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Gas chromatography-mass spectrometry (GC/MS) technology was used to profile volatile metabolites from the headspace gas of McIntosh apple (Malus domestica Borkh.), which were noninoculated or inoculated with four different fungi, Botrytis cinerea Pers, Penicillium expansum Link, Mucor piriformis Fischer and Monilinia sp. The study yielded a total of 498 different volatile metabolites. Among them only 35 occurred relatively consistently in six replicates over three incubation periods. Of the consistent metabolites, 20 were specific to one or more inoculation agents/diseases, including seven that were unique to apples inoculated with different pathogens. Fluoroethene and 3,4-dimethyl-1-hexene were specific for Penicillium, while butanoic acid butyl ester, 4-methyl-1-hexene and 2-methyltetrazole were specific for Mucor. Similarly, acetic acid methyl ester and fluoroethane were specific to Botrytis and Monilinia, respectively. The method developed in this study can be used by storage managers to detect apple diseases at an early stage of disease progress and use this to manage apple diseases in storage, after further validation under commercial conditions.

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Volatile metabolites from headspace gas of carrot cv. Vita-treat inoculated with water or four different pathogens Botrytis cinerea, Erwinia carotovora subsp. carotovora, Aspergillus niger and Fusarium avenaceum were profiled using gas chromatography and mass spectrometry to develop a technology to discriminate diseases. The inoculation of carrot roots with water or different pathogens released a total of 137 different volatile metabolites. Among them, 39 compounds were relatively consistent and 11 were specific to one or more diseases/ inoculations. E. carotovora subsp. carotovora produced seven disease-specific metabolites: 1-butanol, 3-methyl; 1-pentanol; 1-propanol, 2-methyl; 2,3butanedione; boronic acid, ethyl; butane, 1-methoxy-3-methyl; and ethane, ethoxy. Some metabolites were disease/inoculation discriminatory and were not detected in all treatments: 1,2-dimethoxy-ethene was common in carrots inoculated with E. carotovora subsp. carotovora and B. cinerea, while 2-butanone, 3-chloro-4-hydroxy-1,4-diphenyl was common in carrots inoculated with E. carotovora subsp. carotovora, F. avenaceum and water-inoculated control. The significant mass ions, based on univariate analysis, from a total of 150 (46-195 m/z) and compounds from a total of 32 were further subjected to stepwise discriminant analysis and discriminant analysis. The models for 3 days after inoculation (DAI) were better than those for 6 DAI and 3 + 6 DAI, where up to 90% of the observations were correctly classified into respective inoculations. The disease-discriminatory compounds from different diseases/inoculations and discriminant analysis models developed here have the potential for the early detection and discrimination of postharvest diseases of carrot cv. Vita-treat, after validation under commercial conditions.

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The volatile metabolites from the headspace gas of containerised mango ( Mangifera indica ) cv. Tommy Atkins fruits, surface wounded and inoculated with the two fungal anamorphic pathogens Colletotrichum gloeosporioides and Lasiodiplodia theobromae , or non-inoculated (controls), were profiled using a portable gas chromatograph/mass spectrometer to discriminate diseases of mango. Thirty-four compounds were detected relatively consistently among replicates. Several of these were disease/inoculation-discriminatory and were classified into three groups: (i) compounds unique to only one treatment; (ii) compounds common to two or more treatments, but not to all; and (iii) compounds common to all treatments, but varying in their abundance. Two compounds, 1-pentanol and ethyl boronate, were detected in L. theobromae-inoculated mangoes alone, while thujol was observed only in C. gloeosporioides-inoculated mangoes. Discriminant analysis models based on the abundance of significant mass ions and consistent compounds correctly classified diseases/inoculations in up to 100% of cases. The disease-discriminatory compounds and discriminant analysis models developed here have the potential to be used in the early detection of postharvest diseases of mango fruits after validation under commercial conditions.