ABSTRACT
Odorant-binding proteins (OBPs) initiate insect olfactory perception and mediate specific binding and selection of odorants via uncertain binding mechanisms. We characterized the binding characteristics of four OBPs from the striped flea beetle Phyllotreta striolata (SFB), a major cruciferous crop pest. Tissue expression analysis revealed that the two ABPII OBPs (PstrOBP12 and PstrOBP19) were highly expressed mainly in the antenna, whereas the two minus-C OBPs (PstrOBP13 and PstrOBP16) showed a broad expression pattern. Competitive binding assays of cruciferous plant volatiles showed that PstrOBP12, PstrOBP16 and PstrOBP19 had very strong binding capacities for only two phthalate esters (Ki < 20 µM), and PstrOBP13 specifically bound to four aromatic volatiles (Ki < 11 µM). Fluorescence quenching assays displayed that two phthalate esters bound to three PstrOBPs via different quenching mechanisms. PstrOBP12/PstrOBP16-diisobutyl phthalate and PstrOBP19-bis(6-methylheptyl) phthalate followed static quenching, while PstrOBP12/PstrOBP16-bis(6-methylheptyl) phthalate and PstrOBP19-diisobutyl phthalate followed dynamic quenching. Homology modelling and molecular docking displayed that PstrOBP12-diisobutyl phthalate was driven by H-bonding and van der Waals interactions, while PstrOBP16-diisobutyl phthalate and PstrOBP19-bis(6-methylheptyl) phthalate followed hydrophobic interactions. Finally, behavioural activity analysis demonstrated that phthalate esters exhibited different behavioural activities of SFB at different doses, with low doses attracting and high doses repelling. Overall, we thus revealed the different binding properties of the three PstrOBPs to two phthalate esters, which was beneficial in shedding light on the ligand-binding mechanisms of OBPs.
Subject(s)
Coleoptera , Esters , Insect Proteins , Phthalic Acids , Receptors, Odorant , Animals , Receptors, Odorant/metabolism , Receptors, Odorant/genetics , Receptors, Odorant/chemistry , Coleoptera/metabolism , Phthalic Acids/metabolism , Insect Proteins/metabolism , Insect Proteins/chemistry , Insect Proteins/genetics , Esters/metabolism , Ligands , Molecular Docking Simulation , PhylogenyABSTRACT
With the progress of urbanization and industrialization in China, the consumption of fossil fuels blows up. The burning of fossil fuels releases large amounts of particulate matter, leads to smog, and the air quality is gradually getting worsen. Previous studies have shown that vegetation can effectively reduce airborne particles with different size fractions. And large amounts of previous studies pointed to the adsorption ability of urban forest for particles larger than 2.5 µm. The capacity of roadside plants for the capture of fine particles, especially for those smaller than 2.5 µm has been rarely reported. In this study, five external factors including leaf orientation, leaf height, planting location, planting form, and pollution concentration were tested to evaluate their impact on the dust retention capacity of different roadside plants. The results indicate that significant interspecies was found between tested plant species, and with the change of different external factors, the capturing capacity for the same roadside plants varied. The change of leaf orientation has limited effects on the amount of captured fine particles for the tested plants. While, the amount of captured particulate matter by leaves was inversely proportional to its growth height. Plants locating in the central of the road showed significantly higher capturing capacity than they, when they was set alongside the road. The total amount of captured fine particle by Ligustrum japonicum locating in the central green belt of road was about 5 times higher than it when it was planted in the green belt alongside the road. In addition, the correlation between the capturing capacity of roadside plants and its distance to the street curb was found to be negative.
Plants have been widely accepted as an environmentally friendly air particulate filter that can effectively remove fine particulate matter which can be harmful to humans. By analyzing the dust retention of plant leaves, this paper discussed the influence of different factors such as traffic pressure, planting position, and leaf orientation on the capture ability of roadside plants, in addition, we investigated particulate matter with a smaller size (PM0.22). The mainly objective of this study is to investigate the factors affecting the dust retention efficiency of roadside plants and roadside plants as phytoremediation to improve city air quality which consists with the purpose of the journal.
Subject(s)
Air Pollutants , Air Pollution , Particulate Matter/analysis , Air Pollutants/analysis , Environmental Monitoring , Biodegradation, Environmental , Air Pollution/prevention & control , Plants , Plant Leaves/chemistry , Fossil FuelsABSTRACT
This research is to predict heavy metal levels in plants, particularly in Robinia pseudoacacia L., and soils using an effective artificial intelligence approach with some ecological parameters, thereby significantly eliminating common defects such as high cost and seriously tedious and time-consuming laboratory procedures. In this respect, the artificial neural network (ANN) is employed to estimate the concentrations of essential heavy metals such as Fe, Mn and Ni, depending on the Cu and Zn concentrations of plant and soil samples collected from five different locations. The derived relative errors for the constructed ANN model have been computed within the ranges 0.041-0.051, 0.017-0.025, and 0.026-0.029 for the training, testing and holdout data regarding Fe, Mn, and Ni, respectively. In addition, it has been realized that the relative errors could be diminished up to 0.007 for Fe, 0.014 for Mn and 0.022 for Ni by considering the Cu, Zn, location and plant parts as independent variables during the analysis. The results produced seem instructive and pioneering for environmentalists and scientists to design optimal study programs to leave a livable ecosystem.
The levels of essential heavy metals, Fe, Mn, Ni, based on Zn and Cu in plant and soil samples have been predicted through an AI-based prediction model, a class of feedforward artificial neural networks (ANNs) with a multilayer perceptron (MLP). Thereby common drawbacks such as high cost and severely time-consuming laboratory procedures have been significantly eradicated. In the evaluation of different pollution levels at locations, it has been shown that the ANN method can overcome several disadvantages of analytical element analyzers to monitor the amounts of heavy metals such as Fe, Mn, and Ni in soil and plants.
Subject(s)
Metals, Heavy , Soil Pollutants , Environmental Monitoring/methods , Artificial Intelligence , Ecosystem , Soil Pollutants/analysis , Biodegradation, Environmental , Neural Networks, Computer , Soil , Metals, Heavy/analysisABSTRACT
The defensive chemistry and persistence of plant tissues determine their suitability and apparency - the likelihood of being discovered - to insect herbivores. As consumers of plant tissues with transient apparency, florivores and seed-feeders must frequently migrate between host plants to synchronize colonization with plant phenology. Aggregation pheromones could provide information-based solutions to finding ephemeral hosts, but little is known about plant-influenced variation in this form of chemical communication. Combining analytical chemistry, de novo synthesis and field ecology, we investigated the change in colonization of two sympatric host plants, Nicotiana attenuata and Nicotiana obtusifolia, which differ in apparency-related life history traits, by a heteropteran seed-feeder, Corimelaena extensa. We identified a novel pheromone released by C. extensa males - (5Z,8Z)-tetradeca-5,8-dienal - and performed field assays with the synthetic pheromone, showing that it stimulates the formation of feeding aggregations on the post-fire annual N. attenuata. Corimelaena extensa pheromone emission was 40-fold higher when feeding on N. attenuata compared with the perennial N. obtusifolia, as were adult fecundity and seed capsule content of the putative biosynthetic precursor, linoleic acid. Higher pheromone emission increases the apparency and colonization of the ephemeral, high-quality host N. attenuata. This plant-specific variation in insect signaling could facilitate host-finding by seed-feeders migrating between plant patches.
Subject(s)
Heteroptera/physiology , Nicotiana/physiology , Pheromones/physiology , Seeds/physiology , Aldehydes/chemistry , Animals , Herbivory , Linoleic Acid/analysis , Male , Pheromones/chemistry , Species Specificity , Volatile Organic Compounds/analysisABSTRACT
Plant volatile organic compounds play a role in selection of host plants by herbivorous insects. Once the insect reaches the plant, contact cues determine host acceptance. Although the willow sawfly Nematus oligospilus (Hymenoptera: Tenthredinidae) can differentiate among willow genotypes, no knowledge is available on the cues used by this insect to seek and accept the host plant. In this study, we recorded behavioral orientation in a Y-tube olfactometer of willow sawfly females to volatiles of the highly preferred genotype Salix nigra and the non-preferred genotype S. viminalis. The volatiles released by undamaged willows of each genotype were analyzed by coupled gas chromatography-mass spectrometry. Contact cues were evaluated first by oviposition preference bioassays after selective leaf wax removal, and then by studying the micromorphology of abaxial and adaxial leaf surfaces and their chemical composition. Willow sawfly females oriented preferentially to S. nigra volatiles, which contained more than 3 times the amount of volatiles than that collected from S. viminalis. Analysis of volatiles showed significant differences in amounts of (Z) and (E)-ß-ocimene, undecane, decanal, and ß-caryophyllene. The adaxial leaf surface of S. nigra was less preferred after wax removal, suggesting a role of cuticular waxes for oviposition acceptance. No differences were found among the micromorphology of leaf surfaces between preferred and non-preferred genotypes. The chemical analysis of cuticular waxes showed that the abaxial leaf surface of S. viminalis, which is completely avoided for oviposition, possessed 97% of alkanes. The accepted leaf surfaces contained a more diverse wax profile including alcohols, acids, and esters. Thus, non-alkane wax compounds might be related to oviposition. In sum, our study suggests that several cues act in concert to provide oviposition cues for the sawfly N. oligospilus: females are attracted to volatiles from a distance, and once alighting on the plant, they seek specific chemical contact cues in order to lay eggs.
Subject(s)
Food Chain , Hymenoptera/physiology , Oviposition , Salix/anatomy & histology , Salix/physiology , Animals , Cues , Female , Herbivory , Hymenoptera/growth & development , Larva/growth & development , Larva/physiology , Olfactory Perception , Plant Leaves/anatomy & histology , Plant Leaves/physiology , Salix/genetics , Species Specificity , Volatile Organic Compounds/metabolismABSTRACT
The understanding of the geographical variability of biomass energy is an essential requirement for the optimal location of biomass energy conversion plants. This research presents a multicriteria GIS-based assessment of biomass energy potentials and the appropriate siting of biomass plants in Nigeria. The study applies the weighted overlay multicriteria decision analysis method. Crop and forest areas, settlement (energy supply areas), shrub/grasslands, barren land, water bodies, distance from water sources, road accessibility, topography, and aspect are the criteria that were considered for locating a biomass facility in this study. The results suggest that the theoretical, technical, and economical energy potentials of crop residues are highest in the North-East region of Nigeria and estimated at 1,163.32, 399.73, and 110.56 PJ/yr, respectively, and lowest in the South-East at 52.36, 17.99, and 4.98 PJ/yr, respectively. The theoretical, technical, and economical energy potentials of forest residues are highest in the North-West, estimated at 260.18, 156.11, and 43.18 PJ/yr, respectively, and lowest in the South-East at 1.79, 1.08, and 0.30 PJ/yr, respectively. Although most areas were identified to be suitable for siting biomass plants across Nigeria, the most suitable areas are located in the northern part of the country and include Niger, Zamfara, the Federal Capital Territory, Nassarawa, Kano, Kebbi, Kaduna, and Borno State. The study supports the Nigerian bio-energy policy that proposes to effectively utilize Nigeria's non-fuelwood as a substitute for the felling of trees. This is very important to strengthen its commitment at the COP26 International Climate Conference, which is to conserve and restore its forest. Furthermore, this study will serve as a good reference for policymakers to make well-informed decisions on tackling the energy insecurity in Nigeria.
ABSTRACT
Lithium-ion battery (LiB), a leading residual energy resource for electric vehicles (EVs), involves a market presenting exponential growth with increasing global impetus towards electric mobility. To promote the sustainability perspective of the EVs industry, this paper introduces a hybridized decision support system to select the suitable location for a LiB manufacturing plant. In this study, single-valued neutrosophic sets (SVNSs) are considered to diminish the vagueness in decision-making opinions and evade flawed plant location assessments. This study divided into four phases. First, to combine the single-valued neutrosophic information, some Archimedean-Dombi operators are developed with their outstanding characteristics. Second, an innovative utilization of the Method based on the Removal Effects of Criteria (MEREC) and Stepwise Weight Assessment Ratio Analysis (SWARA) is discussed to obtain objective, subjective and integrated weights of criteria assessment with the least subjectivity and biasedness. Third, the Double Normalization-based Multi-Aggregation (DNMA) method is developed to prioritize the location options. Fourth, an illustrative study offers decision-making strategies for choosing a suitable location for a LiB manufacturing plant in a real-world setting. Our outcomes specify that Bangalore (L 2), with an overall utility degree (0.7579), is the best plant location for LiB manufacturing. The consistency and robustness of the presented methodology are discussed with the comparative study and sensitivity investigation. This is the first study in the current literature that has proposed an integrated methodology on SVNSs to select the best LiB manufacturing plant location by estimating both the objective and subjective weights of criteria and by considering ambiguous, inconsistent, and inexact manufacturing-based information.
ABSTRACT
BACKGROUND: Vision plays a critical role in host location and oviposition behavior for herbivorous insects. However, the molecular mechanisms underlying visual regulation in host recognition and oviposition site selection in insects remains unknown. The aim of this study was to explore the key visual genes that are linked to the host plant location of the fruit fly, Bactrocera minax. RESULTS: Using a host specialist fruit fly, B. minax, which lays eggs only into immature green citrus fruit, we undertook behavioral, transcriptomic, and RNAi research to identify the molecular basis for host fruit color recognition. In laboratory and field assays we found that adults prefer green over other colors, and this preference is significantly increased in sexually mature over immature flies. Furthermore, we identified that the Rh6 gene, responsible for green spectral sensitivity, has elevated expression in mature flies over immature flies. RNAi suppression of Rh6 eliminated the preference for green, resulting in a significant decrease in the number of eggs laid by B. minax in green unripe citrus. CONCLUSION: These results show that the Rh6 gene modulates the visual mechanism of host utilization in B. minax, providing a genetic basis for visual host location in a non-model insect herbivore. © 2018 Society of Chemical Industry.
Subject(s)
Insect Proteins/genetics , Rhodopsin/genetics , Tephritidae/genetics , Tephritidae/physiology , Visual Perception/genetics , Animals , Female , Genomics , Male , Oviposition/genetics , PhylogenyABSTRACT
BACKGROUND: The cochineal scale, Porphyrophora sophorae (Hemiptera: Coccoidea, Margarodidae), is one of the most serious arthropod pests of Chinese liquorice, Glycyrrhiza uralensis (Fabaceae), an important medicinal herb. The adult females tend to deposit the ovisacs in soil relatively far away from liquorice plants. After hatching, neonates move out of the soil and may use chemical cues to search for new hosts. RESULTS: We collected and analysed the volatiles from soils with and without liquorice roots, and chromatographic profiles revealed hexanal, ß-pinene and hexanol as potential host-finding cues for P. sphorae. The attractiveness of these compounds to neonates was studied in the laboratory using four-arm olfactometer bioassays. The larvae showed a clear preference for ß-pinene over hexanal and hexanol, as well as all possible combinations of the three compounds. In addition, a field experiment confirmed that ß-pinene was significantly more attractive than hexanal and hexanol. CONCLUSION: Newly eclosed larvae of P. sphorae exploit root volatiles as chemical cues to locate their host plant. ß-Pinene proved to be the major chemical cue used by P. sphorae neonates searching for roots of their host plant. © 2016 Society of Chemical Industry.
Subject(s)
Aldehydes , Bridged Bicyclo Compounds , Glycyrrhiza uralensis/chemistry , Hemiptera/physiology , Hexanols , Monoterpenes , Aldehydes/chemistry , Animals , Appetitive Behavior , Bicyclic Monoterpenes , Bridged Bicyclo Compounds/chemistry , Cues , Glycyrrhiza uralensis/parasitology , Hemiptera/growth & development , Hexanols/chemistry , Larva/physiology , Monoterpenes/chemistry , Odorants , Plant Roots/chemistry , Plant Roots/parasitology , Soil/chemistry , VolatilizationABSTRACT
Projective cover (PC) and aboveground biomass (AGB) are the key traits with space attributes of individual plants. They are crucial to the understanding of the plant dynamics and plant patterns at population level. Spatial patterns based on individual plant positions (IND) have been extensively investigated in previous studies. However, very few have focused on PC and AGB. We tested the hypothesis that different plant traits represent different spatial patterns and plant-to-plant interactions. Two 40 m × 40 m plots of two typical desert shrub populations (Seriphidium terrae-albae and Artemisia songarica) were surveyed in the Gurbantunggut Desert of north-western China. Each plot was divided into a series of subplots (grids) at different scales (17 scales from 0.5 m to 20 m) using GIS (geographic information system). The spatial patterns of IND, PC and AGB were determined using aggregation and information dimension analyses together with changes in the scales. The IND and AGB of the two populations exhibited clumped tendencies at all scales (except at the 0.5 m scale for S. terrae-albae), whereas PC showed uniform distribution patterns at the moderate and small scales, (0.5 m to 8.0 m for S. terrae-albae and 0.5 m to 4.0 m for A. songarica), indicating that crown-to-crown competition for sunlight was strong at these scales. Although IND had a slightly higher coefficient of variation at the small scales, its information dimension was smaller than those of PC and AGB, indicating that PC and AGB had higher spatial complexities. In conclusion, the three parameters represented different spatial patterns across multiple scales; PC and AGB showed strong spatial complexities and PC was also an accurate indicator of plant-to-plant competition.