Search Results (520)

This study evaluated the antifungal potential of essential oils (EOs): oregano (Origanum vulgare), rosemary (Salvia rosmarinus), clove (Syzygium aromaticum), thyme (Thymus vulgaris), cinnamon (Cinnamomum verum), and basil (Ocimum basilicum). These oils were tested against fungi isolated from banana peels (Musa paradisiaca). The fungi tested were identified through macroscopic and microscopic analyses and DNA sequencing, after being isolated in potato dextrose agar (PDA) medium modified with 0.05% chloramphenicol. Subsequently, the antifungal properties of the tested essential oils were evaluated in vitro at concentrations of 200, 400, 600, 800, and 1000 ppm prepared in a 0.05% Tween 80 solution. Cinnamon EOs showed the highest antifungal activity, significantly inhibiting the growth of pathogens at a concentration of 400 ppm. Other EOs showed moderate effects at higher concentrations: rosemary inhibited fungal growth at 600 ppm, oregano at 800 ppm, and clove at 1000 ppm. These findings highlight the potential of EOs as eco-friendly alternatives to synthetic fungicides, contributing to the development of sustainable agricultural practices and the post-harvest management of bananas. It is recommended to conduct future research to assess the economic viability and practical impacts of large-scale applications. Full article

Banana de-handing is a critical yet labor-intensive step in postharvest processing, with current manual methods resulting in high costs and occupational risks. This study addresses the automation of de-handing point localization by integrating high-resolution 3D scanning and morphometric analysis of banana crowns with machine learning techniques. A total of 210 crown samples were analyzed to extract key morphological features, including inner arc length (L_i), inner arc radius (R_i), outer arc radius (R_o), and the distance between inner and outer arcs (D_oi), among others. Four machine learning algorithms, namely, Multi-Layer Perceptron (MLP), Gradient Boosted Decision Trees (GBDT), Extreme Gradient Boosting (XGBoost), and Random Forest (RF), were developed to predict the target radius (R_t) and target distance (D_ti) of the de-handing point. The RF models achieved the optimal predictive performance on the testing set, with the following results: for R_t, R² = 0.95, MAE = 1.50, and RMSE = 1.94; for D_ti, R² = 0.91, MAE = 1.33, and RMSE = 1.66. A Shapley Additive Explanations (SHAP) analysis revealed that L_i, R_i, and R_o were the most influential features for R_t, while D_oi was the most important for D_ti. Notably, feature threshold effects were observed, with limited gains in prediction accuracy beyond specific morphological values. These results provide a quantitative foundation for vision-guided automated de-handing systems, advancing intelligent and efficient banana postharvest management. Full article

Strawberries are highly perishable fruits prone to postharvest losses due to defects, diseases, and uneven ripening. This study proposes a deep learning-based approach for automated quality assessment using the YOLOv8n object detection model. A custom dataset of 5663 annotated strawberry images was compiled, covering eight quality categories, including anthracnose, gray mold, powdery mildew, uneven ripening, and physical defects. Data augmentation techniques, such as rotation and Gaussian blur, were applied to enhance model generalization and robustness. The model was trained over 100 and 200 epochs, and its performance was evaluated using standard metrics: Precision, Recall, and mean Average Precision (mAP). The 200-epoch model achieved the best results, with a mAP50 of 0.79 and an inference time of 1 ms per image, demonstrating suitability for real-time applications. Classes with distinct visual features, such as anthracnose and gray mold, were accurately classified. In contrast, visually similar categories, such as ‘Good Quality’ and ‘Unripe’ strawberries, presented classification challenges. Full article

Agriculture is the foundational industry for human survival, profoundly impacting economic, ecological, and social dimensions. In the face of global challenges such as rapid population growth, resource scarcity, and climate change, achieving technological innovation in agriculture and advancing smart farming have become increasingly critical. In recent years, deep learning and computer vision have developed rapidly. Key areas in computer vision—such as deep learning-based image processing, object detection, and multimodal fusion—are rapidly transforming traditional agricultural practices. Processes in agriculture, including planting planning, growth management, harvesting, and post-harvest handling, are shifting from experience-driven methods to digital and intelligent approaches. This paper systematically reviews applications of deep learning and computer vision in agricultural growth management over the past decade, categorizing them into four key areas: crop identification, grading and classification, disease monitoring, and weed detection. Additionally, we introduce classic methods and models in computer vision and deep learning, discussing approaches that utilize different types of visual information. Finally, we summarize current challenges and limitations of existing methods, providing insights for future research and promoting technological innovation in agriculture. Full article

In forests dominated by deciduous tree species, coniferous species are often disproportionately important because of their contrasting functional traits. Eastern white pine (Pinus strobus L.), once a widespread emergent canopy species, co-occurs with deciduous hardwoods in the northern Lake States, but is often uncommon in contemporary hardwood stands. To gain insights into the potential utility of hardwood management strategies for simultaneously regenerating white pine, we leveraged a northern hardwood silvicultural experiment with scattered overstory pine. Seven growing seasons post-harvest, we conducted a complete census of white pine regeneration (height ≥ 30 cm) and mapped their locations and the locations of potential seed trees. Pine regeneration was sparse and strongly spatially aggregated, with most clusters falling within potential seed shadows of overstory pines. New recruits were found to have the highest density in a scarified portion of the study area leeward of potential seed trees. Low regeneration densities within treatment units, strong spatial aggregation, and the spatial arrangement of potential seed trees precluded generalizable inferences regarding the utility of specific treatment combinations. Nevertheless, our results underscore the critical importance of residual overstory pines as seed sources and highlight the challenges associated with realizing their potential in managed northern hardwoods. Full article

High concentrations of vicine and convicine (v-c) in faba beans can trigger favism in susceptible humans, posing a significant barrier to the broader adoption of faba beans as a food source. While plant breeding and various post-harvest processing methods have been adopted to reduce v-c levels, there is limited understanding of how agronomic practices may assist in reducing v-c levels. This study investigated the effect of sowing time (TOS), soil type, and genotype on v-c levels in faba beans. Twelve faba bean genotypes were evaluated across multiple field sites by applying two sowing times and two diverse soil types. The v-c content was quantified using established chromatographic techniques. Genotypes were identified as the most major factor affecting v-c levels, with significant variation observed in mean vicine and convicine contents. Sowing time also had a significant impact (p < 0.01), with lower v-c levels observed in TOS 1 compared to TOS 2. This reduction may be due to a longer plant development period and extended seed desiccation in TOS 1. Soil conditions, likely linked to nutritional factors, significantly influenced vicine concentrations (p < 0.05) but did not influence convicine levels (p > 0.05). These findings highlight the importance of agronomy practices, such as optimal sowing time, soil nutrition, and moisture management, in minimizing v-c levels; the most effective strategy remains the development of low v-c genotypes combined with farming practices that naturally suppress v-c accumulation. Full article

Culinary melon (Cucumis melo subsp. agrestis var. conomon) is widely cultivated throughout Thailand and represents an important agricultural crop. During 2023–2024, anthracnose, charcoal rot, and fruit rot caused by fungi were observed on postharvest culinary melon fruits in northern Thailand. This study aimed to isolate and identify fungal pathogens associated with these postharvest diseases in culinary melons, as well as to assess their pathogenicity. Eight fungal strains were isolated and identified through morphological characterization and multi-gene phylogenetic analysis. Colletotrichum chlorophyti and C. siamense were identified as the causal agents of anthracnose, Fusarium sulawesiense caused fruit rot, and Macrophomina phaseolina was responsible for charcoal rot. Pathogenicity tests were conducted, and the fungi were successfully re-isolated from the symptomatic lesions. Moreover, sensitivity tests for fungicides revealed that C. siamense was completely inhibited by copper oxychloride and copper hydroxide. Colletotrichum chlorophyti was inhibited by benalaxyl-M + mancozeb, copper hydroxide, and mancozeb. In the case of M. phaseolina, complete inhibition was observed with the use of benalaxyl-M + mancozeb, mancozeb, and propineb. Copper hydroxide successfully inhibited F. sulawesiense completely. To our knowledge, this study is the first to report C. siamense and C. chlorophyti as causes of anthracnose, F. sulawesiense as a cause of fruit rot, and M. phaseolina as a cause of charcoal rot in postharvest culinary melon fruits in Thailand. It also marks the first global report of C. siamense, M. phaseolina, and F. sulawesiense as causal agents of these respective diseases in culinary melon. Furthermore, the results of the fungicide sensitivity tests provide valuable information for developing effective management strategies to control these postharvest diseases in the future. Full article

Postharvest fungal diseases are a major cause of fruit spoilage and economic losses, particularly in perishable commodities like strawberries. In this study, a plant-derived Weissella paramesenteroides strain R2 was isolated from the mango fruit surface and evaluated for its antifungal potential. Dual-culture assays revealed the strong inhibitory activity of strain R2 against key postharvest pathogens, including Botrytis cinerea, Colletotrichum gloeosporioides, and Fusarium oxysporum. Notably, cell-free fermentation broth exhibited no antifungal activity, whereas the volatile organic compounds (VOCs) produced by R2 significantly suppressed fungal growth in sealed plate assays. GC-MS analysis identified 84 VOCs, with pyrazines as the dominant group. Three major compounds, 2,5-dimethylpyrazine, 2,4-di-tert-butylphenol, and 2-furanmethanol, were validated for their antifungal activity. The application of R2 VOCs in strawberry preservation significantly reduced disease incidence and severity during storage. These findings highlight W. paramesenteroides R2 as a promising, food-safe biocontrol agent for postharvest disease management via VOC-mediated mechanisms. Full article

Forest harvesting can alter sedimentary processes in catchments by reducing vegetation cover and exposing the soil surface. To mitigate these effects, post-harvest residue management is commonly used, though its effectiveness needs individual evaluation. This study assessed how windrowed harvest residues influence structural sediment connectivity in two forest catchments in south-central Chile with a Mediterranean climate. Using digital terrain models and the Index of Connectivity, scenarios with and without windrows were compared. Despite similar windrow characteristics, effectiveness varied between catchments. In catchment N01 (12.6 ha, average slope 0.28 m m⁻¹), with 13.6% windrow coverage, connectivity remained unchanged, but in contrast, catchment N02 (14 ha, average slope 0.27 m m⁻¹), with 21.9% coverage, showed a significant connectivity reduction. A key factor was windrows’ orientation: 83.9% aligned with contour lines in N02 versus 58.6% in N01. Distance to drainage channels also played a role, with the decreasing effect of connectivity at 50–60 m in N02. Bootstrap analysis confirmed significant differences between catchments. These results suggest that windrow configuration, particularly contour alignment, may be more critical than coverage percentage. For effective connectivity reduction, especially on moderate to steep slopes, forest managers should prioritize contour-aligned windrows. This study enhances our understanding of structural sediment connectivity and offers practical insights for sustainable post-harvest forest management. Full article

Essential oils (EOs) are widely recognized for their antifungal properties, but their efficacy against specific phytopathogenic fungi associated with banana (Musa paradisiaca) rot remains underexplored. This study aimed to evaluate the antifungal potential of EOs from Origanum vulgare, Salvia rosmarinus, Syzygium aromaticum, Thymus vulgaris, Cinnamomum verum, and Ocimum basilicum against five fungal species isolated from infected banana peels. Fungal isolates were obtained using PDA medium supplemented with chloramphenicol and were purified by weekly subculturing. Morphological and microscopic characterization was complemented by molecular identification based on ITS sequencing and phylogenetic reconstruction using Neighbor-Joining and UPGMA methods in MEGA v11. In vitro and ex vivo antifungal assays were performed at EO concentrations ranging from 200 to 1000 ppm. Thyme oil exhibited the strongest inhibitory effect, with complete growth suppression at 1000 ppm. Cinnamon and oregano also demonstrated effective inhibition at 600 ppm, while clove, rosemary, and basil were markedly less effective. Statistical analysis confirmed significant effects of EO type and concentration on fungal growth (p < 0.001). Molecular results showed strong phylogenetic support for isolate identification, with bootstrap values above 93% in most clades. These findings support the selective use of specific EOs as sustainable alternatives to synthetic fungicides in the postharvest management of banana diseases and provide a molecularly supported basis for their targeted application in integrated control strategies. Full article

Fruit and vegetable production is often impacted by microbial pathogens that compromise the quality of produce and lead to significant economic losses at the postharvest stages. Due to their efficacy, agrochemicals are widely applied in disease management; nevertheless, this practice has led to the appearance of microbial strains resistant to these types of agrochemicals. Additionally, there is growing concern among consumers about the presence of these chemical residues in fruits and the negative impacts they cause on multiple ecosystems. In response, there is a growing need for safe, effective, green, and sustainable disease control technologies. Bionanocomposites, with their unique ability to combine nanomaterials and biopolymers that have attractive properties, represents a promising alternative for postharvest disease control. These technologies allow for the development of functional coatings and films with antimicrobial, antioxidant, and barrier properties, which are critical for extending shelf life and preserving fruit quality. Recent advances have demonstrated that integrating nanoparticles, such as ZnO, TiO₂, Ag, and chitosan-based nanosystems, into biopolymeric matrices, like alginate, pectin, starch, or cellulose, can enhance mechanical strength, regulate gas exchange, and control the release of active agents. This review presents systematized information that is focused on the creation of coatings and films based on bionanocomposites for the management of disease in fruits and vegetables. It also discusses the use of diverse biopolymers and nanomaterials and their impact on the quality and shelf life of fruits and vegetables. Full article

Pesticide residues pose risks to the environment and human health. Little is known about how tillage and straw management affect herbicide behavior in soil. This study investigated the effects of different tillage practices under varying straw incorporation scenarios on the degradation of five commonly used herbicides in a long-term experimental field located in the maize belt of Siping, Jilin Province. Post-harvest soil samples were analyzed for residual herbicide concentrations and basic soil physicochemical properties. A human health risk assessment was conducted, and a controlled incubation experiment was carried out to evaluate herbicide degradation dynamics under three management systems: straw incorporation with traditional rotary tillage (ST), straw incorporation with strip tillage (SS), and no-till without straw (CK). Residual concentrations of atrazine ranged from not detected (ND) to 21.10 μg/kg (mean: 5.28 μg/kg), while acetochlor showed the highest variability (2.29–120.61 μg/kg, mean: 25.26 μg/kg). Alachlor levels were much lower (ND–5.71 μg/kg, mean: 0.34 μg/kg), and neither nicosulfuron nor mesotrione was detected. Soil organic matter (17.6–20.89 g/kg) positively correlated with available potassium and acetochlor residues. Health risk assessments indicated negligible non-cancer risks for both adults and children via ingestion, dermal contact, and inhalation. The results demonstrate that tillage methods significantly influence herbicide degradation kinetics, thereby affecting environmental persistence and ecological risks. Integrating straw with ST or SS enhanced the dissipation of atrazine and mesotrione, suggesting their potential as effective residue mitigation strategies. This study highlights the importance of tailoring tillage and straw management practices to pesticide type for optimizing herbicide fate and promoting sustainable agroecosystem management. Full article

Rhizopus stolonifer causes soft rot disease in strawberry and is considered one of the most destructive pathogens affecting strawberries worldwide. This study investigated the efficacy of three atmospheric non-thermal plasmas (NTPs) consisting of gliding arc (GA), Tesla coil (TC) and dielectric barrier discharge (DBD) for controlling R. stolonifer infection. Fungal mycelial discs were exposed to these plasmas for 10, 15 or 20 min, whereas conidial suspensions were treated for 1, 3, 5 or 7 min. Morphological alterations following non-thermal plasma exposure were studied using scanning electron microscopy (SEM). Exposure to GA and DBD plasmas for 20 min completely inhibited mycelial growth. SEM analysis revealed significant structural damage to the mycelium, sporangia and sporangiospores of treated samples compared to untreated controls. Complete inhibition of sporangiospore germination was achieved with treatments for at least 3 min for all NTPs. Pathogenicity assays on strawberry fruit showed that 15 min exposure to any of the tested NTPs completely prevented the development of soft rot disease. Importantly, NTP treatments did not adversely affect the external or internal characteristics of treated strawberries. These findings suggest that atmospheric non-thermal plasmas offer an effective approach for controlling R. stolonifer infection in strawberries, potentially providing a non-chemical alternative for post-harvest disease management. Full article

Fusarium spp. represent a critical threat to maize production and food safety due to their mycotoxin production. This study introduces a refined molecular identification protocol integrating four genomic regions—ITS1, IGS, TEF-1α, and β-TUB—for robust species differentiation of Fusarium spp. isolates from post-harvest maize in Bulgaria. The protocol enhances species resolution, especially for closely related taxa within the Fusarium fujikuroi species complex (FFSC). A newly optimized multiplex PCR strategy was developed using three primer sets, each designed to co-amplify a specific pair of toxigenic genes: fum6/fum8, tri5/tri6, and tri5/zea2. Although all five genes were analyzed, they were detected through separate two-target reactions, not in a single multiplex tube. Among 17 identified isolates, F. proliferatum (52.9%) dominated, followed by F. verticillioides, F. oxysporum, F. fujikuroi, and F. subglutinans. All isolates harbored at least one toxin biosynthesis gene, with 18% co-harboring genes for both fumonisins and zearalenone. This dual-protocol approach enhances diagnostic precision and supports targeted mycotoxin risk management strategies. Full article

Mating disruption is a commercially available management tactic for pyralid moths, which are pests of stored products. However, evaluations of efficacy have had limited replication, which limits the ability to draw conclusions about its effectiveness or the impact of different variables on its efficacy. We evaluated the mating disruption of Plodia interpunctella in 33 retail pet supply stores (6415 to 17,384 m³) and the impact of factors such as insect density and application rate on efficacy. Prior to starting MD, the average capture of P. interpunctella was 40.2 ± 3.6 moths/trap/month. Immediately after starting treatment, there was a sharp drop in captures (67.8 ± 4.8%) and then a more gradual overall downward. Overall, under mating disruption, the average reduction was 85.0 ± 3.0%. Geographic location, initial moth density, and pheromone application rate did not significantly impact efficacy. Analysis of the relationships between moth captures and mating disruption dispenser density indicated that competitive mechanisms were the primary mechanisms involved. This was the largest replicated assessment of MD for the management of a post-harvest pest and provides valuable foundational and applied insights into the process. Our results show that a standardized MD program can provide pest suppression in retail stores, but it takes time to be fully effective. Finally, identifying the primary mechanism for efficacy provides important information needed for further refinement of MD programs. Full article