Search Results (20)

Prays oleae Bernard, 1788, or the olive moth, is a significant pest in Croatian olive groves. This study aims to develop a functional model based on an artificial neural network to detect olive moths in real time. This study was conducted in two different orchards in Zadar County, Croatia, in the periods from April to September 2022 and from May to July 2023. Moth samples were collected by placing traps with adhesive pads in these orchards. Photos of the pads were taken every week and were later annotated and used to develop the dataset for the artificial neural network. This study primarily focused on the average precision parameter to evaluate the model’s detection capabilities. The average AP value for all classes was 0.48, while the average AP value for the Olive_trap_moth class, which detected adult P. oleae, was 0.59. The model showed the best results at an IoU threshold of 50%, achieving an AP50 value of 0.75. The AP75 value was 0.56 at an IoU = 75%. The mean average precision (mAP) was 0.48. This model is a promising tool for P. oleae detection; however, further research is advised. Full article

The antennal sensilla serve as a crucial olfactory organ, enabling insects to detect semiochemicals and adjust their host-seeking and oviposition behaviors accordingly. Monolepta signata (Oliver) (Coleoptera: Chrysomelidae), has emerged as a significant agricultural pest that affects key economic crops such as maize and cotton. Despite the development of various control methods based on volatile stimulation, there is still limited documentation on the sensilla involved in olfaction. In this study, the ultrastructure of the sensilla, especially the olfactory sensilla on the antennae of both males and females, was investigated with scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Three types of olfactory sensillum types, including trichodea, basiconica, and coeloconica, and four non-olfactory sensilla including chaetica, campaniformia, auricillica, and Böhm bristle were observed. Sensilla trichodea and basiconica on the antennae of M. signata were further classified into two subtypes according to their morphology. For the first time, the pores on the sensilla trichodea, basiconica, and coeloconica cuticular walls were observed in this species, suggesting that they are involved in semiochemical perception. This study contributes new insights into the olfactory system of M. signata, which can be integrated with other molecular, genetic, and behavioral research to establish a comprehensive understanding of its physiological functions. Full article

In recent years, the integration of smartphone technology with novel sensing technologies, Artificial Intelligence (AI), and Deep Learning (DL) algorithms has revolutionized crop pest and disease surveillance. Efficient and accurate diagnosis is crucial to mitigate substantial economic losses in agriculture caused by diseases and pests. An innovative Apple^® and Android™ mobile application for citizen science has been developed, to enable real-time detection and identification of plant leaf diseases and pests, minimizing their impact on horticulture, viticulture, and olive cultivation. Leveraging DL algorithms, this application facilitates efficient data collection on crop pests and diseases, supporting crop yield protection and cost reduction in alignment with the Green Deal goal for 2030 by reducing pesticide use. The proposed citizen science tool involves all Farm to Fork stakeholders and farm citizens in minimizing damage to plant health by insect and fungal diseases. It utilizes comprehensive datasets, including images of various diseases and insects, within a robust Decision Support System (DSS) where DL models operate. The DSS connects directly with users, allowing them to upload crop pest data via the mobile application, providing data-driven support and information. The application stands out for its scalability and interoperability, enabling the continuous integration of new data to enhance its capabilities. It supports AI-based imaging analysis of quarantine pests, invasive alien species, and emerging and native pests, thereby aiding post-border surveillance programs. The mobile application, developed using a Python-based REST API, PostgreSQL, and Keycloak, has been field-tested, demonstrating its effectiveness in real-world agriculture scenarios, such as detecting Tuta absoluta (Meyrick) infestation in tomato cultivations. The outcomes of this study in T. absoluta detection serve as a showcase scenario for the proposed citizen science tool’s applicability and usability, demonstrating a 70.2% accuracy (mAP₅₀) utilizing advanced DL models. Notably, during field testing, the model achieved detection confidence levels of up to 87%, enhancing pest management practices. Full article

The olive fruit fly (Bactrocera oleae Rossi) is the most dangerous pest of olive fruits and negatively influences the chemical and sensory quality of the oil produced. Organic farms have few tools against this pest and are constantly looking for effective and sustainable products such as geomaterials, i.e., zeolite. Since a particle film covers the canopy, a study was carried out on the olive tree’s responses to zeolite foliar coating. The tested treatments were natural zeolite (NZ), zeolite enriched with ammonium (EZ), and Spintor-Fly^® (SF). EZ was associated with higher photosynthetic activity with respect to the other treatments, while no differences were found between SF and NZ. Foliar treatments affect the amount of BVOC produced in both leaves and olives, where 26 and 23 different BVOCs (biogenic volatile organic compounds) were identified but not the type of compounds emitted. Foliar treatment with EZ significantly affected fruit size, and the olive fruit fly more frequently attacked the olives, while treatment with NZ had olives with similar size and attack as those treated with Spintor-Fly^®; no difference in oil quantity was detected. Oil produced from olives treated with NZ presented higher values of phenolic content and intensities of bitterness and spiciness than oils from those treated with EZ and SF. According to the results of this study, using zeolite films on an olive tree canopy does not negatively influence plant physiology; it has an impact on BVOC emission and the chemical and sensory characteristics of the oil. Full article

Olive (Olea europaea L.) fruit and derived products play a pivotal role in the Mediterranean diet, to which they contribute their gastronomic value and their health-promoting properties. The fruit cuticle constitutes the interface between the plant and the surrounding environment, and it modulates relevant traits such as water loss, mechanical resistance, and susceptibility to pests and rots. Hence, a better knowledge of fruit cuticle properties and the impact thereupon of agronomic factors could help improving olive grove management. In this work, time–course changes in fruit cuticle yields and composition were assessed during the on-tree ripening of ‘Arbequina’ olives obtained from irrigated or rain-fed trees grown at a commercial grove located in El Soleràs (Catalonia, Spain), where low annual rainfall occur together with cold winters and hot dry summers. Significantly higher wax contents were observed for rain-fed than for irrigated fruits, both in relative (% over total cuticle) and in absolute terms (from 231 to 840 µg cm⁻² and from 212 to 560 µg cm⁻², respectively, contingent upon the maturity stage), in agreement with their proposed role as a barrier against water loss. Compositional differences in cuticular waxes and in cutin monomers were also detected between irrigated and rain-fed olives, with major changes involving significantly higher loads per surface area of triterpenoids and ω-hydroxy fatty acids in the latter. In contrast to the load and composition of cuticular wax, no apparent impact of irrigation was observed on either total cuticle yields or cuticle thickness. Full article

In recent years, the use of Unmanned Aerial Vehicles (UAVs) has been spreading widely, as in plant pest control. The collection of huge amounts of spatial data raises various issues including that of scale. Data from UAVs generally explore multiple scales, so the problem arises in determining which one(s) may be relevant for a given application. The objective of this work was to investigate the potential of UAV images in the fight against the Xylella pest for olive trees. The data were a multiband UAV image collected on one date in an olive grove affected by Xylella. A multivariate geostatistics approach was applied, consisting firstly of estimating the linear coregionalization model to detect the scales from the data; and secondly, of using multiple factor kriging to extract the sets of scale-dependent regionalized factors. One factor was retained for each of the two selected scales. The short-range factor could be used in controlling the bacterium infection while the longer-range factor could be used in partitioning the field into three management zones. The work has shown the UAV data potential in Xylella control, but many problems still need to be solved for the automatic detection of infected plants in the early stages. Full article

Given the importance of olive growing, especially in Mediterranean countries, it is crucial that there is a constant process of modernization aimed at both environmental sustainability and the maintenance of high standards of production. The use of remote sensing (RS) allows intervention in a specific and differentiated way in olive groves, depending on their variability, in managing different agronomic aspects. The potentialities of the application of RS in olive growing are topics of great agronomic interest to olive growers. Using the tools provided by RS and the modernization of the olive sector can bring great future prospects by reducing costs, optimizing agronomic management, and improving production quantity and quality. This article is part of a review that aims to cover the past, from the 2000s onwards, and the most recent applications of aerial RS in olive growing in order to be able to include research and all topics related to the use of RS on olive trees. As far as the use of RS platforms such as satellites, aircraft, and unmanned aerial vehicles (UAVs) as olive growing is concerned, a literature review showed the presence of several works devoted to this topic. This article covers purely agronomic matters of interest to olive farms (and related research that includes the application of RS), such as yielding and managing diseases and pests, and detection and counting of olive trees. In addition to these topics, there are other relevant aspects concerning the characterization of the canopy structure of olive trees which is particularly interesting for mechanized pruning management and phenotyping. Full article

Olives are an essential crop for Greece and constitute a major economic and agricultural factor. Diseases, pests, and environmental conditions are all factors that can deteriorate the health status of olive crops by causing plant stress. Researchers can utilize remote sensing to assist their actions in detecting these sources of stress and act accordingly. In this experiment, Sentinel-2 data were used to create vegetation indices for commercial olive fields in Halkidiki, Northern Greece. Twelve machine learning algorithms were tested to determine which type would be the most efficient to detect plant stress in olive trees. In parallel, a test was conducted by testing 26 thresholds to determine how setting different thresholds for stress incidence affects model performance and which threshold constitutes the best choice for more accurate classification. The results show that among all tested classification algorithms, the quadratic discriminant analysis provided the best performance of 0.99. The stress incidence threshold used in the current case to generate the best-performing model was 6%, but the results suggest that setting customized thresholds relevant to specific cases would provide optimal results. The best-performing model was used in a one-vs.-rest multiclass classification task to determine the source of the stress between four possible classes: “healthy”, “verticillium”, “spilocaea”, and “unidentified”. The multiclass model was more accurate in detection for the “healthy” class (0.99); the “verticillium” and “unidentified” classes were less accurate (0.76); and “spilocaea” had the lowest score (0.72). Findings from this research can be used by experts as a service to enhance their decision-making and support the application of efficient strategies in the field of precision crop protection. Full article

Pyrethrins are the most widely used insecticide class in olive groves with organic management. Although there are data sets about insect pests of stored products and human parasites developing resistance to pyrethrins, there is no information on the long-term effect on olive agroecosystems. A field method based on the experimental induction of sublethal effects by means of insecticide application, and the monitoring of the response of insects through post-treatment sampling, has recently been developed. This method has allowed for the detection of populations behaviorally resistant to organophosphates in integrated pest management (IPM) and conventional crops. With the application of a similar methodology, this study aimed to verify the possible reaction of natural enemies in organic crops, using pyrethrins as an inducing insecticide. The study was carried out in 2019 in two olive groves in southern Spain (Jaén, Andalusia), one of them being IPM and the other being an organic production system. The results did not allow for verification of the behavioral resistance in populations of natural enemies of both IPM and organic management against pyrethrins, while against dimethoate, behavioral resistance was verified in IPM management. The possible causes involved in obtaining these results are discussed. Full article

Understanding how small mammals (SM) are associated with environmental characteristics in olive groves is important to identify potential threats to agriculture and assess the overall conservation value and functioning of agro-ecosystems. Here, we provide first insights on this topic applied to traditional olive groves in northeast (NE) Portugal by assessing the landscape attributes that determine SM occurrence, focusing on one species of conservation concern (Microtus cabrerae Thomas 1906) and one species often perceived as a potential pest of olives (Microtus lusitanicus Gerbe 1879). Based on SM genetic non-invasive sampling in 51 olive groves and surrounding habitats, we identified seven rodent species and one insectivore. Occupancy modelling indicated that SM were generally less detected within olive groves than in surrounding habitats. The vulnerable M. cabrerae reached a mean occupancy (95% CI) of 0.77 (0.61–0.87), while M. lusitanicus stood at 0.37 (0.24–0.52). M. cabrerae was more likely to occur in land mosaics with high density of agricultural field edges, while M. lusitanicus was more associated with high density of pastureland patches. Overall, our study suggests that the complex structure and spatial heterogeneity of traditionally managed olive grove agro-ecosystems may favor the occurrence of species-rich SM communities, possibly including well-established populations of species of conservation importance, while keeping potential pest species at relatively low occupancy rates. Full article

The olive fruit fly, Bactrocera oleae (Rossi) is economically the most important olive pest, causing yield losses in all olive growing areas where is detected. Considering that EU requires the reduction of pesticide use by up to 100% by 2050, more effective non-pesticide lures for B. oleae monitoring and/or controlling are needed. This research was aimed at investigating the attractiveness of different blends of olive fruit fly-associated yeast volatiles toward B. oleae. Three blends of olive fruit fly-associated yeast volatiles: isoamyl alcohol and 2-phenethyl alcohol; isoamyl alcohol, 2-phenethyl alcohol and 2-phenethyl acetate; and isoamyl alcohol, 2-phenethyl acetate and isobutyl acetate were selected and tested on yellow sticky traps for attraction of B. oleae in olive orchard. Results showed that traps containing all tested blends of olive fruit fly-associated yeast volatile compounds, in total, were significantly more attractive to B. oleae and were not significantly attractive to green lacewings, compared to the control. Among them, the most promising was the one containing the blend of isoamyl alcohol, 2-phenethyl acetate and isobutyl acetate because its attractiveness was constantly significant during investigation compared to the others. This blend in the future could lead us to the discovery of a new attractant for the monitoring and/or controlling of B. oleae. Full article

The olive moth (OM), Prays oleae (Bern.) (Lepidoptera: Yponomeutidae), is a major olive grove pest worldwide; however, until now, very few studies have investigated the effectiveness of mating disruption (MD) techniques against this pest. Experiments were carried out for two successive years (2019 and 2020) in three different olive groves in Andalucía (Southern Spain) to evaluate mating disruption’s efficacy in controlling the OM from the first to the third generation. The effectiveness of MD formulations against the three generations of OM was assessed by determining the percentage of infested olive fruits, the reduction of pheromone trap catches, and the number of affected inflorescences in both MD-treated and untreated control olive groves. The number of release points (one or two aerosol devices per ha) was also evaluated. In all years and trials, the mean number of males caught in traps placed in the MD-treated plots was significantly lower than untreated sites. Mating disruption registered a high suppression of male captures (>75%) in treated plots for two consecutive seasons. Concerning infested olive fruits, substantial reductions (about 80%) were observed in the MD plots of locations B and C, and a reduction of about 40% was detected in location A, compared to the control plot. Results showed that the installation of two aerosol devices/ha reduced fruit damage below 20% of infested olive fruits except for one site where a reduction of about 71% in the MD plot was recorded in 2019. Although few significant differences were associated with OM male catches and infested olive fruits between plots treated with one aerosol/ha and two aerosols/ha in most of the comparisons, significant differences in the number of olive inflorescences infested by P. oleae were found, suggesting a similar performance between the two tested aerosol densities. Results of two-year field trials in Andalucía demonstrated the potential of Mister P X841 aerosol devices as an effective tool for controlling the olive moth, P. oleae. Full article

Plants emit volatile organic compounds (VOCs) that induce metabolomic, transcriptomic, and behavioral reactions in receiver organisms, including insect pollinators and herbivores. VOCs’ composition and concentration may influence plant-insect or plant-plant interactions and affect soil microbes that may interfere in plant-plant communication. Many Trichoderma fungi act as biocontrol agents of phytopathogens and plant growth promoters. Moreover, they can stimulate plant defense mechanisms against insect pests. This study evaluated VOCs’ emission by olive trees (Olea europaea L.) when selected Trichoderma fungi or metabolites were used as soil treatments. Trichoderma harzianum strains M10, T22, and TH1, T. asperellum strain KV906, T. virens strain GV41, and their secondary metabolites harzianic acid (HA), and 6-pentyl-α-pyrone (6PP) were applied to olive trees. Charcoal cartridges were employed to adsorb olive VOCs, and gas chromatography mass spectrometry (GC-MS) analysis allowed their identification and quantification. A total of 45 volatile compounds were detected, and among these, twenty-five represented environmental pollutants and nineteen compounds were related to olive plant emission. Trichoderma strains and metabolites differentially enhanced VOCs production, affecting three biosynthetic pathways: methylerythritol 1-phosphate (MEP), lipid-signaling, and shikimate pathways. Multivariate analysis models showed a characteristic fingerprint of each plant-fungus/metabolite relationship, reflecting a different emission of VOCs by the treated plants. Specifically, strain M10 and the metabolites 6PP and HA enhanced the monoterpene syntheses by controlling the MEP pathway. Strains GV41, KV906, and the metabolite HA stimulated the hydrocarbon aldehyde formation (nonanal) by regulating the lipid-signaling pathway. Finally, Trichoderma strains GV41, M10, T22, TH1, and the metabolites HA and 6PP improve aromatic syntheses at different steps of the shikimate pathway. Full article

The olive fruit fly (Bactrocera oleae Rossi) is the primary insect pest in all olive-growing regions worldwide. New integrated pest management (IPM) techniques are needed for B. oleae to mitigate reliance on pesticides used for its control which can result in negative environmental impacts. More effective lures for monitoring olive flies would help to know when and where direct chemical applications are required. The aim of this research was to find new, more effective methods for B. oleae detection and monitoring. Twelve insect-associated yeasts were selected and tested as living cultures in McPhail traps for the attraction of olive flies. Certain yeasts were more attractive than others to B. oleae; specifically, Kuraishia capsulata, Lachancea thermotolerans, Peterozyma xylosa, Scheffersomyces ergatensis, and Nakazawae ernobii, than the industry-standard dried torula yeast (Cyberlindnera jadinii; syn. Candida utilis). The attractiveness of dry, inactive (i.e., non-living) formulations of these five yeasts was also tested in the field. Inactive formulations of K. capsulata, P. xylosa, N. ernobii, and L. thermotolerans were significantly more attractive to B. oleae than commercially available torula yeast. Green lacewing, Chrysoperla comanche (Stephens) (Neuroptera: Chrysopidae), adults were incidentally caught in traps baited with the live yeast cultures. This is the first field study that compares olive fly attraction to yeast species other than torula yeast. Commercialization of yeasts that are more attractive than the torula standard would improve monitoring and associated control of the olive fruit fly. Full article

The importance of monitoring and modelling the impact of climate change on crop phenology in a given ecosystem is ever-growing. For example, these procedures are useful when planning various processes that are important for plant protection. In order to proactively monitor the olive (Olea europaea)’s phenological response to changing environmental conditions, it is proposed to monitor the olive orchard with moving or stationary cameras, and to apply deep learning algorithms to track the timing of particular phenophases. The experiment conducted for this research showed that hardly perceivable transitions in phenophases can be accurately observed and detected, which is a presupposition for the effective implementation of integrated pest management (IPM). A number of different architectures and feature extraction approaches were compared. Ultimately, using a custom deep network and data augmentation technique during the deployment phase resulted in a fivefold cross-validation classification accuracy of 0.9720 ± 0.0057. This leads to the conclusion that a relatively simple custom network can prove to be the best solution for a specific problem, compared to more complex and very deep architectures. Full article