A study on the occurrence of Aspergillus section Nigri species on grapes from four traditional grape-producing areas in Greece during the 2011/2012 vintage, and their capability to produce OTA was conducted. One hundred and twenty-eight black aspergilli isolates were characterised at the species level initially by the use of morphological criteria in accordance with appropriate keys, followed by molecular characterisation performed with Polymerase Chain Reaction–Restriction Fragment Length Polymorphism (PCR-RFLP) of the 5.8 ribosomal RNA gene Internal Transcribed Spacer region (5.8 rRNA ITS). Restriction enzyme digestion of the ITS amplicons using the HhaI, HinfI and RsaI, endonucleases distinguished eleven different patterns of restriction fragment length polymorphism (RFLP), four for each of the HhaI and RsaI digests and three for HinfI. From a total number of 128 individual isolates, 124 were classified into four Aspergillus species corresponding to A. carbonarius, A. tubingensis, A. japonicus and A. ibericus, and the remaining 4 were classified as members of the A. niger aggregate. A. carbonarius and A. tubingensis being the main representative species were equally counted, with higher geographical representation of the former in southern and the latter in northern regions, respectively. All isolates were tested for their ochratoxigenic potential by use of High Performance Liquid Chromatography (HPLC) and Enzyme Linked Immuno Sorbent Assay (ELISA), resulting in significant interspecies differences in OTA production.

Aims: To develop and validate a logistic regression model to predict the growth and ochratoxin A (OTA) production boundaries of two Aspergillus carbonarius isolates on a synthetic grape juice medium as a function of temperature and water activity (a_w). Methods and Results: A full factorial design was followed between the factors considered. The a_w levels assayed were 0·850, 0·880, 0·900, 0·920, 0·940, 0·960, 0·980 and the incubation temperatures were 10, 15, 20, 25, 30, 35 and 40°C. Growth and OTA production responses were evaluated for a period of 25 days. Regarding growth boundaries, the degree of agreement between predictions and observations was >99% concordant for both isolates. The erroneously predicted growth cases were 3·4–4·1% false‐positives and 0·7–1·4% false‐negatives. No growth was observed at 10°C and 40°C for all a_w levels assayed, with the exception of 0·980 a_w/40°C, where weak growth was observed. Similarly, OTA production was correctly predicted with a concordance rate >98% for the two isolates with 0·7–1·4% accounting for false‐positives and 2·0–2·7% false‐negatives. No OTA production was detected at 10°C or 40°C regardless of a_w, and at 0·850 a_w at all incubation temperatures. With respect to time, the OTA production boundary shifted to lower temperatures (15–20°C) as opposed to the growth boundary that shifted to higher temperature levels (25–30°C). Using two literature datasets for growth and OTA production of A. carbonarius on the same growth medium, the logistic model gave one false‐positive and three false‐negative predictions out of 68 growth cases and 13 false‐positive predictions out of 45 OTA production cases. Conclusions: The results of this study suggest that the logistic regression model can be successfully used to predict growth and OTA production interfaces for A. carbonarius in relation to temperature and a_w. Significance and Impact of the Study: The proposed modelling approach helps the understanding of fungal‐food ecosystem relations and it could be employed in risk analysis implementation plans to predict the risk of contamination of grapes and grape products by A. carbonarius.

Mycotoxins are secondary metabolites of filamentous fungi that can cause toxic effects in human and animal health. Most of the filamentous fungi that produce these mycotoxins belong to four genera, namely, Aspergillus, Penicillium, Fusarium, and Alternaria. Mycotoxigenic fungi, along with mycotoxins, create a constant and serious economic threat for agriculture in many terms, counting product losses due to crop contamination and food spoilage, as well malnutrition when considering nutritional quality degradation. Given the importance of robust and precise diagnostics of mycotoxins and the related producing fungi in the grape food chain, one of the most important agricultural sectors worldwide, the present review initially delivers a comprehensive presentation of mycotoxin reports on grape and derived products, including a wide range of commodities such as fresh grapes, raisins, wine, juices, and other processed products. Next, based on worldwide regulations’ requirements for mycotoxins, and referring to the relative literature, this work presents methodological approaches for mycotoxin determination, and stresses major methods for the detection of fungal species responsible for mycotoxin production. The principle of function and basic technical background on the available analytical and molecular biology techniques developed—including chromatography, mass spectrometry, immunochemical-based assays, biosensors, and molecular assays—is briefly given, and references for their application to grape and derived product testing are highlighted.

Aims: To develop descriptive models for the combined effect of temperature (10–40°C) and water activity (0·850–0·980) on the growth of two ochratoxin A producing strains of Aspergillus carbonarius from Greek wine grapes on a synthetic grape juice medium. Methods and Results: Fungal growth was measured as changes in colony diameter on a daily basis. The maximum specific colony growth rates (μ_max) were determined by fitting the primary model of Baranyi describing the change in colony diameter (mm) with respect to time (days). Secondary models, relating μ_max with temperature and a_w were developed and comparatively evaluated based on polynomial, Parra, Miles, Davey and Rosso equations. No growth was observed at 0·850 a_w (water activity) regardless of temperature, as well as at marginal temperature levels assayed (10 and 40°C) regardless of water activity. The data set was fitted successfully in all models as indicated by the values of regression coefficients and root mean square error. Models with biological interpretable parameters were highly rated compared with the polynomial model, providing realistic cardinal values for temperature and a_w. The optimum values for growth were found in the range 0·960–0·970 a_w and 34–35°C respectively for both strains. The developed models were validated on independently derived data from the literature and presented reasonably good predictions as inferred by graphical plots and statistical indices (bias and accuracy factors). Conclusions: The effect of temperature and a_w on the growth of A. carbonarius strains could be satisfactorily predicted under the current experimental conditions, and the proposed models could serve as a tool for this purpose. Significance and Impact of the Study: The results could be successfully employed as an empirical approach in the development and prediction of risk models of contamination of grapes and grape products by A. carbonarius.