Discrimination of three fungal diseases of potato tubers based on volatile metabolic profiles developed using GC/MS

SummaryVolatiles from the headspace of Russet Burbank potato tubers, non-wounded non-inoculated (N-control), wounded-inoculated-with sterile water (W-control), wounded-inoculated withPhytophthora infestans, Pythium ultimum orBotrytis cinerea, respectively, were sampled at 3 and 6 days after inoculation (dai), using gas chromatography/mass spectrometry (GC/MS).Botrytis inoculated tubers produced two specific volatiles: 2-2-propenyl-l,3-dioxolane and 3, 5-heptadiyn-2-one, while thePythium inoculated tubers produced three: 2-methyl-l-butanol, 2-butanone and 2-methyl-2-butanamine. Similarly, ethoxy-ethene was specific forPhytophthora inoculated tubers. 5-l-methylethylidene-l,3-cyclopentadiene was specific to W-control tubers. Discriminant analysis models based on metabolic fingerprints of metabolites or of mass ions correctly classified 80 to 100% of the observations into respective inoculations/diseases. However, a test-validation correctly classified only 44, 50, 44, 50 and 44% of the fingerprints based on consistent metabolites and 44, 63, 38, 75 and 31% of fingerprints based on mass ions, intoBotrytis, N-control,Phytophthora, Pythium and W-control, respectively. The disease discriminatory metabolite markers and the discriminant models developed here can be used to differentiate the three diseases of Russet Burbank potato tubers, after further validation under commercial conditions.

[1]  R T Marsili,et al.  SPME-MS-MVA as an electronic nose for the study of off-flavors in milk. , 1999, Journal of agricultural and food chemistry.

[2]  Ratcliffe,et al.  Identification of volatiles generated by potato tubers (Solanum tuberosum CV: Maris Piper) infected by Erwinia carotovora, Bacillus polymyxa and Arthrobacter sp. , 1999 .

[3]  B. Costello,et al.  Gas chromatography-mass spectrometry analyses of volatile organic compounds from potato tubers inoculated with Phytophthora infestans or Fusarium coeruleum , 2001 .

[4]  John H. Loughrin,et al.  Metabolism of Natural Volatile Compounds by Strawberry Fruit , 1996 .

[5]  A. Kushalappa,et al.  Volatile Fingerprinting (SPME-GC-FID) to Detect and Discriminate Diseases of Potato Tubers. , 2002, Plant disease.

[6]  G.S.V. Raghavan,et al.  Changes in volatile production during an infection of potatoes by Erwinia carotovora , 2001 .

[7]  M. K. Pritchard,et al.  Volatile monitoring as a technique for differentiating betweenE. carotovora andC. sepedonicum infections in stored potatoes , 1984, American Potato Journal.

[8]  A. Kushalappa,et al.  USE OF VOLATILE METABOLITE PROFILES TO DISCRIMINATE FUNGAL DISEASES OF CORTLAND AND EMPIRE APPLES , 2004 .

[9]  Yvan Gariepy,et al.  AN APPARATUS TO SAMPLE VOLATILES IN A COMMERCIAL POTATO STORAGE FACILITY , 1999 .

[10]  Liangjiang Wang,et al.  The phenylpropanoid pathway and plant defence-a genomics perspective. , 2002, Molecular plant pathology.

[11]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[12]  A. Kushalappa,et al.  Volatile Metabolite Profiling for the Discrimination of Onion Bulbs Infected by Erwinia carotovora ssp. carotovora, Fusariumoxysporum and Botrytis allii , 2004, European Journal of Plant Pathology.

[13]  Ravindra Khattree,et al.  Multivariate Data Reduction and Discrimination With SAS® Software , 2001 .

[14]  Richard J. Ewen,et al.  The development of a sensor system for the early detection of soft rot in stored potato tubers , 2000 .

[15]  Margaret A. Nemeth,et al.  Applied Multivariate Methods for Data Analysis , 1998, Technometrics.

[16]  M. K. Pritchard,et al.  Production of volatile metabolites in potatoes infected by Erwinia carotovora var. carotovora and E. carotovora var. atroseptica , 1985 .

[17]  G. Raghavan,et al.  Volatile metabolic profiling for discrimination of potato tubers inoculated with dry and soft rot pathogens , 2008, American Journal of Potato Research.

[18]  Habiballah Hamzehzarghani,et al.  Volatile metabolite profiling to discriminate diseases of McIntosh apple inoculated with fungal pathogens , 2004 .

[19]  A. Kushalappa,et al.  Models to predict potato tuber infection by Pythium ultimum from duration of wetness and temperature, and leak-lesion expansion from storage duration and temperature , 2003 .

[20]  M. Wisniewski,et al.  Biological control of post-harvest diseases of fruits and vegetables: alternatives to synthetic fungicides , 1991 .

[21]  Cl Wilson,et al.  BIOLOGICAL CONTROL OF POSTHARVEST DISEASES OF FRUITS AND VEGETABLES: AN EMERGING TECHNOLOGY* , 1989 .

[22]  S. Warwick,et al.  Isozyme variation, morphology, and growth response to temperature in Pythium ultimum , 1996 .

[23]  Jerry L. Varns,et al.  Detection of disease in stored potatoes by volatile monitoring , 1979, American Potato Journal.

[24]  M. Goldstein,et al.  Multivariate Analysis: Methods and Applications , 1984 .

[25]  G. Raghavan,et al.  VOLATILE MONITORING TECHNIQUE FOR DISEASE DETECTION IN STORED POTATOES , 1990 .