Near-infrared Spectroscopic Method to Identify &lt;I&gt;Cotesia flavipes&lt;/I&gt; and &lt;I&gt;Cotesia sesamiae&lt;/I&gt; (Hymenoptera: Braconidae)

Cole, Tracey J.; Ram, M. S.; Dowell, Floyd E.; Omwega, C. O.; Overholt, William A.; Ramaswamy, S.

doi:10.1603/0013-8746(2003)096[0865:nsmtic]2.0.co;2

Cited by 19 publications

(14 citation statements)

References 17 publications

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“…Our study thus underscores the enormous potential of the NIRS technique to species identification (e.g., refs. 24, 25, 26, 40, 41), and indicates that it could become an important tool also for the delimitation of species in integrative taxonomy, 42 as well as in other biological fields 43 …”

Section: Discussionmentioning

confidence: 99%

Non-destructive species identification ofDrosophila obscuraandD. subobscura(Diptera) using near-infrared spectroscopy

Fischnaller

Dowell

Lusser

et al. 2012

Fly

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The vinegar flies Drosophila subobscura and D. obscura frequently serve as study organisms for evolutionary biology. Their high morphological similarity renders traditional species determination difficult, especially when living specimens for setting up laboratory populations need to be identified. Here we test the usefulness of cuticular chemical profiles collected via the non-invasive method near-infrared spectroscopy for discriminating live individuals of the two species. We find a classification success for wild-caught specimens of 85%. The species specificity of the chemical profiles persists in laboratory offspring (87–92% success). Thus, we conclude that the cuticular chemistry is genetically determined, despite changes in the cuticular fingerprints, which we interpret as due to laboratory adaptation, genetic drift and/or diet changes. However, because of these changes, laboratory-reared specimens should not be used to predict the species-membership of wild-caught individuals, and vice versa. Finally, we demonstrate that by applying an appropriate cut-off value for interpreting the prediction values, the classification success can be immensely improved (to up to 99%), albeit at the cost of excluding a considerable portion of specimens from identification.

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Section: Discussionmentioning

confidence: 99%

Non-destructive species identification ofDrosophila obscuraandD. subobscura(Diptera) using near-infrared spectroscopy

Fischnaller

Dowell

Lusser

et al. 2012

Fly

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“…The main differences in NIR signatures were attributed to cuticular hydrocarbons. (Siegwart et al, 2015) Noctuidae 2 450-2,500 Supervised 93.4%-89.5% (Jia et al, 2007) Hymenoptera Braconidae 2 750-1,700 Supervised >85% (Cole et al, 2003) Trichogrammatidae 3 405-907 Supervised >90% (Nansen et al, 2014) a For field-collected specimen. Accuracy on laboratory-reared specimens was almost 100%…”

Section: Formicidae (Ants)mentioning

confidence: 99%

Near‐infrared spectroscopy (NIRS) for taxonomic entomology: A brief review

Johnson

2020

J Applied Entomology

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For over two decades, near‐infrared spectroscopy (NIRS) has been applied to a wide spectrum of problems in the field of insect taxonomy. It provides a rapid, non‐destructive and relatively cheap method of metabolomic profiling, which can often be used to discriminate closely related species in the same genus. Furthermore, very little training or entomological knowledge is required to operate the instrument. However, a taxonomist is still required to ensure accurate identification of samples used for NIRS model creation and validation. To date, most research has focused on species of economic or epidemiological importance, such as mosquitoes, flies or stored product pests. However, an increasing number of studies are applying NIRS for entomological research with a purely “academic” purpose. As research continues in this field, NIRS has the potential to become more widely accepted in entomology, allowing for the rapid metabolomic profiling of thousands of species.

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“…Instead greater success has been achieved through the application of near to mid-infrared linear models (1.4–2.1 µm wavelength). These have previously been developed for autonomous species identification of the age and/or species in entomology, such as: mosquitos [12, 13], flies [14], beetles [15], termites [16], wasp pupae [17], psocids [18], worms [19] and ants [20]. These models have been developed using single-point conventional laboratory spectrometers, which provide a composite measure of the infrared-active organic functional groups within the beam of the spectrometer, e.g.…”

Section: Introductionmentioning

confidence: 99%

A method for real-time classification of insect vectors of mosaic and brown streak disease in cassava plants for future implementation within a low-cost, handheld, in-field multispectral imaging sensor

et al. 2018

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BackgroundThe paper introduces a multispectral imaging system and data-processing approach for the identification and discrimination of morphologically indistinguishable cryptic species of the destructive crop pest, the whitefly Bemisia tabaci. This investigation and the corresponding system design, was undertaken in two phases under controlled laboratory conditions. The first exploited a prototype benchtop variant of the proposed sensor system to analyse four cryptic species of whitefly reared under similar conditions. The second phase, of the methodology development, employed a commercial high-precision laboratory hyperspectral imager to recover reference data from five cryptic species of whitefly, immobilized through flash freezing, and taken from across four feeding environments.ResultsThe initial results, for the single feeding environment, showed that a correct species classification could be achieved in 85–95% of cases, utilising linear Partial Least Squares approaches. The robustness of the classification approach was then extended both in terms of the automated spatial extraction of the most pertinent insect body parts, to assist with the spectral classification model, as well as the incorporation of a non-linear Support Vector Classifier to maintain the overall classification accuracy at 88–98%, irrespective of the feeding and crop environment.ConclusionThis study demonstrates that through an integration of both the spatial data, associated with the multispectral images being used to separate different regions of the insect, and subsequent spectral analysis of those sub-regions, that B. tabaci viral vectors can be differentiated from other cryptic species, that appear morphologically indistinguishable to a human observer, with an accuracy of up to 98%. The implications for the engineering design for an in-field, handheld, sensor system is discussed with respect to the learning gained from this initial stage of the methodology development.

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Near-infrared Spectroscopic Method to Identify <I>Cotesia flavipes</I> and <I>Cotesia sesamiae</I> (Hymenoptera: Braconidae)

Cited by 19 publications

References 17 publications

Non-destructive species identification ofDrosophila obscuraandD. subobscura(Diptera) using near-infrared spectroscopy

Non-destructive species identification ofDrosophila obscuraandD. subobscura(Diptera) using near-infrared spectroscopy

Near‐infrared spectroscopy (NIRS) for taxonomic entomology: A brief review

A method for real-time classification of insect vectors of mosaic and brown streak disease in cassava plants for future implementation within a low-cost, handheld, in-field multispectral imaging sensor

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