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Rebuffo, C.A., Schmitt, J., Wenning, M., von Stetten, F. and Scherer, S. (2006) Reliable and rapid identification of Listeria monocytogenes and Listeria species by artificial neural network-based Fourier transform infrared spectroscopy. Applied and Environmental Microbiology, 72, 994-1000. doi:10.1128/AEM.72.2.994-1000.2006

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• TITLE: Spectral footprint of Botrytis cinerea, a novel way for fungal characterization

  AUTHORS: Mohamed Aboelghar, Hala Abdel Wahab

  KEYWORDS: Gray Mold; Fungal Identification; Fungal Classification

  JOURNAL NAME: Advances in Bioscience and Biotechnology, Vol.4 No.3, March 20, 2013

  ABSTRACT: Botrytis cinerea affects plant yield and quality. Many Botrytis species are morphologically similar leading to difficulty in pathogen identification. Spectroscopy can be used to identify pathogenic fungi. This study describes a novel method for fungal characterization. Here, we determined the spectral signatures of different B. cinerea isolates as well as various fungal genera. A unique spectral pattern was investigated at both genus and isolate level. The short wave infrared II (2055 - 2315 nm) provided the best discrimination between the fungal samples observed. Moreover, the spectral analysis was performed on non-transformed data and investigated significant differences among fungal genera as well as B. cinerea isolates, while the results investigated high similarity among replicates of the same isolate of B. cinerea. The results of each spectral test were obtained reproducibly without an expensive cost consumable during sample preparation and measurements. This innovative approach would allow us to identify, discriminate and classify fungi rapidly and inexpensively at the genus, species and isolate level.