Electronic Nose and GC-MS Analysis to Detect Mango Twig Tip Dieback in Mango (Mangifera indica) and Panama Disease (TR4) in Banana (Musa acuminata)

Wathsala Ratnayake, Stanley E. Bellgard, Hao Wang, Vinuthaa Murthy

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
30 Downloads (Pure)

Abstract

Volatile organic compounds (VOCs), as a biological element released from plants, have been correlated with disease status. Although analysis of VOCs using GC-MS is a routine procedure, it has limitations, including being time-consuming, laboratory-based, and requiring specialist training. Electronic nose devices (E-nose) provide a portable and rapid alternative. This is the first pilot study exploring three types of commercially available E-nose to assess how accurately they could detect mango twig tip dieback and Panama disease in bananas. The devices were initially trained and validated on known volatiles, then pure cultures of Pantoea sp., Staphylococcus sp., and Fusarium odoratissimum, and finally, on infected and healthy mango leaves and field-collected, infected banana pseudo-stems. The experiments were repeated three times with six replicates for each host-pathogen pair. The variation between healthy and infected host materials was evaluated using inbuilt data analysis methods, mainly by principal component analysis (PCA) and cross-validation. GC-MS analysis was conducted contemporaneously and identified an 80% similarity between healthy and infected plant material. The portable C 320 was 100% successful in discriminating known volatiles but had a low capability in differentiating healthy and infected plant substrates. The advanced devices (PEN 3/MSEM 160) successfully detected healthy and diseased samples with a high variance. The results suggest that E-noses are more sensitive and accurate in detecting changes of VOCs between healthy and infected plants compared to headspace GC-MS. The study was conducted in controlled laboratory conditions, as E-noses are highly sensitive to surrounding volatiles.

Original languageEnglish
Article number117
Pages (from-to)1-17
Number of pages17
Journalchemosensors
Volume12
Issue number7
DOIs
Publication statusPublished - 24 Jun 2024

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© 2024 by the authors.

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