Next Article in Journal
Clinical Evaluation of a Mobile Sensor-Based Gait Analysis Method for Outcome Measurement after Knee Arthroplasty
Next Article in Special Issue
Development of a Wireless Computer Vision Instrument to Detect Biotic Stress in Wheat
Previous Article in Journal
Development of Phase Detection Schemes Based on Surface Plasmon Resonance Using Interferometry
Previous Article in Special Issue
A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method
Open AccessArticle

Detection of Potato Storage Disease via Gas Analysis: A Pilot Study Using Field Asymmetric Ion Mobility Spectrometry

School of Engineering, University of Warwick, Coventry CV4 7AL, UK
Warwick Crop Centre, School of Life Sciences, University of Warwick, Wellesbourne, Warwick CV35 9EF, UK
Author to whom correspondence should be addressed.
Sensors 2014, 14(9), 15939-15952;
Received: 16 June 2014 / Revised: 21 August 2014 / Accepted: 22 August 2014 / Published: 28 August 2014
(This article belongs to the Special Issue Agriculture and Forestry: Sensors, Technologies and Procedures)
PDF [595 KB, uploaded 29 August 2014]


Soft rot is a commonly occurring potato tuber disease that each year causes substantial losses to the food industry. Here, we explore the possibility of early detection of the disease via gas/vapor analysis, in a laboratory environment, using a recent technology known as FAIMS (Field Asymmetric Ion Mobility Spectrometry). In this work, tubers were inoculated with a bacterium causing the infection, Pectobacterium carotovorum, and stored within set environmental conditions in order to manage disease progression. They were compared with controls stored in the same conditions. Three different inoculation time courses were employed in order to obtain diseased potatoes showing clear signs of advanced infection (for standard detection) and diseased potatoes with no apparent evidence of infection (for early detection). A total of 156 samples were processed by PCA (Principal Component Analysis) and k-means clustering. Results show a clear discrimination between controls and diseased potatoes for all experiments with no difference among observations from standard and early detection. Further analysis was carried out by means of a statistical model based on LDA (Linear Discriminant Analysis) that showed a high classification accuracy of 92.1% on the test set, obtained via a LOOCV (leave-one out cross-validation). View Full-Text
Keywords: FAIMS; soft rot; potato storage disease; early disease detection FAIMS; soft rot; potato storage disease; early disease detection
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Rutolo, M.; Covington, J.A.; Clarkson, J.; Iliescu, D. Detection of Potato Storage Disease via Gas Analysis: A Pilot Study Using Field Asymmetric Ion Mobility Spectrometry. Sensors 2014, 14, 15939-15952.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top