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11140009 Early Detection of Potato Storage Diseases by Gas Analysis

Publication Date: 
1 February 2013
Author/Contact :
Massimo Rutolo

Contractor :
University of Warwick

Full Research Project Title: Early Detection of Potato Storage Diseases by Gas Analysis
Duration: October 2012 - December 2016

Industry Challenge

Storage diseases of potatoes cause major losses each year for the industry. Diseased potatoes and in particular those associated with bacterial soft rots release specific volatile compounds which if recognised would allow early detection and diagnosis, enabling store managers to initiate preventative measures. Early detection of Pectobacterium carotovorum in store is therefore extremely desirable if the disease is to be controlled and contained.


University of Warwick, FERA, Owlstone Nanotech and Sutton Bridge Crop Storage Research (SBCSR) 


This approach will also be investigated for detection of important quarantine diseases of potato in contained import consignments. Other sensors such as the latest electronic noses will also be assessed. The project will be multidisciplinary involving novel approaches to instrument engineering, volatile identification, data analysis and plant pathology.


a) Collect pathogen isolates and develop/adapt methodologies for artificial inoculation of potato tubers focussing on P. carotovorum but also including selected fungal pathogens and the quarantine pathogens Ralstonia. solanacearum and Clavibacter michiganensis.

b) Develop and optimise methodology for recording volatile fingerprints over time for healthy and diseased potato tubers in controlled laboratory conditions using FAIMS and compare with other sensor technologies such as electronic nose.

c) Determine the effect of environmental conditions on volatile release and detection.

d) Identify characteristic volatiles for each disease using gas chromatography-mass spectrometry (GC-MS) and develop a database of FAIMS fingerprints associated with these target molecules.

e) Develop intelligent systems analysis, such as neural networks and genetic algorithms to optimise FAIMS / electronic nose to improve recognition of the target signals.

f) Determine the efficacy of FAIMS / electronic nose to detect diseases in experimental potato stores. Further optimise volatile fingerprint detection.

g) Determine the efficacy of FAIMS / electronic nose to detect diseases in commercial potato stores.

Key Findings

The main finding is that in all laboratory work all gas sensing technologies (though not all sensors) were proven to be effective for both pre-symptomatic and symptomatic detection of soft rot.


The use of gas phase detection and monitoring of potato soft rot infection in store

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