Pest Population Density Research Articles

An effective farmer-centred mobile intelligence solution using lightweight deep learning for integrated wheat pest management

Integrated Pest Management (IPM) techniques have been widely used in agriculture to manage pest damage in the most economical way and to minimise harm to people, property and the environment. However, current research and products on the market cannot consolidate this process. Most existing solutions either require experts to visually identify pests or cannot automatically assess pest levels and make decisions based on detection results. To make the process from pest identification to pest management decision making more automated and intelligent, we propose an end-to-end integrated pest management solution that uses deep learning for semi-automated pest detection and an expert system for pest management decision making. Specifically, a low computational cost sampling point generation algorithm is proposed to enable mobile devices to generate uniformly distributed sampling points in irregularly shaped fields. We build a pest detection model based on YoloX and use Pytorch Mobile to deploy it on mobile phones, allowing users to detect pests offline. We develop a standardised sampling specification and a mobile application to guide users to take photos that allow pest population density to be calculated. A rule-based expert system is established to derive pest management thresholds from prior agricultural knowledge and make decisions based on pest detection results. We also propose a human-in-the-loop algorithm to continuously track and update the validity of the thresholds in the expert system. The mean average precision of the pest detection model is 58.17% for 97 classes, 75.29% for 2 classes, and 57.33% for 11 classes on three pest datasets, respectively. The usability of the pest management system is assessed by the User Experience Surveys and achieves a System Usability Scale (SUS) score of 76. The usability of the proposed solution is validated by qualitative field experiments.

Effect of biotic and abiotic factors on the population dynamics of Nilaparvata lugens in the middle Gangetic Plains of India

Aim: To investigate the effect of biotic and abiotic factors on the population dynamics of brown planthopper Nilaparvata lugens (Stal) (Hemiptera: Delphacidae) in the middle Gangetic plains of India. Methodology: Field trials were conducted in the middle Gangetic plains of India at Agricultural Research Farm, B.H.U., Varanasi, Uttar Pradesh, India during Kharif season of 2018 and 2019 on the variety Swarna sub-1 to study the population dynamics and certain biotic and abiotic interaction with brown planthopper. Results: During Kharif 2018 and 2019, the highest mean number of brown planthopper population (45.00 ± 2.31 and 39.33 ±1.82 nos., respectively) were recorded during September in both seasons. Abiotic factors such as rainfall (r = - 0.556), relative humidity in the morning (r = 0.476), maximum temperature (r = 0.511), and sunshine hour (r = - 0.546) influenced planthopper population dynamics, and predictions were made with reasonable accuracy (R2 = 0.89) using the principal component regression analysis technique. Crop phenology was the most influential biotic factor on pest population density. The crop's booting stage had the highest incidence of planthoppers. Three different predatory populations (wolf spider, damselfly and ladybird beetle) were observed to feed on planthoppers in Kharif 2018 and four different predatory populations (wolf spider, damselfly, ladybird beetle and green mirid bug) were observed to feed on planthoppers in Kharif 2019, resulting in a reduction in crop pest density. Interpretation: These findings can be used to develop the precise management strategies for brown planthopper in the rice ecosystem. Key words: Abiotic, Biotic factors, Brown planthopper, Crop phenology, Middle Gangetic Plains, Natural enemies, Rice

Evaluating the impact of alyssum flower strips on biological control of key pests in flue‐cured tobacco agroecosystems

AbstractFlue‐cured tobacco, Nicotiana tabacum (L.), is often attacked by various pests such as aphids, whiteflies and tobacco budworm. Insecticide application has been the primary method in managing these pests for Yunnan Province. However, it is necessary to look for more sustainable strategies that can help control pests. In this context, conservation biological control is a highly promising alternative, involving the cultivation or conservation of flowering plants within the agricultural ecosystem to attract and support natural enemies. The objective of this study was to evaluate the potential of alyssum, Lobularia maritima (L.) Desv., in attracting natural enemies and managing pests in flue‐cured tobacco cultivation. The study conducted two field experiments over successive years, each with of two treatments and three replicates, arranged in a completely randomized design. The treatments were (1) tobacco monoculture and (2) tobacco intercropped with alyssum flower strips. The population density of natural enemies and pests was monitored weekly throughout the study period. The results showed that the presence of alyssum flowers in the tobaccosalyssum treatment significantly increased the abundance of generalist predators such as syrphids, rove beetles, carabids, Orius sp. and spiders during both experiments. This increase in predator population led to a substantial reduction in tobacco pests, particularly aphids. Intercropping alyssum with tobacco can serve as an effective strategy for managing pests specific to the Nicotiana plant, as well as addressing the limited availability of approved insecticides for this crop. This approach may help to mitigate pest‐related issues and reduce the reliance on insecticides in tobacco cultivation, contributing to more sustainable pest management practices.

Performance of Artificial Diets for Zelus renardii (Hemiptera: Reduviidae) Rearing.

Mass production is a prerequisite for using natural enemies in integrated pest management and organic farming. Natural enemies in agroecosystems include predators that prey on insects, which they can subdue while maintaining adequate pest population densities. The Leafhopper Assassin Bug (LAB), Zelus renardii, can be a natural enemy in agroecosystems, selecting its prey for size and mobility. Some of LAB's prey include Philaenus spumarius (L.), Bactrocera oleae (Rossi), Drosophila suzukii (Matsumura), and Macrohomotoma gladiata Kuwayama, suggesting this reduviid for biocontrol agent in various contexts. We reared LABs for two subsequent broods offering living prey and artificial diets. Our data show that the rearing of Z. renardii is feasible with oligidic, meridic, and holidic artificial formulations. Four artificial diets allowed the complete post-embryonic development of LABs in captivity for two successive generations. The accumulated degree-days (ADDs) accurately predict the growth of LABs based on heat accumulation, estimating that up to three generations could grow per year in captivity at the experimented T°C.

Effects of the area of source habitat and habitat connectivity on soybean pod borer damage: Implications for area-wide management

The soybean pod borer, Leguminivora glycinivorella (Matsumura), is an important soybean pest that reduces both quality and yield in Asia, and chemical control is used irrespective of the damage risk. The pest population density increases at continuously cropped soybean fields (hereafter, source habitat). The present study would contribute to proposing pest management options matched to the damage risk by clarifying the surrounding landscape structures where damage is likely to increase. First, we clarified the relationship between the probability of grain damage and the source habitat within a 350 m radius of the new or continuously cropped soybean fields. The habitat area surrounding continuous soybean fields positively influenced the probability of grain damage but did not detect a significant effect in new soybean fields. Secondly, we clarified the relationship between the probability of grain damage and habitat connectivity in continuous soybean fields. Well-managed fields with high connectivity consistently showed low damage risk. Meanwhile, damage risk varied in fields with low connectivity, indicating that damage is unlikely to occur because soybean pod borers are difficult to invade. However, once invaded, the damage could be extensive. Considering these results, one possible new control system will allow the spatiotemporal variation in the number of insecticide applications. The present study likely contributes to understanding the relationship between soybean pod borer injury and landscape structure, which is important for area-wide pest management.

MODELING THE EFFECTS OF PESTS AND PESTICIDE ON CROP YIELDS IN A MULTIPLE CROPPING SYSTEM

Pest infestation poses a significant threat to agricultural crop yields, and to control it, farmers spray chemical pesticides. The persistent use of these chemical agents not only leads to pesticide residues within crops but also exerts collateral damage on the beneficial pest population. In this research work, we formulate a nonlinear mathematical model to assess the impacts of pesticide on crop yields within a multiple cropping system. Model analysis illustrates that crop consumption rates destabilize, and the spraying rate of pesticide stabilizes the system. Furthermore, we determine conditions for the global stability of the coexisting equilibrium and conduct a global sensitivity analysis to identify model parameters that significantly influence pest population density. Our findings emphasize that, for effective pest population control and enhanced crop yields, farmers should choose either pesticides with a high pest abatement rate or those with a higher pesticide uptake rate. Considering the spraying rate of pesticide as time-dependent, we also suggest an optimal control strategy to minimize the pest population and associated costs. We provide analytical results backed by numerical simulations implemented through the non-standard finite difference scheme to support our findings.

Influence of Different Vegetable Plants on the Population Density of some Piercing-Sucking Insect pests

Influence of Different Vegetable Plants on the Population Density of some Piercing-Sucking Insect pests

Impact of diet composition of <I>Corcyra cephalonica</I> (Lepidoptera: Pyralidae) on the development and reproduction of <I>Trichogramma chilonis</I> (Hymenoptera: Trichogrammatidae)

Utilizing parasitoids for augmentative biological control frequently depends on the physiological state of the parasitoids and the pest population density at the time of release. Trichogramma chilonis Ishii (Hymenoptera: Trichogrammatidae) is commonly used as an egg parasitoid for biological insect pest control via augmentation and field release. A crucial component of mass production programmes is the host’s nutritional compatibility. So, the investigations were carried out to study the effect of diet composition of Corcyra cephalonica (Stainton) (Lepidoptera: Pyralidae) on developmental and reproductive parameters of Trichogramma chilonis Ishii. The T. chilonis was reared on Corcyra cephalonica fed on different diets (D1-D7) in the laboratory at 25℃±1℃ with 75±5% RH. Based on pooled data of two generations T. chilonis had shown significantly highest parasitization of 85.80%, adult emergence percentage 75.00% and sex-ratio 1.62:1 on rice moth eggs obtained from Maize (48.5%) + Sorghum (48.5%) + Groundnut (3%) diet (D5). Trichogramma adult’s emergence was observed earlier (3.10 days) on the host’s eggs reared on the Bajra (100%) diet (D1). In case of adult longevity, the maximum longevity of 7.70 days was recorded on the host’s egg obtained from the D5 diet over the others. These findings may help to improve the developmental and reproductive performance of T. chilonis and an optimized D5 diet may be useful for mass rearing of this egg parasitoid.

An Autoregulatory Model of Forest Insect Population Dynamics and Forest Stand Damage Dynamics in Different Habitats: An Example of Lymantria dispar L.

This paper addresses the problem of constructing a mathematical model of population density dynamics and the dynamics of forest areas damaged by spongy moth (Lymantria dispar L.) outbreaks in the United States, Europe, Russia, and Japan. The key variable of the model is either the pest population density or the area of forests damaged by spongy moths during a season. This variable can be considered proportional to the total current pest abundance in the study area. For the purposes of modeling, data from a number of different authors was used (see bibliography), as well as data from surveys conducted at the egg or caterpillar stage. The complexity of modeling the dynamics of L. dispar abundance is largely due to the fact that, when studying the dynamics of spongy moth population density, the values of external factors such as parasites, predators, and the amount of available food are often unknown. A simple model was proposed using only two types of data: population density and monthly weather characteristics. Our analysis demonstrated that, even in the absence of knowledge regarding the characteristics of ecosystem components interacting with the spongy moth population (parasites, predators, and the state of forage trees), it is possible to introduce models that characterize the regulatory processes in the population in terms of (i) the presence of negative and positive feedbacks in the system and (ii) the influence of external weather factors. The system under investigation was described as an autoregressive system, whereby the current state of the population is dependent on its state in previous years. The order of autoregression in the system was estimated using the order of the maximum significant partial autocorrelation function. It was found that the regulation of spongy moth population density was characterized by the presence of two feedback loops: positive feedback between the current population density and the population density in the previous season and negative feedback between the current population density and the population density two years ago. To evaluate the model, its stability margin was calculated and found to be directly proportional to the positive feedback coefficient and inversely proportional to the negative feedback coefficient. The model was demonstrated to explain up to 90% of the observed variance of real data. Although the model coefficients for different local populations (North America, Europe, and Asia) differ, the general form of the equation describing both direct data on population densities and indirect data on pest dynamics characterized by areas of stand damage is consistent. Consequently, the form of the ADL model is general, irrespective of the location of the local population.

IPM IN SOYBEANS: HOW TO REDUCE CROP DAMAGE AND INCREASE PROFIT FOR THE FARMER

The objective of the present work was to implement integrated pest management (IPM) in the soybean crop, comparing it with the management carried out by the farmer during two consecutive seasons. The monitoring of adult lepidopterans was also evaluated using Delta-type traps baited with the sexual pheromones of Spodoptera frugiperda (Bio Spodotera®), Helicoverpa armigera (Bio Helicoverpa®) and Chrysodeixis includens (Bio Pseudoplusia®). Incidence of caterpillars and stinkbugs in soybeans was weekly determined, both in the IPM area and in the farmer, area using the beat cloth method. Insecticide applications in the IPM area were carried out when pest population densities reached the control level, while in the area managed by the farmer, sprayings were carried out at his discretion. Based on the results obtained, we found that adoption of IPM enabled better control of the pests in soybeans, especially for stink bugs, and the number of insecticide applications in soybeans could be reduced, which provides economic and environmental benefits for the farmer. In addition, we found that the sexual pheromones of the three evaluated pest species are effective in capturing their moths.

Impact of Nitrogen and Silicon Amendments on Hopper Population in Rice

Present study showed that total dry weight values of rice plants were significantly higher in the plant with high nitrogen (N) application (100kg/ ha) as compared to low nitrogen (30 kg/ ha) treatment whereas the silicon (Si) amendment had very little effect on biomass accumulation but both the elements are associated with hopper pest population densities in rice. Here the correlation coefficient values were high- r= 0.759 to 0.999 and r= 0.726 to 0.996 for brown planthopper Nilaparvata lugens (Stål) and green leafhopper Nephotettix virescens (Dist.) respectively when the calculation was made between insect population and plant biomass after application of nitrogen 0 to 100 kg/ ha. However, when calcium silicate was added 140 kg/ ha or above with high doses of nitrogen the N. lugens and N. virescens incidence reduced in comparison to others. Consequently, the interaction between nitrogen and silicon play a significant role in resistance to these hopper pests.

Study on the Population Density of Insect Pests of Broccoli, Brassica Oleracea, in the Jadiriyah Area of Baghdad, Iraq

A field study was conducted in the fields of the College of Agricultural Engineering Sciences at the University of Baghdad in Al-Jadriya during the 2018 agricultural season. The objective was to survey the population densities of pests affecting broccoli (Brassica oleracea). The results revealed that the broccoli plants in the open field were affected by various pests. On September 24, the highest density of two-spotted red mite (Tetranychus urticae) eggs reached 35 eggs per leaf. On November 12, the highest density of mite nymphs was recorded at 28 nymphs per leaf. The leaf miner, Liriomyza sativae, exhibited the highest density of 23 tunnels per leaf on September 17. Additionally, the highest density of whitefly nymphs (Bemisia tabaci) was observed on October 1 and November 17, reaching 29 nymphs per leaf. The results also indicated the presence of the aphid lion, Chrysoperla carnea, as a natural enemy. Furthermore, the parasitoid Diglyphus isaea was found on the leaf miner, while the parasitoid Eretmocerus mundus was identified on the whitefly. Therefore, understanding the species of pests and their density attacking agricultural crops is crucial. This knowledge allows for the release of natural enemies in the field to mitigate pest infestations.

Influence of Plant Age and Weather Factors on Population Density of Main Insect Pests Attacking Eggplants under Open Field Conditions

Influence of Plant Age and Weather Factors on Population Density of Main Insect Pests Attacking Eggplants under Open Field Conditions

Outbreak conditions of Sunn pest, Eurygaster maura L., 1758 (Hemiptera: Scutelleridae): Model of Central Anatolia (Türkiye)

In this study, outbreak conditions of Sunn pest, Eurygaster maura L., 1758 (Hemiptera: Scutelleridae), the main agricultural pest of wheat, Triticum aestivum L., 1753 (Poaceae: Poales) which is the most important crop of the Central Anatolia (Türkiye) in terms of cultivation area and production was investigated. For this purpose, population density of adult sunn pests in its overwintering site and wheat cultivation area were evaluated for Central Anatolian provinces for the years between 1988 and 2021. It is observed that population density of sunn pest reached the level that requires control in 1988 for the first time. After, there were three infestation periods up to 2021 and each of them lasted for 4 years. First of them occurred between 1993 and 1996. It is observed that when average density of overwintered adult sunn pests exceeds 30 per square meter, there can be infestation in all overwintering sites of Central Anatolia. Also, there is a correlation between this density and the intensity of the infestation. Throughout the infestation periods, average temperature was determined as 20 ºC during the reproduction and development period, and it was recorded over 19 ºC during the season when temperature changes and relocations were high in overwintering site.

Fundamental limits of parasitoid-driven host population suppression: Implications for biological control.

Parasitoid wasps are increasingly being used to control insect pest populations, where the pest is the host species parasitized by the wasp. Here we use the discrete-time formalism of the Nicholson-Bailey model to investigate a fundamental question-are there limits to parasitoid-driven suppression of the host population density while still ensuring a stable coexistence of both species? Our model formulation imposes an intrinsic self-limitation in the host's growth resulting in a carrying capacity in the absence of the parasitoid. Different versions of the model are considered with parasitism occurring at a developmental stage that is before, during, or after the growth-limiting stage. For example, the host's growth limitation may occur at its larval stage due to intraspecific competition, while the wasps attack either the host egg, larval or pupal stage. For slow-growing hosts, models with parasitism occurring at different life stages are identical in terms of their host suppression dynamics but have contrasting differences for fast-growing hosts. In the latter case, our analysis reveals that wasp parasitism occurring after host growth limitation yields the lowest pest population density conditioned on stable host-parasitoid coexistence. For ecologically relevant parameter regimes we estimate this host suppression to be roughly 10-20% of the parasitoid-free carrying capacity. We further expand the models to consider a fraction of hosts protected from parasitism (i.e., a host refuge). Our results show that for a given host reproduction rate there exists a critical value of protected host fraction beyond which, the system dynamics are stable even for high levels of parasitism that drive the host to arbitrary low population densities. In summary, our systematic analysis sheds key insights into the combined effects of density-dependence in host growth and parasitism refuge in stabilizing the host-parasitoid population dynamics with important implications for biological control.

A deep learning-based pipeline for whitefly pest abundance estimation on chromotropic sticky traps

Integrated Pest Management (IPM) is an essential approach used in smart agriculture to manage pest populations and sustainably optimize crop production. One of the cornerstones underlying IPM solutions is pest monitoring, a practice often performed by farm owners by using chromotropic sticky traps placed on insect hot spots to gauge pest population densities. In this paper, we propose a modular model-agnostic deep learning-based counting pipeline for estimating the number of insects present in pictures of chromotropic sticky traps, thus reducing the need for manual trap inspections and minimizing human effort. Additionally, our solution generates a set of raw positions of the counted insects and confidence scores expressing their reliability, allowing practitioners to filter out unreliable predictions. We train and assess our technique by exploiting PST - Pest Sticky Traps, a new collection of dot-annotated images we created on purpose and we publicly release, suitable for counting whiteflies. Experimental evaluation shows that our proposed counting strategy can be a valuable Artificial Intelligence-based tool to help farm owners to control pest outbreaks and prevent crop damages effectively. Specifically, our solution achieves an average counting error of approximately 9% compared to human capabilities requiring a matter of seconds, a large improvement respecting the time-intensive process of manual human inspections, which often take hours or even days.

The impact of maize irrigation intervals and potassium fertiliser rates on mealybug populations, vegetative growth, and resulting yield

The mealybug, Phenacoccus solenopsis (Hemiptera: Coccomorpha: Pseudococcidae), is one of the main pests attacking maize plants in Egypt. Field trials were carried out in the maize field to assess the influence of irrigation periods and potassium fertiliser rates on the mealybug ( P. solenopsis) population estimates, vegetative growth, resulting yield, and its components for the maize cultivar (‘Single-Hybrid 168 Yellow’) in the Luxor Governorate, Egypt. Results revealed that unfertilised plants irrigated every seven days had higher pest population densities than other treatments over the two seasons. The fertilised treatments at 114 kg K 2O∙ha –1 that received water every 10 days had the smallest population of P. solenopsis in every season. Data during the two seasons (2021 and 2022) revealed that the maize to which potassium fertiliser was added by 114 kg K 2O∙ha –1 and irrigated every 10 days had vegetative growth (plant height, diameter, and number of green leaves per plant), yield and its components (average ear length, ear weight, number of grains per ear, weight of 1000 grains, and grain yield) significantly increased as compared to those of the plants that were irrigated every 7 days and without adding fertiliser. A higher dose of potassium fertiliser reduces the infestation of P. solenopsis but causes an increment of maize vegetative growth. This affects the final yield. This information aids farmers in comprehending the good agronomic techniques of maize plants to decrease the infestation of mealybugs and increase the yield.

Towards pest outbreak predictions: Are models supported by field monitoring the new hope?

Physiologically-based models are the core of Decision Support Systems (DSS) for insect pest and disease control in cultivated fields. However, the large-scale use of DSS remains scarce and limited, despite the continuous update and formulation of new models by the literature. The main reason behind this lack of real-world use relates to the purely descriptive approach of these models, which are usually validated a posteriori. The major limiting factors that preclude the use of these tools for prediction purposes are their dependence on time zero and initial abundance to start the simulations. In this study, we present a theoretical framework that includes field monitoring data as an active part of a pest population density model simulation, which helps to overcome these obstacles. More specifically, we propose the application of an estimator scheme in the form of an Extended Kalman Filter (EKF) to a revised physiologically-based model from the literature. In the paper, we carry out a preliminary test of the theoretical framework applied to the case of Drosophila suzukii. This case study shows that the dependence of the simulations on the initial conditions and time zero is strongly reduced by using the EKF. Overall, the outcome of this research indicates that an estimator scheme is a necessary step to move from description to prediction in the pest population modelling field.

Cannibalistic enemy-pest model: effect of additional food and harvesting.

Biological control using natural enemies with additional food resources is one of the most adopted and ecofriendly pest control techniques. Moreover, additional food is also provided to natural enemies to divert them from cannibalism. In the present work, using the theory of dynamical system, we discuss the dynamics of a cannibalistic predator prey model in the presence of different harvesting schemes in prey (pest) population and provision of additional food to predators (natural enemies). A detailed mathematical analysis and numerical evaluations have been presented to discuss the pest free state, coexistence of species, stability, occurrence of different bifurcations (saddle-node, transcritical, Hopf, Bogdanov-Takens) and the impact of additional food and harvesting schemes on the dynamics of the system. It has been obtained that the multiple coexisting equilibria and their stability depend on the additional food (quality and quantity) and harvesting rates. Interestingly, we also observe that the pest population density decreases immediately even when small amount of harvesting is implemented. Also the eradication of pest population (stable pest free state) could be achieved via variation in the additional food and implemented harvesting schemes. The individual effects of harvesting parameters on the pest density suggest that the linear harvesting scheme is more effective to control the pest population rather than constant and nonlinear harvesting schemes. In the context of biological control programs, the present theoretical work suggests different threshold values of implemented harvesting and appropriate choices of additional food to be supplied for pest eradication.

The lepidopteran pest complex infesting menthol mint in India: Distribution during the crop development, species composition and associated parasitoids

Menthol mint, Mentha arvensis L. is an important aromatic and medicinal herb cultivated as an industrial crop for its essential oil in the Indo-Gangetic plains of India. The commercial production of menthol mint suffers due to defoliation caused by lepidopteran pests and currently becoming a serious constraint for its clean cultivation. The information on occurrence of lepidopteran caterpillars defoliating menthol mint in the region is limited. In this study, we assessed the occurrence and injury caused by lepidopteran pests from seven major menthol mint growing districts of the Indo-Gangetic plains of India. Further, the species composition of lepidopteran pests and their associated parasitoids were also reported. The survey revealed that seven lepidopteran pest infestations were recorded on different phenological growth stages of menthol mint in the Indo-Gangetic plains of India. The larval population density of lepidopteran pests was significantly different between the districts, species and phenological stages of menthol mint. The larval population density of the lepidopteran pest varied between 0.41 ± 0.31 to 2.37 ± 1.43 larvae/m2 across the locations. The higher occurrence of Spodoptera litura (Fabricius), Spilarctia obliqua Walker and Thysanoplusia orichalcea (Fabricius) was recorded in menthol mint. The higher incidence of lepidopteran pests was recorded at the mid-vegetative growth stage of menthol mint. This study found eight parasitoids parasitizing egg and larval stages of lepidopteran pests. The parasitism rate of egg parasitoids, Trichogramma chilonis Ishii and Trichogramma achaeae Nagaraja and Nagarkatti was 23.53–35.31% and 27.78% to the eggs of Helicoverpa armigera and T. orichalcea, respectively. The larval parasitoids caused a total of 5.78% larval parasitism to the various lepidopteran pests of menthol mints. This information provides a current pest status of lepidopteran pests infesting menthol mint in Indo-Gangetic plains of India. This baseline information could be used for the development of management strategies against lepidopteran pests for sustainable menthol mint production.