Near infrared spectroscopy for the identification of live anurans: Towards rapid and automated identification of species in the field

IF 1.6 4区 化学 Q3 CHEMISTRY, APPLIED Journal of Near Infrared Spectroscopy Pub Date : 2023-02-20 DOI:10.1177/09670335231156472
Kelly Torralvo, F. Durgante, C. Pasquini, W. Magnusson
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Abstract

In megadiverse regions, such as the Amazon, the identification of species generally requires specialists that are often not available. Therefore, the use of new species-recognition tools is necessary to streamline surveys and avoid errors in species identification that lead to ineffective decision-making. Near infrared spectroscopy is a quick and non-destructive tool that has been widely used in the recognition of biodiversity. In addition to being used as an indicator group, anurans have species with high morphological diversity, which make them the focus of studies and application of new tools that help in the identification and recognition at the species level. In this study, the viability of recognition of species of live Amazonian frogs under field conditions using the near infrared technique and portable equipment was examined. The performance of classification models based on a linear discriminant analysis, built using spectra obtained from the dorsal and ventral surfaces of four pairs of phylogenetically-close and morphologically-similar species was evaluated. It was possible to distinguish the species of live anurans in five of the eight species studied with hit rates above 80% when using only one spectral reading per individual. The overall mean of correct prediction of the models was below that of previous studies that tested the method with anurans, which are likely to be due to particularities in the acquisition of spectra under field conditions and live species. Therefore, suggestions are made to improve the predictive capacity of the techniques.
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近红外光谱法鉴定活无尾蛛:实现现场物种的快速和自动化鉴定
在像亚马逊这样的生物多样性巨大的地区,物种的鉴定通常需要专家,而这些专家往往是找不到的。因此,使用新的物种识别工具是必要的,以简化调查和避免物种识别错误,导致无效的决策。近红外光谱是一种快速、无损的生物多样性识别方法。无尾动物除了作为指示类外,还具有高度的形态多样性,这使得无尾动物成为研究和应用新工具的重点,有助于在物种水平上进行鉴定和识别。在野外条件下,利用近红外技术和便携式仪器,研究了识别亚马逊活蛙种类的可行性。基于线性判别分析的分类模型的性能进行了评估,该模型是利用从4对系统发育接近和形态相似的物种的背部和腹部表面获得的光谱建立的。在研究的8个物种中,有5个物种的准确率在80%以上,当只使用每个个体的一个光谱读数时,就有可能区分出活的无尾猿的种类。模型正确预测的总体平均值低于先前用无脊椎动物测试该方法的研究,这可能是由于在野外条件和活物种下获取光谱的特殊性。因此,提出了提高技术预测能力的建议。
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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
35
审稿时长
6 months
期刊介绍: JNIRS — Journal of Near Infrared Spectroscopy is a peer reviewed journal, publishing original research papers, short communications, review articles and letters concerned with near infrared spectroscopy and technology, its application, new instrumentation and the use of chemometric and data handling techniques within NIR.
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