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 these misclassified cases that registered maximum values of a 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.

中文翻译：

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两种遗传不同玉米杂交种籽粒中伏马菌素浓度相关的收获前气象条件分析

分析了吐丝期（Si）和生理成熟度（PM）周围气象条件对玉米籽粒伏马菌素产量（FB=FB1+FB2）的影响。籽粒 FB 含量是根据从阿根廷潘帕斯草原的几个生长季节/地点种植的实验性易感杂交种 (n = 35) 和 Bt 商业杂交种 (n = 23) 收集的籽粒样品确定的。考虑到两个玉米杂交种的遗传差异的影响，总内核 FB 浓度（n = 52）二进制编码，通过基于天气的逻辑回归模型进行了适当的预测，但在一些被 FB 严重污染的样品中被低估了。在删除这些错误分类的案例后，这些案例记录了在 Si 周围 30 天内计算的干旱热应激指数 (DI) 的最大值，和天气条件（通过天气交互组件评估）有利于 PM 中 FB 的感染/产生，安装了新的逻辑模型。这些新模型改进了它们的预测能力指数。一个包含离散遗传变量和与降水同时发生相关的天气变量的模型非常引人注目，温度在 19.5-33 °C 之间，相对湿度 >70%，这是 Si 中真菌感染所需的。还包括以 PM 计算并与谷粒干燥率和真菌感染相关的天气变量的模型，并没有产生更好的预测结果。与总体趋势相反，Si 周围出现严重的热干胁迫和 PM 周围的有利天气导致高内核 FB 含量。