Relevant bibliographies by topics / Insect Pest Prediction

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Insect Pest Prediction'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Insect Pest Prediction"

1

Chaturvedi, Gaurav, Gudipati Naveen, Ulfat Jan, et al. "Predicting Insect Pest Outbreaks Using Climate Models and Remote Sensing." UTTAR PRADESH JOURNAL OF ZOOLOGY 46, no. 5 (2025): 103–9. https://doi.org/10.56557/upjoz/2025/v46i54827.

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Insect pest outbreaks threaten agricultural productivity and global food security. Predicting their outbreaks is crucial for implementing effective pest management strategies. Traditional pest control measures often rely on reactive interventions, leading to significant economic losses. However, climate models and remote sensing technologies have emerged as powerful tools for predicting pest outbreaks before they occur. Climate models analyze atmospheric conditions to forecast pest behaviour, while remote sensing provides real-time data on environmental factors influencing pest populations. Th
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Saleem, Rana Muhammad, Rafaqat Kazmi, Imran Sarwar Bajwa, Amna Ashraf, Shabana Ramzan, and Waheed Anwar. "IOT-Based Cotton Whitefly Prediction Using Deep Learning." Scientific Programming 2021 (July 10, 2021): 1–17. http://dx.doi.org/10.1155/2021/8824601.

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Agriculture is suffering from the problem of low fertility and climate hazards such as increased pest attacks and diseases. Early prediction of pest attacks can be very helpful in improving productivity in agriculture. Insect pest (whitefly) attack has a high influence on cotton crop yield. Internet of Things solution is proposed to predict the whitefly attack to take prevention measures. An insect pest prediction system (IPPS) was developed with the help of the Internet of Things and a RBFN algorithm based on environmental parameters such as temperature, humidity, rainfall, and wind speed. Pe
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Marković, Dušan, Dejan Vujičić, Snežana Tanasković, Borislav Đorđević, Siniša Ranđić, and Zoran Stamenković. "Prediction of Pest Insect Appearance Using Sensors and Machine Learning." Sensors 21, no. 14 (2021): 4846. http://dx.doi.org/10.3390/s21144846.

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The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect’s appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance
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Wallhead, Matthew, and Heping Zhu. "Decision Support Systems for Plant Disease and Insect Management in Commercial Nurseries in the Midwest: A Perspective Review1." Journal of Environmental Horticulture 35, no. 2 (2017): 84–92. http://dx.doi.org/10.24266/0738-2898-35.2.84.

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Abstract Decision-support systems (DSS) are techniques that help decision makers utilize models to solve problems under complex and uncertain conditions. Predicting conditions that warrant intervention is a key tenet of the concept of integrated pest management (IPM) with the use of expert systems and pest models being characteristics of higher-level IPM. In this paper, potentials of four DSS including Ag-Radar, NEWA, RIMpro and Skybit to be used for ornamental nursery production are discussed. These systems were previously developed for orchard growers to effectively manage plant diseases and
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Nitta, Anusha, Vijayakumari Natarajan, Ankireddy Jawahar Reddy, and Thandra Rakesh. "Impact of Climate Change on Pest Biology, Behaviour and Their Distributions." International Journal of Environment and Climate Change 14, no. 4 (2024): 46–56. http://dx.doi.org/10.9734/ijecc/2024/v14i44094.

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Increased temperatures, rising CO2 levels, and changing precipitation patterns are influencing agricultural production. These changes can lead to the expansion of insect pests geographic distribution, increased survival during overwintering, more generations per year, altered synchrony with plants, changed interspecific interactions, higher risk of invasion by migratory pests, increased incidence of insect-transmitted plant diseases, and reduced effectiveness of biological control. There is a serious risk of economic losses in crop production. Human food security is challenged due to potential
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Mandanayake, M. A. R. A., U. G. A. I. Sirisena, A. M. K. R. Bandara, et al. "Temporal variation of insect pest populations of rice and their relationship with meteorological variables in Batalagoda, Sri Lanka." Tropical Agriculturist 166, no. 1 (2018): 119–30. https://doi.org/10.4038/ta.v166i1.112.

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Climate and weather substantially influence on the development and distribution of insects. Forecasting of insect pest outbreaks requires data on insects and climatic information from a thoroughly maintained data base. In Sri Lanka, there are several meteorological stations recording climatic information for over many years; unfortunately, details on the insect pest population are limited. Therefore, the present study was designed to collect information on major insect pest of rice in order to study their population dynamics over the time. A light-trap survey was carried out during 2007-2014 t
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Otuka, Akira. "Prediction of the Overseas Migration of the Fall Armyworm, Spodoptera frugiperda, to Japan." Insects 14, no. 10 (2023): 804. http://dx.doi.org/10.3390/insects14100804.

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(1) Background: The fall armyworm, Spodoptera frugiperda, is an invasive migratory insect pest that first arrived in Japan in early July 2019. Since then, the species has immigrated to Japan mainly in the summer monsoon season and inflicted damage mainly on the maize used as animal feed in the western region, where major immigrations occur. In this study, to know the precise arrival timing and area of S. frugiperda for purposes of pest management, a prediction method for its overseas migration from neighboring source areas was developed. (2) Methods: The method uses the Weather Research and Fo
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AMANA, ASIF LODHI, KAZMI* RAFAQAT, IKRAM SUNNIA, IKRAM AMNA, and AQSA. "IOT BASED TOMATO FLEA BEETLE PEST PREDICTION USING NAÏVE BAYES ALGORITHM FOR SMART FARMING." Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology 56, no. 08 (2023): 198–208. https://doi.org/10.5281/zenodo.8296356.

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<strong>Abstract</strong> Insect pest have great influence in vegetable crop growth. It can be minimized by prediction of insect pest using environmental parameters, IOT and machine learning algorithms. The directly sensed environment conditions are used as input to the machine learning model to make binary decisions regarding the pest population according to the prevailing environmental conditions. After implementation in field 89.2% accuracy have achieved by using na&iuml;ve bayes binary algorithm. The f1, recall, precision and support evaluation metrices have been used for algorithm evaluat
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Wang, Yong, and Zhuang Xiong. "Prediction of the Forest Health Based on BP Neural Networks." Advanced Materials Research 726-731 (August 2013): 4303–6. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.4303.

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This paper simple introduced back propagation (BP) neural networks, and constructed a dynamic predict model, based on it to predict forest disease and insect and rat pest. Then it analyzed and simulated with the BP neural network model with the data produced in the recent ten years. The result indicated that the BP neural network model is reliable for predicting the forest disease and insect and rat pest. The method provides scientific foundation for the forestry management of studied area.
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Chen, Zhenfu, Yang Luo, Liang Wang, et al. "Advancements in Life Tables Applied to Integrated Pest Management with an Emphasis on Two-Sex Life Tables." Insects 16, no. 3 (2025): 261. https://doi.org/10.3390/insects16030261.

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Life tables are indispensable in IPM, offering an analysis of insect population dynamics. These tables record survival rates, fecundity, and other parameters at various developmental stages, enabling the identification of key factors that affect population numbers and the prediction of growth trajectories. This review discusses the application of life tables in agricultural pest management, including the assessment of the pest control capacity of natural enemies, the evaluation of biological agents, and the screening of insect-resistant plant species. In vector insect control, life tables are
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Dissertations / Theses on the topic "Insect Pest Prediction"

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Philips, Christopher Robin. "Food webs and phenology models: evaluating the efficacy of ecologically based insect pest management in different agroecosystems." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/51813.

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Integrated pest management (IPM) is defined as an effective and environmentally sensitive approach to pest management that relies on a combination of common-sense practices. Integrated pest management programs use current, comprehensive information on the life cycles of pests and their interactions with host plants and the environment. This information, in combination with available pest control methods, is used to manage pest populations by the most economical means, and with the least possible hazard to people, property, and the environment. True IPM takes advantage of all appropriate pest m
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Schutze, Mark Kurt. "The significance of genetic and ecological diversity in a wide-ranging insect pest, Paropsis atomaria Olivier (Coleoptera: Chrysomelidae)." Queensland University of Technology, 2008. http://eprints.qut.edu.au/16666/.

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Paropsis atomaria (Coleoptera; Chrysomelidae) is a eucalypt feeding leaf beetle endemic to southern and east coast Australia, and it is an emergent pest of the eucalypt hardwood industry. Paropsis atomaria was suspected to be a cryptic species complex based on apparent differences in life history characteristics between populations, its wide geographical distribution, and extensive host range within Eucalyptus. In this study genetic and ecological characters of P. atomaria were examined to determine the likelihood of a cryptic complex, and to identify the nature and causes of ecological variat
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Schutze, Mark Kurt. "The significance of genetic and ecological diversity in a wide-ranging insect pest, Paropsis atomaria Olivier (Coleoptera: Chrysomelidae)." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/16666/1/Mark_Kurt_Schutze_Thesis.pdf.

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Paropsis atomaria (Coleoptera; Chrysomelidae) is a eucalypt feeding leaf beetle endemic to southern and east coast Australia, and it is an emergent pest of the eucalypt hardwood industry. Paropsis atomaria was suspected to be a cryptic species complex based on apparent differences in life history characteristics between populations, its wide geographical distribution, and extensive host range within Eucalyptus. In this study genetic and ecological characters of P. atomaria were examined to determine the likelihood of a cryptic complex, and to identify the nature and causes of ecological variat
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Wan, Jing. "Prediction of the potential geographic distributions and risk assessment of four trade impacting invasive insect pests in Australia and China." Thesis, Wan, Jing (2020) Prediction of the potential geographic distributions and risk assessment of four trade impacting invasive insect pests in Australia and China. PhD thesis, Murdoch University, 2020. https://researchrepository.murdoch.edu.au/id/eprint/61455/.

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This thesis explores biological invasion through the potential pest distribution and risk analysis of tomato potato psyllid (TPP), Bactericera cockerelli; fall armyworm (FAW), Spodoptera frugiperda; Bactrocera bryoniae; and Bactrocera neohumeralis. Through better understanding of the pest distribution and risk analysis agricultural management policies can be implemented, and containment and eradication actions taken. The TPP is a psyllid native to North America that has recently invaded Australia. The potential for economic losses accompanying invasions of TPP and its associated bacterial
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(6635369), John Jay Ternest. "Integrating Pest and Pollinator Management: Assessing the Impact of Commercial Watermelon Production on Pests and Pollinators." Thesis, 2019.

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Fruit set in cucurbit crops such as watermelon is entirely dependent upon pollinators, which makes them an important aspect of grower management. This reliance on pollinators means that growers must consider them when making pest management decisions, especially when using pesticides, which can have a negative impact on pollinators. Thus, pest management in watermelon production faces a potential trade-off between pests and pollinators. The ways in which growers manage this trade-off could have a large impact on the communities of both groups and the yield of the crop. <br>
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Books on the topic "Insect Pest Prediction"

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W, Onstad David, ed. Insect resistance management: Biology, economics, and prediction. Elsevier, 2008.

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Onstad, David W., and Lisa M. Knolhoff. Insect Resistance Management: Biology, Economics, and Prediction. Elsevier Science & Technology, 2022.

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Insect Resistance Management: Biology, Economics, and Prediction. Elsevier Science & Technology Books, 2013.

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Onstad, David W. Insect Resistance Management: Biology, Economics, and Prediction. Elsevier Science & Technology Books, 2013.

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Onstad, David W., and Lisa M. Knolhoff. Insect Resistance Management: Biology, Economics, and Prediction. Elsevier Science & Technology Books, 2022.

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Onstad, David W. Insect Resistance Management: Biology, Economics, and Prediction. Elsevier Science & Technology Books, 2007.

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Book chapters on the topic "Insect Pest Prediction"

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Venette, Robert C., Doria R. Gordon, Jennifer Juzwik, et al. "Early Intervention Strategies for Invasive Species Management: Connections Between Risk Assessment, Prevention Efforts, Eradication, and Other Rapid Responses." In Invasive Species in Forests and Rangelands of the United States. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45367-1_6.

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AbstractManaging invasive species becomes increasingly difficult and expensive as populations of new pathogens, plants, insects, and other animals (i.e., pests) spread and reach high densities. Research over the past decade confirms the value of early intervention strategies intended to (1) prevent invasive species from arriving within an endangered area or (2) detect and respond quickly to new species incursions (Baker et al. 2009; Ewel et al. 1999; Holden et al. 2016; Leung et al. 2014). The goal of such biosecurity approaches is to keep or return the density of invasive species to zero so t
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Sridhar, Vaddi, and Poluru Venkata Rami Reddy. "Use of Degree Days and Plant Phenology: A Reliable Tool for Predicting Insect Pest Activity Under Climate Change Conditions." In Climate-Resilient Horticulture: Adaptation and Mitigation Strategies. Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-0974-4_25.

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Leybourne, Daniel J., Mark Ramsden, Sacha White, et al. "Online decision support systems, remote sensing and artificial intelligence applications for wheat pest management." In Advances in understanding insect pests affecting wheat and other cereals. Burleigh Dodds Science Publishing, 2023. http://dx.doi.org/10.19103/as.2022.0114.21.

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Infestation with herbivorous insects and other invertebrates (“pests”) can be extremely damaging to wheat production, potentially resulting in up to 80% yield loss. Reducing the damage caused by these pests is a central component of crop protection practices. Decision Support Systems (DSS) are interactive systems (usually software based) that help users identify and solve problems and make decisions as part of an IPM strategy. DSS play an important role in pest management, especially in relation to treatment application. DSS can be used as an umbrella term for any software-based support system
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Ramdinthara, Immanuel Zion, and Shanthi Bala P. "Issues and Challenges in Smart Farming for Sustainable Agriculture." In Modern Techniques for Agricultural Disease Management and Crop Yield Prediction. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9632-5.ch001.

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Sustainable agriculture helps to promote farming practices and methods in order to sustain farmers and resources. It is economically viable, socially supportive, and economically sound. It assists to maintain soil quality, reduce soil erosion and degradation, and also save water resources. Sustainable agriculture improves the biodiversity of the land and thus leads to the healthy and natural environment. The sustainable agriculture is very essential to ordinate with the increasing demand for the food, climate change, and degradation of the ecosystem in future. It plays a major role for preserv
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AMIRI, Nassima, Mohammed Yacoubi Khebiza, and Mohammed Messouli. "The Impact of Climate Change on Insect Pests Damaging Crops." In Climate Change and the Economic Importance and Damages of Insects. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-4824-3.ch004.

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Climate change affects the physiology of insects by accelerating their metabolism, growth, and reproduction, which increases their density, and ultimately leads to the consumption and infestation of crops damaged, this action, contributes to economic losses, especially in countries where agriculture plays an important role in their economic sector. This chapter aims to identify how the climatic parameters, in particular the rise in temperature that promotes the development of its insect pests, also causes the action of expanding their distribution, and further reduces biological control, espec
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von Well, Eben, Mardé Booyse, and Annabel Fossey. "Gamma Irradiation as Tool for Mutation Breeding in Wheat." In Wheat [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.111713.

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Mutation breeding is used to modify a specific character of a plant, while all other characteristics remain the same. Adaptation obtained through mutation breeding to biotic (disease and insect pest resistance) and abiotic (aluminum toxicity, drought, high temperature, salt tolerance) stresses leads to better harvest growth, yield and quality. The main aim is to promote the efficiency of energy conversion into growth as a tool for the prediction of the optimal gamma irradiation dosage for mutation breeding in wheat. Cytogenetic analysis done on Triticum turgidum ssp. durum cv. Orania will be p
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Dharmireddy, Ajay Kumar, Kambham Jacob Silva Lorraine, Ravi Kumar Maddumala, and Kotha Lavanya. "Pesticide Prediction and Disease Identification with AIoT." In The Future of Agriculture: IoT, AI and Blockchain Technology for Sustainable Farming. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815274349124010007.

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Agriculture is vital to human survival and has a significant impact on the economy of any nation. Crop protection costs millions of dollars per year. Insects and other pests pose a serious threat to the health of a harvest. Excessive use of chemical fertilizers and pesticides negatively affects the crop and soil quality. Therefore, one way to safeguard the harvest and mitigate potential losses is through early identification of the pests. Examining the crop at the right moment is the best technique to determine its overall health. While manual inspection is the standard way of conducting field
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Vänninen, Irene. "Advances in insect pest and disease monitoring and forecasting in horticulture." In Improving integrated pest management in horticulture. Burleigh Dodds Science Publishing, 2022. http://dx.doi.org/10.19103/as.2021.0095.05.

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Pest monitoring in horticulture is developing technologically to reduce time and labor needed for sampling and to produce more accurate pest predictions. New ways of detecting pests based on selective e-traps, e-noses, cameras and acoustic signatures are already in use or emerging. Remote sensing of pests requires the development of new economic injury levels and economic thresholds (ET). The relative importance of mechanistic and statistical models is changing due to AI-technologies and Big Data. The use of Big Data will force researchers to collect, use and value data differently than before
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Vittum, Patricia J. "Principles of Integrated Pest Management." In Turfgrass Insects of the United States and Canada. Cornell University Press, 2020. http://dx.doi.org/10.7591/cornell/9781501747953.003.0025.

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This chapter examines the principles of integrated pest management (IPM). IPM often is defined as a program that, in the context of the environment and the population dynamics of pests, uses many different techniques and strategies in as compatible a manner as possible to maintain pest population levels below those causing economic injury. The concept of IPM was initially developed in traditional agriculture, where the success of a crop was measured in economic yield (quantity and quality of produce). The key to such agricultural IPM programs has always been establishing consistent and reliabl
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Myers, Judith H. "Predicting the Outcome of Biological Control." In Evolutionary Ecology. Oxford University Press, 2001. http://dx.doi.org/10.1093/oso/9780195131543.003.0035.

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The movement of humans around the earth has been associated with an amazing redistribution of a variety of organisms to new continents and exotic islands. The natural biodiversity of native communities is threatened by new invasive species, and many of the most serious insect and weed pests are exotics. Classical biological control is one approach to dealing with nonindigenous species. If introduced species that lack natural enemies are competitively superior in exotic habitats, introducing some of their predators (herbivores), diseases, or parasitoids may reduce their population densities. Th
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Conference papers on the topic "Insect Pest Prediction"

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"Migration prediction of overseas migratory insect pest." In Monitoring and Early Warning of Plant Pest and Disease Epidemics in Response to Climate Change. Food and Fertilizer Technology Center for the Asian and Pacific Region, 2021. http://dx.doi.org/10.56669/gils1769.

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Devi, Kharibam Jilenkumari, Maibam Mangalleibi Chanu, Gunakar Challa, Shuma Adhikari, and Khelchandra Thongam. "Identification of insect pests and prediction of pesticides using YOLOv4 deploying onto UbiOps." In PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON INNOVATIONS IN ELECTRONICS AND COMMUNICATION SYSTEMS (ICIECS2022). AIP Publishing, 2025. https://doi.org/10.1063/5.0247101.

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