Spectral Characterization of the Life Stages and Physiological Responses of <em>Diatraea saccharalis</em> Fabricius (Lepidoptera: Crambidae) Larvae Parasitized by <em>Cotesia flavipes</em> Cameron (Hymenoptera: Braconidae)

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Abstract

Hyperspectral Remote Sensing allows the accurate analysis of the developmental stages of insects and their interactions with biocontrol agents. This study spectrally characterizes the life stages of Diatraea saccharalis and evaluates the physiological responses of larvae parasitized by Cotesia flavipes. For this, hyperspectral reflectance data were obtained with high-precision sensors. The experiments took place in the laboratory under controlled conditions to ensure reproducibility. The measurements covered eggs, larvae, pupae and adults, with emphasis on parasitized larvae. Principal Component Analysis (PCA) was applied to identify relevant significant hyperspectral variations and distinguish biological groups.The results showed significant differences in hyperspectral reflectances between the developmental stages and the physiological state of the parasitism larvae. Newly laid eggs and newly formed pupae showed higher reflectance than pre-hatch eggs and old pupae. The larvae of the first stage were significantly distinguished from the other larval stages by their high reflectance. In adults, the dorsal surfaces of males and females were similar, but the ventral surface of females exhibited a distinct pattern.Larvae parasitized by C. flavipes showed differences hyperspectral signatures, especially in the near-infrared (NIR) bands, reflecting biochemical and physiological changes caused by parasitism. Between 8 and 10 days after parasitism, the reflectance of the larvae became similar to that of dead larvae and different from those of live or newly parasitized larvae. PCA confirmed the efficacy of hyperspectral reflectance in discriminating the stages of D. saccharalis.The data generated in this study can integrate a hyperspectral bank for future applications in entomology and biological control, with this technology being able to integrate precision agriculture systems, optimizing for characterization, pest management and reinforcing the sustainable use of agricultural resources.

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