Search Results (99)

The agricultural sector faces significant sustainability, productivity, and environmental impact challenges. In this context, geographic information systems (GISs) have become a key tool to optimize resource management and make informed decisions based on spatial data. These data support planning the best cotton planting and harvest dates based on agroclimatic conditions, such as temperature, precipitation, and soil type, as well as identifying areas with a lower risk of water or thermal stress. As a result, cotton productivity is optimized, and costs associated with supplementary irrigation or losses due to adverse conditions are reduced. However, data from automatic weather stations in Mexico are scarce and incomplete. Instead, grid meteorological databases (DMM, in Spanish) were used with daily temperature and precipitation data from 1983 to 2020 to determine the heat units (HUs) for each cotton crop development stage; daily and accumulated HU; minimum, mean, and maximum temperatures; and mean annual precipitation. This information was used to determine areas that comply with environmental, geographic, and regulatory conditions (NOM-059-SEMARNAT-2010, NOM-026-SAG/FITO-2014) to delimit areas with agricultural potential for planting genetically modified (GM) cotton. The methodology made it possible to produce thirty-four maps at a 1:250,000 scale and a digital GIS with 95% accuracy. These maps indicate whether a given agricultural parcel is optimal for cultivating GM cotton. Full article

Honey is prized for its nutritional and healing properties, but its quality can be affected by contamination with toxic elements. This study evaluates the nutritional value and health risks of fifteen honey samples from different agro-climatic regions of Pakistan. Physicochemical properties such as color, pH, electrical conductivity, moisture, ash, and solids content were within acceptable ranges. ICP-OES analysis was used to assess six essential minerals and ten toxic metals. Except for slightly elevated boron levels (up to 0.18 mg/kg), all elements were within safe limits, with potassium reaching up to 1018 mg/kg. Human health risk assessments—including Average Daily Dose of Ingestion, Total Hazard Quotient, and Carcinogenic Risk—indicated no carcinogenic threats for adults or children, despite some elevated metal levels. Antioxidant activity, measured through total phenolic content (TPC) and DPPH radical scavenging assays, showed that darker honeys had stronger antioxidant properties. While the overall quality of honey samples was satisfactory, significant variations (p ≤ 0.05) were observed across different regions. These differences are attributed to diverse agro-climatic conditions and production sources. The findings highlight the need for continued monitoring to ensure honey safety and nutritional quality. Full article

The European Union’s developing rural development plan places digital and precision agriculture at the centre of agricultural modernisation and economic development. This article examines how agricultural practices in rural EU regions are being influenced by smart technology, such as drones, IoT sensors, satellite-based research, and AI-driven platforms, through an analysis of recent data from sources across the European Union. This study applies a mixed-methods approach, combining quantitative analysis of strategic policy documents and EU databases, to evaluate the ways in which precision agriculture reduces input consumption, increases productivity, reduces labour shortages and rural area depopulation, and improves sustainability. By investing in infrastructure, developing communities for data exchange, and organising training for farmers, European policies such as the Strategic Plans of the Common Agricultural Policy (CAP), the SmartAgriHubs initiative, and the AgData program actively encourage the transition to digital agriculture. Cyprus is analysed as a case study to show how targeted investments and initiatives supported by the EU can help smaller countries, with limited natural resources, to realise the benefits of digital transformation in agriculture. A special focus is placed on how solutions adapted to agro-climatic and socioeconomic conditions can contribute to strengthening the competitiveness of the agricultural sector, attracting young people to get involved in this field and opening up new economic opportunities. The results of previous research indicate that digital agriculture not only improves productivity but also proves to be a strategic mechanism for attracting and retaining young people in rural areas. Thus, this work additionally contributes to the broader goal of the European Union—the development of smart, inclusive, and sustainable rural areas, in which digital technologies are not only seen as tools for efficiency but also as key means for integrated and long-term rural development. Full article

Cotton is the most widely consumed natural fiber globally and emits fewer greenhouse gases compared to synthetic alternatives. Brazil is currently the largest cotton exporter, and understanding its potential for sustainable expansion is crucial. This study developed agroclimatic zoning maps for cotton (Gossypium hirsutum L.) across Brazil under current and future climate conditions using data from the World-Clim and MapBiomas platforms. Four climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) were assessed over multiple time periods. Results showed that rising temperatures and reduced rainfall will likely reduce cotton suitability in traditional producing regions such as Bahia. However, areas with potential for cotton cultivation, especially in Mato Grosso, which currently accounts for 90% of national production, remain extensive, with agroclimatic conditions indicating a theoretical expansion potential of up to 40 times the current cultivated area. This projection must be interpreted with caution, as it does not account for economic, logistical, or social constraints. Notably, Brazilian cotton is cultivated with minimal irrigation, low fertilizer input, and high adoption of no-till systems, making it one of the least carbon-intensive globally. Full article

This study investigates the environmental regulation of sex expression and seed yield stability in four Thai dioecious hemp (Cannabis sativa L.) cultivars (RPF1, RPF2, RPF3, and RPF4) under different seasonal conditions to optimize seed production. The experiment was conducted across two planting periods (in-season and off-season) to evaluate the effects of varying day lengths and temperatures on growth, reproductive development, and yield. The results showed that shorter day lengths and lower temperatures during the off-season led to an increased proportion of female plants across all cultivars, except RPF3, which exhibited a stable female-to-male ratio. RPF4 had the highest increase in female plants (16%), followed by RPF1 and RPF2 (10%). Seed yield was significantly influenced by seasonal changes, with RPF3 and RPF4 consistently outperforming the other cultivars. In the in-season, RPF3 and RPF4 produced the highest seed yields, reaching 83.4 g/plant and 81.6 g/plant, respectively. During the off-season, both cultivars experienced a decline in seed yield (by 24–26%), primarily due to a reduction in seed production in secondary inflorescences. However, RPF3 compensated for this loss with a 31% increase in seed production at main inflorescences, ensuring yield stability. RPF4 maintained its high yield potential by increasing the proportion of female plants, offsetting the decline in seed yield per plant. Additionally, cumulative growing degree days (CGDD) at harvest were comparable between seasons, with values of 2434 °Cd (in-season) and 2502 °Cd (off-season), indicating that temperature accumulation remained within an optimal range for seed maturation. The study highlights the importance of cultivar selection based on yield component stability and adaptability to seasonal variations. These findings provide valuable insights for improving hemp seed production strategies in Thailand’s diverse agro-climatic conditions. Full article

This study investigated soil salinization processes in the Pavlodar region of Kazakhstan by comparing key soil parameters—namely, electrical conductivity (EC), pH, exchangeable sodium percentage (ESP), and sodium adsorption ratio (SAR) under irrigated and non-irrigated conditions across different agro-climatic zones and soil types (Haplic Chernozems, Haplic Kastanozems). The focus was on understanding the effects of irrigation and natural factors on soil salinization. Statistical analysis, including descriptive statistics and significance testing, was employed to evaluate differences between soil types, locations, and management practices. The research revealed secondary salinization (EC > 2 dS/m, ESP > 15%) in the topsoil of irrigated Haplic Kastanozems soils in the central Aksu district. This degradation was markedly higher than in non-irrigated plots or irrigated Haplic Chernozems in the northern Irtysh district, highlighting the high vulnerability of Haplic Kastanozems soils under current irrigation management given Aksu’s climatic conditions, which are characterized by high evaporative demand (driven by summer temperatures) and specific precipitation patterns that contribute to soil moisture deficits without irrigation. While ESP indicated sodicity, SAR values remained low. Natural factors, including potentially saline parent materials and likely shallow groundwater dynamics influenced by irrigation, appear to contribute to the observed patterns. The findings underscore the need for implementing optimized irrigation and drainage management, particularly in the Aksu district, potentially including water-saving techniques (e.g., drip irrigation) and selection of salt/sodicity-tolerant crops. A comprehensive approach integrating improved water management, agronomic practices, and potentially soil amendments is crucial for mitigating soil degradation and ensuring sustainable agriculture in the Pavlodar region. Further investigation including groundwater monitoring is recommended. Full article

Climate change requires efficient water resource management, especially in regions where viticulture is developing. This study evaluates the water requirements, precipitation deficits, and irrigation needs of vineyards in two locations in southern Poland. The analysis covers both a reference period (1931–2020) and a forecast period (2030–2100), based on two climate change scenarios: RCP 4.5 and RCP 8.5. Grapevine water requirements were estimated using a crop coefficient tailored to Poland’s agroclimatic conditions, combined with meteorological data on air temperature and precipitation. Monthly crop coefficient values were calculated as the ratio of grapevine potential evapotranspiration, estimated using the Penman–Monteith method, to reference evapotranspiration, calculated using the Treder approach for the period 1981–2010. Precipitation deficits were assessed for normal, medium dry, and very dry years using the Ostromęcki method. Irrigation water demand was estimated for light, medium, and heavy soils using the Pittenger method. The results indicate a significant increase in both water demand and precipitation deficits in the forecast period, regardless of the scenario. In very dry years, irrigation will be necessary for all soil types. In medium dry years, water deficits will primarily affect vineyards on light soils. These findings underscore the urgent need for improvements in irrigation planning, especially in areas with low soil water. They offer practical insights for estimating future water storage needs and implementing precision irrigation adapted to changing climate conditions. Adopting such adaptive strategies is essential for sustaining vineyard productivity and improving water use efficiency. This study also supports the integration of climate projections into regional planning and calls for investment in innovative, water-saving technologies to strengthen the long-term resilience of Poland’s wine industry. Full article

Climate variability and extremes adversely affect the agricultural production system, food security, livestock sector, and water resources. With the cumulative effects of climate variability, there is a need to anticipate and develop appropriate adaptation strategies to cope with changing climatic conditions. It is necessary to study the adaptation strategies that are to be followed for climate change to examine the ability of vulnerable communities and people, frequently affected by drought and other climate-related risks, to adapt to climate change impacts. Hence, the present study examined the determinants of various climate change adaptation strategies followed by farmers as a measure to face climate variability, which will be ultimately beneficial and enlightening to policymakers to gain knowledge about the measures to be taken to mitigate the impact of climate change. The study was undertaken using data collected from 105 farm households with an organized pre-tested interview schedule in the central agro-climatic zone of Afghanistan. The multivariate probit econometric model was used to analyze the factors responsible for major adaptation strategies to mitigate the impact of climate change. The key findings of the model indicated that the probability of educated farmers migrating to the non-agricultural sector for employment has increased by 1.3 percent, and those who have more land area have adopted a reduction in irrigation by 5.2 percent as an adaptive mechanism. The study also found that having access to technical guidance from extension officials increased the likelihood of farmers changing their cropping pattern by 18.6 percent and of diversifying their farms by 19.2 percent. On the other hand, expert guidance reduced the likelihood of drilling new bore wells by 20.5 percentage points and decreased the probability of selling livestock by 10.8 percentage points. The results of the study provide policy insights to improve the ability of farmers to modify their practices through improvement in extension services, irrigation infrastructure facilities, watershed development, and climate-resilient agricultural systems. Full article

The aim of this study was to evaluate the influence of altitude on the phenolic content, antioxidant activity and mineral content of multifloral honeys collected in three different areas (plain, hill and mountain areas) of the Basilicata region. Our results show that the total phenolic and flavonoid contents and the multimineral profile were influenced by the altitudes of the different agro-climatic areas which are characterized by different soil characteristics and floral biodiversity. There was a negative correlation between altitude and total phenols, but there was a positive correlation between altitude and total flavonoids. Furthermore, altitude is closely related to antioxidant activities. Furthermore, the low correlations between antioxidant activities and polyphenols indicate that antioxidant activity is not only promoted by polyphenols but also by other biologically active substances (catalase, ascorbic acid and proteins) which contribute to the antioxidant activity of honey. This research demonstrates how different altitudes influence the analyzed parameters, confirming the uniqueness of honey with respect to the area of origin. Full article

Agricultural productivity is significantly influenced by climate-related factors. Understanding the impacts of climate change on agroclimatic conditions is critical for ensuring sustainable agricultural practices. This study investigates how key agroclimatic variables—temperature, moisture conditions, and length of the growing season (LGS)—influence wheat suitability in the Upper Blue Nile Basin (UBNB), Ethiopia. The Global Agroecological Zones (GAEZ) methodology was employed to assess agroclimatic suitability, integrating climate projections from Climate Models Intercomparison Project v6 (CMIP6) under shared socioeconomic pathway (ssp370 and ssp585) scenarios. The CMIP6 data provided downscaled projections for temperature and precipitation, while the GAEZ framework translated these climatic inputs into agroclimatic indicators, enabling spatially explicit analyses of land suitability. Projections indicate significant warming, with mean annual temperatures expected to rise between 1.13 °C and 4.85 °C by the end of the century. Precipitation levels are anticipated to increase overall, although spatial variability may challenge moisture availability in some regions. The LGS is projected to extend, particularly in the southern and southeastern UBNB, enhancing agricultural potential in these areas. However, wheat suitability faces considerable declines; under ssp585, the highly suitable area is expected to drop from 24.21% to 13.31% by the 2080s due to thermal and moisture stress. This study highlights the intricate relationship between agroclimatic variables and agricultural productivity. Integrating GAEZ and CMIP6 projections provides quantified insights into the impacts of climate change on wheat suitability. These findings offer a foundation for developing adaptive strategies to safeguard food security and optimize land use in vulnerable regions. Full article

Paddy rice mapping is critical for food security and environmental management, yet existing methods face challenges such as cloud obstruction in optical data and speckle noise in synthetic aperture radar (SAR). To address these limitations, this study introduces PRICOS, a novel paddy rice index that systematically combines time series Sentinel-2 optical features (NDVI for bare soil/peak growth, MNDWI for the submerged stages) and Sentinel-1 SAR backscatter (VH polarization for structural dynamics). PRICOS automates key phenological stage detection through harmonic fitting and dynamic thresholding, requiring only 10–20 samples per region to define rice growth cycles. Validated across six agroclimatic regions, PRICOS achieved overall accuracy (OA) and F1 scores of 0.90–0.98, outperforming existing indices like SPRI (OA: 0.79–0.95) and TWDTW (OA: 0.85–0.92). By integrating multi-sensor data with minimal sample dependency, PRICOS provides a robust, adaptable solution for large-scale paddy rice mapping, advancing precision agriculture and climate change mitigation efforts. Full article

Agriculture is an important part of the economy of southwestern United States (Southwest). The production of food and fiber in the Southwest is supported by irrigation, much of which is sourced from groundwater. Climate projections suggest an increasing risk of drought and heat, which can affect water supply and demand, and will challenge the future of agricultural production in the Southwest. Also, as groundwater in the Southwest is highly regulated, producers may not be able to readily rely on groundwater to meet increased demand. Climate exposure of five economically-important crops—alfalfa, cotton, pecans, pistachios, and processing tomatoes—was analyzed over twelve regulated groundwater basins by quantifying changes in a suite of both crop-specific and non-specific agroclimatic indicators between contemporary (1981–2020) and future (2045–2074, SSP2-4.5) climates. Generally, groundwater basins that are currently the most exposed to impactful climate conditions remain so under future climate. The crops with the greatest increase in exposure to their respective crop-specific indicators are cotton, which may be impacted by a ~180% increase in exposure to extreme heat days above 38 °C, and processing tomatoes, which may see a ~158% increase in exposure to high temperatures and reduced diurnal temperature range during flowering. These results improve understanding of the potential change in exposure to agroclimatic indicators, including crop-specific indicators, at the scale of regulated groundwater basins. This understanding provides useful information for the long-term implications of climate change on agriculture and agricultural water, and can inform adaptation efforts for coupled agricultural and water security in groundwater-dependent regions. These results may also be useful for assessing the adaptive potential of water conservation actions—some of which are outlined herein—or the suitability of other adaptation responses to the challenges that climate change will pose to agriculture. Full article

The application of reflective vegetation indices is crucial for advancing precision agriculture, particularly in monitoring crop growth and development. Among these indices, the Normalized Difference Vegetation Index (NDVI) is the most widely used due to its reliability in capturing vegetation dynamics. This study focuses on the applicability and temporal dynamics of the NDVI in monitoring winter wheat (Triticum aestivum) under the specific climatic conditions of Southern Dobrudja, Bulgaria. Using a Survey3W Camera RGN mounted on DJI unmanned aerial vehicles (Phantom 4 Pro and Mavic 2 Pro) at an altitude of 100 m, NDVI data were collected over a five-year period (2019–2024). Results reveal distinct NDVI trends, with maximum values reaching 0.56 during favorable conditions, and sharp declines during late spring frosts or drought periods. These NDVI variations correlate strongly with environmental factors, including precipitation and temperature fluctuations. For instance, during the 2019–2020 season, the NDVI decreased by 30% due to severe drought and high winter temperatures. In this study, vegetation indices, including the Soil-Adjusted Vegetation Index (SAVI) and the Enhanced Vegetation Index (EVI), were utilized to compare the results with the NDVI. The high-resolution UAV methodology demonstrated in this study proves highly effective for breeding and agronomic applications, offering precise data for optimizing wheat cultivation under variable agro-climatic conditions. These findings highlight the NDVI’s potential to enhance crop monitoring, yield prediction, and stress response management in winter wheat. Full article

Assessing runoff under changing land use/land cover (LULC) and climatic conditions is crucial for achieving effective and sustainable water resource management on a global scale. In this study, the focus was on runoff predictions across three diverse Indian watersheds—Wunna, Bharathapuzha, and Mahanadi—spanning distinct agro-climatic zones to capture varying climatic and hydrological complexities. The soil and water assessment (SWAT) tool was used to simulate future runoff influenced by LULC and climate change and to explore the related sustainability implications, including related challenges and proposing countermeasures through a sustainable action plan (SAP). The methodology integrated high-resolution satellite imagery, the cellular automata (CA)–Markov model for projecting LULC changes, and downscaled climate data under representative concentration pathways (RCPs) 4.5 and 8.5, representing moderate and extreme climate scenarios, respectively. SWAT model calibration and validation demonstrated reliable predictive accuracy, with the coefficient of determination values (R²) > 0.50 confirming the reliability of the SWAT model in simulating hydrological processes. The results indicated significant increases in surface runoff due to urbanization, reaching >1000 mm, 600 mm, and 400 mm in southern Bharathapuzha, southeastern Wunna, and northwestern Mahanadi, respectively, especially by 2040 under RCP 8.5. These findings indicate that water quality, agricultural productivity, and urban infrastructure may be threatened. The proposed SAP includes nature-based solutions, like wetland restoration, and climate-resilient strategies to mitigate adverse effects and partially achieve sustainable development goals (SDGs) related to clean water and climate action. This research provides a robust framework for sustainable watershed management in similar regions worldwide. Full article

Agroclimatic indicators help convey information about climate variability and change in terms that are meaningful to the agricultural sector. This study evaluated climate projections for Angola, particularly for provinces with more significant agricultural potential. To this end, 15 predefined agroclimatic indicators in 2041–2070 and 2071–2099, under the anthropogenic forcing scenarios RCP4.5 and RCP8.5, were compared with the historical period 1981–2010 as a baseline. We selected two climate scenarios and two temporal horizons to obtain a comprehensive view of the potential impacts of climate change in Angola. Data were extracted within the geographic window of longitudes 10–24° E and latitudes 4–18° S and from five general circulation models (GCM), namely MIROC-ESM-CHEM, HadGEM2-ES, IPSL-CM5A-LR, GFDL-ESM2M, and NorESM1-M. The set averages of agroclimatic indicators and their differences between historical and future periods are discussed in relation to the likely implications for agriculture in Angola. The results show significant increases in average daily maximum (2–3 °C) and minimum (2–3 °C) temperatures in Angola. For the future, a generally significant reduction in precipitation (and its associated indicators) is expected in all areas of Angola, with the southwest region (Namibe and Huíla) recording the most pronounced decrease, up to 300 mm. At the same time, the maximum number of consecutive dry days will increase across the country, especially in the Northeast. A widespread increase in temperatures is expected, leading to hot and dry conditions in Angola that could lead to more frequent, intense, and prolonged extreme events, such as tropical nights, the maximum number of consecutive summer days, hot and rainy days, and warm period duration index periods. These changes can seriously affect agriculture, water resources, and ecosystems in Angola, thereby requiring adaptation strategies to reduce risks and adverse effects while ensuring the sustainability of the country’s natural resources and guaranteeing its food security. Full article