Makassar, Indonesia, April 21, 2026/BIONE/–The fall armyworm (Spodoptera frugiperda) is one of the most invasive agricultural pests in the world. Originally from the American continent, this species has rapidly spread across Africa and Asia, including Indonesia. In East Nusa Tenggara (NTT), the pest has become a serious threat to corn production, attacking leaves and growing points, and significantly reducing crop yields. What makes this pest particularly challenging is not only its ability to spread quickly up to 100 km per day but also its biological diversity. Different strains of S. frugiperda may behave differently, making control strategies more complex and less predictable.
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This article is based on the study titled “Fall Armyworm Spodoptera frugiperda J.E. Smith (Lepidoptera: Noctuidae) in East Nusa Tenggara Province of Indonesia: Genetic Characterization and Strain Detection”, published on September 18, 2024, in Caraka Tani: Journal of Sustainable Agriculture, published by Universitas Sebelas Maret (UNS), Indonesia. The study aims to identify the genetic variation and strain composition of fall armyworm populations in East Nusa Tenggara (NTT). Samples were collected from three major islands Timor, Flores, and Sumba to represent different geographic conditions and provide insights into the distribution of fall armyworm strains in the region.
How Molecular Analysis Works in Practice
The research process involved DNA extraction from collected larvae, followed by amplification using polymerase chain reaction (PCR). Specific primers were used to target the COI and Tpi genes, producing DNA fragments that could be analyzed further. The PCR results showed a clear amplification band of 811 base pairs for the COI marker. After sequencing, the genetic data were compared using bioinformatics tools such as BioEdit and BLAST. Phylogenetic analysis was then conducted using MEGA software to determine the relationship between local samples and global reference populations. Although these techniques may sound complex, they essentially allow scientists to “read” the genetic code of insects and identify their lineage with high accuracy.
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Two Strains, One Region
The findings reveal that fall armyworm populations in NTT consist of two main strains: the corn strain and the rice strain. Phylogenetic analysis shows that these strains form distinct genetic groups, or clades, within the population. Interestingly, the corn strain dominates, accounting for approximately 63.6% of the population, while the rice strain makes up about 36.4% . Further analysis using the COI marker classifies the population into the h4 haplotype subgroup, while the Tpi marker confirms the dominance of the corn strain.
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Understanding the genetic composition of pest populations is more than just an academic exercise. Different strains may vary in their feeding behavior, host preference, and response to control methods. This means that a strategy effective against one strain may not work as well against another. By identifying the dominant strain in a specific region, farmers and researchers can design more targeted and efficient pest management strategies. This reduces unnecessary pesticide use and improves overall effectiveness. This study contributes directly to Sustainable Development Goal (SDG) 2: Zero Hunger, by supporting efforts to protect crop productivity. It also aligns with SDG 15: Life on Land, as it promotes better understanding of biodiversity and ecosystem interactions. In addition, the research supports SDG 9: Industry, Innovation, and Infrastructure, through the application of molecular technology in agriculture.
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Seeing Pests Through a Different Lens
What this study ultimately shows is that pests are not always as simple as they appear. Behind what looks like a single species lies a complex genetic structure that influences behavior and impact. By combining field sampling with molecular analysis, researchers can uncover hidden patterns that are essential for effective pest control. This approach represents a shift toward more precise and science-based agriculture where decisions are guided not just by observation, but by genetic insight.
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Reference:
DOI:Â http://dx.doi.org/10.20961/carakatani.v39i2.91748
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Contact Info:
Prof. Dr. Ir. Itji Diana Daud, M.S.
+62811445853
itjidianadaud@unhas.ac.id
