity (r = 0.98; T-count = 12.96), indicating that higher rainfall suppressed pest population growth. Furthermore, pest attack intensity had a very strong negative correlation with FFB productivity (r = 0.97; T-count = 9.83). The small sample size (n = 5) constrains statistical power and limits causal inference; results should be interpreted as descriptive associations. Nevertheless, findings suggest that rainfall monitoring could support early warning systems for pest outbreaks and inform integrated pest management strategies for oil palm plantations.