Combined impact of predatory insects and bio-pesticide over pest population: impulsive model-based study

Fahad Al Basir , Jahangir Chowdhury , Suvendu Das , Santanu Ray

Energy, Ecology and Environment ›› 2022, Vol. 7 ›› Issue (2) : 173 -185.

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Energy, Ecology and Environment ›› 2022, Vol. 7 ›› Issue (2) : 173 -185. DOI: 10.1007/s40974-021-00226-1
Original Article

Combined impact of predatory insects and bio-pesticide over pest population: impulsive model-based study

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Abstract

The production with increasing demands maintaining the balance of nature and natural diversity is the most challenging part of the agricultural system. However, pests and other insect populations are significant obstacles to the continuous food supply. This study proposes a crop pest management mathematical model using the predator (pests’ natural enemy) and viral infection through bio-pesticides. Impulsive differential equations have been implemented to study the dynamics between all populations, considering the repetitive release of virus micro-pesticides and predator insects in the crop field. The hypothesized model gives the outlook of complex natural dynamics. Two types of scenarios have been analyzed here using the model: One deals with the complete eradication of the field’s pest population, and another is sounder from a biodiversity conservation perspective, that defines the minimum pest population below the economic injury level, which is, nowadays, the major challenge in the agricultural field. Numerical examples show that pest management is successful when considering the minimum pest level that keeps the economic threshold by optimizing predator and virus levels cost-effectively.

Keywords

Integrated Pest Management (IPM) / Mathematical modeling and simulations / Viral infection / Predatory insect / Impulsive differential equation / Economic injury level (EIL)

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Fahad Al Basir, Jahangir Chowdhury, Suvendu Das, Santanu Ray. Combined impact of predatory insects and bio-pesticide over pest population: impulsive model-based study. Energy, Ecology and Environment, 2022, 7(2): 173-185 DOI:10.1007/s40974-021-00226-1

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References

[1]

Abbas N, Shad SA, Razaq M. Fitness cost, cross resistance and realized heritability of resistance to imidacloprid in Spodoptera litura (Lepidoptera: Noctuidae). Pestic Biochem Phys, 2012, 103(3): 181-188

[2]

Abraha T, Al Basir F, Obsu LL, Torres DF. Pest control using farming awareness: Impact of time delays and optimal use of biopesticides. Chaos Soliton Fract, 2021, 146: 110869

[3]

Al Basir F, Elaiw AM, Ray S. Effect of time delay in controlling crop pest using farming awareness. Int J Appl Comput Math, 2019, 5(4): 1-9

[4]

Al Basir F. A multi-delay model for pest control with awareness induced interventions-Hopf bifurcation and optimal control analysis. Int J Biomath, 2020, 13(06): 2050047

[5]

Barclay HJ. Models for pest control using predator release, habitat management and pesticide release in combination. J Appl Ecol, 1982, 19: 337-348

[6]

Barclay HJ. Models for pest control: complementary effects of periodic releases of sterile pests and parasitoids. Theor Popul Biol, 1987, 32(1): 76-89

[7]

Bhattacharyya S, Bhattacharya DK. Pest control through viral disease: mathematical modeling and analysis. J Theor Biol, 2006, 238(1): 177-197

[8]

Croft BA. Arthropod biological control agents and pesticides, 1990 London Wiley

[9]

Chowdhury J, Al Basir F, Pal J, Roy PK. Pest control for Jatropha curcas plant through viral disease: a mathematical approach. Nonlinear Stud, 2016, 23(4): 515-30

[10]

Chattopadhyay P, Banerjee G, Mukherjee S. Recent trends of modern bacterial insecticides for pest control practice in integrated crop management system. 3 Biotech, 2017, 7(1): 60

[11]

Eizi Y. Effects of intraguild predation and interspecific competition among biological control agents in augmentative biological control in greenhouses, 2005 Davos USDA Forest Service Publication 523-530

[12]

Flexner J, Lighthart B, Croft BA. The effects of microbial pesticides on non-target, beneficial arthropods. Agric Ecosyst Environ, 1986, 16(3–4): 203-254

[13]

Freedman HI. Graphical stability, enrichment, and pest control by a natural enemy. Math Biosci, 1976, 31(3–4): 207-225

[14]

Georgescu P, Zhang H. An impulsively controlled predator-pest model with disease in the pest. Nonlinear Anal Real World Appl, 2010, 11(1): 270-287

[15]

Ghosh S, Bhattacharyya S, Bhattacharya DK. The role of viral infection in pest control: a mathematical study. Bull Math Biol, 2007, 69(8): 2649-2691

[16]

Idris AL, Fan X, Muhammad MH, Guo Y, Guan X, Huang T. Ecologically controlling insect and mite pests of tea plants with microbial pesticides: a review. Arch Microbiol, 2020, 17: 1

[17]

Jana S, Kar TK. A mathematical study of a prey–predator model in relevance to pest control. Nonlinear Dyn, 2013, 74(3): 667-83

[18]

Kar TK, Ghorai A, Jana S. Dynamics of pest and its predator model with disease in the pest and optimal use of pesticide. J Theor Biol, 2012, 310: 187-198

[19]

Katti G. Biopesticides for insect pest management in rice-present status and future scope. J Rice Res, 2013, 6(1): 1-15

[20]

Kropff MJ, Teng PS, Rabbinge R. The challenge of linking pest and crop models. Agric Syst, 1995, 49(4): 413-434

[21]

Liu B, Teng Z, Chen L. Analysis of a predator-prey model with Holling II functional response concerning impulsive control strategy. J Comput Appl Math, 2006, 193(1): 347-362

[22]

Liu B, Zhang Y, Chen L. Dynamic complexities of a Holling I predator–prey model concerning periodic biological and chemical control. Chaos Soliton Fract, 2004, 22(1): 123-134

[23]

Liu B, Zhang Y, Chen L. Dynamic complexities in a Lotka–Volterra predator–prey model concerning impulsive control strategy. Int J Bifur Chaos, 2005, 15(02): 517-531

[24]

Lakshmikantham V, Simeonov PS. Theory of impulsive differential equations, 1989 Singapore World Scientific

[25]

Tian Y, Tang S, Cheke RA. Dynamic complexity of a predator–prey model for IPM with nonlinear impulsive control incorporating a regulatory factor for predator releases. Math Model Anal, 2019, 24(1): 134-54

[26]

Perdikis D, Fantinou A, Lykouressis D. Enhancing pest control in annual crops by conservation of predatory Heteroptera. Biol Control, 2011, 59(1): 13-21

[27]

Luff ML. The potential of predators for pest control. Agric Ecosyst Environ, 1983, 10(2): 159-81

[28]

Ostad-Ali-Askari K, Shayannejad M. Quantity and quality modelling of groundwater to manage water resources in Isfahan-Borkhar Aquifer. Environ Dev Sustain, 2021

[29]

Ostad-Ali-Askari K, Shayannejad M, Ghorbanizadeh-Kharazi H. Artificial neural network for modeling nitrate pollution of groundwater in marginal area of Zayandeh-rood River, Isfahan, Iran. KSCE J Civ Eng, 2017, 21(1): 134-140

[30]

Páez CJ, Jungmann D, Siegmund S. Modeling and analysis of integrated pest control strategies via impulsive differential equations. Int J Diff Eqns, 2017

[31]

Páez CJ, Jungmann D, Siegmund S. A comparative study of integrated pest management strategies based on impulsive control. J Biol Dyn, 2018, 12(1): 318-41

[32]

Prokopy R, Kogan M (2009) Integrated pest management. In: Encyclopedia of insects. Academic Press, pp 523–528

[33]

Sajap AS, Kotulai JR, Kadir HA, Hussein MY. Impact of prey infected by nuclear polyhedrosis virus on a predator, Sycanus leucomesus Walk (Hem., Reduviidae). J Appl Entomol, 1999, 123(2): 93-97

[34]

Samada LH, Tambunan US. Biopesticides as promising alternatives to chemical pesticides: a review of their current and future status. OnLine J Biol Sci, 2020, 20(2): 66-76

[35]

Tang S, Chen L. Modelling and analysis of integrated pest management strategy. Dis Cont Dyn Syst B, 2004, 4(3): 759

[36]

Tang S, Tang G, Cheke RA. Optimum timing for integrated pest management: modelling rates of pesticide application and natural enemy releases. J Theor Biol, 2010, 264(2): 623-638

[37]

van Lenteren JC Biological control using invertebrates and microorganisms: plenty of new opportunities. Biocontrol, 2018, 63(1): 39-59

[38]

Tuan S-J Economic injury level and demography-based control timing projection of Spodoptera litura (Lepidoptera: Noctuidae) at different growth stages of Arachis hypogaea. J Econom Entomol, 2017, 110(2): 755-762

[39]

Wei DAI Selectivity and sublethal effects of some frequently-used biopesticides on the predator Cyrtorhinus lividipennis Reuter (Hemiptera: Miridae). J Integrative Agric, 2019, 18(1): 124-133

[40]

Wilby A, Thomas MB. Are the ecological concepts of assembly and function of biodiversity useful frameworks for understanding natural pest control?. Agric For Entomol, 2002, 4(4): 237-43

[41]

Yu H, Zhong S, Agarwal RP. Mathematics analysis and chaos in an ecological model with an impulsive control strategy. Commun Nonlinear Sci Numer Simul, 2011, 16(2): 776-786

Funding

University Grants Commission

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