Mycotoxin are toxic secondary metabolite produced by fungi able to colonize crops and thus posing a potential menace to human/animal health. Several strategies have been considered to mitigate the problem studying the variables related to mould growth and mycotoxin production. This thesis focuses on the development and validation of mechanistic models to predict mycotoxins (deoxinivalenol, fumonisins and aflatoxins) contamination in cereals (maize/ wheat) based on meteorological data. The first chapter introduce modelling theory, and patho-systems analysed. Chapter 2 focuses on trichothecenes and zearalenone occurrence in wheat produced in Italy. Predictive performance of empirical and mechanistic models for deoxnivalenol contamination in wheat were discussed in chapter 3. Chapter 4 described fumonisins and aflatoxins occurrence in maize grown in Italy. Chapters 5 and 6 analised the patho-system maize-Aspergillus flavus; the former focuses on the dynamics of A. flavus sporulation the lalatter on the development of a mechanistic model to predict aflatoxin produced by A. falvus. Another mechanistic model for Fusarium ear rot and fumosin production in maize (chapter 7). The last chapter summarised the activity done in the European project MYCORED in which several countries worldwide were involved and wheat and/or maize samples collected with data necessary for model validation.
Italian production of peanuts has recently increased. Aflatoxin B1 (AFB1) contamination of peanuts is currently not in Italy, but changing climatic conditions of the Mediterranean region may increase risks posed by this mycotoxin. A mechanistic weather-driven prototype model to predict AFB1 contamination in peanuts was developed by adapting the mechanistic AFLA-maize model for the Aspergillus flavus-peanut pathosystem. The peanut growth stages were examined to develop a phenology model based on growing degree days (GDD), which was linked to an A. flavus infection cycle model, and exploited to develop the “AFLA-peanut” prototype model. Starting from sowing, 686 GDD were required to reach flowering (as the critical growth stage for A. flavus infection), and 1925 GDD were required to reach harvesting, in a short season peanut variety. Variability of the AFB1 index, across years and locations, highlighted the capacity of AFLA-peanuts to account for weather data inputs in predicting AFB1 contamination risks. Although model validation will be mandatory to assess AFLA-peanut performance, this study has provided the first evidence that the prototype model could become an important tool for aflatoxin risk management.
Diaporthe eres, strain (PH01), isolated from defected hazelnuts and confirmed by morphological and molecular analysis (Battilani et al., 2018), was used to define the its ecological needs. Plugs from the margin of one-week old water agar (WA) plates, were transferred into the middle of Potato Dextrose Agar (PDA) Petri dishes (Ø=90 mm) and under different incubation conditions. Incubation temperature ranged between 5 and 35°C; PDA was amended to obtain different water activities (aw), between 0.90 and 0.99 (PDA modified according to Dallyn and Fox, 1980), Measurements were conducted to evaluate: i) mycelial growth, ii) pycnidial conidiomata production and iii) cirrhi occurrence. The germination of α conidia, collected from cirrhi produced by D. eres pycnidial conidiomata was observed under different T (5-45°C, step of 5°C) and relative humidity (RH; 94%, 97%, 99%), according to Ciliberti et al. (2015). In the following sheets, raw data obtained from different experiments, are reported. Sheet 'Legend' includes the list of acronyms, unit of measures and eventual explanations Sheet 'Growth (T)' includes raw data obtained measuring colony diameter (Ø, mm), at different temperatures (T, °C - ranged between 5-35°C, step of 5°C) and incubation time (t, days), in 5 replicates (rep); Sheet 'Growth (aw)' includes raw data of colony diameter growth (Ø, mm) on Potato Dextrose Agar (PDA) with modified aw (aw= 0.99, 0.98, 0.96, 0.93, 0.90), in different incubation time (t, days), in 5 replicates (rep); Sheet 'Pycnidial and cirrhi (T)' reports data of pycnidial conidiomata (n) and cirrhi (n), observed on Potato Dextrose Agar (PDA) under different temperatures regimes (T, °C - ranged between 5-35°C, step of 5°C), in different incubation time (days), in 5 replicates (rep); Sheet 'Pycnidial and cirrhi (aw)' reports data of pycnidia conidiomata (n) and cirrhi (n), observed on Potato Dextrose Agar (PDA) with modified water activity (aw= 0.99, 0.98, 0.96, 0.93, 0.90), in different incubation time (days), in 5 replicates (rep); Sheet 'Germination' includes the germinated α conidia (Germ, n) observed in trials conducted at different relative humidity (RH= 94%, 97%, 99%), at different temperatures (T, °C - from 5 to 45°C, step of 5°C), in different incubation time (6, 12, 24 and 48 h). References used in the caption: Battilani P, Chiusa G, Arciuolo R, Somenzi M, Fontana M, Castello G, Spigolon N.. Diaporthe as the main cause of hazelnut defects in the Caucasus region. Phytopathologia Mediterranea 2018; 57: 220–233. DOI: 10.14601/Phytopathol Ciliberti N, Fermaud M, Languasco L, Rossi V. Influence of fungal strain, temperature, and wetness duration on infection of grapevine inflorescences and young berry clusters by Botrytis cinerea. Phytopathology. 2015; 105(3):325-33. Epub 2014/10/30. doi: 10.1094/PHYTO-05-14-0152-R. PubMed PMID: 25354016 Dallyn H, Fox A. Spoilage of material of reduced water activity by xerophilic fungi. Society of Applied Bacteriology Technical Series, Academic Press, London. 1980:129-39.
The aim of this study was to identify the fungi associated with Turkish hazelnuts and verify and confirm the role of Diaporthe in causing kernel defects. Hazelnuts were sampled from 10 hazelnut orchards in seven Turkish provinces (Samsun, Ordu, Girensun, Trabzon, Sakarya, Düzce, and Zonguldak) during the early and full ripening stages in 2018, 2019, and 2020. Fungal isolation and identification at the genus level were performed for healthy hazelnut kernels and those with visible or hidden defects. Several fungal genera were isolated; those with a mean incidence greater than 10% were Aspergillus, Botryosphaeria, Diaporthe, Fusarium, and Penicillium. The incidence of Diaporthe spp. was higher in the full ripening stage than in the early ripening stage; it was also higher in kernels with defects than in healthy kernels. A similar pattern was observed for Botryosphaeria, but the opposite pattern was observed for Aspergillus. Diaporthe positively correlated with both hidden (ρ = 0.80) and visible defects (ρ = 0.77), confirming its key role in causing hazelnut defects. The role of Botryosphaeria appears limited to hidden defects; however, additional work is needed to substantiate this last finding. There is also a need to clarify the eventual interaction of Diaporthe with Aspergillus. The low incidence of defective hazelnuts among the 3 years of sampling precluded the role of meteorological factors in the incidence of hazelnut defects from being elucidated.
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