Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy
Fumonisins are major mycotoxins found worldwide in maize and maize products. Because of their toxicity for both human and animals, European Union regulations were created to fix the maximal fumonisin B1 and B2 content allowed in foods and feeds. Unfortunately, directly measuring these mycotoxins by...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Journal of Chemistry |
| Online Access: | http://dx.doi.org/10.1155/2015/485864 |
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| author | Cecile Levasseur-Garcia Sylviane Bailly Didier Kleiber Jean-Denis Bailly |
| author_facet | Cecile Levasseur-Garcia Sylviane Bailly Didier Kleiber Jean-Denis Bailly |
| author_sort | Cecile Levasseur-Garcia |
| collection | DOAJ |
| description | Fumonisins are major mycotoxins found worldwide in maize and maize products. Because of their toxicity for both human and animals, European Union regulations were created to fix the maximal fumonisin B1 and B2 content allowed in foods and feeds. Unfortunately, directly measuring these mycotoxins by current analytical techniques is tedious and expensive and most measurement methods do not lend themselves to online control. Alternative approaches to chemical analysis have been developed and involve models that allow the mycotoxin contamination to be predicted based on environmental conditions and analysis by near-infrared (NIR) spectroscopy. In the present work, we use NIR spectroscopy to determine the fumonisin and fungal contents of 117 samples of maize. The determination coefficient between fumonisin and fungal-biomass content was 0.44. We establish herein a threshold for the number of CFUs for fungal biomass beyond which the fumonisin content is likely to exceed the European regulatory level of 4000 μg/kg. In addition, we determine the fungal content by using a NIR-spectroscopy model that allows us to sort samples of maize. Upon calibration, the percentage of well-classified samples was 96%, which compares favorably to the 82% obtained by independent verification. |
| format | Article |
| id | doaj-art-56b5a3881c024744b1f31d394535b410 |
| institution | Kabale University |
| issn | 2090-9063 2090-9071 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Chemistry |
| spelling | doaj-art-56b5a3881c024744b1f31d394535b4102025-02-03T06:10:51ZengWileyJournal of Chemistry2090-90632090-90712015-01-01201510.1155/2015/485864485864Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared SpectroscopyCecile Levasseur-Garcia0Sylviane Bailly1Didier Kleiber2Jean-Denis Bailly3Université de Toulouse, Ecole d’Ingénieurs de Purpan, INPT, LCA, 31076 Toulouse Cedex 03, FranceINRA, UMR1331, Research Centre in Food Toxicology (Toxalim), 31027 Toulouse, FranceDépartement Sciences Agronomiques et Agroalimentaires, Université de Toulouse, Ecole d’Ingénieurs de Purpan, INPT, 31076 Toulouse Cedex 03, FranceINRA, UMR1331, Research Centre in Food Toxicology (Toxalim), 31027 Toulouse, FranceFumonisins are major mycotoxins found worldwide in maize and maize products. Because of their toxicity for both human and animals, European Union regulations were created to fix the maximal fumonisin B1 and B2 content allowed in foods and feeds. Unfortunately, directly measuring these mycotoxins by current analytical techniques is tedious and expensive and most measurement methods do not lend themselves to online control. Alternative approaches to chemical analysis have been developed and involve models that allow the mycotoxin contamination to be predicted based on environmental conditions and analysis by near-infrared (NIR) spectroscopy. In the present work, we use NIR spectroscopy to determine the fumonisin and fungal contents of 117 samples of maize. The determination coefficient between fumonisin and fungal-biomass content was 0.44. We establish herein a threshold for the number of CFUs for fungal biomass beyond which the fumonisin content is likely to exceed the European regulatory level of 4000 μg/kg. In addition, we determine the fungal content by using a NIR-spectroscopy model that allows us to sort samples of maize. Upon calibration, the percentage of well-classified samples was 96%, which compares favorably to the 82% obtained by independent verification.http://dx.doi.org/10.1155/2015/485864 |
| spellingShingle | Cecile Levasseur-Garcia Sylviane Bailly Didier Kleiber Jean-Denis Bailly Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy Journal of Chemistry |
| title | Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy |
| title_full | Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy |
| title_fullStr | Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy |
| title_full_unstemmed | Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy |
| title_short | Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy |
| title_sort | assessing risk of fumonisin contamination in maize using near infrared spectroscopy |
| url | http://dx.doi.org/10.1155/2015/485864 |
| work_keys_str_mv | AT cecilelevasseurgarcia assessingriskoffumonisincontaminationinmaizeusingnearinfraredspectroscopy AT sylvianebailly assessingriskoffumonisincontaminationinmaizeusingnearinfraredspectroscopy AT didierkleiber assessingriskoffumonisincontaminationinmaizeusingnearinfraredspectroscopy AT jeandenisbailly assessingriskoffumonisincontaminationinmaizeusingnearinfraredspectroscopy |