Pest Of Soybean Research Articles

Optimizing Mass Rearing of the Egg Parasitoid, Telenomus podisi, for Control of the Brown Stink Bug, Euschistus heros

The parasitoid Telenomus podisi Ashmead, 1893 is used in biological control programs in Brazil against eggs of Euschistus heros (Fabricius, 1798), a key pest of soybean, Glycine max (L.) Merr. To optimize the mass production of parasitoids, artificial diets and storage of host eggs at low temperatures have been developed; however, direct comparisons of the effects of these conditions have not occurred. We assessed a double factorial arrangement composed of six treatments (fresh or cryopreserved E. heros eggs from adults fed on natural or two artificial diets). We evaluated the biological characteristics and parasitism capacity of T. podisi produced from these treatments across seven temperatures. The thermal range between 21 and 30 °C resulted in satisfactory daily parasitism in all treatments tested, with an inverse relationship between temperature and female survival. The best parasitoid biological parameters were found between 21 and 27 °C, where all tested diets supported T. podisi development, with the best results from artificial diets. Fresh eggs and those frozen in liquid nitrogen and stored at -196 °C until use supported parasitoid development. These results suggest that the best method to mass rear T. podisi is to use artificial diets to rear E. heros and store eggs until needed, and then rear parasitoids at 24 °C.

Re‐evaluation of the economic threshold for Crocidosema aporema injury to indeterminate Bt soybean cultivars

AbstractThe neotropical soybean budborer (Crocidosema aporema [Walsingham, 1914] [Lepidoptera: Tortricidae]) is classified as a major pest of soybean that is difficult to manage with insecticides because larvae cause leaf‐rolling and can bore into the stem. Genetically modified Bt (Bacillus thuringiensis) soybean has been effective in managing C. aporema populations until recently when resistance has emerged and high infestation rates have been observed in Brazilian Bt soybean fields expressing Cry1Ac. The economic threshold (ET) for C. aporema was previously studied only in conventional (non‐Bt) determinate varieties of soybean. The present work evaluated the potential of C. aporema to injure indeterminate Bt soybean cultivars in two independent field trials carried out in 2020–2021 and 2021–2022 growing seasons. One field trial compared the response of individual injured and noninjured plants in the same field. The number of pods per plant, number of seeds per plant, and seed mass per plant in 12 of 13 trials were similar. In the second field trial, areas with and without insecticide applications were compared. There was a reduction in C. aporema damage after three insecticide applications, but yields were similar between treatments. Based on these results, C. aporema had low potential to cause economic injury to indeterminant Bt soybean cultivars. Thus, the current ET for C. aporema of 25%–30% of infested plants can be increased to 50%.

Effect of soybean variety and pest management on the sustainable production

Pests are one of the limiting factors in increasing soybean production. Pest control carried out by farmers using pesticides is feared to threaten the sustainability of soybean production in Indonesia. This study aimed to identify the effect of different pest management systems and various soybean varieties on pest population dynamics, abundance and diversity of natural enemies, plant damage, and soybean production. A split plot design with three replications was applied, where the main plot was pest management systems i.e. (1) control (which received neither chemicals nor integrated pest management), (2) chemical control, and (3) integrated pest management, and the sub-plot was soybean varieties i.e. (1) Anjasmoro, (2) Demas 1, and (3) Dering 1. Results indicated that variety affects pest diversity and abundance, however, it affected leaf damage, pod damage, and production. The pest management systems influenced the diversity and abundance of pests and natural enemies, plant damage, and production. Interaction between variety and pest management system affected plant damage. We conclude that the use of resistant varieties combined with integrated pest management could reduce plant damage, maintain the natural enemy population, and optimize soybean production.

Out of East Asia: Early Warning of the Possible Invasion of the Important Bean Pest Stalk-Eyed Seed Bug Chauliops fallax (Heteroptera: Malcidae: Chauliopinae)

The short stay at the beginning of the invasion process is a critical time for invasive species identification and preventing invasive species from developing a wider distribution and significant economic impact. The stalk-eyed seed bug Chauliops fallax is an important agricultural pest of soybean and was first reported to occur outside East Asia. Here, we reported the native evolutionary history, recent invasion history, and potential invasion threats of C. fallax for the first time based on population genetic methods and ecological niche modelling. The results showed that four native East Asian genetic groups (EA, WE, TL, and XZ) were well supported, showing an east-west differentiation pattern consistent with the geographical characteristics of three-step landforms in China. Two main haplotypes existed: Hap1 might have experienced a rapid northwards expansion process after the LGM period, and Hap5 reflected local adaptation to the environment in southeastern China. The Kashmir sample was found to come from the recent invasion of populations in the coastal areas of southern China. Ecological niche modelling results suggested that North America has a high risk of invasion, which might pose a serious threat to local soybean production. In addition, with future global warming, the suitable habitat in Asia will move towards the higher latitude region and gradually deviate from the soybean planting area, which indicates the threat of C. fallax to soybean production in Asia will decrease in the future. The results could provide new insights into the monitoring and management of this agricultural pest in the early invasion stage.

Climate change impacts on the potential worldwide distribution of the soybean pest, Piezodorus guildinii (Hemiptera: Pentatomidae).

The redbanded stink bug, Piezodorus guildinii (Westwood, 1837), is a highly destructive soybean pest native to the Neotropical Region. In the past 60 yr, P. guildinii has been observed to expand its distribution in North and South America, causing significant soybean yield losses. In order to predict the future distribution direction of P. guildinii and create an effective pest control strategy, we projected the potential global distribution of P. guildinii using 2 different emission scenarios, Shared Socioeconomic Pathways 126 and 585, and 3 Earth system models, with the maximum entropy niche model (MaxEnt). Then, the predicted distribution areas of P. guildinii were jointly analyzed with the main soybean-producing areas to assess the impact for different soybean region. Our results showed that temperature is the main environmental factor limiting the distribution of P. guildinii. Under present climate conditions, all continents except Antarctica have suitable habitat for P. guildinii. These suitable habitats overlap with approximately 45.11% of the total global cultivated soybean areas. Moreover, P. guildinii was predicted to expand its range in the future, particularly into higher latitudes in the Northern hemisphere. Countries, in particular the United States, where soybean is widely available, would face a management challenge under global warming. In addition, China and India are also high-risk countries that may be invaded and should take strict quarantine measures. The maps of projected distribution produced in this study may prove useful in the future management of P. guildinii and the containment of its disruptive effects.

Resistance Level of Soybean Genotypes against Pod Sucking Bug (Riptortus linearis F. Hemiptera: Alydidae)

Background: Pod sucking bug (Riptortus linearis F. Hemiptera: Alydidae) is one of the major insect pest in soybean that cause yield loss up to 79%. This study was carried out to identify the level of resistance to pod sucking bug on soybean genotypes. Methods: Field research was conducted at Muneng Experimental Farm, Probolinggo, East Java, Indonesia in the Dry Season (March-June) 2019. A randomized block design repeated two times were used on a total of 16 soybean genotypes included two varieties (Anjasmoro and Gema) as check. The experiment consisted of two growing environments namely controlled environment (P1): two insecticides with active ingredients Deltamethrin and Fipronil were applied to soybean crops alternately; and uncontrolled environment (P0): no insecticide was applied to soybean crops Observations were recorded on the intensity of borer attack and dry seed weight. Result: In uncontrolled environment (P0), the percentage number of infected seed to healthy seed was higher than that in controlled environment (P1). The mean effectiveness of control of pod sucking was 35% which was based on infestation intensity of seed number/plant infected in in two environments. The total seed weight/plant in controlled environment (P1) was 95% higher than that in uncontrolled environment (P0). Based on infestation intensity in uncontrolled environment (P0), five genotypes (G1 to G5) were categorized as resistant against pod sucking bug while the check varieties Anjasmoro and Gema were categorized as moderate resistant and susceptible, respectively.

Genomic-proteomic analysis of a novel Bacillus thuringiensis strain: toxicity against two lepidopteran pests, abundance of Cry1Ac5 toxin, and presence of InhA1 virulence factor.

Bacillus thuringiensis (Bt) is a biological alternative to the indiscriminate use of chemical insecticides in agriculture. Due to resistance development on insect pests to Bt crops, isolating novel Bt strains is a strategy for screening new pesticidal proteins or strains containing toxin profile variety that can delay resistance. Besides, the combined genomic and proteomic approaches allow identifying pesticidal proteins and virulence factors accurately. Here, the genome of a novel Bt strain (Bt TOL651) was sequenced, and the proteins from the spore-crystal mixture were identified by proteomic analysis. Toxicity bioassays with the spore-crystal mixture against larvae of Diatraea saccharalis and Anticarsia gemmatalis, key pests of sugarcane and soybean, respectively, were performed. The toxicity of Bt TOL651 varies with the insect; A. gemmatalis (LC50 = 1.45ngcm-2) is more susceptible than D. saccharalis (LC50 = 73.77ngcm-2). Phylogenetic analysis of the gyrB gene indicates that TOL651 is related to Bt kenyae strains. The genomic analysis revealed the presence of cry1Aa18, cry1Ac5, cry1Ia44, and cry2Aa9 pesticidal genes. Virulence factor genes such as phospholipases (plcA, piplc), metalloproteases (inhA), hemolysins (cytK, hlyIII, hblA, hblC, hblD), and enterotoxins (nheA, nheB, nheC) were also identified. The combined use of the genomic and proteomic data indicated the expression of Cry1Aa18, Cry1Ac5, and Cry2Aa9 proteins, with Cry1Ac5 being the most abundant. InhA1 also was expressed and may contribute to Bt TOL651 pathogenicity. These results provide Bt TOL651 as a new tool for the biocontrol of lepidopteran pests.

Reduction in productivity of soybean plants infested with Neohyadatothrips variabilis (Thysanoptera: Thripidae) with and without soybean vein necrosis virus

Soybean thrips, Neohyadatothrips variabilis (Beach), a vector of Soybean Vein Necrosis Virus (SVNV), has been recognized as a widespread pest of soybean [Glycine max (L.) Merr.] in USA and Canada. Several experiments investigated the effect on soybean when infested with soybean thrips with and without SVNV. Experiment 1 compared soybean infested at V1 and V5 growth stages (GS) with soybean thrips without SVNV and noninfested plants. For plants infested at GS V1, plant height, number of seeds, and seed weights were reduced by 50, 80, and 75%, respectively. When plants were infested at GSs V1 and V5, the counts of soybean thrips peaked at 1,803 and 4,214 per plant 4 weeks after infestation (WAI), respectively. Experiment 2 used SVNV-infected soybean thrips and compared soybean infested versus control at GS V1 and V5. For plants infested at GS V1, plant height was reduced 77.8%, and plants died before setting pods. For plants infested at GS V5, height, number of seeds, and seed weights were reduced 56, 78, and 92%, respectively. When plants were infested at GSs V1 and V5, the counts of soybean thrips peaked at 282 and 883 per plant 2 WAI, respectively. Experiment 3, five soybean genotypes were infested with SVNV-infected thrips at GS V1. Number and weight of seeds per plant were higher and with lower visual disease ratings (progressive chlorosis, necrosis and rugosity) for the more resistant genotypes Merschman Kennedy and plant introduction (PI) 171451 than for the more susceptible genotypes: soybean breeding line LD12-12734a (Rag1/2), cv Williamsfield Illini 3509N, and PI 417136.

A salivary secretory protein from Riptortus pedestris facilitates pest infestation and soybean staygreen syndrome.

The bean bug (Riptortus pedestris), one of the most important pests of soybean, causes staygreen syndrome, delaying plant maturation and affecting pod development, resulting in severe crop yield loss. However, little is known about the underlying mechanism of this pest. In this study, we found that a salivary secretory protein, Rp614, induced cell death in nonhost Nicotiana benthamiana leaves. NbSGT1 and NbNDR1 are involved in Rp614-induced cell death. Tissue specificity analysis showed that Rp614 is mainly present in salivary glands and is highly induced during pest feeding. RNA interference experiments showed that staygreen syndrome caused by R. pedestris was significantly attenuated when Rp614 was silenced. Together, our results indicate that Rp614 plays an essential role in R. pedestris infestation and provide a promising RNA interference target for pest control.

SOYBEAN PEST IDENTIFICATION BASED ON CONVOLUTIONAL NEURAL NETWORK AND TRANSFER LEARNING

Despite the fact that the ensemble classifier improved classification precision by integrating texture and colour. However, the significant image preparation process is a laborious and time-consuming. Manually depicting constrained feature extraction can result in a semantic void in a picture. These limits cause inaccuracy of agricultural disease identification. Thus, this study proposes a soybean pest detection method based on a hybrid of Transfer learning and pyramidal convolutional neural networks that can identify soybean pests quickly and accurately on small sample sets. Bean borer, soybean poison moth, mite, stink bug, and pod borer photographs are first pre-processed using standard data improvement methods, and then manually categorized into six groups based on pest characteristics. The weight parameters from the VGG16 model trained on the ImageNet image dataset were then transferred to the recognition of soybean pests using the transfer learning method, and the VGG16 convolutional and pooling layers were used as feature extraction layers, while the top layer was redesigned as a pyramidal convolutional layer, an average pooling layer, and a SoftMax output layer, with some of the convolutional layers frozen during training. According to the testing statistics, the model's average test accuracy is 98.23%, and the model size is only 95.4 M. For bean borer, soybean poison moth, mite, skewed night moth, stink bug, and bean pod moth, the model's recognition accuracy is 96.4, 97.78, 98.12, 98.4, 99.56, and 99.16, respectively. The results of the experiments show that the method has a high identification efficiency and a good recognition effect.

Histopathological changes in Lithobates catesbeianus tadpoles used as biomarkers of pesticide poisoning

The use of biological indicators has increased in recent years with the aim of investigating environmental pollution in aquatic environments that are vulnerable to the constant use of pesticides. Some biomarkers can help assess the health status, indicating physical, metabolic, and behavioral changes under acute and sublethal poisoning. The mixture of the active ingredients cyproconazole and picoxystrobin is a widely used fungicide for the control of pests in cotton, rice, coffee, sugarcane, corn, soybean, and wheat. The objective of this study was to verify the occurrence of possible histopathological lesions in the liver and kidneys of bullfrog tadpoles (Lithobates catesbeianus) caused by a fungicide commercial formula composed of picoxystrobin and cyproconazole. The animals were subjected to different concentrations of the fungicide to determine the median lethal concentration (LC50-96h = 0.05 mg L-1), that is, the lethal dose for 50% of the animals in 96 h. After determining the value of LC50-96h, the animals were subjected to three sublethal concentrations (LC50-96h/2, LC50-96h/10, and LC50-96h/100). Through histological biomarkers, it was verified that this fungicide changed the morphology of the animals' kidney and liver tissues in a chronic way, impairing the functioning of organs that are essential for their survival and metamorphosis, which can result in an imbalance in the biodiversity of aquatic ecosystems.

Discovering and prioritizing candidate resistance genes against soybean pests by integrating GWAS and gene coexpression networks

Soybean is one of the most important legume crops worldwide. Soybean pests have a considerable impact on crop yield. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate resistance genes against the insects Aphis glycines and Spodoptera litura, and the nematode Heterodera glycines. We identified 171, 7, and 228 high-confidence candidate resistance genes against A. glycines, S. litura, and H. glycines, respectively. We found some overlap of candidate genes between insect species, but not between insects and H. glycines. Although 15% of the prioritized candidate genes encode proteins of unknown function, the vast majority of the candidates are related to plant immunity processes, such as transcriptional regulation, signaling, oxidative stress, recognition, and physical defense. Based on the number of resistance alleles, we selected the ten most promising accessions against each pest species in the soybean USDA germplasm. The most resistant accessions do not reach the maximum theoretical resistance potential, indicating that they might be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression networks we inferred in this work are available in a user-friendly web application (https://soypestgcn.venanciogroup.uenf.br/) and an R/Shiny package (https://github.com/almeidasilvaf/SoyPestGCN) that serve as a public resource to explore soybean-pest interactions at the transcriptional level.

Bemisia tabaci (Hemiptera: Aleyrodidae): Evaluation of Leaf Trichome Density based Resistance on Several Soybean Varieties

The whitefly Bemisia tabaci (Gennadius) is one of the important soybean pests which can reduce production up to 80 %. Soybean defense mechanism against B. tabaci is affected by the physical characteristics of the leaf surface, e.g. leaf thickness, density of trichomes, and sticky glandular trichomes. The objective of this research was to investigate B. tabaci population – trichome density relationship on ten soybean varieties. The experiment was carried out in Ngale Station, Ngawi District, East Java. The tested soybean varieties were Anjasmoro, Demas 1, Dena 1, Dering 1, Devon, Detam 3, Dewah, Gema, Grayak 1, and Wilis. The experiment was done by completely randomized design with three replications. Observation on the whitefly population was conducted weekly from 2 until 10 weeks after planting on 23 sample plants in each plot. The result showed that Devon was the variety with the highest population levels of B. tabaci, 10.89 (eggs), 14.48 (nymphs) individuals per leaf, respectively. The population of B. tabaci was affected by trichomes density. Devon was the highest density of trichomes (613.7 hairs per cm2). The density of trichomes and the number of whitefly eggs and nymphs relationship were significant (R2= 0,78 (egg) and 0.84 (nymph), n= 10, ?= 1 %, F Value= 0.00157, respectively).

Non-Destructive Detection of Soybean Pest Based on Hyperspectral Image and Attention-ResNet Meta-Learning Model

Soybean plays an important role in food, medicine, and industry. The quality inspection of soybean is essential for soybean yield and the agricultural economy. However, soybean pest is an important factor that seriously affects soybean yield, among which leguminivora glycinivorella matsumura is the most frequent pest. Aiming at the problem that the traditional detection methods have low accuracy and need a large number of samples to train the model, this paper proposed a detection method for leguminivora glycinivorella matsumura based on an A-ResNet (Attention-ResNet) meta-learning model. In this model, the ResNet network was combined with Attention to obtain the feature vectors that can better express the samples, so as to improve the performance of the model. As well, the classifier was designed as a multi-class support vector machine (SVM) to reduce over-fitting. Furthermore, in order to improve the training stability of the model and the prediction performance on the testing set, the traditional Batch Normalization was replaced by the Layer Normalization, and the Label Smooth method was used to punish the original loss. The experimental results showed that the accuracy of the A-ResNet meta-learning model reached 94.57 ± 0.19%, which can realize rapid and accurate nondestructive detection, and provides theoretical support for the intelligent detection of soybean pests.

Relation Extraction for Knowledge Graph Generation in the Agriculture Domain: A Case Study on Soybean Pests and Disease

HighlightsWith the aim to reduce the burden of acquiring expert knowledge and strengthen the connection between written knowledge and the fields, this article investigated the problem of automatically extracting and organizing soybean pests and disease knowledge from text.Entities and relations were extracted using multiple models with deep neural network structures. Performance of these models were compared and evaluated in detail.A knowledge graph was automatically constructed using the extracted information, and made publicly available.ABSTRACT. Precision agriculture is an emerging type of agriculture that intensively uses information technology to automate agricultural production. Soybean (Glycine max (L.) Merri.), is an important crop in China, with an annual demand of approximately 110 million tons. However, in China, soybean production is threatened by more than 30 kinds of disease and 100 kinds of pests. With the rapidly increasing specialized information in the literature, it is difficult for farmers to keep up. Relation extraction automatically identifies and extracts structured knowledge from natural language text and thus can help to alleviate the problem. In this study, we propose to employ relation extraction to systematically extract information from expert-written text, and generate a knowledge graph from the extracted information. This case study was planned in China, therefore we mainly used Chinese texts. Firstly, we carefully chose expert-written text on soybean pests and disease, labeled the entities, and classified their thematic relations into five categories. Then, we built and trained three relation extraction models using state-of-the-art deep learning architectures and evaluated their performance on our task. Finally, we constructed an example knowledge graph from the extracted information and demonstrated their potential usage for automatic reasoning and solution recommendation for pests and disease prevention. In total, this study sampled 1038 entities and 1569 relation instances. Experimental results showed that our best model achieved an F1 score of 98.49% on identifying relations from text. Experimental results also showed the effectiveness of the example knowledge graph. Keywords: Bidirectional encoder representation from transformers, Knowledge graph, Relation extraction, Soybean pests and disease.

Overview of the spread of soybean pests in the Russian Federation

Soy is the most demanded and widespread leguminous culture in the world. She received this status due to the rich chemical composition of seeds and its wide use for food, technical and fodder purposes. The sown area under this crop is increasing every year. Soy is an attractive object for many insects. In its agrocenosis there are both useful and harmful species. The object of our research was soybean pests. The article analyzes publications in order to clarify the species composition and distribution of soybean pests in the last century to the present. The paper presents data on the distribution of soy phytophages in the main regions of soybean cultivation in Russia. Among the pests of soybeans in the Russian Federation there are both specialized and multi -stage species: leaf - shocking insects - Lepidoptera (scaly), Coleoptera (hard -winged), Hemiptera (semi -burned -winged), Homoptera (equivalent), Acariformes (ticks), Thysanoptera - thrips (Thrips sp.), insects damaging seeds - diptera (double -winged). The most common phytophages causing significant harm to soybeans in Russia are: Leguminivora glycinivorella Mats., Paraluperodes suturalis nigrobilineatus Motsch., Aphis glycines Mats., Loxostege sticticalis L., Etiella zinckenella Tr., Orthosia ella Butl, Pyrrhia umbra Hufn, Heliothis maritime Grasl. and Tetranychus urticae C.L.Kocn. According to the results of phytosanitary monitoring in 2022 in Primorsky Krai, the most common soybean pests were: soybean striped leaf beetle, polyphagous soybean leaf beetle, soybean moth and various types of bugs.

Influência da adição de adjuvantes à calda de pulverização de teflubenzuron em linhagens resistentes e suscetíveis da lagarta falsa-medideira Chrysodeixis includens em soja (Lepidoptera: Noctuidae)

ABSTRACT: The soybean looper (SBL), Chrysodeixis includens (Walker, [1858]) (Lepidoptera: Noctuidae), is a soybean and cotton pest in South America countries. Field-evolved resistance of SBL to inhibitors of chitin biosynthesis has been reported in Brazil; however, this mode of action is still widely used against SBL. On this basis, we conducted laboratory bioassays to investigate if adjuvants (Nimbus®, TA 35®, Break-Thru® S 240, and Rizospray Extremo®) added to the teflubenzuron spray increase the mortality of SBL strains (resistant, heterozygous, and susceptible to chitin biosynthesis inhibitors). Using chromatography analysis, we also evaluated the amount of teflubenzuron on soybean leaves when applied alone or in combination with adjuvants. In laboratory bioassays, the biological activity of teflubenzuron increased against the susceptible SBL strain when adjuvants were added. In contrast, no relevant effects of adjuvants added to the teflubenzuron spray against heterozygous and resistant SBL larvae were detected. In leaf bioassays, even leaves from the upper third part of the plants containing a significantly higher amount of teflubenzuron (3.4 mg/kg vs 1.7 and 0.6 mg/kg); the mortality of SBL strains was similar when teflubenzuron was applied alone or in mixture with adjuvants. Our findings indicated that adjuvants added to teflubenzuron spray do not provide a substantial increase in the mortality of SBL strains resistant to chitin biosynthesis inhibitors. Therefore, it is necessary to reduce the use of this mode-of-action insecticide against SBL and to give preference to other insecticides or control tactic.

Seleção de fungos entomopatogênicos para controle de percevejos e bicudo-do-algodoeiro

ABSTRACT Entomopathogenic fungi stand out in the biological control of several agriculturally important insects. Six isolates of Metarhizium anisopliae, Cordyceps javanica, Beauveria sp. and B. bassiana were screened to control Anthonomus grandis, Euschistus heros, Oebalus poecilus, O. ypsilongriseus and Thyanta perditor, important insect pests of soybean, cotton and rice. The bioassays were conducted in a completely randomized design, with four replications (10 insects/replication). Significant differences for virulence were observed between the tested fungal species and isolates. For A. grandis, the most virulent isolate was M. anisopliae BRM 2335, followed by Beauveria BRM 14527 and BRM 67744 [82.5 to 97.5 % of mortality; average lethal time (LT50) of 5.9 to 7.8 days]. M. anisopliae BRM 2335 was also highly virulent to the four stink bug species (75 to 97.5 % of mortality; LT50 of 5.2 to 9.7 days). For the stink bugs, Beauveria sp. BRM 67744 was infectious to O. poecilus (75 % of mortality), but failed to control E. heros (16.9 % of mortality). C. javanica BRM 27666 and BRM 14526 showed average virulence to the stink bugs and A. grandis (17.5 to 57.3 % of mortality; LT50 of 6.0 to 9.7 days). M. anisopliae was consistently more virulent to the stink bugs than the other fungi. Therefore, M. anisopliae BRM 2335 was selected for further studies under screenhouse and field conditions to control A. grandis and other stink bug species, especially E. heros.

Types of soybean pests and measures against them

The article observes that soybean crops are damaged by a number of specialized and omnivorous pests in the field, during the storage of grain in warehouses and private homes.These pests are mainly noctudae,TetranychusurticaeKoch,beetles, aphids, caterpillars, long-nosed beetles, cicadas (cancers), which have been found to cause severe damage to soybean crops.The study included 21 species of pests belonging to different families, includingEuxoa agricolaB.,Agrotis segetumSchiff,Heliothis armigeraHb.,Tettigonia viridissimaL.,Tettigonia caudateCharp.,Setona crinitusHbst.,Setona cylindricollisFahr.,Setona cylindricollisFahr.,Lethrus pygmaecusBall.,Opatrum SabulasumL.,Mulovzis bigutkataGelb.,Acanthoscelides altectusSag,Callosebruchus maculatesZ.,Colliptamus italicusL.,Colliptamus turanicusTarb.,Dociostaurus maroccanusThumb.,Agrotis meticulosusCond.,Cloncerambycinus Sem., Blaps halophilaF.W.,Dailognatha nasuteMen.,Gryllotalpa gryllotalpaL.,have been reported to damage the plant to varying degrees during young germination and growth.The main pest of the soybean crop is the Avalanche 70% n.kuk 5kg/t consumption rate and the cruiser 35% s.k. Consumption of 4 l/t at the rate of at least 20 days before sowing of seeds is protected from the long snouts for 25-35 days after germination, preventing the damage caused by these pests.In addition, plant growth and development have also improved relative to control.

State of knowledge on biology and ecology of field bugs of the genus Lygus Hahn, 1833 (Hemiptera: Heteroptera: Miridae) in agrocenoses of Ukraine and the world

Lygus bugs (Lygus Hahn, 1833) are omnivorous pests of great economic importance in field crop rotations. The bugs L. rugulipennis (Poppius, 1911) and L. pratensis (Linnaeus, 1758) are part of the permanent complex of pests of sunflower, soybean, pea, wheat and winter barley, berry crops in Ukraine. The article analyzes literary data devoted to the features of biology and ecology of field bugs. Particular attention is paid to the issues of species composition and seasonal changes of fodder plants of field bugs, their harmfulness, natural enemies, agroecological approaches in the regulation lygus bugs’ populations. Data from studies conducted in European countries, North America, and China are presented