Rapid species discrimination of similar insects using hyperspectral imaging and lightweight edge artificial intelligence

Species discrimination of insects is an important aspect of ecology and biodiversity research. The traditional methods based on human visual experience and biochemical analysis cannot strike a balance between accuracy and timeliness. Morphological identification using computer vision and machine learning is expected to solve this problem, but image features have poor accuracy for very similar species and usually require complicated networks which are unfriendly to portable edge devices. In this work, we propose a fast and accurate species discrimination method of similar insects using hyperspectral features and lightweight machine learning algorithm. Feature regions selection, feature spectra selection and model quantification are used for the optimization of discriminating network. The experimental results of six similar butterfly species in the genus of Graphium show that, compared to morphological recognition with machine vision, our work achieves a higher accuracy of 100% and a shor..., The dataset comprises hyperspectral measurements collected from six butterfly species belonging to the genus Graphium, including G. sarpedon, G. milon, G. doson, G. chironides, G. eurypylus, and G. meyeri. A total of 36 samples were collected, with six samples per species.
All spectral data were acquired using a handheld Specim IQ hyperspectral camera (Specim Spectral Imaging Ltd.), covering a wavelength range from 400 to 1000 nm with a spectral resolution of 7 nm.
As a full-spectrum dataset of all samples, a total of 360 spectra were obtained. Each species contributed 60 spectra, and each individual sample contributed 10 spectra.
, , # Rapid species discrimination of similar insects using hyperspectral imaging and lightweight edge artificial intelligence

[https://doi.org/10.5061/dryad.cfxpnvxdc](https://doi.org/10.5061/dryad.cfxpnvxdc)

According to the ratio of 2:1, all samples of the six species were divided into training set and test set. We use the number from 0 to 5 to show the species of G.sarpedon, G.milon, G.doson, G.chironides, G.eurypylus and G.meyeri.

## Description of the data and file structure

Butterflies (Lepidoptera: Rhopalocera) are the second largest species of insects, with approximately 17,000 recorded species on earth. The species classification and identification of butterfly have been a significant area of research in the field of entomological taxonomy for a long time. In this work, six butterfly species in the genus of Graphium are selected for experiments, including G.sarpedon, G.milon, G.doson, G.chironides, G.eurypylus and G.meyeri. The total number of samples is 36, and for each speci...,