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Aerobiology, epidemiology and disease forecasting of false smut disease of rice in West Bengal, India

机译:印度西孟加拉邦稻稻瘟病病的健美学,流行病学和疾病预测

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In India, since 2001, false smut disease of rice has been observed in severe form among major rice growing states. This disease is difficult to tackle, because pathogens infect the plant during flowering stage, and the symptoms are only visible after emergence of the panicle. Thus, disease forecasting is necessary to predict the chance of disease in a certain set of conditions. We analysed 3 years of aerobiological data including pathogenic spore (Ustilaginoidea virens) concentration over the rice canopy in West Bengal, India. The crop growth stages in both rabi (winter or dry) and kharif (rainy) seasons during which rapid development of false smut disease takes place were also recorded. Multiple regression analysis of per cent disease index values was done using age of the plant, pathogen concentration and meteorological factors. In dry season, the false smut disease severity depends on age of the plant as well as pathogenic spore concentration, while in rainy season, the severity depends upon spore concentration, RH and minT. From all the analysed data, it can be predicted that spore concentration is the common factor for false smut disease incidence and severity in rice. If pathogen concentration is increased by one unit, there will be 0.981 unit increased in the expected value of disease severity. With odds ratio value, it can be assumed that with a change in spore concentration by 1 unit, the odds of "Severe" versus "High" or "Moderate" or "Low" or "Absent" combined will be 1.1031 times greater, when other variables held constant. The regression model made from the present study would be beneficial to the farmers for early prediction of false smut disease of rice by estimating the spore concentration over rice canopy in West Bengal, India.
机译:在印度,自2001年以来,在主要水稻生长州的严重形式中,在严重的形式观察到稻米的假粉碎疾病。这种疾病难以解决,因为病原体在开花阶段感染植物,并且症状仅在穗产生后可见。因此,疾病预测是在某种条件下预测疾病的可能性。我们分析了在印度西孟加拉邦的水稻冠层上的致病性孢子(Ustilaginoidea Virens)浓度的3年的健美性数据。还记录了Rabi(冬季或干燥)和Kharif(雨季)季节的作物生长阶段,在此期间发生了虚假稀检的快速发展。使用植物的年龄,病原体浓度和气象因素进行百分之疾病指数值的多元回归分析。在干燥的季节中,虚假的黑穗病疾病严重程度取决于植物的年龄以及致病性孢子浓度,而在雨季,严重程度取决于孢子浓度,RH和薄荷。从所有分析的数据来看,可以预测孢子浓度是假菌疾病发病率和大米严重程度的常见因素。如果通过一个单元增加病原体浓度,则疾病严重程度的预期值将增加0.981单位。具有差距值的含量,可以假设随着孢子浓度的变化,“严重”与“高”或“低”或“低”或“低”或“缺席”的组合将是1.1031倍,当时其他变量保持不变。通过估算印度西孟加拉邦山丘覆盆子的孢子浓度,从本研究制作的回归模型对农民进行了早期预测水稻假粉末疾病。

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