Search Results (364)

Over the past years, increasing attention has been drawn to the adverse effects of agricultural pesticide use on pollinators, with honeybees being especially vulnerable. The aim of this study was to evaluate the levels of residues detectable and/or quantifiable of neonicotinoid pesticides and other pesticides in biological materials (bees, bee brood, etc.) and beehive products (honey, pollen, etc.) applied as seed dressings in rapeseed and sunflower plants in two growing seasons (2020–2021) in fields located in three agro-climatic regions in Romania. The study involved the comparative sampling of hive products (honey, pollen, adult bees, and brood) from experimental and control apiaries, followed by pesticide residue analysis in an accredited laboratory (Primoris) using validated chromatographic techniques (LC-MS/MS and GC-MS). Toxicological analyses of 96 samples, including bees, bee brood, honey, and pollen, confirmed the presence of residues in 46 samples, including 10 bee samples, 10 bee brood samples, 18 honey samples, and 8 pollen bread samples. The mean pesticide residue concentrations detected in hive products were 0.032 mg/kg in honey, 0.061 mg/kg in pollen, 0.167 mg/kg in bees, and 0.371 mg/kg in bee brood. The results highlight the exposure of honeybee colonies to multiple sources of pesticide residue contamination, under conditions where legal recommendations for the controlled application of agricultural treatments are not followed. The study provides relevant evidence for strengthening the risk assessment framework and underscores the need for adopting stricter monitoring and regulatory measures to ensure the protection of honeybee colony health. Full article

Quinoa (Chenopodium quinoa Willd.) has emerged as a climate-resilient, nutrient-dense crop with increasing global popularity because of its adaptability under current environmental variations. To address the limited understanding of quinoa’s genotypic performance under local agro-environmental conditions, this study hypothesized that elite genotypes would exhibit significant variation in agronomic, physiological, and biochemical traits. This study aimed to elucidate genotypic variability among 23 elite quinoa lines under field conditions in Faisalabad, Pakistan, using a multidimensional framework that integrated phenological, physiological, biochemical, root developmental, and yield-related attributes. The results revealed that significant variation was observed across all measured parameters, highlighting the diverse adaptive strategies and functional capacities among the tested genotypes. More specifically, genotypes Q4, Q11, Q15, and Q126 demonstrated superior agronomic potential and canopy-level physiological efficiencies, including high biomass accumulation, low infrared canopy temperatures and sustained NDVI values. Moreover, Q9 and Q52 showed enhanced accumulation of antioxidant compounds such as phenolics and anthocyanins, suggesting potential for functional food applications and breeding program for improving these traits in high-yielding varieties. Furthermore, root trait analysis revealed Q15, Q24, and Q82 with well-developed root systems, suggesting efficient resource acquisition and sufficient support for above-ground plant parts. Moreover, principal component analysis further clarified genotype clustering based on trait synergistic effects. These findings support the use of multidimensional phenotyping to identify ideotypes with high yield potential, physiological efficiency and nutritional value. The study provides a foundational basis for quinoa improvement programs targeting climate adaptability and quality enhancement. Full article

The review summarizes the historical and current research on perennial grain breeding in Russia within the context of growing global interest in perennial crops. N.V. Tsitsin’s pioneering work in the 1930s produced the first wheat–wheatgrass amphiploids, which demonstrated the capacity to regrow after harvest and survive for 2–3 years. Subsequent research at the Main Botanical Garden in Moscow focused on characterizing Tsitsin’s material, selecting superior germplasm, and expanding genetic diversity through new cycles of hybridization and selection. This work led to the development of a new crop species, Trititrigia, and the release of cultivar ‘Pamyati Lyubimovoy’ in 2020, designed for dual-purpose production of high-quality grain and green biomass. Intermediate wheatgrass (Thinopyrum intermedium) is native to Russia, where several forage cultivars have been released and cultivated. Two large-grain cultivars (Sova and Filin) were developed from populations provided by the Land Institute and are now grown by farmers. Perennial rye was developed through interspecific crosses between Secale cereale and S. montanum, demonstrating persistence for 2–3 years with high biomass production and grain yields of 1.5–2.0 t/ha. Hybridization between Sorghum bicolor and S. halepense resulted in two released cultivars of perennial sorghum used primarily for forage production under arid conditions. Russia’s agroclimatic diversity in agricultural production systems provides significant opportunities for perennial crop development. The broader scientific and practical implications of perennial crops in Russia extend to climate-resilient, sustainable agriculture and international cooperation in this emerging field. Full article

According to Victor Ernest Shelford’s ‘Law of Tolerance,’ organisms within ecosystems thrive optimally when environmental conditions are favorable. Applying this principle to ecosystems and agro-ecosystems facing water scarcity or environmental challenges can significantly enhance their productivity. In these ecosystems, phytocenosis adjusts its conditions by utilizing water with varying salinity levels. Moreover, establishing optimal drinking water conditions for human populations within an ecosystem can help mitigate future negative succession processes. The purpose of this study is to evaluate the quality of two distinct water sources in the Amudarya district of the Republic of Karakalpakstan, Uzbekistan: collector-drainage water and groundwater at depths of 10 to 25 m. This research is highly relevant in the context of climate change, as improper management of water salinity, particularly in collector-drainage water, may exacerbate soil salinization and degrade drinking water quality. The primary methodology of this study is as follows: The Food and Agriculture Organization of the United Nations (FAO) standard for collector-drainage water is applied, and the water quality index is assessed using the CCME WQI model. The Canadian Council of Ministers of the Environment (CCME) model is adapted to assess groundwater quality using Uzbekistan’s national drinking water quality standards. The results of two years of collected data, i.e., 2021 and 2023, show that the water quality index of collector-drainage water indicates that it has limited potential for use as secondary water for the irrigation of sensitive crops and has been classified as ‘Poor’. As a result, salinity increased by 8.33% by 2023. In contrast, groundwater quality was rated as ‘Fair’ in 2021, showing a slight deterioration by 2023. Moreover, a comparative analysis of CCME WQI values for collector-drainage and groundwater in the region, in conjunction with findings from Ethiopia, India, Iraq, and Turkey, indicates a consistent decline in water quality, primarily due to agriculture and various other anthropogenic pollution sources, underscoring the critical need for sustainable water resource management. This study highlights the need to use organic fertilizers in agriculture to protect drinking water quality, improve crop yields, and promote soil health, while reducing reliance on chemical inputs. Furthermore, adopting WQI models under changing climatic conditions can improve agricultural productivity, enhance groundwater quality, and provide better environmental monitoring systems. Full article

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

Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. In this study, VR-N technology was applied to durum wheat in two small-scale commercial fields (3–4 ha each) located in distinct agro-climatic zones of Thessaly, central Greece. A real-time VR-N application algorithm was used to calculate N rates based on easily obtainable near-real-time data from unmanned aerial vehicle (UAV) imagery, tailored to the crop’s actual needs. VR-N implementation was carried out using conventional fertilizer spreaders equipped to read prescription maps. Results showed that VR-N reduced N input by up to 49.6% compared to the conventional uniform-rate N (UR-N) application, with no significant impact on wheat yield or grain quality. In one of the fields, the improved gain of VR-N when compared to UR-N was 7.2%, corresponding to an economic gain of EUR 163.8 ha⁻¹, while in the second field—where growing conditions were less favorable—no considerable VR-N economic gain was observed. Environmental benefits were also notable. The carbon footprint (CF) of the wheat crop was reduced by 6.4% to 22.0%, and residual soil nitrate (NO₃⁻) levels at harvest were 13.6% to 36.1% lower in VR-N zones compared to UR-N zones. These findings suggest a decreased risk of NO₃⁻ leaching and ground water contamination. Overall, the study supports the viability of VR-N as a practical and scalable approach to improve N use efficiency (NUE) and reduce the environmental impact of wheat cultivation which could be readily adopted by farmers. 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

Utilizing environmentally friendly techniques for pathogen control in agriculture is a sustainable and eco-friendly approach to managing crop diseases. These techniques leverage the natural environment and ecosystem dynamics to reduce pathogen pressure, minimize the use of chemical inputs, and promote long-term agricultural productivity. Key strategies include crop rotation, intercropping, and maintaining biodiversity, all of which disrupt pathogen life cycles and enhance soil health. Biological control, such as introducing natural antagonists like beneficial fungi or bacteria, suppresses pathogen populations while promoting plant resilience. Additionally, practices such as mulching, soil solarization, and water management optimize environmental conditions to limit the development and spread of pathogens. These techniques also contribute to integrated pest management by providing sustainable, cost-effective solutions that reduce chemical dependency and mitigate climate change and other environmental impacts. This review discusses the importance of utilizing environmentally friendly techniques, highlighting their advantages, practical challenges, and limitations in different agro-ecological settings, and their role in advancing sustainable agriculture. 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

The seasonal and interannual irregularity of temperature and precipitation is a feature of the Mediterranean climate that is intensified by climate change and constitutes a relevant driver of water and soil degradation. This study was developed during three years in a hydro-agricultural area of the Alqueva irrigation system (Portugal) with Mediterranean climate conditions. The sampling campaigns included collecting water samples from eight irrigation hydrants, analyzed four times yearly. The analysis incorporated meteorological data and indices (precipitation, temperature, and drought conditions) alongside chemical parameters, using multivariate statistics (factor analysis and cluster analysis) to identify key water quality drivers. Additionally, machine learning models (Random Forest regression and Gradient Boosting machine) were employed to predict electrical conductivity (ECw), sodium adsorption ratio (SAR), and pH based on chemical and climatic variables. Water quality evaluation showed a prevalence of a slight to moderate soil sodification risk. The factor analysis outcome was a three-factor model related to salinity, sodicity, and climate. The cluster analysis revealed a grouping pattern led by year and followed by stage, pointing to the influence of inter-annual climate irregularity. Variations in water quality from the reservoirs to the distribution network were not substantial. The Random Forest algorithm showed superior predictive accuracy, particularly for ECw and SAR, confirming its potential for the reliable forecasting of irrigation water quality. This research emphasizes the importance of integrating time-sensitive monitoring with data-driven predictions of water quality to support sustainable water resources management in agriculture. This integrated approach offers a promising framework for early warning and informed decision-making in the context of increasing drought vulnerability across Mediterranean agro-environments. 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

Rural settlements in agro-pastoral ecotones reflect the complex interplay between natural constraints and human land use, particularly in ecologically sensitive and climatically transitional regions. This study investigated the agro-pastoral ecotone of eastern Inner Mongolia, a representative region characterized by environmental heterogeneity and competing land use functions. Landscape pattern indices, ordinary least squares (OLS) regression, and geographically weighted regression (GWR) were employed to analyze settlement morphology and its environmental determinants. The results reveal a distinct east–west spatial gradient: settlements are larger and more concentrated in low-elevation plains with favorable hydrothermal conditions, whereas those in mountainous and pastoral areas are smaller, sparser, and more fragmented. OLS regression revealed a strong positive correlation between arable land and settlement density (r > 0.8), whereas elevation and slope were significantly negatively correlated. GWR results further highlight spatial non-stationarity in the influence of key environmental factors. Average annual temperature generally shows a positive influence on settlement density, particularly in the central and eastern agricultural areas. In contrast, forest cover is predominantly negative, especially in the Greater Khingan Mountains. Proximity to water resources consistently enhances settlement density, although the magnitude of this effect varies across regions. Based on spatial characteristics and land use structure, rural settlements were categorized into four types: alpine pastoral, agro-pastoral transitional, river valley agricultural, and forest ecological. This study provides empirical evidence that natural factors (topography, climate, and hydrology) and land use variables (farmland, pasture, and woodland) collectively shape rural settlement patterns in transitional landscapes. The findings offer methodological and practical insights for targeted land management and sustainable rural development in agro-pastoral regions under ecological and socioeconomic pressures. Full article

An exploration and understanding of cultivar adaptability to specific environmental conditions are critical in rice breeding. This study aimed to compare the agro-morphological data of 36 japonica rice cultivars (Oryza sativa L.) from Chinese rice accessions grown under two different environments (Fengyang and Hexian) and to identify important genes associated with key traits in the cultivars. Higher significant differences were observed between Fengyang and Hexian in traits like, grain width, grain length, yield per plot, plant height, and tiller number with cultivars grown in Hexian having the greatest values. This revealed that the environment in Hexian favored these traits, and most cultivars performed better in Hexian than in Fengyang. Correlation analysis also showed strong positive correlations between tiller number and yield per plot in both environments, indicating the influence of tiller number on rice yield potential. The PCR analysis showed the amplification of DEP1, Ghd7, Wx, Chalk5, COLD1, DST, Xa13, and Bph6 in most japonica cultivars, indicating presence of these genes in the cultivars. This study suggests that differences in agronomic performance between the cultivars grown in Fengyang and Hexian might be caused by differences in environmental conditions. This finding could be valuable for future breeding of high-yielding and climate-resilient cultivars. Full article

Flax cultivation is influenced by geographical conditions and soil properties, affecting yield and fiber quality. This study examines the performance of two fiber flax varieties, Artemida and Hermes, in 2021–2023 in central–eastern Poland’s agroclimatic and soil conditions using a value chain approach. Field trials were conducted in soils of varying fertility under a continental climate, employing a randomized block design with four replications. Flax straw underwent dew-retting, and long fibers were extracted through laboratory scutching. Results showed significant differences between the varieties. Artemida achieved higher straw yields, particularly in moderately fertile soils, while Hermes produced a higher proportion of long fibers and adapted better to less-fertile soils. Hermes fibers were thinner and more delicate, whereas Artemida fibers were coarser and stronger. The average straw yield of the Artemida variety was higher by 1.5 t ha⁻¹ than that of the Hermes variety. The yield and quality of fiber were determined by soil fertility and climate, and the genotype–environment interaction was of the greatest importance. These findings provide valuable insights for farmers and stakeholders in selecting suitable flax varieties for different soil and climatic conditions in central–eastern Poland. The value chain approach also supports optimizing cultivation practices and improving the economic sustainability of flax production. Full article