2025

Now showing 1 - 2 of 2

A fractional model for insect management in agricultural fields utilizing biological control
(Springer Science and Business Media Deutschland GmbH, 2025) Arvind Kumar Misra; Akash Yadav; Ebenezer Bonyah
Bio-insecticides, such as baculoviruses, are the most well-known and environment friendly alternative to chemical insecticides in agriculture. In this research work, our main goal is to develop a sustainable and effective approach to control insect population by using the potential of baculoviruses. To achieve this, we formulate a novel fractional-order model utilizing the Caputo fractional operator to meticulously analyze the effects of baculovirus as a biological insecticide on insect population and consequently on crop yield. Since the virus density depletes rapidly due to ultraviolet (UV) radiation, enzymatic attacks, temperature variations and other factors in the crop field, a one-time spray of bio-insecticide may not be effective in controlling insects within a sufficient time frame. Therefore, we posit that the spraying of baculovirus is proportional to the density of the susceptible insects. The dynamic behavior of the baculovirus model underscores the critical influence of the fractional-order derivative in shaping the system’s behavior and stability. Additionally, the model analysis brings to light the intricate interplay between virus replication rate and virus infection rate in regulating insect density. To further enhance the model’s applicability, we also propose a fractional optimal control strategy to effectively reduce the insect density and associated costs, taking into account the time-dependent spraying rate of the virus. Numerical results obtained using the Adams–Bashforth–Moulton method, corroborate our analytical insights and underscore the importance of fractional-order derivative in this context. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
When to perform cloud seeding for maximum agricultural crop yields? A modeling study
(Emerald Publishing, 2025) Arvind Kumar Misra; Gauri Agrawal; Akash Yadav
Purpose – Agricultural crops play a crucial role in food security and require commensurating environmental conditions, including adequate rainfall to ensure optimum growth. However, in the recent past, a reduction in the agriculture crop yield has been observed due to the deteriorating rainfall pattern. This paper aims to present a novel mathematical model to analyze the impact of rainfall on the growth of agriculture crops, as well as the impact of cloud seeding for promoting the rainfall, in case of less rainfall to ensure the optimum growth of agriculture crops. Design/methodology/approach – The authors formulate a mathematical model assuming that the growth of agriculture crops wholly depends on rainfall. Also, agricultural crops can sustain and give optimal yields at a threshold of rainfall, after which rainfall negatively affects the growth rate of agriculture crops. Further, if the agriculture crops get insufficient rain to grow, the authors assume that cloud seeding agents are introduced in the regional atmosphere in proportion to the density of cloud droplets to increase rainfall. Findings – This research shows that while cloud seeding agents boost crop yield, excessive rainfall poses significant risks on the yield. For any given value of (conversion of cloud droplets into raindrops because of introduced cloud seeding agents), we have identified the threshold value of (introduction rate of cloud seeding agents into clouds) where crop yield can be maximized. Research limitations/implications – This model highlights the delicate balance between rainfall and cloud seeding, offering policymakers valuable insights for maximizing agricultural crop yields. Originality/value – This research provides strategies to mitigate crop loss due to unpredictable rainfall patterns. © 2024 Emerald Publishing Limited

2025

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