Detection of potato brown rot and ring rot by electronic nose: From laboratory to real scale

• Published in: Talanta (Oxford) Vol. 129; pp. 422 - 430
• Main Authors: Biondi, E., Blasioli, S., Galeone, A., Spinelli, F., Cellini, A., Lucchese, C., Braschi, I.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01-11-2014
• Subjects: Adsorption; Chemistry Techniques, Analytical; Discriminant Analysis; E-nose; Electronic Nose; Environmental Monitoring; Europe; LDA statistical analysis; PCA statistical analysis; Plant Diseases - microbiology; Ralstonia - pathogenicity; Sensorial analysis; Solanum tuberosum - microbiology; Temperature; Volatile compounds; Volatile Organic Compounds - analysis; Europe; Sensorial analysis; Volatile compounds; LDA statistical analysis; PCA statistical analysis; E-nose
• ISSN: 0039-9140; 1873-3573
• DOI: 10.1016/j.talanta.2014.04.057

A commercial electronic nose (e-nose) equipped with a metal oxide sensor array was trained to recognize volatile compounds emitted by potatoes experimentally infected with Ralstonia solanacearum or Clavibacter michiganensis subsp. sepedonicus, which are bacterial agents of potato brown and ring rot, respectively. Two sampling procedures for volatile compounds were tested on pooled tubers sealed in 0.5–1L jars at room temperature (laboratory conditions): an enrichment unit containing different adsorbent materials (namely, Tenax® TA, Carbotrap, Tenax® GR, and Carboxen 569) directly coupled with the e-nose (active sampling) and a Radiello™ cartridge (passive sampling) containing a generic Carbograph fiber. Tenax® TA resulted the most suitable adsorbent material for active sampling. Linear discriminant analysis (LDA) correctly classified 57.4 and 81.3% total samples as healthy or diseased, when using active and passive sampling, respectively. These results suggested the use of passive sampling to discriminate healthy from diseased tubers under intermediate and real scale conditions. 80 and 90% total samples were correctly classified by LDA under intermediate (100 tubers stored at 4°C in net bag passively sampled) and real scale conditions (tubers stored at 4°C in 1.25t bags passively sampled). Principal component analysis (PCA) of sensorial analysis data under laboratory conditions highlighted a strict relationship between the disease severity and the responses of the e-nose sensors, whose sensitivity threshold was linked to the presence of at least one tuber per sample showing medium disease symptoms. At intermediate and real scale conditions, data distribution agreed with disease incidence (percentage of diseased tubers), owing to the low storage temperature and volatile compounds unconfinement conditions adopted.
[Display omitted]
•A commercial electronic nose was used to detect brown and ring rot of potato.•Experiments were performed from laboratory to real scale.•At lab scale, e-nose detection threshold was correlated to tuber disease severity.•Tubers with latent infections and low disease symptoms were not detected as diseased.•At real scale, diseased tuber detection was related to disease incidence.