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The effects of meteorological conditions around silking (Si) and physiological maturity (PM) on production of fumonisins (FB=FB1 + FB2) in maize kernels were analyzed. Kernel FB contents were determined on kernel samples collected from an experimental susceptible hybrid (n = 35) and a Bt commercial hybrid (n = 23) planted in several growing seasons/sites from the Argentinean Pampas. Considering the effect of genetic divergence of the two maize hybrids,
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dc.contributor.author | Moschini, Ricardo | |
dc.contributor.author | Borsarelli, M. | |
dc.contributor.author | Martinez, Malvina Irene | |
dc.contributor.author | Presello, Daniel Alberto | |
dc.contributor.author | Ferraguti, Facundo Javier | |
dc.contributor.author | Cristos, Diego Sebastian | |
dc.contributor.author | Rojas, Dante Emanuel | |
dc.date.accessioned | 2021-04-14T11:12:51Z | |
dc.date.available | 2021-04-14T11:12:51Z | |
dc.date.issued | 2020-09-25 | |
dc.identifier.issn | 1833-928X | |
dc.identifier.other | https://doi.org/10.1007/s13313-020-00742-4 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12123/9083 | |
dc.identifier.uri | https://link.springer.com/article/10.1007%2Fs13313-020-00742-4 | |
dc.description.abstract | The effects of meteorological conditions around silking (Si) and physiological maturity (PM) on production of fumonisins (FB=FB1 + FB2) in maize kernels were analyzed. Kernel FB contents were determined on kernel samples collected from an experimental susceptible hybrid (n = 35) and a Bt commercial hybrid (n = 23) planted in several growing seasons/sites from the Argentinean Pampas. Considering the effect of genetic divergence of the two maize hybrids, total kernel FB concentrations (n = 52) binary coded, were predicted appropriately by weather-based logistic regression models but underestimated in some samples severely contaminated with FB. After removing thesemisclassified cases that registered maximum values ofa drought-heat stress index (DI) calculated over 30 days around Si, and weather conditions (assessed by weather interactive components) conducive to infection/production of FB in PM, new logistic models were fitted. These new models improved their predictive ability indices. It was remarkable a model including the discrete genetic variable and the weather variable associated with the simultaneous occurrence of precipitation, temperature between 19.5–33 °C and relative humidity >70%, required for fungal infection in Si. Models that also included weather variables calculated in PM and associated with the kernel drying rate and fungal infection, did not result in better prediction outcomes. Opposite to the general trend, the occurrence of both severe heat-drought stress around Si and favorable weather around PM led to high kernel FB contents. We hypothesize that husk shortening by stress at silking might expose ears, promoting Fusarium verticillioides colonization/FB synthesis in late stages of kernel development and maturity, whenever favorable environmental conditions for both processes prevail. | eng |
dc.format | application/pdf | es_AR |
dc.language.iso | eng | es_AR |
dc.publisher | Springer | es_AR |
dc.rights | info:eu-repo/semantics/restrictedAccess | es_AR |
dc.source | Australasian Plant Pathology 49 (6) : 665-677 (20209 | es_AR |
dc.subject | Fusarium | es_AR |
dc.subject | Mycotoxins | eng |
dc.subject | Micotoxinas | es_AR |
dc.subject | Weather Variables | eng |
dc.subject | Variables Meteorológicas | es_AR |
dc.subject | Maíz | |
dc.subject | Maize | eng |
dc.subject | Híbridos | |
dc.subject | Hybrids | eng |
dc.subject | Fumonisinas | |
dc.subject | Fumonisins | eng |
dc.subject.other | Logistic Regression Models | eng |
dc.subject.other | Modelos de Regresión Logística | es_AR |
dc.title | Analysis of preharvest meteorological conditions in relation to concentration of fumonisins in kernels of two genetically different maize hybrids | es_AR |
dc.type | info:ar-repo/semantics/artículo | es_AR |
dc.type | info:eu-repo/semantics/article | es_AR |
dc.type | info:eu-repo/semantics/publishedVersion | es_AR |
dc.description.fil | Fil: Moschini, Ricardo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina | es_AR |
dc.description.fil | Fil: Borsarelli. M. Bayer Argentina; Argentina | es_AR |
dc.description.fil | Fil: Martinez, Malvina Irene. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina | es_AR |
dc.description.fil | Fil: Presello, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Maíz; Argentina | es_AR |
dc.description.fil | Fil: Ferraguti, Facundo Javier. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina. | es_AR |
dc.description.fil | Fil: Cristos, Diego Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Tecnología de Alimentos; Argentina | es_AR |
dc.description.fil | Fil: Rojas, Dante Emanuel. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Tecnología de Alimentos; Argentina | es_AR |
dc.subtype | cientifico |
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