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<p>Maydis leaf blight (<i>Bipolaris maydis</i>) is a&#xa0;menace to global maize cultivation. Majority of genotypes or varieties of maize are suffering from the infection of MLB disease. Therefore, the investigation was conducted to determine the influence of meteorological variables, develop a&#xa0;suitable weather-based forewarning model, and evaluate novel fungal-toxicants with and without combination. Maximum temperature and crop age had a&#xa0;positive relationship (<i>p</i> &lt; 0.01), while minimum temperature, mean temperature, afternoon RH, and mean RH had a&#xa0;negative relationship (<i>p</i> &lt; 0.01) with PDI and AUDPC. Further, stepwise linear regression analysis revealed that the weather variable, minimum temperature, and crop age had the strongest relationship with PDI and AUDPC of MLB, which recorded more than 99.16 &amp; 99.38% of variability, respectively. Six growth models (Logistic, Weibull, Monomolecular, Gompertz, Exponential, and Linear) were examined, Among them, the logistic model was found the best-fitted model by recording the lowest AIC and BIC values (i.e., 35.214 &amp; 36.344 for PDI and 84.937 &amp; 86.067 for AUDPC), which not only predicts the severity and the progress curve of disease but also determines the timing of the application of novel fungi-toxicants. The management study demonstrated that two foliar sprays of pre-mixtures of Azoxystrobin + Tebuconazole and Pyraclostrobin + Epoxiconazole recorded lowest PDI and AUDPC and highest PDC and found most effective and cheapest fungicides against MLB disease of maize.</p>

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Development and Evaluation of a Weather-based Forewarning Model for Managing Maydis Leaf Blight in Maize Using Novel Fungicides

  • 期刊论文

  • 发表日期：

    2026年2月19日

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  • Jitendar Kumar Sharma,
  • Vijay Kamal Meena,
  • Lekha,
  • Harsh Vardhan Singh Shekhawat,
  • Kapil Choudhary,
  • Kapil Sharma,
  • Neeshu Joshi,
  • Shourabh Joshi,
  • Sita Ram Kumawat,
  • H. P. Patel

摘要

Maydis leaf blight (Bipolaris maydis) is a menace to global maize cultivation. Majority of genotypes or varieties of maize are suffering from the infection of MLB disease. Therefore, the investigation was conducted to determine the influence of meteorological variables, develop a suitable weather-based forewarning model, and evaluate novel fungal-toxicants with and without combination. Maximum temperature and crop age had a positive relationship (p < 0.01), while minimum temperature, mean temperature, afternoon RH, and mean RH had a negative relationship (p < 0.01) with PDI and AUDPC. Further, stepwise linear regression analysis revealed that the weather variable, minimum temperature, and crop age had the strongest relationship with PDI and AUDPC of MLB, which recorded more than 99.16 & 99.38% of variability, respectively. Six growth models (Logistic, Weibull, Monomolecular, Gompertz, Exponential, and Linear) were examined, Among them, the logistic model was found the best-fitted model by recording the lowest AIC and BIC values (i.e., 35.214 & 36.344 for PDI and 84.937 & 86.067 for AUDPC), which not only predicts the severity and the progress curve of disease but also determines the timing of the application of novel fungi-toxicants. The management study demonstrated that two foliar sprays of pre-mixtures of Azoxystrobin + Tebuconazole and Pyraclostrobin + Epoxiconazole recorded lowest PDI and AUDPC and highest PDC and found most effective and cheapest fungicides against MLB disease of maize.