Search Results (526)

Indoor horticulture requires a substantial quantity of electricity to meet crops extended photoperiodic requirements for optimal photosynthetic rate. Simultaneously, global electricity costs have grown dramatically in recent years, endangering the sustainability and profitability of indoor vertical farms and/or modern greenhouses that use artificial lighting systems to accelerate crop development and growth. This study investigates the growth rate and physiological development of cherry tomato plants cultivated in a pilot indoor vertical farm at the Agricultural University of Athens’ Laboratory of Farm Structures (AUA) under continuous and disruptive lighting. The leaf physiological traits from multiple photoperiodic stress treatments were analyzed and utilized to estimate the plant’s tolerance rate under varied illumination conditions. Four different photoperiodic treatments were examined and compared, firstly plants grew under 14 h of continuous light (C-14L10D/control), secondly plants grew under a normalized photoperiod of 14 h with intermittent light intervals of 10 min of light followed by 50 min of dark (NI-14L10D/stress), the third treatment where plants grew under 14 h of a load-shifted energy demand response intermittent lighting schedule (LSI-14L10D/stress) and finally plants grew under 13 h photoperiod following of a load-shifted energy demand response intermittent lighting schedule (LSI-13L11D/stress). Plants were subjected also under two different light spectra for all the treatments, specifically WHITE and Blue/Red/Far-red light composition. The aim was to develop flexible, energy-efficient lighting protocols that maintain crop productivity while reducing electricity consumption in indoor settings. Results indicated that short periods of disruptive light did not negatively impact physiological responses, and plants exhibited tolerance to abiotic stress induced by intermittent lighting. Post-harvest data indicated that intermittent lighting regimes maintained or enhanced growth compared to continuous lighting, with spectral composition further influencing productivity. Plants under LSI-14L10D and B/R/FR spectra produced up to 93 g fresh fruit per plant and 30.4 g dry mass, while consuming up to 16 kWh less energy than continuous lighting—highlighting the potential of flexible lighting strategies for improved energy-use efficiency. Full article

Increased consumer awareness on food safety has spurred the development of detection techniques for pesticide residues. In this study, a rapid detection card on the basis of enzyme action was developed for the visual detection of pesticides, in which the thermally crosslinked and surface-decorated polyvinyl alcohol/citric acid nanofiber mat (PCNM) was employed as a novel immobilization matrix for acetylcholinesterase (AChE). The PCNM, crosslinked at 130 °C for 50 min, exhibited appropriate microstructure and water stability, making it suitable for AChE immobilization. The activation of carboxyl groups by surface decoration resulted in a 2.5-fold increase in enzyme loading capacity. Through parameter optimization, the detection limits for phoxim and methomyl were determined to be 0.007 mg/L and 0.10 mg/L, respectively. The detection card exhibited superior sensitivity and a reduced detection time (11 min) when compared to a commercially available pesticide detection card. Furthermore, the detection results of pesticide residues in fruit and vegetable samples confirmed its feasibility and superiority over commercial alternatives, suggesting its great potential for practical application in the on-site detection of pesticide residues. Full article

Neuroinflammation, driven by activated microglia, contributes to the progression of neurodegenerative diseases. Extracellular vesicles mediate intercellular communication and influence immune responses. Chrysin, a natural flavone found in fruits and propolis, has demonstrated anti-inflammatory effects. This study explored the immunomodulatory potential of chrysin-loaded EVs (EVs-Chry) derived from BV2 microglial cells. BV2 cells were treated with chrysin for 24 h to assess cytotoxicity and proliferation. EVs were isolated from treated and untreated cells, characterized by nanoparticle tracking analysis, and applied to naïve BV2 cells prior to LPS stimulation. Effects on cell morphology, migration, cytokine expression (IL-1β, IL-6), inflammasome activity (caspase-1), and apoptosis-related protein Bcl-xL were investigated. Our results show that EVs-Chry significantly reduced LPS-induced cell proliferation, restored resting microglial morphology, and reduced migratory capacity. Furthermore, co-treatment with EVs-Chry and LPS reduced pro-inflammatory cytokines such as IL-1β, IL-6, and caspase-1 expression while enhancing anti-apoptotic Bcl-xL levels, indicating a shift toward an anti-inflammatory, neuroprotective micro-glial phenotype. Together, our results demonstrated that EVs-Chry have neuroprotective effects on LPS-induced microglial activation and modulate microglial responses to inflammatory stimuli, attenuating pro-inflammatory signaling and promoting cellular homeostasis. These findings support the therapeutic potential of EVs-Chry in the context of neuroinflammatory and neurodegenerative disorders. Full article

Apple harvesting faces increasing challenges owing to rising labor costs and the limited seasonal workforce availability, highlighting the need for robotic harvesting solutions in precision agriculture. This study presents a 6-DOF robotic arm system designed for harvesting in dwarf hedge-planted orchards, featuring a lightweight perception module, a task-adaptive motion planner, and an adaptive soft gripper. A lightweight approach was introduced by integrating the Faster module within the C2f module of the You Only Look Once (YOLO) v8n architecture to optimize the real-time apple detection efficiency. For motion planning, a Dynamic Temperature Simplified Transition Adaptive Cost Bidirectional Transition-Based Rapidly Exploring Random Tree (DSA-BiTRRT) algorithm was developed, demonstrating significant improvements in the path planning performance. The adaptive soft gripper was evaluated for its detachment and load-bearing capacities. Field experiments revealed that the direct-pull method at 150 mN·m torque outperformed the rotation-pull method at both 100 mN·m and 150 mN·m. A custom control system integrating all components was validated in partially controlled orchards, where obstacle clearance and thinning were conducted to ensure operation safety. Tests conducted on 80 apples showed a 52.5% detachment success rate and a 47.5% overall harvesting success rate, with average detachment and full-cycle times of 7.7 s and 15.3 s per apple, respectively. These results highlight the system’s potential for advancing robotic fruit harvesting and contribute to the ongoing development of autonomous agricultural technologies. Full article

Background: Diabetes and cancer are two of the most life-threatening disorders affecting individuals of all ages worldwide. This study aimed to develop a novel Acrocomia aculeata (bocaiuva) fruit pulp oil-loaded nanoemulsion and evaluate its inhibitory effects on α-glucosidase and pancreatic lipase, as well as its antiglycant activity and cytotoxicity against cancer cells. Additionally, this study assessed the impact of both the oil and the nanoemulsion on blood cells. Methods: The pulp oil was extracted by cold pressing. The oil’s physicochemical properties were determined according to the AOAC and the Brazilian Pharmacopeia. The lipid profile was performed by GC-MS. The nanoemulsion was prepared by the phase inversion method using ultrasonic stirring for particle size reduction and for homogenization. Response Surface Methodology was used for optimizing nanoemulsion preparation. Enzyme inhibition tests were conducted using assay kits. Cytotoxicity in cancer cells was evaluated using the Sulforhodamine B assay. Results: Comprehensive physicochemical and chemical characterization of bocaiuva oil was performed, identifying oleic acid (71.25%) as the main component. The oil contains 23.04% saturated fatty acids, 73.79% monounsaturated acids, and 3.0% polyunsaturated fatty acids. The nanoemulsion (particle size 173.6 nm; zeta potential −14.10 mV) inhibited α-glucosidase (IC₅₀: 43.21 µg/mL) and pancreatic lipase (IC₅₀: 41.99 µg/mL), and revealed a potent antiglycation effect (oxidative IC₅0: 18.36 µg/mL; non-oxidative pathway IC₅₀: 16.33 µg/mL). The nanoemulsion demonstrated good cytotoxicity and selectivity against prostate cancer cells (IC₅₀: 19.13 µg/mL) and breast cancer cells (IC₅₀: 27.22 µg/mL), without inducing hemolysis, platelet aggregation, or anticoagulant effects. Conclusions: In this study, a comprehensive physical and chemical characterization of bocaiuva fruit pulp oil was conducted for the first time as a preliminary step toward its future standardization as an active ingredient in cosmetic and pharmaceutical formulations. The resulting nanoemulsion represents a novel alternative for managing diabetes and cancer. Although the nanoemulsion exhibited lower cytotoxicity compared to doxorubicin, it remains promising due to its composition of essential fatty acids, phenols, and carotenoids, which offer multiple health benefits. Further studies are needed to validate its efficacy and safety in clinical applications. Full article

Reliable early-stage yield forecasts are essential in precision viticulture, enabling timely interventions such as harvest planning, canopy management, and crop load regulation. Since grape yield is directly related to the number and size of bunches, the early detection of inflorescences and bunches, carried out even before flowering, provides a valuable foundation for estimating potential yield far in advance of veraison. Traditional yield prediction methods are labor-intensive, subjective, and often restricted to advanced phenological stages. This study presents a deep learning-based approach for detecting grapevine inflorescences and bunches during early development, assessing how phenological stage and illumination conditions influence detection performance using the YOLOv11 architecture under commercial field conditions. A total of 436 RGB images were collected across two phenological stages (pre-bloom and fruit-set), two lighting conditions (daylight and artificial night-time illumination), and six grapevine cultivars. All images were manually annotated following a consistent protocol, and models were trained using data augmentation to improve generalization. Five models were developed: four specific to each condition and one combining all scenarios. The results show that the fruit-set stage under daylight provided the best performance (F1 = 0.77, R² = 0.97), while for inflorescences, night-time imaging yielded the most accurate results (F1 = 0.71, R² = 0.76), confirming the benefits of artificial lighting in early stages. These findings define optimal scenarios for early-stage organ detection and support the integration of automated detection models into vineyard management systems. Future work will address scalability and robustness under diverse conditions. Full article

This article addresses the impact of deficit irrigation on the agronomic and physiological performance of “Rojo Brillante” persimmon trees in a Mediterranean climate. It compares the effect of a sustained deficit irrigation (SDI; imposing water deficit uniformly throughout the entire crop cycle) strategy and two regulated deficit irrigation (RDI; enforcing a water deficit during the phenological phases that are less sensitive to water stress) strategies. Field trials were conducted from 2022 to 2024 at the Cajamar Experimental Center in Paiporta, Valencia, Spain. The trees respond to mild water stress reducing transpiration through stomatal closure. RDI resulted in modest irrigation water savings (11–16%), minimizing fruit drop, leading to an increased number of fruits per tree and a higher marketable yield, although this came at the cost of a reduced unit fruit weight. SDI achieved a 30% reduction in irrigation water usage without impacting on the marketable yield, but it also caused a decrease in unit fruit weight. RDI increased water productivity (yield obtained per amount of water applied) primarily through higher yields, while SDI improved productivity mainly by lowering the amount of irrigation water applied. Both irrigation strategies are recommended for cultivating “Rojo Brillante” persimmons. RDI is especially advisable in years with lower fruit loads as more intensive thinning may be necessary in years with higher fruit loads. Conversely, SDI is recommended in situations where water availability is limited. Full article

Accurate estimation of fruit quantity is essential for efficient harvest management, storage, transportation, and marketing in the agricultural industry. To address the limited generalizability of single-species models, this study presents a comprehensive deep learning-based framework for multi-species fruit-load estimation, leveraging the MetaFruit dataset, which contains images of five fruit species collected under diverse orchard conditions. Four representative object detection and regression models—YOLOv8, RT-DETR, Faster R-CNN, and a U-Net-based heatmap regression model—were trained and compared as part of the proposed multi-species learning strategy. The models were evaluated on both the internal MetaFruit dataset and two external datasets, NIHS-JBNU and Peach, to assess their generalization performance. Among them, YOLOv8 and the RGBH heatmap regression model achieved F1-scores of 0.7124 and 0.7015, respectively, on the NIHS-JBNU dataset. These results indicate that a deep learning-based multi-species training strategy can significantly enhance the generalizability of fruit-load estimation across diverse field conditions. Full article

This study used Xinxin 2 (Juglans regia L. ‘Xinxin2’), a major cultivated walnut variety in Xinjiang, China, to clarify the response and adaptation mechanisms of the anatomical structures of walnut related to source–sink–flow under altered source–sink relationships. We anatomically observed the leaves, fruit stalks, and fruit of bearing branches by artificially adjusting the leaf-to-fruit ratio (LFR). The LFR substantially affected the leaf structure and thickness of the fruit-bearing branches obtained via girdled (p < 0.05). The results of the analysis of the leaf anatomy revealed that a low LFR impeded leaf growth and internal structural development while accelerating senescence, whereas a high LFR promoted leaf growth and delayed senescence. The same trend was observed for the phloem area (PA) of the fruit stalk with the increase in fruit load when the number of leaves on the fruit branch was the same. The maximum PA was reached when the number of fruits was high (except for 4L:3F). This indicates that the micro-anatomical structure of the fruit stalk is more developed under the treatment of a higher number of pinnate compound leaves and fruit level of LFRs. The cells of the 1L:3F and 2L:3F were considerably smaller in the green peel and kernel of the fruit on the branches obtained via girdled than those of 5L:1F plants (p < 0.05). No significant difference was found in the number of cells per unit area or the cross-sectional area of cells in the pericarp and kernel of the fruit under LFRs (p > 0.05); however, a large difference was noted in the microanatomical structure of the pericarp and kernel of fruit. Changes in the structural adaptation characteristics of walnut leaves (source), fruit stalk (flow), and fruit (sink) are related to source–sink regulation. A change in the LFR affects the carbohydrate synthesis in the leaves (source), transport in fruit stalks (flow), and the carbohydrate reception in fruits (sink). Full article

Plums are one of the most important stone fruits worldwide. Surprisingly, the effect of UV-C light on improving their bioactive compounds and its effect during storage has not been explored. This research aimed to assess the effect of UV-C light on the bioactive compounds and antioxidant capacity of plums, as well as to evaluate the storage conditions on the quality attributes of these fruits. Plums were UV-C light-irradiated (0, 0.175, and 0.356 kJ/m²) to analyze their effect on phenolic compounds, total anthocyanins, and antioxidant capacity. A selected dose of UV-C light treatment was applied to plums as a pretreatment to assess the effect of packaging (non-packed, packed in closed polyethylene boxes, and packed in closed polyethylene boxes with perforations) and temperature (5, 15, and 20 °C) on the quality characteristics of plums using a 3² experimental design. The results showed that phenolic compounds (3–10%), total anthocyanins (22–39%), and antioxidant capacity (8–15%) increased with the UV-C light treatment (0.356 kJ/m²). In storage, firmness remained constant, and color parameters (a* and b*) were reduced in all conditions, whereas weight loss was lower in plums stored in closed packages. Moreover, total anthocyanins and antioxidant capacity were enhanced under all storage conditions. The microbial load decreased due to the UV-C light treatment and remained constant during storage time (<100 CFU/g). Storing the plums at a low temperature in a closed package effectively preserved the quality attributes of plums for 40 days without affecting the sensory acceptance. Full article

Vegetables are commodities frequently sold in local markets and have been associated with foodborne outbreaks in short and local supply outlets worldwide. These outbreaks could potentially be mitigated through the implementation of good handling practices (GHPs) at points of sale. Numerous studies have assessed microbiological contamination in small-scale vegetable outlets in developing countries. In contrast, research on these risks in developed countries is comparatively scarce. However, with the increasing demand for vegetables, along with the increasing popularity of local markets, there is potential for an increase in foodborne outbreaks in developed countries. This study aimed to perform a microbiological assessment in local and short supply chain outlets of farmers in Portugal, as a case study, and to observe behaviors regarding GHPs in these outlets. The study was performed before and after the implementation of improved GHPs. This research employed quantitative analysis to measure the microbial load on vegetables, bench surfaces, and vendors’ hands. Additionally, a qualitative analysis was conducted to understand farmers’ behavior regarding GHPs using observational methods. Microbial hazards were detected in vegetables, on surfaces, and on hands both before and after the implementation of these practices, although the implementation of GHPs reduced the number of contaminations potentially associated with the practices used at the outlets. The results of this study highlight the importance of implementing GHPs in local and short supply chain markets for vegetables and fruits in developed countries, not only to protect consumers’ health, but also the farmers’ businesses. Full article

Background/Objectives: Gestational diabetes mellitus (GDM) is a major pregnancy complication with rising global prevalence. The Mediterranean Diet (MD) has shown metabolic benefits, but total adherence scores may obscure meaningful variation in dietary quality. This study aimed to investigate whether specific dietary patterns, identified within the MD framework, and their glycemic load (GL) are associated with GDM risk. Methods: This prospective cohort is part of the BORN2020 longitudinal study on pregnant women in Greece; dietary intake was assessed using a validated food frequency questionnaire (FFQ) at two time points (pre-pregnancy and during pregnancy). MD adherence was categorized by Trichopoulou score tertiles. GL was calculated for food groups using glycemic index (GI) reference values and carbohydrate content. Dietary patterns were identified using factor analysis. Logistic regression models estimated adjusted odds ratios (aORs) for GDM risk, stratified by MD adherence and time period, controlling for maternal, lifestyle, and clinical confounders. Results: In total, 797 pregnant women were included. Total MD adherence was not significantly associated with GDM risk. However, both food-specific GLs and dietary patterns with distinct dominant foods were predictive. GL from boiled greens/salads was consistently protective (aOR range: 0.09–0.19, p < 0.05). Patterns high in tea, coffee, and herbal infusions before pregnancy were linked to increased GDM risk (aOR = 1.96, 95% CI: 1.31–3.02, p = 0.001), as were patterns rich in fresh juice, vegetables, fruits, legumes, and olive oil during pregnancy (aOR = 2.91, 95% CI: 1.50–6.24, p = 0.003). A pattern dominated by sugary sweets, cold cuts, animal fats, and refined products was inversely associated with GDM (aOR = 0.34, 95% CI: 0.17–0.64, p = 0.001). A pattern characterized by sugar alternatives was associated with higher risk for GDM (aOR = 4.94, 95% CI: 1.48–19.36, p = 0.014). These associations were supported by high statistical power (power = 1). Conclusions: Within the context of the MD, evaluating both the glycemic impact of specific food groups and identifying risk-associated dietary patterns provides greater insight into GDM risk than overall MD adherence scores alone. Full article

The successful introduction of new cultivars depends on the evaluation of complex parameters essential for the consumers, market, and fruit producers. A new scab-resistant apple cultivar, ‘Wuranda’ (SQ159/Natyra^®/Magic Star^® × Honeycrisp), recently introduced in Norway and managed under the name Fryd^©, is prone to biennial bearing. Therefore, one of the first tasks, investigated in Southwestern Norway by the Norwegian Institute of Bioeconomy Research, NIBIO-Ullensvang in 2021–2024, was the establishment of optimal crop load level based on the combination of productivity, fruit quality, and return bloom. The apple cultivar Fryd (‘Wuranda’) was propagated on ‘M.9’ rootstock and planted in 2019. The trial was performed in the same orchard for four consecutive years, starting three years after planting. Crop load level affected average fruit mass but had no impact on cv. Fryd fruit quality parameters at harvest such as blush, ground color, firmness, soluble solid content, or starch degradation. Fruit size variation was diminished by crop load regulation, and most fruits fell into 2–3 grading classes. Crop load, not the yield per tree, was the determining factor for the return bloom. The optimal crop load level depended on the orchard age. To guarantee a regular bearing mode of cv. Fryd planted on M.9 rootstock at a 3.5 × 1 m distance and trained as slender spindle, crop load of 5.5–6 fruits cm⁻² TCSA (trunk cross-sectional area) in the 3rd year, 7.5–8 fruits cm⁻² TCSA in the 4th year, and 6.5–7 fruits cm⁻² TCSA in the 5th year should be maintained. Full article

Smart packaging not only has a preservation effect on food, but can also monitor the change of food quality in real time to ensure food safety. In this study, hollow mesoporous silica loaded with cinnamaldehyde was used as the antimicrobial agent, anthocyanin as the color developer, and nanocellulose as the film matrix, to obtain smart packaging with excellent antimicrobial activity and pH-responsive color development (CBF). Modified silica has a good regulatory characteristic on the release of cinnamaldehyde, and the cumulative release rate of cinnamaldehyde in the NH₂-HMSN@CA preservative reaches 72% after 7 days. Additionally, the film has good antibacterial properties, with inhibition rates of 82% and 92% against E. coli and S. aureus, respectively. In addition, the film has good mechanical properties and water vapor permeability. In terms of pH response, the film shows excellent color rendering and good stability. Therefore, the CBF films can be applied to preservation and real-time monitoring of fruits and vegetables, meat, and other food products, which has great potential for intelligent food packaging. Full article

Accurate identification of tomato ripeness and precise detection of picking points is the key to realizing automated picking. Aiming at the problems faced in practical applications, such as low accuracy of tomato ripeness and picking points detection in complex greenhouse environments, which leads to wrong picking, missed picking, and fruit damage by robots, this study proposes the YOLO-TMPPD (Tomato Maturity and Picking Point Detection) model. YOLO-TMPPD is structurally improved and algorithmically optimized based on the YOLOv8 baseline architecture. Firstly, the Depthwise Convolution (DWConv) module is utilized to substitute the C2f module within the backbone network. This substitution not only cuts down the model’s computational load but also simultaneously enhances the detection precision. Secondly, the Content-Aware ReAssembly of FEatures (CARAFE) operator is utilized to enhance the up-sampling operation, enabling precise content-aware processing of tomatoes and picking keypoints to improve accuracy and recall. Finally, the Convolutional Attention Mechanism (CBAM) module is incorporated to enhance the model’s ability to detect tomato-picking key regions in a large field of view in both channel and spatial dimensions. Ablation experiments were conducted to validate the effectiveness of each proposed module (DWConv, CARAFE, CBAM), and the architecture was compared with YOLOv3, v5, v6, v8, v9, and v10. The experimental results reveal that, when juxtaposed with the original network model, the YOLO-TMPPD model brings about remarkable improvements. Specifically, it improves the object detection F1 score by 4.48% and enhances the keypoint detection accuracy by 4.43%. Furthermore, the model’s size is reduced by 8.6%. This study holds substantial theoretical and practical value. In the complex environment of a greenhouse, it contributes significantly to computer-vision-enabled detection of tomato ripening. It can also help robots accurately locate picking points and estimate posture, which is crucial for efficient and precise tomato-picking operations without damage. Full article