Classification of Plenodomus lingam and Plenodomus biglobosus in Co-Occurring Samples Using Reflectance Spectroscopy

Andrzej Wójtowicz, Jan Piekarczyk (), Marek Wójtowicz (), Jarosław Jasiewicz, Sławomir Królewicz and Elżbieta Starzycka-Korbas
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Andrzej Wójtowicz: Institute of Plant Protection-National Research Institute, 60-318 Poznan, Poland
Jan Piekarczyk: Faculty of Geographic and Geological Sciences, Adam Mickiewicz University, 60-680 Poznan, Poland
Marek Wójtowicz: Plant Breeding and Acclimatization Institute-National Research Institute in Radzików, 60-479 Poznan, Poland
Jarosław Jasiewicz: Faculty of Geographic and Geological Sciences, Adam Mickiewicz University, 60-680 Poznan, Poland
Sławomir Królewicz: Faculty of Geographic and Geological Sciences, Adam Mickiewicz University, 60-680 Poznan, Poland
Elżbieta Starzycka-Korbas: Plant Breeding and Acclimatization Institute-National Research Institute in Radzików, 60-479 Poznan, Poland

Agriculture, 2023, vol. 13, issue 12, 1-14

Abstract: Under natural conditions, mixed infections are often observed when two or more species of plant pathogens are present on one host. Thus, the detection and characterization of co-occurring pest species is a challenge of great importance. In this study, we focused on the development of a spectral unmixing method for the discrimination of two fungi species, Plenodomus lingam and Plenodomus biglobosus , the pathogens of oilseed rape. Over 24 days, spectral reflectance measurements from Petri dishes inoculated with fungi were conducted. Four experimental combinations were used: the first two were pure fungal samples, while the other two were co-occurring fungal samples. The results of the study show the possibility of distinguishing, based on spectral characteristics, between P. lingam and P. biglobosus not only in pure but also in co-occurring samples. We observed the changes in the reflectance of electromagnetic radiation from the tested fungi over time and a strong correlation between the reflectance and changes in the areas of the mycelia on the Petri dishes. Moreover, the wavelengths most useful for spectral classification of the tested fungal mycelia were selected. Finally, a spectral unmixing model was proposed, which enables the estimation of the areas of two pathogens in co-occurring samples based on the spectral characteristics of the entire plate with an error smaller than 0.2. To our knowledge, the present study is the first report examining the use of reflectance spectroscopy methods for classifying pathogens on the same Petri dish. The study results indicate the feasibility of reflectance spectroscopy as a nondestructive sampling method for plant pathogen detection and classification.

Keywords: reflectance spectroscopy; fungi discrimination; reflectance spectra; spectral unmixing; machine learning; pathogen discrimination (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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