“AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination
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 contamin...
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| Format: | Article |
| Language: | English |
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Firenze University Press
2024-12-01
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| Series: | Phytopathologia Mediterranea |
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| Online Access: | https://oajournals.fupress.net/index.php/pm/article/view/15771 |
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| author | Matteo CROSTA Marco CAMARDO LEGGIERI Paola BATTILANI |
| author_facet | Matteo CROSTA Marco CAMARDO LEGGIERI Paola BATTILANI |
| author_sort | Matteo CROSTA |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-5d4bfff304cf42518bbbdedbc8e6c475 |
| institution | OA Journals |
| issn | 0031-9465 1593-2095 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Firenze University Press |
| record_format | Article |
| series | Phytopathologia Mediterranea |
| spelling | doaj-art-5d4bfff304cf42518bbbdedbc8e6c4752025-08-20T02:11:29ZengFirenze University PressPhytopathologia Mediterranea0031-94651593-20952024-12-0163348148810.36253/phyto-1577114608“AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contaminationMatteo CROSTA0https://orcid.org/0009-0002-2238-8395Marco CAMARDO LEGGIERI1https://orcid.org/0000-0002-6547-7702Paola BATTILANI2https://orcid.org/0000-0003-1287-1711Department of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, Piacenza, ItalyDepartment of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, Piacenza, ItalyDepartment of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, Piacenza, ItalyItalian 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.https://oajournals.fupress.net/index.php/pm/article/view/15771 aspergillus flavusmodel transferweatherphenologymycotoxinclimate change |
| spellingShingle | Matteo CROSTA Marco CAMARDO LEGGIERI Paola BATTILANI “AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination Phytopathologia Mediterranea aspergillus flavus model transfer weather phenology mycotoxin climate change |
| title | “AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination |
| title_full | “AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination |
| title_fullStr | “AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination |
| title_full_unstemmed | “AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination |
| title_short | “AFLA-peanut”, a mechanistic prototype model to predict aflatoxin B1 contamination |
| title_sort | afla peanut a mechanistic prototype model to predict aflatoxin b1 contamination |
| topic | aspergillus flavus model transfer weather phenology mycotoxin climate change |
| url | https://oajournals.fupress.net/index.php/pm/article/view/15771 |
| work_keys_str_mv | AT matteocrosta aflapeanutamechanisticprototypemodeltopredictaflatoxinb1contamination AT marcocamardoleggieri aflapeanutamechanisticprototypemodeltopredictaflatoxinb1contamination AT paolabattilani aflapeanutamechanisticprototypemodeltopredictaflatoxinb1contamination |