Search Results (336)

Plantations of the valuable Chinese timber species, Chamaecyparis hodginsii, established by planting, primarily rely on seed orchards for propagation. Therefore, effective management of the genetic composition of these orchards is essential to ensure a sustainable supply of high-quality seeds. However, the mating system and pollen dispersal mechanisms in its high-generation seed orchards remain unclear, limiting precise genetic management. To address this, we analyzed 30 parental clones and 75 of their open-pollinated progeny from a second-generation seed orchard using 15 polymorphic EST-SSR markers. Compared to reported natural populations of C. hodginsii, both parental and progeny populations maintained high genetic diversity (mean uHe = 0.438 and 0.449, respectively), with a significant excess of heterozygotes (mean Fis = −0.084 and −0.066, respectively). Population genetic structure analysis indicated weak genetic differentiation among the parental genetic groups (mean Fst = 0.012), which was further reduced in the progeny population (mean Fst = 0.003) due to open pollination, reflecting a trend toward genetic homogenization. The mating system was characterized exclusively by outcrossing (tm = 1.000). However, paternity analysis revealed highly skewed paternal contributions, a low effective number of pollen donors (Nep = 8.13), and contributions of S5, S11, and S17 as dominant pollen parents, with 17.33% external pollen flow. These findings elucidate the mechanisms underlying sustained genetic diversity despite unequal paternal contributions and provide a theoretical basis for optimizing parental configuration and pollen management. Full article

To enhance the automation and intelligence of trenching fertilization operations, this research proposes a real-time trunk detection model (Trunk-Seek) designed for spindle-shaped orchards. The model employs a customized data augmentation strategy and integrates the YOLO deep learning framework to effectively address visual challenges such as lighting variation, occlusion, and motion blur. Multiple object tracking algorithms were evaluated, and ByteTrack was selected for its superior performance in dynamic trunk tracking. In addition, a Positioning and Triggering Algorithm (PTA) was developed to enable precise localization and triggering for target-oriented fertilization. The system was deployed on an edge device, a test bench was established, and both laboratory and field experiments were conducted to validate its performance. Experimental results demonstrated that the detection model achieved an mAP50 of 98.9% and maintained a stable 32.53 FPS on the edge device, fulfilling real-time detection requirements. Test bench analysis revealed that variations in trunk diameter and operation speed affected triggering accuracy, with an average dynamic localization error of ±1.78 cm. An empirical model (T) was developed to describe the time-delay behavior associated with positioning errors. Field verification in orchards confirmed that Trunk-Seek achieved a triggering accuracy of 91.08%, representing a 24.08% improvement over conventional training methods. Combining high accuracy with robust real-time performance, Trunk-Seek and the proposed PTA provide essential technical support for the development of a visual target-oriented fertilization system in modern orchards. Full article

Mango is the second most widely cultivated tropical fruit in the world. Its harvesting mainly relies on manual labor. During the harvest season, the hot weather leads to low working efficiency and high labor costs. Current research on automatic mango harvesting mainly focuses on locating the fruit stem harvesting point, followed by stem clamping and cutting. However, these methods are less effective when the stem is occluded. To address these issues, this study first acquires images of four mango varieties in a mixed cultivation orchard and builds a dataset. Mango detection and occlusion-state classification models are then established based on YOLOv11m and YOLOv8l-cls, respectively. The detection model achieves an AP_0.5–0.95 (average precision at IoU = 0.50:0.05:0.95) of 90.21%, and the accuracy of the classification model is 96.9%. Second, based on the mango growth characteristics, detected mango bounding boxes and binocular vision, we propose a spatial localization method for the mango grasping point. Building on this, a mango-grasping and stem-cutting end-effector is designed. Finally, a mango harvesting robot system is developed, and verification experiments are carried out. The experimental results show that the harvesting method and procedure are well-suited for situations where the fruit stem is occluded, as well as for fruits with no occlusion or partial occlusion. The mango grasping success rate reaches 96.74%, the stem cutting success rate is 91.30%, and the fruit injury rate is less than 5%. The average image processing time is 119.4 ms. The results prove the feasibility of the proposed methods. Full article

Oxyfertigation with hydrogen peroxide (H₂O₂) has been successfully applied in several crops and production systems, but its use in mature citrus orchards under no-tillage conditions and semi-arid Mediterranean environments remains scarcely studied. This study aimed to evaluate the physiological responses of adult citrus trees and the agronomic performance of a mature citrus orchard subjected to chemical oxyfertigation based on the application of H₂O₂ in irrigation water as an oxygen source for the root zone. The experiment was conducted over four consecutive seasons (2018–2021) on adult ‘Ortanique’ hybrid mandarin trees grown in an orchard located in Torre Pacheco (Murcia, Spain). Two treatments were established: a ‘Control’ (0 mg L⁻¹ of H₂O₂) and an ‘OXY’ treatment (50–100 mg L⁻¹ of H₂O₂ applied throughout the growing season). Oxyfertigation significantly increased the dissolved oxygen in irrigation water and soil oxygen diffusion rate, with treatment and treatment × time effects showing greater oxygenation under conditions favoring transient root-zone hypoxia. Soil CO₂ and H₂O vapor fluxes exhibited marked seasonal dynamics but no consistent treatment effect, and soil salinity and macro- and micronutrient contents were not significantly altered. At the plant level, oxyfertigation episodically enhanced leaf gas exchange and transiently improved the water status, but did not produce a sustained increase in leaf-level water use efficiency. In contrast, OXY trees showed greater pruning biomass, more fruits (+18%), higher cumulative yield (+13%), and significantly higher crop water use efficiency (YWUE) while the mean fruit weight and most quality attributes were governed by interannual climatic variability. In summary, oxyfertigation acted as a complementary and safe agronomic practice that improved rhizosphere oxygenation and supported modest gains in fruit load and YWUE in mature citrus orchards. Full article

The conservation and characterisation of traditional apple cultivars are essential for safeguarding agrobiodiversity and supporting regional economies. Reineta de Fontanelas, a long-established cultivar from the Saloia region of Sintra, Portugal, remains insufficiently described despite its cultural relevance. This study provides the first integrated characterisation of Reineta de Fontanelas apples collected from six local producers, evaluating biometric traits, physicochemical and nutritional composition, free sugars, organic acids, phenolic compounds, antioxidant capacity, colour, texture, and sensory attributes. The multi-site sampling design enabled the assessment of intra-cultivar qualitative variability across different local environments and traditional low-input practices, which constituted the primary objective. A commercial Reineta sample was included solely as a contextual retail benchmark, acknowledging that differences in origin, orchard management, and storage conditions do not allow for strict cultivar-level comparisons. Reineta de Fontanelas apples consistently exhibited high soluble solids (SS), lower titratable acidity (TA), and enriched levels of key phenolic compounds, together with stronger antioxidant activity. Sensory evaluation indicated a sweeter and more aromatic profile for the local apples. Multivariate analysis revealed a coherent compositional fingerprint and identified the main sources of intra-cultivar variability. Overall, the findings show that Reineta de Fontanelas maintains distinctive nutritional, bioactive, and sensory attributes across local environments, supporting ongoing efforts for its conservation and valorization. Full article

Sweet cherry (Prunus avium L.) cultivation in China covers an estimated area of 25,600 hectares, representing more than one-third of the global total. Viral diseases present a serious challenge to cherry production worldwide; however, the phytosanitary status of sweet cherry in China has remained poorly understood. In this study, 191 sweet cherry samples were collected from major growing regions and screened using RT-PCR combined with DNA sequencing for the presence of 14 viruses previously reported in China. Results revealed that 80.1% of the tested samples were infected with at least one virus, with mixed infections detected in 51.3% of the samples. Prevalent viruses included cherry virus A (CVA, 53.4%), prunus necrotic ringspot virus (PNRSV, 35.1%), cherry green ring mottle virus (CGRMV, 32.5%), plum bark necrosis stem pitting-associated virus (PBNSPaV, 31.4%), and prune dwarf virus (PDV, 10.5%). Cherry necrotic rusty mottle virus (CNRMV) was found at a very low frequency (0.5%), and the remaining eight viruses were not detected in any sample. Based on these findings, we developed multiplex RT-PCR assays for simultaneous detection of CVA, PNRSV, CGRMV, PBNSPaV, and PDV. Several dual and triplex RT-PCR systems were successfully established, including combinations such as PBNSPaV/PNRSV, CVA/PDV, CVA/CGRMV, PBNSPaV/PDV/CGRMV, and PBNSPaV/PNRSV/PDV. This study identifies CVA, PNRSV, CGRMV, PBNSPaV, and PDV as the prevalent viruses in the investigated Chinese sweet cherry orchards. Accordingly, multiplex RT-PCR assays were developed for their simultaneous detection. Our work advances the understanding of sweet cherry viral diseases in China and provides a valuable complementary tool for the existing diagnostic toolkit. Full article

Apple fruit quality is primarily determined by Vitamin C (VC), Soluble Saccharides (SSs), Titratable Acid (TA), and the Soluble Saccharides/Titratable Acid (SSs/TA). This study aims to establish a prediction model based on the Back Propagation (BP) neural network by analyzing the intrinsic relationships between these quality indicators and the photosynthetic physiological characteristics of fruit trees, providing a new method for the precise prediction and regulation of fruit quality. Using ‘Fuji’ apple as the material, fruit quality indicators, leaf photosynthetic parameters, canopy structure indicators, and carbon–water–nitrogen metabolism indicators were systematically measured. Correlation analysis was employed to identify key influencing factors, BP neural network models with different hidden layer structures were constructed, and the optimal feature subset was screened through feature importance analysis, single-factor sensitivity analysis, and ablation experiments, ultimately establishing a simplified and efficient prediction model. Pn, Gs, SPCI, and DUE showed significant positive correlations with VC, SS, and SS/TA, whereas N and NLT were significantly positively correlated with TA content. SUE was identified as a common core driving factor for VC, SS, and SS/TA. The BP neural network demonstrated strong predictive performance for the four quality indicators, with the optimal model achieving validation set R² values of 0.87, 0.86, 0.86, and 0.89, respectively. The simplified model developed through feature screening exhibited further improved performance: the validation set R² for the VC prediction model increased to 0.93, while MAE and MAPE decreased by 32% and 35%, respectively. Photosynthetic characteristics and nitrogen metabolism status of the fruit trees serve as key physiological foundations determining apple quality. The quality prediction model based on the BP neural network achieved high accuracy, and its predictive performance was significantly enhanced after feature refinement, providing an effective tool for precise apple quality prediction and smart orchard management. Full article

The use of convolutional neural networks in nursery production remains limited, emphasizing the need for advanced vision-based approaches to support automation. This study evaluated the feasibility of detecting chip-budding graft sites in apple nurseries using YOLO object detection and segmentation models. A dataset of 3630 RGB images of budding sites was collected under variable field conditions. The models achieved high detection precision and consistent segmentation performance, confirming strong convergence and structural maturity across YOLO generations. The YOLO12s model demonstrated the most balanced performance, combining high precision with superior localization accuracy, particularly under higher Intersection-over-Union threshold conditions. In the segmentation experiments, both architectures achieved nearly equivalent performance, with only minor variations observed across evaluation metrics. The YOLO11s-seg model showed slightly higher Precision and overall stability, whereas YOLOv8s-seg retained a small advantage in Recall. Inference efficiency was assessed on both high-performance (RTX 5080) and embedded (Jetson Orin NX) platforms. YOLOv8s achieved the highest inference efficiency with minimal Latency, while TensorRT optimization further improved throughput and reduced Latency across all YOLO models. These results demonstrate that framework-level optimization can provide substantial practical benefits. The findings confirm the suitability of YOLO-based methods for precise detection of grafting sites in apple nurseries and establish a foundation for developing autonomous systems supporting nursery and orchard automation. Full article

Accurate geospatial inventories of fruit orchards are essential for precision horticulture and food security, yet Pakistan lacks consistent spatial datasets at district and tehsil levels. This study presents the first national-scale, object-based Random Forest (RF) framework for orchard delineation and yield estimation by integrating multi-temporal Sentinel-2 imagery on Google Earth Engine (GEE) with high-resolution Pakistan Remote Sensing Satellite-1 (PRSS-1) data. Among the tested classifiers, RF achieved the highest performance on Sentinel-2 data (Overall Accuracy (OA) = 79.0%, kappa (κ) = 0.78), outperforming Support Vector Machines (OA = 74.5%, κ = 0.74) and Gradient Boosting Decision Trees (OA = 73.8%, κ = 0.73), with statistical significance confirmed (McNemar’s χ², p < 0.01). Integrating RF with Object-Based Image Analysis (OBIA) on PRSS-1 imagery further enhanced boundary precision (OA = 92.6%, κ = 0.89), increasing Producer’s and User’s accuracies to 90.4% and 91.5%, and increasing Intersection-over-Union (IoU) from 0.71 to 0.86 (p < 0.01). Regression-based yield modeling using field-observed data revealed that mean- and median vegetation index aggregations provided the most stable predictions (R² = 0.77–0.79; RMSE = 72–105 kg tree⁻¹), while extreme-value models showed higher errors (R² = 0.46–0.56; RMSE > 560 kg tree⁻¹). The resulting multisensory geospatial inventory of citrus and mango orchards establishes a scalable, transferable, and operationally viable framework for orchard mapping yield forecasting, and resource planning, demonstrating the strategic value of national satellite assets for food security monitoring in data-scarce regions. Full article

Water scarcity strongly limits the establishment and productivity of young orchards. Although cover crops are increasingly adopted to improve soil health, their integrated effects on soil–plant–water interactions under drought remain unclear. Here, a two-year field study evaluated Legume, Gramineae, and Legume-Gramineae mixture covers in relation to soil water dynamics, evapotranspiration (ET), and water use efficiency (WUE). Gramineae cover reduced 0–100 cm soil water storage by 5.99% compared with bare soil, whereas the Legume-Gramineae mixture effectively buffered drought-induced water loss. All cover treatments increased total ET, with the mixture showing the highest (10.31%), indicating that enhanced transpiration compensated for reduced soil evaporation. As a result, WUE improved, particularly during winter and spring when water demand was lower. Stepwise analysis identified rainfall as the primary climatic drivers of ET and WUE. Overall, the Legume-Gramineae mixture offers a promising strategy for improving WUE and mitigating drought stress in water-limited orchards. Full article

With the advancement of precision agriculture and agriculture 4.0, path tracking control technologies for autonomous agricultural vehicles (AAVs) have become essential for achieving efficient and automated operations. This paper begins by introducing the theoretical framework of AAV path tracking, including its applications across various working scenarios such as dry fields, paddy fields, and orchards, and establishes corresponding vehicle dynamics models suited to these environments. AAVs are classified into wheeled and tracked types based on structural characteristics and specific operational requirements. Subsequently, path tracking control methods are divided into linear and nonlinear approaches according to their system applicability, with detailed discussions on the implementation and adaptations of these strategies in real agricultural settings. Given its strong robustness and extensive adoption, sliding mode control receives particular emphasis in this review. Finally, the paper addresses persistent challenges in complex farmland environments and identifies future research directions aimed at enhancing practicality and adaptability. This review provides a comprehensive and structured analysis of AAV path tracking technologies, with a focus on environmental adaptability and operational feasibility, thereby offering valuable insights for further research and technological development in precision agriculture. Full article

The successful establishment of young chestnut orchards is increasingly challenged by drought stress and limited irrigation availability, especially in areas with limited water access. This study evaluated the effects of ridge planting and plastic foil mulching, individually and in combination, on the early growth and stress physiology of vegetatively propagated Castanea sativa × C. crenata ‘Marsol’ trees under rainfed conditions. Over a two-year field trial, vegetative traits, photosynthetic pigments, and leaf phenolic profiles were assessed to determine treatment effects. Ridge planting combined with foil mulching significantly improved tree growth, leading to a 2.6-fold increase in leaf number and 1.6-fold increase in height compared to control (flat planting without foil). This treatment also minimized stress indicators, such as chlorosis and elevated phenolic content. Notably, the ellagitannin chestanin emerged as a dominant stress-related metabolite in the first year, suggesting its potential as an early biochemical marker of transplantation stress. Over time, a compositional shift in phenolic groups, from hydroxycinnamic acids and flavanols to flavonols and hydroxybenzoic acids, was observed, reflecting the plant’s transition from acute stress response to developmental acclimation. These results support ridge planting with foil as a practical, climate-adaptive solution for chestnut orchard establishment and highlight chestanin as a candidate marker for stress monitoring in young trees. Full article

Biochar has gained attention as a promising soil amendment capable of improving soil structure, nutrient retention and plant resilience to stress. However, its performance in perennial horticultural systems, particularly during the early stages of orchard establishment, remains insufficiently documented. This study, conducted in 2021 in a newly established apple orchard (‘Gala Brookfield Baigent’/P 60) in Wieluń, Central Poland, aimed to evaluate the effectiveness of three methods of using cattle-manure-derived biochar at a dose of 10 t ha⁻¹ (application before ploughing prior to orchard establishment, application to planting holes and surface spreading). Neither tree growth nor fruiting potential were affected by biochar, which made the comparison of its application methods inconclusive. According to the principal component analysis performed, mineral nitrogen showed a tendency to promote the formation of mixed-type buds on short shoots, a propitious growing pattern for intensive orchard management. In contrast, compost fertilisation favoured vegetative growth over generative development, as reflected by the significantly negative coefficient in regression analysis (b = −0.12; 95% CI: −0.25 to –0.00 for the Box-Cox-scaled fruiting-to-growth potential ratio). Nonetheless, the overall growth response of apple trees in the first year after planting to the applied soil-enriching practices was rather modest, with this observation validating the strategy of reducing fertiliser doses during orchard establishment on productive soils maintained in good agricultural condition. Long-term studies under abiotic or nutrient-limiting constraints, as well as the combined use of biochar with microbial inoculants, are recommended to fully elucidate its potential in apple production. Full article

Mango (Mangifera indica L.) is a tropical fruit tree characterized by vigorous growth and high fruit production, making it one of Peru’s main export crops. However, its extensive vegetative development requires substantial space, limiting productivity per unit area. This study evaluated the effects of rootstock and interstock combinations on agronomic traits and fruit biometrics, highlighting the potential of interstocks to modulate tree vigor in mango orchards of Peru’s dry forest region. A total of 216 trees were established using ‘Chulucanas’ and ‘Chato’ as rootstocks and ‘Chulucanas,’ ‘Chato,’ ‘Irwin,’ and ‘Julie’ as interstocks, apically grafted with the ‘Kent’ cultivar, with a spacing of 6.0 m × 6.0 m. Tree performance was assessed after 10 years during the 2017–2019 growing seasons in Piura, Peru, under a randomized complete block design (2 × 4 factorial). The combination of the ‘Chulucanas’ rootstock with ‘Chulucanas’ and ‘Julie’ interstocks reduced tree height by 10.94% and 11.70%, respectively, facilitating orchard management and potentially increasing planting density. Yield varied significantly among growing seasons, with a 15% reduction in 2017 attributed to El Niño–Southern Oscillation (ENSO)-related increases in temperature and rainfall that affected flowering and fruit set. These results underscore the importance of cultivar selection and climate-adaptive strategies to sustain mango productivity in regions prone to climatic variability. Full article

Urban edible greening initiatives, such as urban orchards and community fruit gardens, can deliver ecological and social benefits, but their long-term success depends on community acceptance. This study examines the establishment phase of a newly planted orchard in a housing estate in a mid-sized Czech city and operationalizes esthetic fit over time, i.e., the extent to which early-phase design is perceived as orderly, suitable, and promising using targeted items on design legibility, species–site suitability, and perceived promise. Data were collected through standardized face-to-face interviews with 150 residents, using a stratified sampling strategy. The survey elicited anticipated burdens and benefits, current and future evaluations of the orchard, and attitudes toward its care. Attitudes were measured with an adapted Urban Green Attachment Scale (UGAS). Descriptive and inferential analyses, including logistic regression and non-parametric tests, were conducted. Findings reveal that residents credited the orchard with design legibility, beauty, and ecological promise, while pragmatic concerns focused on maintenance tasks (leaf litter, watering) and questions of fruit access. Window views of the orchard and general satisfaction with the residential environment significantly increased the odds of higher attachment, while gender differences suggested varied engagement pathways. Importantly, attachment was strongly associated with stewardship intentions; residents with higher UGAS scores were more likely to defend the orchard, taste the fruit, participate in maintenance, and even support its preservation through higher property taxes. The results underscore that attachment is measurable before full ecological performance emerges, arising from a combination of design legibility and daily visibility. Practically, visible routines of care can pace expectations and sustain legitimacy. Conceptually, the study demonstrates that early-phase esthetic fit spans installation with stewardship, providing a foundation for long-term resilience and co-stewardship of edible urban greening. Full article