Search Results (31)

We integrate morphological variation, CO1 distance and clustering, and geographic distribution to document unrecognized diversity within Meranoplus ‘berrimah’ and M. ‘snellingi’, members of the M. diversus group of specialist seed harvesters from Australia’s monsoonal (seasonal) tropics. This follows similar analyses of two other monsoonal ‘species’ of the group, M. ajax and M. unicolor, showing that both represent highly diverse complexes comprising an estimated 100 species each. We recognize eleven species among the 34 sequenced specimens attributable to M. berrimah and ten species among the 29 sequenced specimens attributable to M. snellingi. Images of all these species are provided. The M. berrimah complex has a far broader geographic range than was apparent when M. berrimah was originally described, occurring in the Kimberley region of Western Australia in addition to the Top End of the Northern Territory, whereas the M. snellingi complex appears to be restricted to the Top End. The limited geographic representation of our sequenced specimens suggests that many additional species occur in both complexes. We estimate that the M. snellingi complex contains 15–20 species in total, and that this number is considerably higher in the M. berrimah complex because of its broader distributional range. Our study provides further evidence that monsoonal Australia is a global centre of ant diversity, but it is not formally recognized as such because the great majority of its species is undescribed. Full article

Habitat fragmentation profoundly alters ecological processes such as seed predation and dispersal. Ants play a central role as seed removers and dispersers, yet the effects of fragmentation on seed-carrying ant assemblages in dry tropical forests remain insufficiently studied. In this work, we examined the influence of forest fragmentation on seed-carrying ants in the Chaco forests of central Argentina. Ants were sampled across nine forest fragments of varying sizes and two continuous forests within an agroecosystem landscape, and species richness, composition, and occurrence were analyzed. Our results revealed that species richness did not vary significantly with fragment size; however, fragmentation caused pronounced shifts in species composition, with clear distinctions between continuous forests and fragments. Large-bodied specialist harvester ants declined in fragments, whereas small- to medium-sized generalist species from genera such as Pheidole and Solenopsis persisted. These compositional changes suggest that although overall seed removal rates may remain stable, the functional quality of seed dispersal likely diminishes. This study highlights the sensitivity of seed-carrying ant assemblages to habitat fragmentation and underscores the need for further research that integrates behavioral and landscape-scale approaches to better assess impacts on seed removal, dispersal, and forest regeneration in fragmented dry forests. Full article

This study addresses the core challenges of precise marigold corollas recognition and efficient continuous path planning under complex natural conditions (strong illumination, occlusion, adhesion) by proposing an integrated lightweight visual recognition and real-time path planning framework. We introduce MPD-YOLO, an optimized model based on YOLOv11n, incorporating (1) a Multi-scale Information Enhancement Module (MSEE) to boost feature extraction; (2) structured pruning for significant model compression (final size: 2.1 MB, 39.6% of original); and (3) knowledge distillation to recover accuracy loss post-pruning. The resulting model achieves high precision (P: 89.8%, mAP@0.5: 95.1%) with reduced computational load (3.2 GFLOPs) while demonstrating enhanced robustness in challenging scenarios—recall significantly increased by 6.8% versus YOLOv11n. Leveraging these recognition outputs, an adaptive ant colony algorithm featuring dynamic parameter adjustment and an improved pheromone strategy reduces average path planning time to 2.2 s—a 68.6% speedup over benchmark methods. This integrated approach significantly enhances perception accuracy and operational efficiency for automated marigold harvesting in unstructured environments, providing robust technical support for continuous automated operations. Full article

Against the backdrop of global food security challenges, precise pre-harvest yield estimation of large-scale soybean crops is crucial for optimizing agricultural resource allocation and ensuring stable food supplies. This study developed an integrated prediction model for county-level soybean yield forecasting, which combines multi-source remote-sensing data with advanced deep learning techniques. The ant colony optimization-convolutional neural network with gated recurrent units and multi-head attention (ACGM) model showcases remarkable predictive prowess, as evidenced by a coefficient of determination (R²) of 0.74, a root mean square error (RMSE) of 123.94 kg/ha, and a mean absolute error (MAE) of 105.39 kg/ha. When pitted against other models, including the random forest regression (RFR), support vector regression (SVR), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) models, the ACGM model clearly emerges as the superior performer. This study identifies August as the optimal period for early soybean yield prediction, with the model performing best when combining environmental and photosynthetic parameters (ED + PP). The ACGM model demonstrates a good accuracy and generalization ability, providing a practical approach for refined agricultural management. By integrating deep learning with open-source remote-sensing data, this research opens up new avenues for enhancing agricultural decision-making and safeguarding food security. Full article

Recent advancements in agricultural mobile robots (agribots) have enabled the execution of critical tasks such as crop inspection, precision spraying, and selective harvesting. While agribots show significant potential, conventional path-planning algorithms suffer from three limitations: (1) inadequate dynamic obstacle avoidance, which may compromise operational safety, (2) premature convergence to local optima, and (3) excessive energy consumption due to suboptimal trajectories. To overcome these challenges, this study proposes an enhanced Dynamic Genetic Algorithm—Ant Colony Optimization (DGA-ACO) framework. It integrates a 2D risk-penalty mapping model with dynamic obstacle avoidance mechanisms, improves max–min ant system pheromone allocation through adaptive crossover-mutation operators, and incorporates a hidden Markov model for accurately forecasting obstacle trajectories. A multi-objective fitness function simultaneously optimizes path length, energy efficiency, and safety metrics, while genetic operators prevent algorithmic stagnation. Simulations in different scenarios show that DGA-ACO outperforms Dijkstra, A*, genetic algorithm, ant colony optimization, and other state-of-the-art methods. It achieves shortened path lengths and improved motion smoothness while achieving a certain degree of dynamic obstacle avoidance in the global path-planning process. Full article

Maize productivity has remained low and has worsened in the wake of a changing climate, resulting in new invasive pests, with pests that were earlier designated as minor becoming major and with pathogens being transported by pests and/or entering their feeding sites. A study was conducted in 2021 in the Kisumu and Makueni counties, Kenya, to determine how different maize cropping systems affect insect diversity, insect damage to maize, and insects’ ability to spread mycotoxigenic fungi in pre-harvest maize. The field experiments used a randomized complete block design, with the four treatments being maize monocrop, maize intercropped with beans, maize–bean intercrop with the addition of Trichoderma harzianum at planting, and push–pull technology. The FAW, Spodoptera frugiperda (J.E Smith) (Lepidoptera: Noctuidae), was the most damaging pest in the two regions. The push–pull and the maize–bean intercropping technologies significantly reduced the maize foliage and ear damage caused by the FAW. Beetles passively spread mycotoxigenic Aspergillus spp. and Fusarium verticillioides on pre-harvest maize. Maize weevils, namely, Sitophilus zeamais Motschulsky, 1855 (Coleoptera: Curculionidae), and Carpophilus dimidiatus Fabricius, 1792 (Coleoptera: Nitidulidae), earwigs, namely, Forficula spp. L. (Dermaptera: Forficulidae), and carpenter ants, namely, Camponotus spp. L. (Hymenoptera: Formicidae) carried the highest number of spores on their exoskeletons. This study stresses the role of insects in the spread of fungi on pre-harvest maize and their possible control by intercropping and other cropping technologies. Full article

The cultivation model for spindle-shaped apple trees is widely used in modern standard apple orchards worldwide and represents the direction of modern apple industry development. However, without an effective obstacle avoidance path, the robotic arm is prone to collision with obstacles such as fruit tree branches during the picking process, which may damage fruits and branches and even affect the healthy growth of fruit trees. To address the above issues, a three-dimensional path -planning algorithm for full-field fruit obstacle avoidance harvesting for spindle-shaped fruit trees, which are widely planted in modern apple orchards, is proposed in this study. Firstly, based on three typical tree structures of spindle-shaped apple trees (free spindle, high spindle, and slender spindle), a three-dimensional spatial model of fruit tree branches was established. Secondly, based on the grid environment representation method, an obstacle map of the apple tree model was established. Then, the initial pheromones were improved by non-uniform distribution on the basis of the original ant colony algorithm. Furthermore, the updating rules of pheromones were improved, and a biomimetic optimization mechanism was integrated with the beetle antenna algorithm to improve the speed and stability of path searching. Finally, the planned path was smoothed using a cubic B-spline curve to make the path smoother and avoid unnecessary pauses or turns during the harvesting process of the robotic arm. Based on the proposed improved ACO algorithm (ant colony optimization algorithm), obstacle avoidance 3D path planning simulation experiments were conducted for three types of spindle-shaped apple trees. The results showed that the success rates of obstacle avoidance path planning were higher than 96%, 86%, and 92% for free-spindle-shaped, high-spindle-shaped, and slender-spindle-shaped trees, respectively. Compared with traditional ant colony algorithms, the average planning time was decreased by 49.38%, 46.33%, and 51.03%, respectively. The proposed improved algorithm can effectively achieve three-dimensional path planning for obstacle avoidance picking, thereby providing technical support for the development of intelligent apple picking robots. Full article

In order to solve the problem of the low pickup efficiency of the robotic arm when harvesting safflower filaments, we established a pickup trajectory cycle and an improved velocity profile model for the harvest of safflower filaments according to the growth characteristics of safflower. Bezier curves were utilized to optimize the picking trajectory, mitigating the abrupt changes produced by the delta mechanism during operation. Furthermore, to overcome the slow convergence speed and the tendency of the ant colony algorithm to fall into local optima, a safflower harvesting trajectory planning method based on an ant colony genetic algorithm is proposed. This method includes enhancements through an adaptive adjustment mechanism, pheromone limitation, and the integration of optimized parameters from genetic algorithms. An optimization model with working time as the objective function was established in the MATLAB environment, and simulation experiments were conducted to optimize the trajectory using the designed ant colony genetic algorithm. The simulation results show that, compared to the basic ant colony algorithm, the path length with the ant colony genetic algorithm is reduced by 1.33% to 7.85%, and its convergence stability significantly surpasses that of the basic ant colony algorithm. Field tests demonstrate that, while maintaining an S-curve velocity, the ant colony genetic algorithm reduces the harvesting time by 28.25% to 35.18% compared to random harvesting and by 6.34% to 6.81% compared to the basic ant colony algorithm, significantly enhancing the picking efficiency of the safflower-harvesting robotic arm. Full article

Most plants produce floral nectar to attract pollinators that impact pollination and seed production; some of them also secrete extrafloral nectar harvested by insects that may influence the plant reproductive success. The aim of this study was to analyze the effects of excluding pollinators and/or ants on the per-plant reproductive success in two species (Dyckia floribunda Griseb. and Dyckia longipetala Baker, Bromeliaceae) that produce floral and extrafloral nectar. The hypothesis states that both ecological processes (pollination and ant defense) involving nectar-mediated animal–plant interactions are beneficial for plant reproductive success. We expected the highest decrease in the plant fruit and seed sets when the pollinators and ants were excluded, and a moderate decrease when solely ants were excluded, compared to the control plants (those exposed to pollinators and ants). In addition, a lower natural reproductive success was also expected in the self-incompatible D. longipetala than in the self-compatible D. floribunda, as the former totally depends on animal pollination for seed production. D. floribunda and D. longipetala presented similar trends in the response variables, and the expected results for the experimental treatments were observed, with some variations between species and among populations. The ecological function of nectar is important because these two plant species depend on pollinators to produce seeds and on ants to defend flowers from the endophytic larvae of Lepidoptera. The study of multispecies interactions through mechanistic experiments could be necessary to clarify the specific effects of different animals on plant reproductive success. Full article

The production of the Korla fragrant pear is significant, but the optimal harvesting time is short; therefore, the reasonable use of mechanical arms for harvesting is conducive to promoting the sustainable development of the fragrant pear industry. The efficiency of a robot arm when picking fragrant pears is not only determined by the successful extraction of fragrant pears in a complex environment, but the picking sequence of fragrant pears also directly affects the efficiency of the robot arm. In order to simulate an orchard-picking scenario, this paper built three fragrant pear tree models indoors. The number of fragrant pears on the fragrant pear trees was 5, 10, and 20. Three sets of experiments were designed for comparison with real-world conditions. The main steps were as follows: calibrate the three-dimensional coordinates of each fragrant pear on the fragrant pear trees; determine the end position of the robotic arm at each picking point; find the inverse solution for each group; transform the solutions into matrix form using the rated power of each joint as the weight, and identify the minimum value, which is the angle of each joint in the robotic arm when picking the fragrant pear; use the intelligent socket to find the average energy consumption and average time consumed for picking each group of fragrant pears; and determine the loss ratio of the robotic arm based on the amount of rotation in each joint during picking. The experimental results show that the multiple weighting method reduced the energy consumption by 10.627%, 16.072%, and 24.417%, and the time consumption by 11.988%, 14.428%, and 22.561%, respectively, relative to the hybrid ant colony–particle swarm optimization algorithm, which proves the rationality of the fragrant pear picking order delineated using the multiple weighting method. Full article

The amount of energy that a thermoelectric generator (TEG) is capable of harvesting mainly depends on the temperature difference between the hot and cold sides of the TEG. To ensure that the TEG operates efficiently under any condition or temperature variation, it is crucial to have a reliable MPPT that keeps the TEG as close as possible to its MPP. Fractional control is usually preferred over integer control because it allows for more precise, flexible, and robust control over a system. The controller parameters in fractional control are not limited to integer values, but rather can have fractional values, which enables more precise control of the system’s dynamics. In this paper, an optimized fractional PID-based MPPT that effectively addresses two primary issues, dynamic response and oscillation around MPP, is proposed. Firstly, the five unknown parameters of the optimized fractional PID-based MPPT were estimated by the BES “bald eagle search” algorithm. To validate the superiority of the BES, the results were compared with those obtained using other optimization algorithms, such as ant lion optimizer (ALO), equilibrium optimizer (EO), cuckoo search (CS), and WOA “whale optimization algorithm”. The results demonstrate that BES outperforms ALO, EO, CS, and WOA. Additionally, the tracking performance of proposed MPPT was evaluated using two scenarios that involved variations in temperature differences and sudden changes in the load demanded. Overall, the proposed optimized fractional PID-based MPPT effectively improves dynamic performance and eliminates oscillation around MPP under steady state compared to other tracking methods, such as P&O “perturb and observe” and incremental conductance (INR). Full article

The intranidal myrmecophilous arthropod fauna of the Maltese Islands is reviewed. Thirty species from nine orders are found to be obligate myrmecophiles, of which four species are recorded from the Maltese archipelago for the first time: Phrurolithus sp. (Araneae: Phrurolithidae), Pogonolaelaps canestrinii (Berlese, 1904), Gymnolaelaps messor Joharchi, Halliday, Saboori & Kamali, 2011 and G. myrmecophilus (Berlese, 1892) (Mesostigmata: Laelapidae). Phrurolithus also represents the first record of the family Phrurolithidae in Malta. Notes on the biology and local distribution of each species are provided, including ant-myrmecophile associations, of which two appear to be previously unknown: the occurrence of Smynthurodes betae Westwood, 1849 (Hemiptera: Aphididae) in the nest of Plagiolepis pygmaea (Latreille, 1798) and Phrurolithus in the nest of Pheidole pallidula (Nylander, 1849). Fourteen additional species are found to be either only occasionally myrmecophilic, accidental ant-guests or potentially myrmecophilous, the latter remaining ambiguous due to a lack of knowledge of their biology. Of these, the family Caeculidae (Arachnida: Trombidiformes) represents a new record for the Maltese Islands, on the basis of Microcaeculus sp. occurring in a nest of Camponotus barbaricus Emery, 1905. Preliminary results indicate that Messor nests may be repositories of considerable myrmecophile diversity, with the most unique symbionts. Full article

Ant nests’ relatively stable and long-lasting microhabitats present ideal living conditions for many uni- and multicellular organisms, whose relationships range from mutualistic to parasitic. Messor harvester ants inhabit arid and semi-arid open areas where their colonies consist of large numbers of individuals. Due to the high number of other organisms associated with harvester ants, their nests can be defined as islands for unique biota. Despite significant progress in research on ant-associated fungi in Europe, little is still known about the recently described ectoparasitic fungus Rickia lenoirii Santamaria, 2015 (Laboulbeniales), found on two species of ants of the genus Messor. Here we report for the first time the occurrence of the ectoparasitic ant-associated fungus R. lenoirii from three countries (Albania, Bulgaria, and continental Greece) and multiple localities in the Balkans. The fungus was detected on four ant host species—Messor structor (Latreille, 1798), M. wasmanni Krausse, 1910, M. hellenius Agosti & Collingwood, 1987, and M. mcarthuri Steiner et al., 2018 with the latter two representing new host records. Furthermore, spores of the widespread endoparasitic fungus of ants, Myrmicinosporidium durum Hölldobler, 1933 (Blastocladiomycota), were reported for the first time in Messor structor (Bulgaria). Images of the ant-associated Rickia lenoirii taken with a scanning electron microscope, a comparison with R. wasmannii, and a distribution map are also presented. Full article

There are several well-studied examples of protective symbiosis between insect host and symbiotic actinobacteria, producing antimicrobial metabolites to inhibit host pathogens. These mutualistic relationships are best described for some wasps and leaf-cutting ants, while a huge variety of insect species still remain poorly explored. For the first time, we isolated actinobacteria from the harvester ant Messor structor and evaluated the isolates’ potential as antimicrobial producers. All isolates could be divided into two morphotypes of single and mycelial cells. We found that the most common mycelial morphotype was observed among soldiers and least common among larvae in the studied laboratory colony. The representative of this morphotype was identified as Streptomyces globisporus subsp. globisporus 4-3 by a polyphasic approach. It was established using a E. coli JW5503 pDualRep2 system that crude broths of mycelial isolates inhibited protein synthesis in reporter strains, but it did not disrupt the in vitro synthesis of proteins in cell-free extracts. An active compound was extracted, purified and identified as albomycin δ2. The pronounced ability of albomycin to inhibit the growth of entomopathogens suggests that Streptomyces globisporus subsp. globisporus may be involved in defensive symbiosis with the Messor structor ant against infections. Full article

Observations have shown that seeds collected by harvester ants are less likely to mold. Based on evolutionary analysis and other research, it was hypothesized that harvester ants could apply actinomycetes to protect seeds, similar to the protection of mutualistic fungi by leafcutter ants. Two actinomycetes were successfully isolated from the harvester ant Messor orientalis. The taxonomic status of the actinomycetes was determined by 16S rRNA sequence analysis and biochemical experimental observations. Their inhibitory effects on plant pathogens were measured. One of the bacteria was identified as Brachybacterium phenoliresistens and denoted as B. phenoliresistens MO. The other belonged to the genus Microbacterium. It was named Microbacterium sp. Growth rate determination and coculture experiments were performed to explore the inhibitory effect of actinomycetes on indicator plant pathogens. The inhibition rates of the actinomycetes toward Peronophythora litchii and Rhizoctonia solani were 100% in media containing 30% or more fermentation broth, and they also showed an inhibitory effect on Colletotrichum siamense. The coculture experiment supported this result by showing that the growth of P. litchii and R. solani was inhibited in the presence of actinomycetes. Therefore, the results of this study show the agricultural application potential of these bacteria and may provide a reference for research on the symbiosis of harvester ants with actinomycetes. Full article