An infrared diagnostic system to detect causal agents of grapevine trunk diseases
In most vineyards worldwide, agents of grapevine trunk diseases represent a real threat for viticulture and are responsible for significant economic loss to the wine industry. The conventional microbiological isolation technique used to diagnose this disease is tedious and frequently leads to false...
Gespeichert in:
Veröffentlicht in: | Journal of microbiological methods 2016-12, Vol.131 (131), p.1-6 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | In most vineyards worldwide, agents of grapevine trunk diseases represent a real threat for viticulture and are responsible for significant economic loss to the wine industry. The conventional microbiological isolation technique used to diagnose this disease is tedious and frequently leads to false negatives. Thus, a dire need exists for an alternative method to detect this disease. One possible way involves infrared spectroscopy, which is a rapid, nondestructive analytical tool that is commonly used for quality control of feed stuffs. In the present work, a midinfrared spectrometer was tested as a fast tool for detecting agents of grapevine trunk disease. Midinfrared spectra were collected from 70 Vitis vinifera L. cv. Cabernet-Sauvignon one year old trunk-wood samples that were infected naturally in one viticulture nursery of the south of France. The samples underwent polymerase chain reaction and morphological identification, and the results were correlated to the midinfrared spectra by using multivariate analysis to discriminate between noninfected and infected samples. Based on comparison with some control samples, the highest percentage of correct identification of fungal contamination when using the midinfrared spectroscopy method is 80%.
•Grapevine trunk diseases fungi were isolated from wood samples.•Fourier infrared spectra of wood powder were collected.•Qualitative and quantitative PCR, and microbiological isolation were done.•A discrimination model was built to identify infected wood samples. |
---|---|
ISSN: | 0167-7012 1872-8359 |
DOI: | 10.1016/j.mimet.2016.09.022 |