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Population phenology of insect pests in vegetable French bean, Phaseolus vulgaris L. and environmental forecast modeling for major pests using ARIMAX analysis

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Abstract

Nineteen insect species from four major insect orders viz., Hemiptera, Lepidoptera, Coleoptera, and Orthoptera, were found belong to sixteen families damaging common bean, which is also known as French bean cultivation in subtropical climates. Among the insect pests, sucking insects occupies maximum incidence; aphid, Aphis craccivora Koch incidence was peak in both seasons 2018 (77.4 aphids/plant) and 2019 (77.6 aphids/plant) during 8th SMW followed by Leafhoppers, Empoasca kerri Pruthi (6.4 Nos/plant). The impact of weather factors on the insect populations showed that minimum temperature negatively correlated with aphids (r =—0.189), leafhopper (r = -0.315) populations and positively correlated with whitefly, Bemisia tabaci Gennadius (r = 0.118) and thrips, Thrips palmi Karny population (r = 0.052). Relative humidity and rainfall were negatively correlated with French bean sucking pests. In defoliators, serpentine leaf miner, Liriomyza trifolii Burgess larvae incidence was high in both seasons (18.4 larva/plant) and (20.6 larva/plant) followed by hairy caterpillar, Euproctis fraterna Moore (1.4 larva/plant) and leaf folder, Nacoleia spp (1.15 larvae/plant). Among the pod borers, spotted pod borer, Maruca vitrata incidence was higher than others and influenced by both maximum (r = 0. 791) and minimum temperature (r = 0.714). Relative humidity and wind speed parameters were negatively correlated with pod borers viz., M. vitrata Fabricius and Helicoverpa armigera Hubner respectively. The model ARIMAX (3, 0, 0) of aphids showed that the incidence of the pest depended on the weather parameters such as minimum temperature, relative humidity, and rainfall significantly. The ARIMAX (2, 0, 0) model of M. vitrata showed that the weather parameters such as maximum temperature, minimum temperature and relative humidity played a significant role in the incidence of the M. vitrata.

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References

  • Bierens HJ (1987) ARIMAX model specification testing, with an application to unemployment in the Netherlands. J Econom 35:161–190

    Article  Google Scholar 

  • Boopathi T, Singh SB, Manju T, Ramakrishna Y, Akoijam RS, Chowdhury S, Singh NH, Ngachan SV (2015) Development of temporal modeling for forecasting and prediction of the incidence of lychee, Tessaratoma papillosa (Hemiptera: Tessaratomidae), using time-series (ARIMA) analysis. J Insect Science 15:55

    Article  Google Scholar 

  • Boopathi T, Singh SB, Manju T, Dutta SK, Singh AR, Chowdhury S, Ramakrishna Y, Dayal V, Lungmuana (2017) Temporal modeling for forecasting of the incidence of litchi stink bug using ARIMAX analysis. Indian J Hortic 74:604–607

    Article  Google Scholar 

  • Cavanaugh JE (1997) Unifying the derivations for the Akaike and corrected Akaike information criteria. Stat Probabil Lett 33:201–208

    Article  Google Scholar 

  • Elango K, Jeyarajan Nelson S (2020) Population dynamics of exotic rugose spiralling whitefly, Aleurodicus rugioperculatus Martin (Hemiptera: Aleyrodidae) on coconut as influenced by weather factors and natural enemies. J Plant Crops 48:120–125

    Article  Google Scholar 

  • Elango K, Nelson SJ, Dineshkumar P (2021) Incidence forecasting of new invasive pest of coconut rugose spiraling whitefly (Aleurodicus rugioperculatus) in India using ARIMAX analysis. J Agrometeorol 23:194–199

    Article  Google Scholar 

  • Ghoshal S (2013) Population dynamics and biochemical fluctuations in relation to the infestation of tetranychus neocaledonichus andre on the leaves of Tulsi (Ocimum sanctum). Int J Life Sci Biotechnol Pharm Res 2:225–231

    Google Scholar 

  • Jakkaray BC, Hanumanthaswamy S, Adivappar N (2020) Seasonal incidence of lepidopteran pests in French bean (Phaseolus vulgaris L.) Int J Ecol Environ Sci 2:312–315

  • Jhansi Rani B, Hanumantharaya L (2016) Population dynamics of insect pests of French bean under hill zone of Karnataka. Adv Life Sci 5:1951–1956

  • Kannan M, Rao NV (2006) Incidence of homopteran pests in relation to weather conditions in mango. Indian J Ecol 33:146–149

    Google Scholar 

  • Kishor DR, Prasad R, Moses S, Singh PP (2019) Population dynamics of aphid and pod borer on lentil and their natural enemies during rabi Season 2017 at Pusa, Samastipur. Curr Appl Sci Technol 32:1–6

    Article  Google Scholar 

  • Kooner BS, Chhabra KS (1980) Pests of pulse crops and their control. In: Gill KS (ed) Breeding Methods for Improvement of Pulse crops. Punjab Agric. Univ, Ludhiana (India), pp 132–141

    Google Scholar 

  • Kumar RP, Singh ON, Singh Y, Singh JP (2006) Integrated nutrient management for quantitative and qualitative yield of French bean (Phaseolus vulgaris L.). Veg Sci 33:155–159

  • Lohr B (2006) High value crops research and development: The ICIPE experience. International Centre of Insect Physiology and Ecology, Nairobi, Kenya

    Google Scholar 

  • Mallikarjuna J, Kumar CTA, Chakravarthy AK, Revadi S (2012) Seasonal incidence and abundance of pod borers in Dolichos bean, Lablab purpureus L. (Sweet) in Bengaluru, Karnataka, South India. Curr Biotica 6:107–112

    Google Scholar 

  • Mondal A, Shankar U, Abrol DP, Kumar A, Singh AK (2018) Incidence of major insect pests on french bean and relation to environmental variables. Indian J Entomol 80:51–55

    Article  Google Scholar 

  • Naik MG (2014) Studies on population dynamics, varietal screening, and management of spotted pod borer, Maruca vitrata (geyer) in blackgram. M. Sc. (Agri.) Thesis, Univ. Agril. Sci., Dharwad, Karnataka (India). 23–25

  • Narava R, DV SR, Jaba J, GV RR, Mishra SP, Kukanur V (2022) Development of temporal model for forecasting of Helicoverpa armigera (Noctuidae: Lepidopetra) Using Arima and artificial neural networks. J Insect Sci 22:2

    Article  PubMed  PubMed Central  Google Scholar 

  • Nderitu J, Mwangi F, Nyamasyo G, Kasina M (2009) Evaluation of cropping systems as a strategy for managing snap bean flower thrips in Kenya. Int J Sustain Crop Produc 4:22–25

    Google Scholar 

  • Nderitu JH, Mwangi F, Nyamasyo G, Kasina M (2010) Utilization of synthetic and botanical insecticides to manage thrips (Thysan.: Thrip.) on snap beans (Fabaceae) in Kenya. Int J Sustain Crop Produc 5:1–4

    Google Scholar 

  • Patel SK, Patel BH, Korat DM, Dabhi MR (2010) Seasonal incidence of major insect pests of cowpea, Vigna unguiculata (Linn.) Walpers in relation to weather parameters. Karnataka J Agric Sci 23:497–499

    Google Scholar 

  • Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6(2). https://doi.org/10.1214/aos/1176344136

  • Thejaswi L, Mohan I, Naik MM (2010) Studies on population dynamics of pest complex of field bean (lablab purpureus l.) and natural enemies of pod borers. Karnataka J Agric Sci 21:399–402

    Google Scholar 

  • Tomar SPS (2014) Impact assessment of plant protection technologies for management of insect pest and disease in fruits. Ann Pl Protec Sci 22:34–38

    Google Scholar 

  • Tripathi SM, Singh AK, Singh DC, Kumar P (2018) Evaluation of IPM modules for management of sucking pests and pod borers of Mung bean, Vigna radiata (L.) Wilczek. Ann Plant Protec Sci 26:25–27

    Article  Google Scholar 

  • Ulrichs CH, Mewis I (2004) Evaluation of the efficacy of Trichogramma evanescens Westwood (Hym., Trichogrammatidae) inundative releases for the control of Maruca vitrata F. (Lep., Pyralidae). J Appl Entomol 128:426–431

    Article  Google Scholar 

  • Van Heerden SM, Schonfeldt HC (2004) The need for food composition tables for Southern Africa. J Food Compos Anal 17:531–537

    Article  Google Scholar 

  • Yadav KS, Pandya HV, Patel SM, Patel SD, Saiyad MM (2015a) Population dynamics of major insect pests of cowpea [Vigna ungiculata (L.) Walp.]. Int J Plant Protec 8:112–117

    Article  Google Scholar 

  • Yadav SR, Kumawat KC, Khinchi SK (2015b) Efficacy of new insecticide molecules and bioagents against sucking insect pests of cluster bean, Cyamopsis tetragonoloba (Linn.) Taub. Legume Res: an Int J 38:407–441

    Article  Google Scholar 

Download references

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M. Kannan—Conceptualization, Methodology, investigation, data collection, writing the original draft; K. Elango—Data curation, Writing-reviewing, formal analysis; S. A. Jayaprakash – Data curing and analysis; P. Dinesh Kumar- ARIMAX model analysis of the data and interpretation; K. Govindaraju—Review & editing.

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Kannan, M., Elango, K., Jayaprakash, S.A. et al. Population phenology of insect pests in vegetable French bean, Phaseolus vulgaris L. and environmental forecast modeling for major pests using ARIMAX analysis. Int J Trop Insect Sci 43, 475–484 (2023). https://doi.org/10.1007/s42690-023-00947-2

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