Mutual learning with memory for semi-supervised pest detection.

Effectively monitoring pest-infested areas by computer vision is essential in precision agriculture in order to minimize yield losses and create early scientific preventative solutions. However, the scale variation, complex background, and dense distribution of pests bring challenges to accurate detection when utilizing vision technology. Simultaneously, supervised learning-based object detection heavily depends on abundant labeled data, which poses practical difficulties. To overcome these obstacles, in this paper, we put forward innovative semi-supervised pest detection, PestTeacher. The framework effectively mitigates the issues of confirmation bias and instability among detection results across different iterations. To address the issue of leakage caused by the weak features of pests, we propose the Spatial-aware Multi-Resolution Feature Extraction (SMFE) module. Furthermore, we introduce a Region Proposal Network (RPN) module with a cascading architecture. This module is specifically designed to generate higher-quality anchors, which are crucial for accurate object detection. We evaluated the performance of our method on two datasets: the corn borer dataset and the Pest24 dataset. The corn borer dataset encompasses data from various corn growth cycles, while the Pest24 dataset is a large-scale, multi-pest image dataset consisting of 24 classes and 25k images. Experimental results demonstrate that the enhanced model achieves approximately 80% effectiveness with only 20% of the training set supervised in both the corn borer dataset and Pest24 dataset. Compared to the baseline model SoftTeacher, our model improves mAP @0.5 (mean Average Precision) at 7.3 compared to that of SoftTeacher at 4.6. This method offers theoretical research and technical references for automated pest identification and management.

Prosapia bicincta (Hemiptera: Cercopidae) abundance, plant associations, and impacts on groundcover in Hawai'i Island rangelands.

The twolined spittlebug, Prosapia bicincta (Say), is a major economic pest of forage grass and turfgrass. Prosapia bicincta was first detected in rangelands on Hawai'i Island in 2016 and has since spread to an estimated 72,000 ha in the North and South Kona districts. This study aimed to quantify P. bicincta abundance, plant associations, and impacts on groundcover over time. Monthly surveys of P. bicincta nymphs and adults were conducted from February 2018 to September 2022 along 17 established 100-m transects at 4 ranches located in Kona, Hawai'i Island, spanning an elevation gradient from 519 to 1,874 m above sea level (a.s.l.). Monitoring revealed P. bicincta occurs from 519 to 1,679 m a.s.l., primarily in Kikuyu grass (Cenchrus clandestinus (Hochst. ex Chiov.)) Morrone (Poales: Poaceae) pastures. Peaks in P. bicincta abundance coincided with the wet season, with most activity occurring from April to October and little to no activity between November and March. Mid elevation (1,000-1,300 m) transects had significantly higher mean P. bicincta abundance (126 nymphs/m2) relative to low (500-999 m) (64 nymphs/m2) and high elevations (>1,300 m) (20 nymphs/m2). Sites with the highest abundance of P. bicincta were also associated with the greatest decrease in mean grass cover (30%) and were replaced by forbs, bare ground, and shrubs. Grasses accounted for 72% of the total P. bicincta detections, with the remaining plants comprised of legumes (16%), sedges (6%), and forbs (6%). Twenty new P. bicincta plant associations were found. This information will help improve the effectiveness of management to suppress populations below economic thresholds.

Towards a better future for DNA barcoding: Evaluating monophyly- and distance-based species identification using COI gene fragments of Dacini fruit flies.

The utility of a universal DNA 'barcode' fragment (658 base pairs of the Cytochrome C Oxidase I [COI] gene) has been established as a useful tool for species identification, and widely criticized as one for understanding the evolutionary history of a group. Large amounts of COI sequence data have been produced that hold promise for rapid species identification, for example, for biosecurity. The fruit fly tribe Dacini holds about a thousand species, of which 80 are pests of economic concern. We generated a COI reference library for 265 species of Dacini containing 5601 sequences that span most of the COI gene using circular consensus sequencing. We compared distance metrics versus monophyly assessments for species identification and although we found a 'soft' barcode gap around 2% pairwise distance, the exceptions to this rule dictate that a monophyly assessment is the only reliable method for species identification. We found that all fragments regularly used for Dacini fruit fly identification >450 base pairs long provide similar resolution. 11.3% of the species in our dataset were non-monophyletic in a COI tree, which is mostly due to species complexes. We conclude with recommendations for the future generation and use of COI libraries. We revise the generic assignment of Dacus transversus stat. rev. Hardy 1982, and Dacus perpusillus stat. rev. Drew 1971 and we establish Dacus maculipterus White 1998 syn. nov. as a junior synonym of Dacus satanas Liang et al. 1993.

Pest categorisation of Coniella castaneicola.

The European Commission requested the EFSA Panel on Plant Health to conduct a pest categorisation of Coniella castaneicola (Ellis & Everh) Sutton, following commodity risk assessments of Acer campestre, A. palmatum, A. platanoides, A. pseudoplatanus, Quercus petraea and Q. robur plants from the UK, in which C. castaneicola was identified as a pest of possible concern to the EU. When first described, Coniella castaneicola was a clearly defined fungus of the family Schizoparmaceae, but due to lack of a curated type-derived DNA sequence, current identification based only on DNA sequence is uncertain and taxa previously reported to be this fungus based on molecular identification must be confirmed. The uncertainty on the reported identification of this species translates into uncertainty on all the sections of this categorisation. The fungus has been reported on several plant species associated with leaf spots, leaf blights and fruit rots, and as an endophyte in asymptomatic plants. The species is reported from North and South America, Africa, Asia, non-EU Europe and Oceania. Coniella castaneicola is not known to occur in the EU. However, there is a key uncertainty on its presence and geographical distribution worldwide and in the EU due to its endophytic nature, the lack of systematic surveys and possible misidentifications. Coniella castaneicola is not included in Commission Implementing Regulation (EU) 2019/2072 and there are no interceptions in the EU. Plants for planting, fresh fruits and soil and other growing media associated with infected plant debris are the main pathways for its entry into the EU. Host availability and climate suitability in parts of the EU are favourable for the establishment and spread of the fungus. Based on the scarce information available, the introduction and spread of C. castaneicola in the EU is not expected to cause substantial impacts, with a key uncertainty. Phytosanitary measures are available to prevent its introduction and spread in the EU. Because of lack of documented impacts, Coniella castaneicola does not satisfy all the criteria that are within the remit of EFSA to assess for this species to be regarded as potential Union quarantine pest.

Causality-inspired crop pest recognition based on Decoupled Feature Learning.

BACKGROUND: Ensuring the efficient recognition and management of crop pests is crucial for maintaining the balance in global agricultural ecosystems and ecological harmony. Deep learning-based methods have shown promise in crop pest recognition. However, prevailing methods often fail to address a critical issue: biased pest training dataset distribution stemming from the tendency to collect images primarily in certain environmental contexts, such as paddy fields. This oversight hampers recognition accuracy when encountering pest images dissimilar to training samples, highlighting the need for a novel approach to overcome this limitation. RESULTS: We introduce the Decoupled Feature Learning (DFL) framework, leveraging causal inference techniques to handle training dataset bias. DFL manipulates the training data based on classification confidence to construct different training domains and employs center triplet loss for learning class-core features. The proposed DFL framework significantly boosts existing baseline models, attaining unprecedented recognition accuracies of 95.33%, 92.59%, and 74.86% on the Li, DFSPD, and IP102 datasets, respectively. CONCLUSION: Extensive testing on three pest datasets using standard baseline models demonstrates the superiority of DFL in pest recognition. The visualization results show that DFL encourages the baseline models to capture the class-core features. The proposed DFL marks a pivotal step in mitigating the issue of data distribution bias, enhancing the reliability of deep learning in agriculture. © 2024 Society of Chemical Industry.

Pest categorisation of Popillia quadriguttata.

The EFSA Panel on Plant Health performed a pest categorisation of Popillia quadriguttata (Coleoptera: Scarabaeidae), following a commodity risk assessment of bonsai Pinus parviflora grafted onto P. thunbergii from China, in which P. quadriguttata was identified as a pest of possible concern for the territory of the European Union. This is a univoltine polyphagous pest that occurs in eastern Asia from Vietnam northwards through eastern China and Taiwan, South Korea and into Far East Russia. Hosts include species of fruit trees within the genera Malus and Prunus, trees of forestry and environmental importance such as Quercus and Ulmus, shrubs such as Wisteria, soft fruit such as Rubus, grasses, including amenity turf and field crops such as potatoes, maize and soybean. Adults feed on host leaves, tender stems, flower buds, flowers and fruits; larvae feed on host roots. In northern China P. quadriguttata is a major pest of soybean; in South Korea, P. quadriguttata is one of the most serious insect pests of golf course turf. P. quadriguttata could enter the EU on various pathways including infested soil and growing media accompanying host plants for planning. Biotic factors (host availability) and abiotic factors (climate suitability) suggest that large parts of the EU would be suitable for establishment. Local spread would be mainly via natural dispersal of adults. Long distance spread would be facilitated by the movement of eggs, larvae and pupae infesting soil especially with plants for planting; adults could spread on plants for planting without soil. Economic and or environmental impacts would be expected on a range of plants if P. quadriguttata were to establish in the EU. Phytosanitary measures are available to reduce the likelihood of its introduction. P. quadriguttata satisfies all of the criteria that are within the remit of EFSA to assess for it to be regarded as a potential Union quarantine pest.

Pest categorisation of Cenopalpus irani.

The EFSA Panel on Plant Health performed a pest categorisation of Cenopalpus irani (Trombidiformes: Tenuipalpidae), known as the Iranian false spider mite, following the commodity risk assessment of Malus domestica plants from Türkiye, in which C. irani was identified as a pest of possible concern for the territory of the European Union (EU). The pest is only known to be present in Iran and Türkiye and has not been reported from the EU. The mite primarily feeds on Rosaceae plants but is considered polyphagous. Important crops of the EU that are hosts of C. irani include apples (Malus domestica), pears (Pyrus communis) and figs (Ficus carica). Plants for planting and fruits provide potential pathways for entry into the EU. Host availability and climate suitability in southern EU countries would most probably allow this species to successfully establish and spread. This mite is not listed in Annex II of Commission Implementing Regulation (EU) 2019/2072. Phytosanitary measures are available to reduce the likelihood of entry and spread of this species into the EU. The mite C. irani satisfies the criteria that are within the remit of EFSA to assess for it to be regarded as a potential Union quarantine pest, although there is a key uncertainty over the likelihood and magnitude of impact.

The implementation of robotic dogs in automatic detection and surveillance of red imported fire ant nests.

BACKGROUND: The Red Imported Fire Ant (RIFA), scientifically known as Solenopsis invicta, is a destructive invasive species causing considerable harm to ecosystems and generating substantial economic costs globally. Traditional methods for RIFA nests detection are labor-intensive and may not be scalable to larger field areas. This study aimed to develop an innovative surveillance system that leverages artificial intelligence (AI) and robotic dogs to automate the detection and geolocation of RIFA nests, thereby improving monitoring and control strategies. RESULTS: The designed surveillance system, through integrating the CyberDog robotic platform with a YOLOX AI model, demonstrated RIFA nest detection precision rates of >90%. The YOLOX model was trained on a dataset containing 1118 images and achieved a final precision rate of 0.95, with an inference time of 20.16 ms per image, indicating real-time operational suitability. Field tests revealed that the CyberDog system identified three times more nests than trained human inspectors, with significantly lower rates of missed detections and false positives. CONCLUSION: The findings underscore the potential of AI-driven robotic systems in advancing pest management. The CyberDog/YOLOX system not only matched human inspectors in speed, but also exceeded them in accuracy and efficiency. This study's results are significant as they highlight how technology can be harnessed to address biological invasions, offering a more effective, ecologically friendly, and scalable solution for RIFA detection. The successful implementation of this system could pave the way for broader applications in environmental monitoring and pest control, ultimately contributing to the preservation of biodiversity and economic stability. © 2024 Society of Chemical Industry.

Effective multidimensional treatment identification of different chemical fertilizers: Response of insect dynamics and rice production.

Effective management of fertilizers is essential in influencing the prevalence of insects in rice (Oryza sativa L.) fields. Over two years (2019-20 and 2020-21), an experiment conducted at Bangladesh Rice Research Institute (BRRI), Habiganj, during the boro season aimed to identify the most effective multidimensional treatment (EMT) by testing various combinations of chemical fertilizers and its effect on rice insects. The goal was to optimize rice grain yield while minimizing harmful insect infestation and supporting natural enemies. Eight different chemical fertilizer applications were used as follows: T1 contained a full mix of nitrogen (N), phosphorus (P), potassium (K), and sulfur (S); T2 had PKS but lacked N; T3 had NKS but lacked P; T4 had NPS but lacked K; T5 had NPK but lacked S; T6 had KS but lacked N and P; T7 had PS but lacked N and K; and T8 lacked all four elements - N, P, K, and S. The relationship between the dynamics of harmful insects and natural enemies was highly positively correlated (r = 0.72 to 0.97). In two consecutive growing years, the 2020-21 season exhibited notably higher counts of harmful insects, with Rice Leafroller (RLR) dominating in the booting stage and White Backed Planthopper (WBPH) in mid-tillering, while Green Mirid Bug (GMB) prevailed among natural enemies across both stages, surpassing insect pest counts, notably GMB, Lady bird beetle (LBB), Carabid beetle (CDB), and Staphylinid (STD). However, the yield was notably higher in the 2019-20 growing season despite these pest pressures. Throughout the mid-tillering and booting stages, T1 consistently exhibited the highest average populations of harmful insects and natural enemies, while T7 demonstrated the lowest count of harmful insects, followed by T2 at both growth stages. Additionally, the highest grain yield (GY) was consistently recorded in T1, followed by T5, T6, and T3, with yields of 7.98 t/ha, 7.63 t/ha, 7.38 t/ha, and 7.33 t/ha, respectively. In both stages, beneficial insects prevailed over harmful ones in all fertilizer applications, with significant declines noted in T2 and T7. Factor analysis showed successful selection for EMT in the MGIDI index for all variables except INT and GY during the 2019-20 season, with selection differentials (SD) ranging from -0.10 to 8.29. However, in 2020-21, selection was achieved for all variables with SD ranging from 0.37 to 6.08. According to the MGIDI index, the top-ranked EMTs were identified as T4 and T3 for the 2019-20 period, and T3 and T5 for the 2020-21 period. The EMT shared in both years, T3, proved effective because of its positive impact on enhancing natural enemies throughout both periods (with SD ranging from 4.76 to 8.29 for 2019-20 and 3.03 to 6.08 for 2020-21), and its notable contribution to rice grain yield (SD = 0.37) in 2020-21. This study uniquely integrates EMT to optimize rice grain yield while simultaneously managing harmful insect infestations and supporting natural enemies, addressing a critical need in sustainable rice cultivation. The suggestion is to give preference to fertilizer application T3, which omits P but contains N and K, to improve rice grain yield and boost natural enemies, thereby reducing harmful insect infestation. Moreover, future investigations should concentrate on refining fertilizer blends to strike a harmony between maximizing yield and fostering ecological robustness in rice cultivation.

Performance evaluation of facility locations using integrated DEA-based techniques.

Facility location, particularly in the context of international investments by global enterprises, stands out as a paramount concern within the purview of top management's strategic decision-making process. The selection of a suitable location plays a pivotal role in determining the ultimate achievement of organizational objectives. The process of selecting an appropriate location requires the comprehensive analysis of a substantial volume of data, encompassing diverse tangible and intangible evaluation criteria that may exhibit inherent conflicts. This paper addresses the challenge of determining the best location for a manufacturing facility by employing alternative performance measures within the framework of the data envelopment analysis (DEA) model. In a performance evaluation process, not only positive but also negative aspects should be determined. This paper, therefore, proposes a double-frontier DEA-AR model, which is an integrated approach that incorporates the efficient frontier, anti-efficient frontier, and assurance region weight restrictions, with the aim of increasing the discrimination ability of the DEA method. An efficient frontier evaluates the information of each location from a positive viewpoint, while the worst side is evaluated by an anti-efficient frontier. The technique of weight restrictions, which allows incorporating expert opinion into the assessment, is also applied with both frontiers to restrict the regions of weights to some specific area. The prescribed approach is illustrated by a numerical example of selecting the best location among ten different countries under consideration of 22 selection criteria obtained from PEST analysis. The results show that the proposed alternative performance measures significantly improve discrimination capability, enabling the ranking of candidates based on their suitability for the optimal location.

Commodity risk assessment of Prunus avium plants from United Kingdom.

The European Commission requested the EFSA Panel on Plant Health to prepare and deliver risk assessments for commodities listed in Commission Implementing Regulation (EU) 2018/2019 as 'High risk plants, plant products and other objects'. This Scientific Opinion covers plant health risks posed by plants of Prunus avium possibly grafted on rootstocks of either P. avium, P. canescens, P. cerasus, P. pseudocerasus or their hybrids imported from the UK, taking into account the available scientific information, including the technical information provided by the UK. All pests associated with the commodities were evaluated against specific criteria for their relevance for this opinion. Three quarantine pests Scirtothrips dorsalis, tobacco ringspot virus and tomato ringspot virus), one protected zone EU quarantine pest (Bemisia tabaci (European population), and three non- regulated pests (Colletotrichum aenigma, Eulecanium excrescens and Takahashia japonica) that fulfilled all relevant criteria were selected for further evaluation. The risk mitigation measures proposed in the technical Dossier from the UK were evaluated, taking into account the possible limiting factors. For these pests, expert judgement is given on the likelihood of pest freedom, taking into consideration the risk mitigation measures acting on the pest, including uncertainties associated with the assessment. The degree of pest freedom varies among the pests evaluated, with Colletotrichum aenigma being the pest most frequently expected on the imported potted plants. The Expert Knowledge Elicitation indicated with 95% certainty that between 9971 and 10,000 plants per 10,000 would be free from the above-mentioned fungus.

Melanaphis sacchari/sorghi complex: current status, challenges and integrated strategies for managing the invasive sap-feeding insect pest of sorghum.

Melanaphis sacchari (Zehntner;Hemiptera: Aphididae), sugarcane aphid (SCA), is an invasive phloem-feeder found worldwide with a wide host range of economically important plants including sorghum and sugarcane. Given its high reproductive capacity and ability to rapidly spread over long distances, SCA presents challenges for effective control, leading to substantial economic losses. Recent studies have identified two multiloci SCA genotypes specialized in feeding on sugarcane (MLL-D) and sorghum (MLL-F) in the USA, which raises concerns as the USA is the second largest sorghum-producing country. This has encouraged research towards identifying these two biotypes where some research has stated them as two species; MLL-D clade to be M. sacchari and MLL-F clade to be M. sorghi Theobald (Hemiptera: Aphididae), sorghum aphid (SA). This review aims at compiling research progress that has been made on understanding the SCA/SA species complex. Furthermore, this review also highlights a wide range of management strategies against SCA/SA that includes both biological and chemical methods. In addition, the review emphasizes studies examining host plant resistance to understand and evaluate the role of R-genes and phytohormones such as jasmonic acid, salicylic acid and ethylene against SCA. Beside this, plant volatiles and other secondary metabolites such as flavonoids, terpenes and phytanes are also explored as potential control agents. Being an invasive pest, a single management tactic is inadequate to control SCA population and hence, integrated pest management practices incorporating physical, cultural and biological control methods should be implemented with exclusive chemical control as a last resort, which this review examines in detail. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Silencing sensory neuron membrane protein RferSNMPu1 impairs pheromone detection in the invasive Asian Palm Weevil.

The red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier), also known as the Asian palm weevil, is an invasive pest that causes widespread damage to palm trees around the globe. As pheromone communication is crucial for their mass attack and survival on palm trees, the olfactory concept of pest control strategies has been widely explored recently. We aim to understand the molecular basis of olfaction in RPW by studying one of the key olfactory proteins in insect pheromone communication, sensory neuron membrane proteins (SNMPs). SNMPs belong to the CD36 (cluster of differentiation 36) family that perform two distinct olfactory roles in insects, either in pheromone (odorant) transfer to the odorant receptors (SNMP1) or in the pheromone clearing process (SNMP2). In this study, we performed antennal transcriptomic screening and identified six SNMPs, mapping them on the R. ferrugineus genome, and confirmed four distinct SNMPs. Both SNMP1 proteins in RPW, viz., RferSNMPu1 and RferSNMPu2, were mapped onto the same scaffold in different loci in the RPW genome. To further understand the function of these proteins, we first classified them using phylogenetic analysis and checked their tissue-specific expression patterns. Further, we measured the relative transcript abundance of SNMPs in laboratory-reared, field-collected adults and pheromone-exposure experiments, ultimately identifying RferSNMPu1 as a potential candidate for functional analysis. We mapped RferSNMPu1 expression in the antennae and found that expression patterns were similar in both sexes. We used RNAi-based gene silencing to knockdown RferSNMPu1 and tested the changes in the RPW responses to aggregation pheromone compounds, 4-methyl-5-nonanol (ferrugineol) and 4-methyl-5-nonanone (ferrugineone), and a kairomone, ethyl acetate using electroantennogram (EAG) recordings. We found a significant reduction in the EAG recordings in the RferSNMPu1 knockdown strain of adult RPWs, confirming its potential role in pheromone detection. The structural modelling revealed the key domains in the RferSNMPu1 structure, which could likely be involved in pheromone detection based on the identified ectodomain tunnels. Our studies on RferSNMPu1 with a putative role in pheromone detection provide valuable insight into understanding the olfaction in R. ferrugineus as well as in other Curculionids, as SNMPs are under-explored in terms of its functional role in insect olfaction. Most importantly, RferSNMPu1 can be used as a potential target for the olfactory communication disruption in the R. ferrugineus control strategies.

Palearctic flea beetle and pest of hops and Cannabis, Psylliodesattenuata (Coleoptera, Chrysomelidae, Galerucinae), new to North America.

Background: The univoltine leaf beetle Psylliodesattenuata (Koch, 1803) is a pest of Cannabis and Humulus (Cannabaceae) and native to the Palaearctic Region, known from eastern Asia to western Europe. New information: First North American records are presented for P.attenuata from Canada: Ontario and Québec. Adult beetle feeding damage to hops Humuluslupulus L. (Cannabacaea) plants is recorded from Québec. Diagnostic information is presented to distinguish P.attenuata from other North American Chrysomelidae and a preliminary assessment of its potential to spread in North America is presented. While our climate analysis is limited by a lack of data, it appears P.attenuata is physiologically capable of persisting throughout the range of Humulus in North America.The United States of America and Canada are now known to be home to 71 or more species of adventive Chrysomelidae.

Mating behavior and oviposition of Palpita forficifera (Lepidoptera: Crambidae).

Palpita forficifera Munroe, 1959 (Lepidoptera: Crambidae) is considered the main pest of the olive tree (Olea europaea L., Oleaceae) in Brazil and Uruguay. The aim of this work was to study the mating and oviposition behavior of P. forficifera in the field and laboratory. In the field, the sex emitting the mating pheromone was determined and in the laboratory, the rate of emergence of males and females; the age, time and duration of mating; number of copulations and oviposition time of P. forficifera were recorded. The field results showed that it was possible to capture up to five males per trap in just one night in traps with the presence of female P. forficifera. Copulation occurs between the seventh and twenty-third day of life and is most frequent during the third and sixth hours of scotophase. The average duration of the first copulation was 174 min, with 35% of couples recopulating, and there were cases of up to five copulations. Oviposition times were concentrated between 20:00 and 02:00. The results obtained provide insight into the reproductive behavior of P. forficifera and are useful for future studies aimed at identifying the sex pheromone to improve monitoring of the pest in olive orchards.

First trials exploring the potential of phytoseiid mites in managing lychee erinose mite, Aceria litchii (Keifer) (Acari: Eriophyidae), infestations on lychee plants.

Phytoseiid mites have been frequently found in association with the lychee erinose mite, Aceria litchii, on lychee plants in Brazil, suggesting that they are promising candidates as biological control agents against this pest. Here, we investigated whether phytoseiids would suppress A. litchii infestation, i.e. formation of erinea, on lychee plants under field conditions. Four groups of A. litchii-infested plants were randomly distributed in the field, with each group receiving either Phytoseius intermedius, Amblyseius herbicolus, A. herbicolus supplemented with cattail pollen or no predator. During a three-month period, the released predators, along with others present in the surrounding environment, were allowed to freely walk among all plants. In each plant, we evaluated the occurrence of phytoseiid species, their abundance, and the dynamics of erinea formation. A total of 2,097 mites, including 13 other phytoseiid species were identified. The most abundant species were Iphiseiodes zuluagai and Euseius ho, rather than the two predator species that were released. A. herbicolus and P. intermedius failed to establish populations in the majority of the plants, regardless of the presence of pollen, suggesting their ineffectiveness in controlling A. litchii infestations. While there was a significant difference in the proportion of erinea among the four treatments, this contrast was not associated with the presence of phytoseiids, suggesting that other factors might have hindered erinea formation on lychee plants. The reasons behind this outcome are further explored and discussed.

Validation of fungicide spray strategies and selection for fenhexamid resistance in Botrytis cinerea on greenhouse-grown grapevines.

In this study, in planta assays were conducted to assess the effects of fungicide spray tactics, such as the reduction of the labeled fungicide dose and mixture with a multi-site fungicide, on fungicide resistance selection and disease control using Vitis vinifera 'Cabernet Sauvignon' grown in a greenhouse for two years. The entire clusters were inoculated with B. cinerea isolates at varying frequencies of fenhexamid resistance, followed by fungicide sprays, disease and fenhexamid resistance investigations at critical phenological stages. Our findings indicate that the lower dose of the at-risk fungicide, fenhexamid, effectively managed fenhexamid resistance and disease as well as the higher, labeled dose. In addition, mixture with the multi-site fungicide captan generally resulted a net-positive effect on both resistance management and disease control.

Effectiveness and genetic control of Trichoderma spp. as a biological control of wheat powdery mildew disease.

Wheat powdery mildew (WPM) is one of the most devasting diseases that affects wheat yield worldwide. Few efforts have been done to control such a serious disease. Looking for an effective way to control WPM is urgently needed. Biological control is an effective way in controlling plant diseases worldwide. In this study, the efficiency of three different Trichoderma spp. in controlling WPM at seedling growth stage was tested using 35 highly diverse wheat genotypes. Highly significant differences were found in WPM resistance among the four treatments confirming the efficiency of Trichoderma in controlling WPM. Out of the three species, Trichoderma asperellum T34 (T34) was the most effective species in controlling WPM as it reduced the symptoms with a percentage of 50.56%. A set of 196 wheat genotypes was used to identify the genetic control of the WPM induced resistance by T34. A total of 39, 27, and 18 gene models were identified to contain the significant markers under Pm, T34, and the improvement in powdery mildew resistance due to T34 (T34_improvement) conditions. Furthermore, no gene model was common between T34 and Pm suggesting the presence of completely different genetic systems controlling the resistance under T34 and Pm. The functional annotation and biological process pathways of the detected gene models confirm their association with the normal and induced resistance. This study, for the first time, confirm the efficiency of T34 in controlling WPM and provide a deep understanding of the genetic control of induced and normal resistance to WPM.

Phytocytokine StPep1-secreting bacteria suppress potato powdery scab disease.

Powdery scab is an important potato disease caused by the soilborne pathogen Spongospora subterranea f. sp. subterranea. Currently, reliable chemical control and resistant cultivars for powdery scab are unavailable. As an alternative control strategy, we propose a novel approach involving the effective delivery of a phytocytokine to plant roots by the rhizobacterium Bacillus subtilis. The modified strain is designed to secrete the plant elicitor peptide StPep1. In our experiments employing a hairy root system, we observed a significant reduction in powdery scab pathogen infection when directly applying the StPep1 peptide. Furthermore, our pot assay, which involved pretreating potato roots with StPep1-secreting B. subtilis, demonstrated a substantial decrease in disease symptoms, including reduced root galling and fewer tuber skin scabs. These findings underscore the potential of engineered bacteria as a promising strategy for safeguarding plants against powdery scab.

Effects of sulfur dioxide fumigation on mortality of confused flour beetle (Coleoptera: Tenebrionidae) and rice weevil (Coleoptera: Curculionidae).

Sulfur dioxide (SO2) fumigation was studied in laboratory to determine its potential as an alternative treatment for postharvest control of stored product insects, confused flour beetle, Tribolium confusum Jacquelin du Val (Coleoptera: Tenebrionidae), and rice weevil, Sitophilus oryzae (L.) (Coleoptera: Curculionidae). Three-hour fumigations with 0.1%-2.0% SO2 were conducted against eggs, immature stages, and adults of the 2 insects at 20 °C. Effective control of both insects was achieved. However, there were considerable variations between the 2 insects and among different life stages. Confused flour beetle was more susceptible to SO2 fumigation than rice weevil. Complete control of adults and all life stages of confused flour beetle was achieved in 3-h fumigations with 0.5% and 2.0% SO2, respectively. For rice weevil, 3-h fumigation with 1.5% SO2 resulted in 96.5% adult mortality and the fumigation with 2.0% SO2 resulted in 99.27% mortality of adults and 87.5% mortality of immature stages. Three-hour fumigations with 1% SO2 resulted in <5% egg survival to adults. The study demonstrated high efficacy of SO2 fumigation against the insects and suggested that SO2 fumigation has good potential for postharvest pest control on stored products.