Search Results (50)

The N fertilization to reach high cranberry (Vaccinium macrocarpon) yields resulted in high proportions of soft berries. Our objective was to define the mineral nutrient balance of cranberry to reach a high yield of firm berries. The database comprised 393 observations on cv. ‘Stevens’. Berries were analyzed for total S, N, P, K, Ca, Mg, B, Cu, Zn, Mn, Fe, Al, and Si. Random Forest and XGBoost machine learning models were run to predict yield and firmness classes using raw concentrations, centered log ratios (clr) accounting for nutrient interactions, and weighted log ratios (wlr) that also considered the importance of each dual interaction. The wlr returned the most accurate models. The wlr standards elaborated from the high-yielding and nutritionally balanced subpopulation most often differed between the high-yield class and the high-firmness class. The wlr Cu level was significantly (p ≤ 0.01) too high to reach the high-yielding class in the nutritionally imbalanced subpopulation. There was excessive Al and shortage of Si and Mg to reach high berry firmness in the nutritionally imbalanced subpopulation (p ≤ 0.01), indicating the large influence of soil genesis on berry firmness. Despite statistical evidence, cranberry response to Al and Si corrective measures should be tested to elaborate site-specific recommendations based on soil and tissue tests. Full article

Macleania rupestris, a fruit-bearing species of the Ericaceae family, has traditionally been used for its potential medicinal properties. Background/Objectives: This study investigates the phytochemical composition and antimicrobial activity of M. rupestris fruit extract, focusing on its antibacterial, antibiofilm, and antifungal effects. Methods: M. rupestris (Kunth) A.C.Sm. berries (code: 4456, Herbario QUPS-Ecuador) were collected from the cloud forest Montano Alto, Cuenca-Ecuador, and the extract was obtained using an ethanolic-based extraction and chemically characterized. The antibacterial and antifungal activity of the fruit extract was assessed against seven multidrug-resistant bacteria strains and four fungal strains using the microdilution method. The biofilm inhibition potential was evaluated using a microplate assay with the crystal violet staining method. The antioxidant activity was evaluated using DPPH and ABTS assays. Results: The bioactive compounds showed 853.9 mg phenols/100 g DW, 573.2 mg organic acid/100 g DW, and 21.5 mg C-3-gl/100 g DW of anthocyanins. The antibacterial assays demonstrated significant inhibitory activity against Enterococcus faecalis, Enterococcus faecium, Escherichia coli, and Staphylococcus epidermidis, with MIC values ranging from 1.25 to 5 mg/mL. Additionally, the biofilm inhibition assays confirmed the potential of M. rupestris extract to disrupt bacterial biofilms, particularly in S. aureus and L. monocytogenes. Nevertheless, no significant antifungal activity was observed against Candida spp., suggesting selective antimicrobial properties. Finally, the antioxidant activity was strong (1.62 mmol TE/100 g DW by DPPH and 3.28 mmol TE/100 g DW by ABTS). Conclusions: These findings indicate that M. rupestris possesses promising antibacterial, antibiofilm, and antioxidant properties, which may be attributed to its phenolic and organic acid composition. Further fractionation and targeted bioassays are required to elucidate the specific bioactive compounds responsible for these effects and explore their potential applications in antimicrobial formulations. Full article

The fruit of berry plants is primarily used for industrial purposes, while the leaves are often regarded as waste. However, these leaves, rich in valuable bioactive compounds, have the potential to serve as raw materials for various industries, including cosmetics. This study compared the content of micro- and macronutrients in the leaves of wild strawberry, blackberry, and blueberry plants. It revealed a high mineral content, particularly in the leaves of wild strawberry and blackberry plants. The plant leaves were also shown to contain vitamin C and exhibited antioxidant activity. The leaves of berry plants were used to obtain micellar extracts, which were then incorporated into the formulation of prototype bath washes. A cosmetic formulation without any extracts served as a reference. In the next step, the prototype cosmetics were evaluated for their chosen properties. The findings showed that incorporating micellar leaf extracts into cosmetic formulations reduced their viscosity and ability to generate long-lasting foam, even in the presence of model sebum. Furthermore, the cosmetics formulated with the extracts exhibited a reduced capacity to emulsify fatty soils compared to the reference formulation, which could present an advantageous option for individuals with sensitive skin. Full article

Urban afforestation is increasingly regarded as a key strategy for fostering biodiversity to restore and enhance the ecosystem services needed to counteract the effects of climate change in built-up areas. In Italy, several experimental afforestation projects have been launched as part of the National Recovery and Resilience Plan (NRRP), focusing on cities or metropolitan areas such as Milan, Rome, Pistoia and Campobasso. These projects follow a multidisciplinary approach, integrating botanists, foresters, urban planners, landscape architects and remote sensing specialists. The goal is to address the challenging complexity of urban forest restoration through reforestation and afforestation actions. Key innovations include the integration of transdisciplinary methodologies (landscape analysis, landscape design, forest and plant ecology) with the application of advanced remote sensing technologies and participatory community engagement frameworks to address ecological and social challenges. Experimental plots have been set up across various urban areas, testing a range of planting schemes to maximise climate change resilience and ensure long-term ecological sustainability. Emphasis has been placed on selecting drought-tolerant and thermophilic species that are better adapted to widespread warming and local urban heat islands. ‘Biodiversity strips’ with perennial flowers for insects, shrubs with berries for birds and nests for wild bees and vertebrates have been set up to enhance biodiversity in new afforestation areas. Advanced monitoring tools, such as Light Detection and Ranging (LiDAR) and multi-sensor drones, have been employed alongside field observations to assess forest growth, species survival, structural complexity and biodiversity enhancement over time. Historical analyses of landscape patterns and ecological connectivity over the past 200 years, along with evaluations of afforestation projects from the last 70 years, have provided critical insights into the successes and challenges of previous interventions, serving as a guide for future efforts. By focusing on ecological connectivity, the integration of afforested areas into the urban matrix, and citizen engagement, the current project aims to align urban forestry efforts with sustainable development goals. This comprehensive project framework addresses environmental restoration and the social and aesthetic impacts on local communities, contributing to the overall resilience and well-being of urban and peri-urban ecosystems. Full article

Repeated expeditions across various regions of Georgia in the early 2000s led to the identification of 434 wild grapevine individuals (Vitis vinifera L. subsp. sylvestris (C.C. Gmel.) Hegi) across 127 different sites, with 45% of these sites containing only a single vine and only 7% more than 9 vines. A total of 70 accessions were propagated in a germplasm collection, 41 of them were descripted from the ampelographic point of view and 32 from the phenological one. The geographical and ecological analysis confirmed that wild grapevines primarily grow in humid environments with warm and fully humid climates, often near rivers. They favor deep, fertile, and evolved soils, mainly alluvial and cinnamonic types (80%), with a marginal presence on strongly eroded soils. Their main natural vegetations are forests and open woodlands, with some individuals in the Southeast found in steppes. The altitudinal range spans from 0 to 1200 m, with 80% of vines distributed between 400 and 900 m. The phenological analysis revealed significant differences among the accessions but no difference among populations, with only a slight variation in bud-break timing, indicating a high level of synchronicity overall. Flowering timing proved to be the most uniform stage, suggesting minimal environmental pressure on genetic adaptation. The mature leaf morphology exhibited significant polymorphism, though leaves were generally three- or five-lobed, weak-wrinkling, and -blistering, with a low density of hairs. Bunch and berry morphology were more uniform. Bunches were consistently very small, cylindrical, and never dense or winged. Berries were also very small, mostly globular, always blue-black in color, and non-aromatic. A striking feature was the frequency of red flesh coloration, which ranged from weak to strong, with uncolored flesh being rare. The Georgian population of wild grapevines was found to be fragmented, often consisting of scattered single individuals or small groups. Therefore, we believe it is urgent for Georgia to implement specific protection measures to preserve this vital genetic resource. Full article

Assessing vines’ vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. The input features for ML model training comprise spectral, structural, and texture feature types generated from multispectral orthomosaics (spectral features), Digital Terrain and Surface Models (DTM/DSM- structural features), and Gray-Level Co-occurrence Matrix (GLCM) calculations (texture features). The specific features were selected based on extensive literature research, including especially the fields of precision agri- and viticulture. To integrate only vine canopy-exclusive features into ML classifications, different feature types were extracted and spatially aggregated (zonal statistics), based on a combined pixel- and object-based image-segmentation-technique-created vine row mask around each single grapevine position. The extracted canopy features were progressively grouped into seven input feature groups for model training. Model overall performance metrics were optimized with grid search-based hyperparameter tuning and repeated-k-fold-cross-validation. Finally, ML-based growth class prediction results were extensively discussed and evaluated for overall (accuracy, f1-weighted) and growth class specific- classification metrics (accuracy, user- and producer accuracy). Full article

The genus Vaccinium, which includes approximately 450 species, features economically significant berries such as bilberries (Vaccinium myrtillus) and blueberries (Vaccinium corymbosum). Bilberries flourish in acidic, well-drained soils, typically found in heathlands and coniferous forests, while blueberries benefit from a broader range of soil types and intensive agricultural practices. Sustainable cultivation strategies, including organic fertilization and efficient water management, are vital for optimizing production and addressing the environmental challenges posed by climate change. Both berries are rich in antioxidants and other nutrients, driving consumer interest and market growth despite competition from alternative crops. Additionally, tailored fertilization techniques are crucial for maximizing yield and fruit quality. By implementing circular economy principles, the production of bilberries and blueberries can enhance sustainability and profitability, ensuring their long-term success in agricultural systems. Full article

Juçara is an important element for biodiversity in the Atlantic Forest, not only providing a rich source of nutritional and bioactive compounds, but also holding promising potential for sustainability. However, despite its virtues, there remains a dearth of studies fully exploring its potential. In our pioneering study, conducted using a panel of eight trained specialists, we delved into a sensory analysis of dehydrated juçara pulp, employing both descriptive analysis and the temporal dominance of sensations (TDS) technique. The findings revealed striking differences between juçara and açaí, not only in terms of flavor and aroma, but also in their potential to drive more mindful eating habits. By promoting the consumption of juçara, we are supporting the sustainability of the Atlantic Forest, where it is cultivated in an environmentally responsible manner. Thus, we are contributing to the preservation of this unique ecosystem and the well-being of local communities. Full article

Accurately predicting grapevine yield and quality is critical for optimising vineyard management and ensuring economic viability. Numerous studies have reported the complexity in modelling grapevine yield and quality due to variability in the canopy structure, challenges in incorporating soil and microclimatic factors, and management practices throughout the growing season. The use of multimodal data and machine learning (ML) algorithms could overcome these challenges. Our study aimed to assess the potential of multimodal data (hyperspectral vegetation indices (VIs), thermal indices, and canopy state variables) and ML algorithms to predict grapevine yield components and berry composition parameters. The study was conducted during the 2019/20 and 2020/21 grapevine growing seasons in two South Australian vineyards. Hyperspectral and thermal data of the canopy were collected at several growth stages. Simultaneously, grapevine canopy state variables, including the fractional intercepted photosynthetically active radiation (fiPAR), stem water potential (Ψ_stem), leaf chlorophyll content (LCC), and leaf gas exchange, were collected. Yield components were recorded at harvest. Berry composition parameters, such as total soluble solids (TSSs), titratable acidity (TA), pH, and the maturation index (IMAD), were measured at harvest. A total of 24 hyperspectral VIs and 3 thermal indices were derived from the proximal hyperspectral and thermal data. These data, together with the canopy state variable data, were then used as inputs for the modelling. Both linear and non-linear regression models, such as ridge (RR), Bayesian ridge (BRR), random forest (RF), gradient boosting (GB), K-Nearest Neighbour (KNN), and decision trees (DTs), were employed to model grape yield components and berry composition parameters. The results indicated that the GB model consistently outperformed the other models. The GB model had the best performance for the total number of clusters per vine (R² = 0.77; RMSE = 0.56), average cluster weight (R² = 0.93; RMSE = 0.00), average berry weight (R² = 0.95; RMSE = 0.00), cluster weight (R² = 0.95; RMSE = 0.13), and average berries per bunch (R² = 0.93; RMSE = 0.83). For the yield, the RF model performed the best (R² = 0.97; RMSE = 0.55). The GB model performed the best for the TSSs (R² = 0.83; RMSE = 0.34), pH (R² = 0.93; RMSE = 0.02), and IMAD (R² = 0.88; RMSE = 0.19). However, the RF model performed best for the TA (R² = 0.83; RMSE = 0.33). Our results also revealed the top 10 predictor variables for grapevine yield components and quality parameters, namely, the canopy temperature depression, LCC, fiPAR, normalised difference infrared index, Ψ_stem, stomatal conductance (g_s), net photosynthesis (P_n), modified triangular vegetation index, modified red-edge simple ratio, and ANT_gitelson index. These predictors significantly influence the grapevine growth, berry quality, and yield. The identification of these predictors of the grapevine yield and fruit composition can assist growers in improving vineyard management decisions and ultimately increase profitability. Full article

Agroforestry practices evolve with the development of basic and advanced facilities, changes in natural and artificial factors of land, and land use trade-offs. This study aims to examine the farmers’ socioeconomic characteristics and perception of land use changes that define optimal agroforestry practices in Khost Province, Afghanistan. Data were collected from 662 farmers and analyzed using univariate Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA). The results found that forest and vegetable products, including fruits, berries, herbs, mushrooms, wild animals, oils, wood, honey, okra, eggplant, carrot, cucumber, pine nuts, pepper, and timber, have different impacts in terms of satisfaction with basic and advanced facilities, knowledge of land use changes, satisfaction with natural and artificial resources of land, and barriers to and economic benefits of land use. The limitations of this study included an absence of exogenous factors in the model such as climate change, financial conditions, market fluctuations, regulatory system, the area in which this study is selected, research design, and current condition of endogenous factors. Overall, this study defined a set of optimal agroforestry practices (expressed as crops and products) based on the farmers’ perception of land use changes in Khost Province, Afghanistan. This study provided useful insights for policymakers and development practitioners to promote agroforestry practice adoption and improve the socioeconomic development of agroforestry-dependent communities. Future works could explore the implications of agroforestry practices on the socioeconomic development of other dependent communities in Afghanistan. Full article

This paper examines the socio-economic significance of forest visits and the collection of forest berries and mushrooms (FBMs) in the Czech Republic, emphasising their role in enhancing human well-being and contributing to regional economies. Over a 30-year period, data were collected on the quantities and economic values of FBMs, alongside the intensity of forest visits by the Czech population. This study incorporates a detailed analysis of time series data on FBM collection, exploring trends and fluctuations in the harvested quantities and their economic value. A Lorenz curve analysis reveals significant disparities in the distribution of economic benefits, with a small segment of the population accounting for the majority of the FBM-derived value. Additionally, the research investigates the impact of forest visitation on well-being at the regional level, highlighting the relationship between forest access, visitation intensity, and public health benefits. This study also examines visitors’ expectations, motivations, and perceptions regarding an ideal forest for visitation, providing recommendations for effective marketing strategies. Furthermore, the study explores the contribution of FBMs to net income across different regions, demonstrating substantial regional variation in their economic importance. Notably, the analysis shows that the value of FBMs represents approximately 37% of the net income generated by traditional forestry activities, underscoring its significant economic potential. The findings emphasise the potential of territorial marketing strategies to enhance well-being, particularly in economically disadvantaged regions, and advocate for sustainable forest management practices to protect these valuable resources and ensure equitable access to the benefits provided by forest ecosystems. Full article

Advances in mobile robotics and AI have significantly expanded their application across various domains and challenging conditions. In the past, this has been limited to safe, controlled, and highly structured settings, where simplifying assumptions and conditions allowed for the effective resolution of perception-based tasks. Today, however, robotics and AI are moving into the wild, where human–robot collaboration and robust operation are essential. One of the most demanding scenarios involves deploying autonomous drones in GNSS-denied environments, such as dense forests. Despite the challenges, the potential to exploit natural resources in these settings underscores the importance of developing technologies that can operate in such conditions. In this study, we present a methodology that addresses the unique challenges of natural forest environments by integrating positioning methods, leveraging cameras, LiDARs, GNSS, and vision AI with drone technology for under-canopy wild berry mapping. To ensure practical utility for fruit harvesters, we generate intuitive heat maps of berry locations and provide users with a mobile app that supports interactive map visualization, real-time positioning, and path planning assistance. Our approach, tested in a Scandinavian forest, refines the identification of high-yield wild fruit locations using V-SLAM, demonstrating the feasibility and effectiveness of autonomous drones in these demanding applications. Full article

The Khanty-Mansi Autonomous Okrug-Yugra, situated within Russia’s Far North, has undergone substantial industrialization and economic development. However, it is confronted with considerable environmental challenges, notably soil contamination. This study examines the presence of heavy metals (lead, cadmium, copper and zinc) in medicinal and berry plants from the forest ecosystem of this region. The following plant species were analyzed: Hypericum perforatum, Rubus arcticus, Origanum vulgare and Thymus vulgaris. The samples were taken from both open ground and hydroponic cultivation under artificial lighting. The findings indicate that the levels of lead present in all samples remain below the permissible limit of 10 mg/kg. Cadmium levels exhibited variability, with hydroponically grown plants containing 0.01 to 0.5 mg/kg and open ground Hypericum and Rubus perforatum containing up to 0.8 mg/kg. The combination of hydroponic cultivation and specific lighting conditions has been demonstrated to reduce lead and cadmium accumulation by a minimum of 1.6 times in comparison to open ground cultivation. The copper content of the samples ranged from 3 to 8 mg/kg, while the zinc content was 1.2–1.5 times higher in the plants grown in the open compared to those grown hydroponically. Notwithstanding these variations, the heavy metal content of all plant samples remains below the threshold values, thus rendering them safe for harvesting and utilization. This research serves to illustrate the environmental impact of industrial activities and to identify hydroponics as a potential strategy for their mitigation. Full article

Background: The activity of heavy metal (HM) mining and processing industries causes soils contamination with HM. The metals could be transferred from contaminated soils to edible plants and fungi. This study aimed to assess the content of Cd, Pb, Hg, As, and Ni in berries and edible mushrooms collected in the forests located near Miasteczko Slaskie zinc smelter and in the Lubliniec region, in the context of consumers’ health risk. Methods: The ET-AAS method was used to determine the content of Cd, Pb, Ni, and As. Mercury concentration was determined using the CV-AFS method. Results: The studies showed high levels of Cd and Pb in the examined products. A statistically significant impact of the distance from the smelter on the Cd concentration in the berries was observed. Total non-cancer health risk from the combined exposure of adults to all HM in mushrooms and berries was significant when consuming the most heavily contaminated produce. The risk to children was significant, even when consuming products with moderate levels of the metals. Ingestion of Cd by children with mushrooms was related to a high cancer risk. The uncertainty of the results was determined. Conclusions: It is recommended to take action to increase awareness among residents of the areas adjacent to the forests regarding the existing health risk and to take possible measures to reduce exposure to HM. Full article

Sustainable and efficient agricultural production is a growing priority in modern society. Viticulture, an important agricultural and food sector, also faces this challenge. Precision Viticulture (PV) has gained prominence as it aims to foster high-quality, efficient, and environmentally sustainable practices. The Soluble Solids Content (SSC) is essential for assessing grape ripeness and quality in the winemaking process. Conventional methods for determining SSC values (expressed in °Brix) are invasive, expensive, and labour-intensive, necessitating sample preparation, making large-scale analysis impractical. In response to these limitations, this study presents an innovative approach within the field of Precision Viticulture. It focuses on the non-invasive prediction of SSC using low-cost proximal hyperspectral optical sensors. These sensors rely on spectral reflectance measurements in the range of 340–850 nm. This study was conducted in a commercial vineyard in the Demarcated Douro Region, Cima-Corgo sub-region, Portugal, over six weeks during ripening. In total, 169 grape berries from Touriga Nacional vines were analysed under three irrigation regimes (no irrigation, 30% ETc, and 60% ETc). After organising and preprocessing the data, machine learning algorithms, namely Partial Least Squares Regression (PLS), Random Forest (RF), and the Generalised Linear Model (GLM), were applied to predict SSC values. These models’ performance was thoroughly evaluated using cross-validation techniques. The performance of different models was evaluated, showing significant differences according to the metrics used (R2, RMSE, and MAPE). The RF model demonstrated effectiveness and precision. A high R² value of 0.9312, coupled with low RMSE (0.9199 °Brix) and MAPE (3.88%), signifies a strong fit to the data and accurate predictive capabilities. The results of this benchmarking study on predictive models of SSC provide valuable insights into the performance of various models, aiding winegrowers and winemakers in decision making. Full article