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首页> 外文期刊>Agricultural Sciences >Effects of Climate and Agricultural Practices on Temporal Progress of Sclerotinia sclerotiorum for Soybean in Brazil
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Effects of Climate and Agricultural Practices on Temporal Progress of Sclerotinia sclerotiorum for Soybean in Brazil

机译：气候和农业实践对巴西菌核盘菌时间进展的影响

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Currently the soybean crop is affected by the white mold (Sclerotinia sclerotiorum). The disease can reduce the crop yield and quality and decrease the prices of agricultural lands. The aim of the current research was to assess epidemiology of white mold on soybean crop grown at Arapoti, PR, Brazil, utilizing data related to agricultural practices and local meteorological factors. The experiment was conducted in a naturally infested area. The soybean crop was sown on October 18th, 2011. The experimental design adopted herein was a randomized block in a factorial combination with 4 row spacings (0.35, 0.45, 0.60, 0.75 m) and 4 plant populations (150, 200, 250, 300 thousand plants per hectare) and 4 replications. The temporal analysis of the epidemic was evaluated using mathematical models, such as Logistics, Monomolecular and Gompertz, in order to determine the best model that described the progress of the disease as a function of local meteorological elements. For the incidence data it has been shown that both logistic and monomolecular models were those that were best fitted to the experimental data. For severity, the best model related to the experimental data was the logistic one. Either for incidence or for severity, air temperature was considered to be the environmental factor most affecting the progress of the disease. The variability in the apparent infection rates of white mold on soybean was not affected by different row spacings and plant populations; therefore, suggesting that macroclimatic variations prevailed in such a fashion to mitigate the effect of cultural practices adopted in the field.
机译：目前，大豆作物受到白色霉菌（菌核菌）的影响。该病会降低农作物的产量和质量，并降低农地的价格。本研究的目的是利用与农业实践和当地气象因素有关的数据，评估在巴西阿拉波蒂（Arapoti）种植的大豆作物上白霉病的流行病学。实验是在自然出没的地区进行的。大豆作物于2011年10月18日播种。本文采用的实验设计是因子分解组合的随机区组，具有4行间距（0.35、0.45、0.60、0.75 m）和4种植物种群（150、200、250、300）每公顷一千株）和4个复制品。使用诸如后勤，单分子和Gompertz等数学模型对流行病的时间分析进行了评估，以便确定最佳模型，该模型将疾病的进展描述为当地气象要素。对于发病率数据，已经证明逻辑模型和单分子模型都是最适合实验数据的模型。对于严重性，与实验数据相关的最佳模型是逻辑模型。无论是发病率还是严重程度，气温都被认为是最影响疾病进展的环境因素。大豆白霉病表观感染率的变异性不受行距和植物种群的影响。因此，这表明宏观气候变化以减轻该领域采用的文化习俗的影响的方式盛行。

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