Multidimensional discriminant analysis of species, strains and culture age of closely related entomopathogenic fungi using reflectance spectroscopy.

The diversity of fungal strains is influenced by genetic and environmental factors, growth conditions and mycelium age, and the spectral features of fungal mycelia are associated with their biochemical, physiological, and structural traits. This study investigates whether intraspecific differences can be detected in two closely related entomopathogenic species, namely Cordyceps farinosa and Cordyceps fumosorosea, using ultraviolet A to shortwave infrared (UVA-SWIR) reflectance spectra. Phylogenetic analysis of all strains revealed a high degree of uniformity among the populations of both species.

Reflectance spectroscopy and machine learning as a tool for the categorization of twin species based on the example of the Diachrysia genus.

In our work we used noninvasive point reflectance spectroscopy in the range from 400 to 2100 nm coupled with machine learning to study scales on the brown and golden iridescent areas on the dorsal side of the forewing of Diachrysia chrysitis and D. stenochrysis. We used our approach to distinguish between these species of moths.

A random forest model for the classification of wheat and rye leaf rust symptoms based on pure spectra at leaf scale.

The pure spectra acquisition of plant disease symptoms is essential to improving the reliability of remote sensing methods in crop protection. The reflectance values read from the pure spectra can be used as valuable training data for development of algorithms designed for plant disease detection at leaf and canopy scale. The aim of this paper is to identify and distinguish spectrally the leaf rust symptoms caused by two closely related special forms (f.

An application of reflectance spectroscopy to differentiate of entomopathogenic fungi species.

Fourier Transform Infrared Spectroscopy (FTIR) methods are the most commonly used spectroscopic techniques for differentiation of fungi species, however reflectance spectroscopy as a non-invasive technique can also be used. The aim of the study was to develop a method to rapidly differentiate fungi by means of reflectance spectroscopy using visible-infrared spectrum. Spectral measurements were conducted on six entomopathogenic fungi: Beauveria bassiana, Isaria fumosorosea, I.