Search Results (469)

Snow serves as a crucial water source for vegetation growth on the Mongolian Plateau, and its temporal and spatial variations exert profound influences on terrestrial vegetation phenology. In recent years, global climate change has led to significant changes in snow and vegetation start of growing season (SOS). Therefore, it is necessary to study the mechanism of snow cover on vegetation growth and changes on the Mongolian Plateau. The study found that the spatial snow cover fraction (SCF) of the Mongolian Plateau ranged from 50% to 60%, and the snow melt date (SMD) ranged from day of the year (DOY) 88 to 220, mainly concentrated on the northwest Mongolian Plateau mountainous areas. Using different SOS methods to calculate the vegetation SOS distribution map. Vegetation SOS occurs earlier in the eastern part compared to the western part of the Mongolian Plateau. In this study, we assessed spatiotemporal distribution characteristics of snow on the Mongolian Plateau over the period from 2001 to 2023. The results showed that the SOS of the Mongolian Plateau was mainly concentrated on DOY 71-186. The Cox survival analysis model system established SCF and SMD on vegetation SOS. The SCF standard coefficient is 0.06, and the SMD standard coefficient is 0.02. The SOS_NDVI coefficient is −0.15, and the SOS_NDGI coefficient is −0.096. The results showed that the vegetation SOS process exhibited differential response characteristics to snow driving factors. These research results also highlight the important role of snow in vegetation phenology and emphasize the importance of incorporating the unique effects of vegetation SOS on the Mongolian Plateau. Full article

Accurate phenological information on sugarcane is crucial for guiding precise cultivation management and enhancing sugar production. Remote sensing offers an efficient approach for large-scale phenology retrieval, but most studies have primarily focused on staple crops. The methods for retrieving the sugarcane phenology—the germination, tillering, elongation, and maturity stages—remain underexplored. This study addresses the challenge of accurately monitoring the sugarcane phenology in complex terrains by proposing an optimized strategy integrating spatiotemporal fusion data. Ground-based validation showed that the change detection method based on the Double-Logistic curve significantly outperformed the threshold-based approach, with the highest accuracy for the elongation and maturity stages achieved at the maximum slope points of the ascending and descending phases, respectively. For the germination and tillering stages with low canopy cover, a novel time-windowed change detection method was introduced, using the first local maximum of the third derivative curve (denoted as Point A) to establish a temporal buffer. The optimal retrieval models were identified as 25 days before and 20 days after Point A for germination and tillering, respectively. Among the six commonly used vegetation indices, the NDVI (normalized difference vegetation index) performed the best across all the phenological stages. Spatiotemporal fusion using the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) significantly improved the monitoring accuracy in heterogeneous agricultural landscapes, reducing the RMSE (root-mean-squared error) by 21–46%, with retrieval errors decreasing from 18.25 to 12.97 days for germination, from 8.19 to 4.41 days for tillering, from 19.17 to 10.78 days for elongation, and from 19.02 to 15.04 days for maturity, highlighting its superior accuracy. The findings provide a reliable technical solution for precision sugarcane management in heterogeneous landscapes. Full article

Background: Conventional practices for the cultivation of “Cipollotto Nocerino” spring onion are mainly based on growers’ experience, and up to 250 kg/ha for N is commonly furnished among growing cycles. Facing the issue of reduced availability of natural resources for crop production (for example mineral resources), we investigated the optimization of the productivity. Methods: In our research, we tested the use of depletion nutrient supply strategy (CAL-FERT^®) to enhance fertilization in accordance with the principle of sustainable agriculture included in the Farm to Fork strategy. In our study, besides the common initial fertilization, three different strategies for cover fertilizations have been elaborated with the support of CAL-FERT^® software. The treatments were as follows: (i) commercial standard fertilization as control (named CF); (ii) fertilization equivalent to 50% of the N applied in the control (named F-50); (iii) fertilization corresponding to 25% of the N applied in the control (named F-25); and (iv) strongly reduced fertilization compared to the control (named F-0). The parameters investigated included the following: plant height, yield, SPAD index, nitrogen use efficiency, dry matter, soluble solid content, and pyruvate contents in bulbs and leaves. Nitrogen content was also analyzed for both hypogeous and epigeous apparatuses. Results: Among the most interesting vegetative results, plant height and SPAD readings were reduced only by the extreme treatment F-0 compared with the other treatments at 104 days after planting. Regarding qualitative and productive parameters, the treatments F-50 and F-25 showed the highest yield without prejudging Soluble Solid Content and reducing pungency. Conclusion: In nutritional experiments, onion could be considered as a crop model to investigate quality in vegetables due to its consumption as fresh product and for its particular response, in terms of yield and quality, to fertilization. The use of simulation software can support the identification of strategies to reduce the nutrient supply without any detrimental effect on yield and other vegetative and qualitative parameters in onion crops. Full article

The Saiss plain in northern Morocco covers an area of 2300 km² and is one of the main agricultural contributors to the national economy. However, climate change and water scarcity reduce the region’s agricultural yields. Conventional methods of estimating evapotranspiration (ET) provide localized results but cannot capture regional-scale variations. This study aims to estimate the spatiotemporal evolution of daily crop ET (olives, fruit trees, cereals, and vegetables) across the Saiss plain. The METRIC model was adapted for the region using Landsat 8 data and was calibrated and validated using in situ flux tower measurements. The methodology employed an energy balance approach to calculate ET as a residual of net radiation, soil heat flux, and sensible heat flux by using hot and cold pixels for calibration. METRIC-ET ranged from 0.1 to 11 mm/day, demonstrating strong agreement with reference ET (R² = 0.76, RMSE = 1, MAE = 0.78) and outperforming MODIS-ET in accuracy and spatial resolution. Olives and fruit trees showed higher ET values compared to vegetables and cereals. The results indicated a significant impact of ET on water availability, with spatiotemporal patterns being influenced by vegetation cover, climate, and water resources. This study could support the development of adaptive agricultural strategies. Full article

Surface all-wave net radiation ($R_n$) is one of the essential parameters to describe surface radiative energy balance, and it is of great significance in scientific research and practical applications. Among various acquisition approaches, the estimation of $R_n$ from satellite data is gaining more and more attention. In order to obtain the daily $R_n$ ($R_{nd}$) from the instantaneous satellite observations, a parameter $C_d$, which is defined as the ratio between the $R_n$ at daily and at instantaneous under clear sky was proposed and has been widely applied. Inspired by the sinusoidal model, a new model for $C_d$ estimation, namely New Model, was proposed based on the comprehensive clear-sky $R_n$ measurements collected from 105 global sites in this study. Compared with existing models, New Model could estimate $C_d$ at any moment during 9:30~14:30 h, only depending on the length of daytime. Against the measurements, New Model was evaluated by validating and comparing it with two popular existing models. The results demonstrated that the $R_{nd}$ obtained by multiplying $C_d$ from New Model had the best accuracy, yielding an overall $R^2$ of 0.95, root mean square error (RMSE) of 14.07 Wm⁻², and Bias of −0.21 Wm⁻². Additionally, New Model performed relatively better over vegetated surfaces than over non- or less-vegetated surfaces with a relative RMSE (rRMSE) of 11.1% and 17.89%, respectively. Afterwards, the New Model $C_d$ estimate was applied with MODIS data to calculate $R_{nd}$. After validation, the $R_{nd}$ computed from $C_d$ was much better than that from the sinusoidal model, especially for the case MODIS transiting only once in a day, with $R_{nd}$-validated $R^2$ of 0.88 and 0.84, RMSEs of 19.60 and 27.70 Wm⁻², and Biases of −0.76 and 8.88 Wm⁻². Finally, more analysis on New Model further pointed out the robustness of this model under various conditions in terms of moments, land cover types, and geolocations, but the model is suggested to be applied at a time scale of 30 min. In summary, although the new $C_d$ model only works for clear-sky, it has the strong potential to be used in estimating $R_{nd}$ from satellite data, especially for those having fine spatial resolution but low temporal resolution. Full article

Active packaging films have been an essential component in food material research to ensure the safe and efficient preservation of food, fruit, and vegetables. The shelf life of fruits and vegetables may likely be extended by covering them with high-performance nanofiber (NF) films. The selection of materials for active packaging film has been a critical factor in preventing food materials from environmental contaminants (microbes) and extending the shelf life. This study aims to develop NF-based materials for cherry tomatoes to prevent fungal and bacterial damage. Bioactive NFs were produced through an electrospinning process using tannic acid (TA) within a polyvinylidene fluoride (PVDF) template. These NFs offer a sustainable alternative to synthetic packaging for food preservation. TA was incorporated into the PVDF matrix at varying concentrations (0.4 to 1.2%). Key parameters, including moisture content, thickness, opacity, water-contact angle, and thermal shrinkage, were assessed. The physicochemical results indicate that the TA NFs are suitable for further shelf-life performance evaluations. The antifungal and antibiofilm activity of the NFs was tested, showing that the TA_1.2 in the PVDF matrix was more effective than other concentrations. Shelf-life tests demonstrated that cherry tomatoes covered with TA_1.2 NFs showed no surface changes for up to 4 days. Importantly, the NFs were confirmed to be non-toxic to normal cells, as evidenced by tests on mouse 3T3-L1 fibroblast cells. In summary, we have developed bioactive NFs composed of TA in a PVDF matrix that enhance the shelf life of cherry tomatoes by preventing bacterial and fungal attacks on the fruit surfaces. Full article

Urbanisation and land-use change are among the main pressures on soil health in periurban areas, but the multifunctionality of grassland soils is still not sufficiently recognised. In this study, the physical and chemical properties of soils under grassland, forest and croplands in the periurban area of Zagreb were investigated in a two-year period. Grasslands consistently exhibited multifunctional benefits, including high organic matter content (4.68% vs. 2.24% in cropland), improved bulk density (1.14 vs. 1.24 g cm⁻³) and an active carbon cycle indicated by increased CO₂ emissions (up to 1403 kg ha⁻¹ day⁻¹ in 2021). Forest soils showed the highest aggregate stability (91.4%) and infiltration (0.0006 cm s⁻¹), while croplands showed signs of structural degradation with the highest bulk density and lowest water retention (39.9%). Temporal variation showed that grassland was particularly responsive to favourable climatic conditions, with soil porosity and water content improving yearly. Principal component analysis showed that soil structure, biological activity and moisture regulation were linked, with grassland plots favourably positioned along the axes of resilience. The absence of tillage and the presence of permanent vegetation cover contributed to their high capacity for climate and water regulation and carbon sequestration. These results emphasise the importance of protecting and managing grasslands as an important component of urban green areas. Practices such as mulching, minimal disturbance and continuous cover can maximise the ecosystem services of grassland soils. In addition, the results highlight the potential risk of trace metal accumulation in cropland and grassland soils located near urban and farming infrastructure, underlining the need for regular monitoring in periurban environments. Integrating grassland functions into urban planning and policy is essential for improving the sustainability and resilience of periurban landscapes. Full article

Upland fields are a significant source of N₂O emissions. Thus, an accurate estimation of these emissions is essential. This study employed four classical modeling approaches—the Stepwise Regression Model, Decision Tree Regression, Support Vector Machine, and Random Forest (RF)—to simulate soil N₂O emissions from Chinese upland fields. The upland crops considered in this study covered food crops, oil crops, cash crops, sugar crops, fruits, and vegetables, excluding flooded rice. Comparative analysis revealed that the RF algorithm performed the best, with the highest R² at 0.66 and the lowest root mean square error at 0.008 kg N₂O ha⁻¹ day⁻¹. The application rate of mineral nitrogen fertilizers, mean temperature during the growing season, and soil organic carbon content were the key driving factors in the N₂O emission model. Utilizing the RF model, total N₂O emissions from Chinese upland fields in 2020 were estimated at 183 Gg. Future projections under Representative Concentration Pathway (RCP) scenarios indicated a 2.80–5.92% increase in national N₂O emissions by 2050 compared to 2020. The scenario analysis demonstrated that the proposed nitrogen reduction strategies fail to counteract climate-driven emission amplification. Under the combined scenarios of RCP8.5 and nitrogen reduction strategies, a net 4% increase in national N₂O emissions was projected, highlighting the complex interplay between anthropogenic interventions and climate feedback mechanisms. This study proposes that future attention should be paid to the development of nitrogen optimization strategies under the impact of climate change. Full article

In this study, a Life Cycle Assessment (LCA) was conducted to evaluate the environmental impact of osmotically dehydrated, fresh-cut, pre-packaged potatoes compared to conventional untreated ones. The case study focused on a small processing line in Naxos Island, Greece, aiming to extend shelf-life by up to 5 days. The analysis covered the full value chain, from cultivation to household consumption, considering changes in energy and material use, transport volumes, waste generation, and cultivation demand. Three scenarios were assessed: (i) conventional untreated potatoes, (ii) dehydrated potatoes using market glycerol, and (iii) dehydrated potatoes using glycerol from vegetable oil treatment. Systems and life cycle inventories (LCI) were modelled in OpenLCA v2.4 software with the ecoinvent v3.11 database, applying the Environmental Footprint (EF) method, v3.1. The selected impact categories included the following: global warming potential, water use, freshwater ecotoxicity, freshwater and marine eutrophication, energy resource use, particulate matter formation, and acidification. Results showed that applying osmotic dehydration (OD) improved environmental performance in most, but not all, categories. When market glycerol was used, some burdens increased due to glycerol production. However, using glycerol from vegetable oil treatment resulted in reductions of 25.8% to 54.9% across all categories compared to the conventional scenario. Overall, OD with alternative glycerol proved to be the most environmentally beneficial approach. Full article

Objectives: This study comparatively evaluated changes in the food habits and dietary patterns of adults aged ≥65 years before and during the coronavirus disease 2019 (COVID-19) pandemic using a retrospective study. Methods: Data covering the 2018–2021 period were derived from the Korea National Health and Nutrition Examination Survey. Results: Comparing the 2943 individuals in the “Before-COVID-19” individuals with the 2916 people in the “During COVID-19” group, the frequency of drinking four or more times a week decreased among the older adults during the pan-demic, as did the frequency of eating three meals a day and eating-out at least once a week. On the other hand, food security improved during the pandemic compared with before the pandemic. During the pandemic, the intake of cereals and grains decreased, while that of potatoes and starches, legumes, vegetables, eggs, milk and dairy products, and oils and fats increased. Although energy and carbohydrate intake decreased, protein, fiber, calcium, phosphorus, magnesium, potassium, zinc, riboflavin, vitamin E, vitamin C, folic acid, and fat intake increased. However, the intake of vitamin A, vitamin C, and calcium remained lower than the estimated adequate requirement of the Dietary Reference Intakes for Koreans. Additionally, the rate of nutritional insufficiency “During COVID-19” (20.76%) was 1.31–1.42 times higher than that “Before COVID-19” (16.45%). Even in models that adjusted for other factors, the rate of nutritional insufficiency was higher during the pandemic than before. Conclusions: Based on these findings, measures such as dietary education programs and guidelines for proper nutrient intake should be formulated to prevent imbalances in nutrient intake among older Koreans. Full article

This Technical Note presents the design and implementation of a low-cost modular growth chamber developed to keep mother plants under controlled environmental conditions for vegetative propagation. The system was conceived as an accessible alternative to expensive commercial equipment, offering reproducibility and adaptability for small-scale and research-based cultivation. The proposed chamber integrates thermal insulation, LED lighting, forced ventilation through the implementation of extractors, a recirculating irrigation system with double filtration, and a sensor-based environmental monitoring platform operated via an Arduino UNO microcontroller. The design features a removable tray that serves as a support for the mother plant, an observation window covered by a movable dark acrylic that prevents the passage of external light, and a vertical structure that facilitates optimal space utilization and ergonomic access. Functionality was conducted using a Stevia rebaudiana Bertoni mother plant maintained for 30 days under monitored conditions. Environmental parameters—temperature, relative humidity, and illuminance—were recorded continuously. The plant showed vegetative development through new shoot emergence and the growth in height of the plant, and despite a loss in foliage expansion, it confirmed the chamber’s capacity to support sustained growth. Although no statistical replication or control group was included in this preliminary evaluation, the system demonstrates technical feasibility and practical utility. This chamber provides a replicable platform for future experimentation and propagation studies. Complete technical specifications, schematics, and component lists are provided to enable replication and further development by other researchers. The growth chamber design aligns with the goals of open-source agricultural innovation and supports knowledge transfer in controlled-environment plant propagation technologies. Full article

This study analyzed the impact of land use and cover changes, along with climate variability, on water consumption by quantifying actual evapotranspiration (${\mathrm{ET}}_{\mathrm{a}}$) in the Tres Cruces River basin (TCR) in Uruguay. Using Landsat 8 and 9 images from 2014 to 2024, the SAFER method (Simple Algorithm for Evapotranspiration Retrieving), applied for the first time in Uruguay, estimated ${\mathrm{ET}}_{\mathrm{a}}$ for natural vegetation (grasslands and riparian forests) and commercial afforestation areas. Quality metrics, including determination coefficient (r² = 0.87), Pearson correlation (r = 0.94), root mean square error (RMSE = 1.46 mm/day), and Nash–Sutcliffe efficiency (NSE = 0.34), were utilized for SAFER’s optimal parameterization based on the literature. Results revealed monthly ${\mathrm{ET}}_{\mathrm{a}}$ variability and highlighted higher ${\mathrm{ET}}_{\mathrm{a}}$ values for afforestation areas, exceeding grasslands by 26.5% and riparian forests by 4.79%, reflecting increased water demand due to greater biomass and photosynthetic activity. Additionally, prolonged drought periods correlated with increased water consumption by forest vegetation, despite the Standardized Precipitation-Evapotranspiration Index (SPEI) remaining within normal bounds during the 2020–2023 drought. These findings underscore the significant hydrological implications of converting grasslands to afforestation and the need for integrated water resource management amid expanding commercial forestry in the region. Full article

The accurate detection of mowing events is important in many applications, including in agricultural contexts such as yield and fodder production, as well as biodiversity assessments, habitat modeling, and protected area monitoring. This work presents the first free and open dataset of mowing events covering the entire Austrian territory for the year 2023 at a spatial resolution of 10 × 10 m. We use the Sentinel-2 time series of the Normalized Difference Vegetation Index (NDVI) to detect mowing events, and additionally, we use the mean of the two ShortWave InfraRed (SWIR) bands to exclude misclassification caused by remaining cloud artifacts and shadows. The validation procedure builds on a visual interpretation of the Panomax webcam archive complemented by a selection of field observations. The final validation dataset consists of 211 mowing events recorded in 85 different locations across Austria. In total, 77.73% of these mowing events were detected with a mean time delay of 4 days. The detection delay in summer was smaller than the values recorded in spring and fall. The pixel-based approach exhibited superior efficacy, especially for meadows with three or more mowing events, compared to the polygon-based approach. The results of our study are consistent with those of previous works demonstrating the capacity to produce high-quality mowing event data for various grassland areas in a fully automated manner, independent from training datasets. The results could be used in research on biodiversity or in practical applications such as agricultural policy support and control, fodder supply evaluation, or impact assessment in nature restoration efforts. Full article

This study evaluated the effects of selected polysaccharide edible coatings (apple pectin and sodium alginate) on the quality characteristics of fresh-cut beetroot. The changes in texture (hardness), optical parameters such as colour and Hue angle, polyphenols, flavonoids, and red and yellow colourants during 4 weeks of refrigerated storage, as well as changes in microstructure, were examined. Self-standing coatings have also been prepared and characterised by continuous structure without pores, cracks, and high lightness. The obtained results for hardness showed reduced values during storage. Colour parameters (L*, a*, and b*) and Hue angle remained mostly consistent, indicating the preservation of the desired colour, though slight changes were noted during storage. Lightness (parameter L*) increased over time, suggesting changes in the beetroot surface. However, these changes were less pronounced in samples covered with coatings. The use of polysaccharide coatings and storage time positively impacted flavonoids in fresh-cut beetroots, except after 28 days when the lowest values for both parameters were observed. It can also be noted that the polyphenol content in coated samples decreased at a slower rate. Moreover, there was a significant decrease in the content of red and yellow colourants for both control and coated samples. However, greater changes were noted for samples treated with coatings. Scanning electron microscopy used at 0 and 28 days showed lower pores in beetroot tissue as a result of applied polysaccharide coatings, and refrigerated storage negatively affected the minimally processed beetroot surface. Nevertheless, minimally processed beetroots obtained with the treatment of polysaccharide coatings as mild technology showed modifications to the quality characteristics, which can find practical use in reducing the waste of fresh-cut vegetables during storage. Full article

Being an agricultural country, Pakistan requires lots of water for irrigation. A major portion of its water resources is located in the upper indus basin (UIB). The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system that boosts the water supply. Snow accumulation during the winter period in the highlands in the watershed(s) becomes a source of water inflow during the snow-melting period, which is described according to characteristics like snow depth, snow density, and snow water equivalent. Snowmelt water release (SWE) and snowmelt water depth (SD) maps are generated by tracing snow occurrence from MODIS-based images of the snow-cover area, evaluating the heating degree days (HDDs) from MODIS-derived images of the land surface temperature, computing the solar radiation, and then assimilating all the previous data in the form of the snowmelt model and ground measurements of the snowmelt water release (SWE). The results show that the average snow-cover area in the Astore river basin, in the upper indus basin, ranges from 94% in winter to 20% in summer. The maps reveal that the annual average values of the SWE range from 150 mm to 535 mm, and the SD values range from 600 mm to 2135 mm, for the snowmelt period (April–September) over the years 2010–2020. The areas linked with vegetation experience low SWE accumulation because of the low slopes in the elevated regions. The meteorological parameters and basin characteristics affect the SWE and can determine the SD values. Full article