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The increasing consumption and demand of jujube fruits has accelerated production over the recent past. However, the aspects of eco-friendly strategies for pest control and high-quality fruit production are becoming more important to combat the impending dangers of repeated chemicals use in orchard management. This study identified for the first time, the sap beetle (Phenolia (Lasiodites) picta) larvae (based on mitochondrial DNA barcode sequencing), as the major insect pest causing damage in jujube fruits in Korea. The study investigated the insecticidal potential of cuticle-degrading enzymes from Bacillus licheniformis PR2 against P. picta larvae, and the enhancement of fruit quality and yield, through phytohormone production, ammonia production and phosphate solubilizing properties of the bacterium. Bacillus licheniformis PR2 produced chitinase and protease and caused larval mortalities of 55.56 % and 68.89 % when treated with the bacterial broth culture and crude enzyme fraction, respectively. The insecticidal activity in both treatments were characterized by deep cuticle fissures with swollen/depressed surfaces and loss of sensilla. Field application of B. licheniformis PR2 effectively controlled P. picta larvae in jujube orchard during active feeding period as they moved from fruit-to-fruit which reduced the damage and premature fruit-drop. Moreover, B. licheniformis PR2 produced indole-3-acetic acid (IAA) and gibberellic acid (GA) phytohormones, and increased the soil concentration of nitrogen and phosphorus concentration in the soil. The application of B. licheniformis PR2 in jujube orchard increased the chlorophyll content/photosynthetic activity, fruit yield, fruit characteristics (such as length, diameter and fruit weight) and the organoleptic properties (such as the Ca content, firmness and sugar concentration) of jujube fruits, compared to the control and conventional treatment. Thus, we demonstrate that B. licheniformis PR2 can be a viable alternative to chemical pesticides and fertilizers and could enhance the eco-friendly and sustainable production of high-quality jujube fruits to meet the increasing demands.

期刊论文 2025-04-01 DOI: 10.1016/j.biocontrol.2025.105739 ISSN: 1049-9644

BACKGROUND Chaetanaphothrips orchidii is an invasive thrips of tropical origin that was detected in 2016 in Spanish citrus, where it can damage up to 70% of the fruit. Pupation site and emergence rates are key biological traits for thrips management that are unknown for C. orchidii. Here, we determined the pupation site and period of C. orchidii in citrus and evaluated the effect of soil moisture on adult emergence. RESULTS A two-year field study showed that C. orchidii pupated in the soil from May to December in commercial citrus orchards. Chaetanaphothrips orchidii emergence was very low compared to other harmful thrips species in citrus. Using D/E traps, we demonstrated that the thrips emerged mainly from wet areas near drip irrigation emitters during the summer, and its emergence was strongly related to the soil water content. A laboratory experiment confirmed that C. orchidii did not emerge at RH below 70%, and its emergence peaked at 97% RH. CONCLUSIONS Our results have important implications for the sustainable management of C. orchidii because soil moisture is very low in Mediterranean citrus during summer, except in areas near drip irrigation emitters. Therefore, these and other potential high-humidity areas should be considered crucial targets to manage this pest in citrus during summer, reducing cost and labor.

期刊论文 2025-03-01 DOI: 10.1002/ps.8558 ISSN: 1526-498X

Understanding the effects of landscape greening pest control modes (LGPCMs) on carbon storage and soil physicochemical properties is crucial for promoting the sustainable development of urban landscape greening. Climate change and green development have led to increased landscape pest occurrences. However, the impacts of different LGPCMs on carbon storage and soil properties remain unclear. We examined six typical LGPCMs employed in Beijing, China: chemical control (HXFZ), enclosure (WH), light trapping (DGYS), biological agent application (SWYJ), natural enemy release (SFTD), and trap hanging (XGYBQ). Field surveys and laboratory experiments were conducted to analyze their effects on carbon storage and soil physicochemical properties, and their interrelationships. The main results were as follows: (1) Different LGPCMs significantly affected carbon storage in the tree and soil layers (p 0.05). Carbon storage composition across all modes followed the following order: tree layer (64.19%-93.52%) > soil layer > shrub layer > herb layer. HXFZ exhibited the highest tree layer carbon storage (95.82 t/hm(2)) but the lowest soil layer carbon storage (6.48 t/hm(2)), while DGYS performed best in the soil, herb, and shrub layers. (2) LGPCMs significantly influenced soil bulk density (SBD), clay (SC), silt particle (SSP), sand (SS), pH, organic carbon (OC), total nitrogen (TN), and heavy metal content (lead (Pb), cadmium (Cd), mercury (Hg)). WH had the highest TN (1.37 g/kg), TP (0.84 g/kg), SC (10.71%) and SSP (42.14%); HXFZ had the highest Cd (8.98 mg/kg), but lowest OC and Pb. DGYS had the highest OC and Hg, and the lowest Cd, SC, and TP. Under different LGPCMs, the heavy metal content in soil ranked as follows: Pb > Cd > Hg. (3) There were significant differences in the relationship between carbon storage and soil physicochemical properties under different LGPCMs. A significant positive correlation was observed between the soil layer carbon storage, TN, and OC, while significant negative correlations were noted between SS and SC as well as SSP. Under SFTD, the tree layer carbon storage showed a negative correlation with Cd, while under DGYS, it correlated negatively with pH and Hg. In summary, While HXFZ increased the short-term tree layer carbon storage, it reduced carbon storage in the other layers and damaged soil structure. Conversely, WH and DGYS better supported carbon sequestration and soil protection, offering more sustainable control strategies. We recommend developing integrated pest management focusing on green control methods, optimizing tree species selection, and enhancing plant and soil conservation management. These research results can provide scientific guidance for collaborative implementation of pest control and carbon sequestration in sustainable landscaping.

期刊论文 2024-12-01 DOI: 10.3390/f15122235

Wireworms are the most destructive soil insect pests affecting horticultural crops. The damage often renders them unsuitable for commercial purposes, resulting in substantial economic losses. RNA interference (RNAi) has been broadly used to inhibit gene functions to control insect populations. It employs double-stranded RNA (dsRNA) to knockdown essential genes in target organisms, rendering them incapable of development or survival. Although it is a robust approach, the primary challenges are identifying effective target genes and delivering their dsRNA into wireworms. Thus, the present study established a liquid ingestion methodology that efficiently delivers dsRNA into wireworms. We then investigated the effects of four target genes on wireworm mortality. The highest mortality rate reached 50% when the gene encoding vacuolar ATPase subunit A was targeted. Its transcript content in the fed wireworms was also significantly reduced. The mortality rates of the other three target genes of vacuolar ATPase subunit E, beta-actin, and chitin synthase 1 were 28%, 33%, and 35%, respectively. This is the first report demonstrating an efficient feeding methodology and the silencing of target genes in wireworms. Our findings indicate that RNAi is an effective alternative method for controlling the wireworm pest, and can be used to develop field treatment strategies.

期刊论文 2024-12-01 DOI: 10.3390/insects15120983

Heavy metal contamination represents a critical global environmental concern. The movement of heavy metals through the food chain inevitably subjects insect natural enemies to heavy metal stress, leading to various adverse effects. This review assesses the risks posed by heavy metal exposure to insect natural enemies, evaluates how such exposure impacts their pest control efficacy, and investigates the mechanisms affecting their fitness. Heavy metals transfer and accumulate from soil to plants, then to herbivorous insects, and ultimately to their natural enemies, impeding growth, development, and reproduction of insect natural enemies. Typically, diminished growth and reproduction directly compromise the pest control efficacy of these natural enemies. Nonetheless, within tolerable limits, increased feeding may occur as these natural enemies strive to meet the energy demands for detoxification, potentially enhancing their pest control capabilities. The production of reactive oxygen species and oxidative damage caused by heavy metals in insect natural enemies, combined with disrupted energy metabolism in host insects, are key factors contributing to the reduced fitness of insect natural enemies. In summary, heavy metal pollution emerges as a significant abiotic factor adversely impacting the pest control performance of these beneficial insects.

期刊论文 2024-10-05 DOI: 10.1016/j.jhazmat.2024.135587 ISSN: 0304-3894

Larvae of the southern corn rootworm (SCR) Diabrotica undecimpunctata howardi Barber (Coleoptera: Chrysomelidae) are primary pests of peanut in the Virginia-Carolina region of the United States, and are relatively sporadic pests in southern states such as Georgia, Alabama, and Florida. Peanuts have strict quality standards which, when they are not met, can diminish crop value by more than 65%. Management of direct pests like SCR is therefore crucial to maintaining the economic viability of the crop. The soil-dwelling nature of SCR larvae complicates management due to difficulties associated with monitoring and predicting infestations. Nonchemical management options are limited in this system; preventative insecticide applications are the most reliable management strategy for at-risk fields. Chlorpyrifos was the standard product for larval SCR management in peanut until its registration was revoked in 2022, leaving no effective chemical management option for larvae. We tested a novel insecticide, isocycloseram, for its ability to reduce pod scarring, pod penetration, and non-SCR pod damage in field studies conducted in Suffolk, Virginia in 2020-2022. Overall injury was low in 2020 and 2022, and in 2022 there was not a significant effect of treatment. In 2021, 2 simulated chemigation applications of isocycloseram in July significantly reduced pod scarring and overall pod injury relative to chlorpyrifos and the untreated control. Our results suggest that isocycloseram may become an effective option for managing SCR in peanut, although more work is needed to understand the mechanisms by which it is effective as a soil-applied insecticide.

期刊论文 2024-04-12 DOI: 10.1093/jee/toae017 ISSN: 0022-0493

Agriculture is the cultivation of soil, the cultivation of crops, and the raising of livestock. Agriculture is essential to the economic development of any country. Despite significant advancement in the service sector, agriculture remains India's most important employer and source of income. The agricultural sector has great potential to improve food needs and provide healthy and nutritious food. But nowadays, the situation is not favoring the farmers. Farmers have to bear a lot of loss due to diseases, pests, and lack of moisture in soil, destroying the crop. Detecting insects and diseases in plants is one of the most challenging tasks for farmers, as large portions of crops are damaged, and quality is affected as a result. Farmers have so far adopted conventional farming methods. These techniques were imprecise, slowing productivity and taking a lot of time. Precision agriculture helps improve productivity by identifying steps that need to be taken at different phases of crop production. Precision farming uses advanced techniques such as collecting data, training systems, and predicting outcomes using IoT, data mining, data analytics, machine learning, and more. With the help of emerging technologies, precise farming reduces manual work and increases productivity. The application of machine learning with IoT data analytics in the agricultural sector brings new benefits to improve the quantity and quality of production from crop fields and meet the growing demand for food. The proposed model will predict the task needed to be performed at the time of disease in the crop, lack of moisture in the soil, in case of pests, etc. The goal of this work is to enable individuals to grow crops efficiently and achieve high productivity at low cost.

期刊论文 2024-01-01 DOI: 10.1007/978-3-031-64076-6_11 ISSN: 1865-0929
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