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Understanding the change dynamics of land use and land cover (LULC) is critical for efficient ecological management modification and sustainable land-use planning. This work aimed to identify, simulate, and predict historical and future LULC changes in the Sohag Governorate, Egypt, as an arid region. In the present study, the detection of historical LULC change dynamics for time series 1984–2002, 2002–2013, and 2013–2022 was performed, as well as CA-Markov hybrid model was employed to project the future LULC trends for 2030, 2040, and 2050. Four Landsat images acquired by different sensors were used as spatial–temporal data sources for the study region, including TM for 1984, ETM+ for 2002, and OLI for 2013 and 2022. Furthermore, a supervised classification technique was implemented in the image classification process. All remote sensing data was processed and modeled using IDRISI 7.02 software. Four main LULC categories were recognized in the study region: urban areas, cultivated lands, desert lands, and water bodies. The precision of LULC categorization analysis was high, with Kappa coefficients above 0.7 and overall accuracy above 87.5% for all classifications. The results obtained from estimating LULC change in the period from 1984 to 2022 indicated that built-up areas expanded to cover 12.5% of the study area in 2022 instead of 5.5% in 1984. This urban sprawl occurred at the cost of reducing old farmlands in old towns and villages and building new settlements on bare lands. Furthermore, cultivated lands increased from 45.5% of the total area in 1984 to 60.7% in 2022 due to ongoing soil reclamation projects in desert areas outside the Nile Valley. Moreover, between 1984 and 2022, desert lands lost around half of their area, while water bodies gained a very slight increase. According to the simulation and projection of the future LULC trends for 2030, 2040, and 2050, similar trends to historical LULC changes were detected. These trends are represented by decreasing desert lands and increasing urban and cultivated newly reclaimed areas. Concerning CA-Markov model validation, Kappa indices ranged across actual and simulated maps from 0.84 to 0.93, suggesting that this model was reasonably excellent at projecting future LULC trends. Therefore, using the CA-Markov hybrid model as a prediction and modeling approach for future LULC trends provides a good vision for monitoring and reducing the negative impacts of LULC changes, supporting land use policy-makers, and developing land management.

Urban Green Spaces (UGS) are critical for fostering ecological sustainability and social equity in rapidly urbanizing cities like Islamabad, Pakistan. This study aimed to comprehensively map and classify Islamabad’s UGS, identify spatial disparities, and evaluate their ecological, recreational, and social functions. The research also proposed sustainable strategies for managing UGS to address urban challenges, including climate adaptation, biodiversity loss, and social inequity. The study developed a detailed spatial map of Islamabad’s UGS using Geographic Information Systems (GIS) and high-resolution satellite imagery. Seven typologies were categorized and analyzed, including parks, playgrounds, institutional green spaces, and waterways. Field surveys and random sampling validated the thematic maps, achieving an accuracy rate of 95.68% based on statistical metrics like Kappa coefficients. The study revealed significant disparities in UGS distribution. Wealthier zones had larger, well-maintained green spaces, while denser areas lacked accessible and functional UGS. Recreational spaces, institutional greenery, and waterways played a vital role in enhancing biodiversity, urban aesthetics, and community well-being, though many remain underutilized or degraded. Institutional green spaces contributed significantly to urban sustainability, comprising 17.05 km² of the total UGS area. The research highlights UGS as an essential Nature-Based Solution (NBS) for addressing urban challenges like heat islands, stormwater management, and social inequalities. The findings serve as a model for other rapidly urbanizing cities seeking ecological and social balance.

Essential oils are promising, safe, and eco-friendly alternatives to chemical fungicides. This study aimed to develop an effective biological control agent using Cinnamomum cassia essential oil (CCEO) as potential fungicidal agent against Saccharomyces cerevisiae and Acremonium sp, both isolated from natural orange juice. The yield, chemical composition and antifungal activity of CCEO were evaluated. The essential oil was extracted via hydro-distillation, and its composition was analyzed using gas chromatography-mass spectrometry (GC-MS). The antifungal activity was assessed using the disk diffusion agar method. Minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) were determined using microdilution methods. The extraction yield was 2.8%. (E)-cinnamaldehyde was identified as the major compound (37.72%). Inhibition zones ranged from 51 mm to 80 mm against Saccharomyces cerevisiae and from 75 mm to 90 mm against Acremonium sp. Equal MIC and MFC values were recorded for both fungal strains: MIC = MFC = 6.25% against Saccharomyces cerevisiae and MIC = MFC = 3.125% against Acremonium sp. These findings demonstrate for the first time that CCEO could be a promising antifungal agent against the two primary fungal contaminants of fruit products, Saccharomyces cerevisiae and Acremonium sp.

The thrust of the study was to determine the chemical composition of the essential oils extracted from Thymus pallescens de Noé and Cymbogon citratus Stapf. as well as to evaluate their efficacy in controlling Sitophilus zeamais Motschulsky and Tribolium castaneum (Herbst) in either single or combined populations. Carvacrol (56.04%) and geraniol (20.86%) were identified as the major constituents of T. pallescens and C. citratus respectively. The tested essential oils showed pronounced insecticidal activity against the pest species in relation with the applied doses. T. pallescens EO had the highest efficacy and S. zeamais was found to be more susceptible to both individual and combined treatments. With reference to the contact and fumigation assessments, T. pallescens EO effectuated corrected mortality rates ranging from 42.5–100% to 25–100% in S. zeamais with corresponding lethal concentration (LC 50 ) values of 17.7 µl/ml and 15µL/L air respectively. Whereas, the T. pallescens EO exhibited corrected mortality rates of 42.5–100% and 20–100% with corresponding LC 50 values of 18.1 µl/ml and 15.5 µL/L air against T. castaneum in contact and fumigation assessments, respectively. The corrected mortality rates increased for both insect species when using combination treatments, with significant increases in the LC 50 values, ranging from 8.59 to 49.9% for both pest species. Analysis of energy biomarkers in the treated insects indicate significantly increased protein and carbohydrate contents and decreased lipids levels. The study therefore demonstrated the bio-insecticidal toxicity of the EOs from T. pallescens and C. citratus against two important maize post-harvest pests, concurrently revealing significant positive and negative insecticidal activity gradients in relation to single or combined populations.

The study investigated the antifungal and phytochemical properties of three forest plants ( Eucalyptus globulus, Pistacia lentiscus, and Juniperus phoenicea ) against apple diseases caused by Colletotrichum gloeosporioides and Alternaria alternata . The determination of the total polyphenol and flavonoid contents in the three aqueous extracts of studied plants showed that E. globulus exhibited the highest contents than those of P. lentiscus and J. phoenicea . Furthermore, the three studied extracts showed very appreciable antioxidant activity with decreasing order: E. globulus , P. lentiscus , and J. phoenicea . The phytochemical analysis showed different common phenolic acids in the three studied plants namely: quinic acid, gallic acid, chlorogenic acid, and caffeoylquinic acid as well as other flavonoids mainly quercetin and catechin. The results of the current study demonstrated that the fungistatic activity of E. globulus EO (4 and 2 µl/ml) seemed to be the most effective under laboratory conditions with an inhibition zone diameter above 16 mm. However, the poisoned food technique indicated that the aqueous extract (80%) and the essential oil (4 µl/ml) of E. globulus exhibited the highest mycelial growth (> 67%) and spore germination (> 99%) inhibition. Preventive treatments with essential oils (4 µl/ml) and aqueous extracts (80%) applied to apple fruits inoculated with A. alternata and C. gloeosporioides resulted in the lowest lesion diameter (< 6.80 mm) and disease severity index (< 15%) and the most favorable inhibitory growth (> 85.45%) and protective potentials (> 84.92%). The results suggest that E. globulus has a brilliant future in the management of anthracnose and Alternaria rot of apple and provide a basis for further studies on its effects under field conditions.

Urban Heat Islands (UHIs) pose a significant environmental challenge in rapidly urbanizing regions, influencing climate resilience, energy consumption, and public health. This study presents a comprehensive spatiotemporal analysis of UHI dynamics in Rawalpindi, Pakistan. Time-series analysis over 30 years (1990–2020) using Landsat satellite data processed through Google Earth Engine (GEE). Unlike previous studies, this research integrates a hybrid methodology. Random Forest classification for high-precision Land Use Land Cover (LULC) mapping correlates with the Statistical Mono-Window algorithm for accurate Land Surface Temperature (LST) estimation. The findings reveal a 22.2% increase in built-up areas. That impacts the past three decades, correlating with a 3.04 °C rise in LST, at an annual increment of 0.12 °C. This study applies the Cellular Automata-Artificial Neural Network (CA-ANN) model to project future UHI intensification in Rawalpindi. Results aim to forecast a 13.8% increase in built-up areas by 2030, which is expected to exacerbate thermal stress and energy demand. According to the results, the built-up area has grown highly erratic, mainly at the expense of vegetated land. A statistically significant correlation (r = 0.43) between LST and urban expansion underscores the urgency of adopting targeted mitigation strategies. Our research has some limitations; one of the important ones was that we could not assess multiple potential socio-economic drivers of urban growth because of a scarcity of spatial data. The results highlight the necessity for sustainable urban planning approaches, including integrating vegetation and heat-mitigating urban infrastructure to reduce thermal stress and enhance climate resilience.

Wheat is considered to be a strategic crop for achieving food security. Wherefore, one of the current objectives of today’s agriculture is to ensure a consistent and sustainable yield of this particular crop while mitigating its environmental footprint. However, along with the genetic potential of varieties, agricultural practices play a key role in ensuring a high and stable yield of wheat. Under changing climatic conditions, new eco-friendly practices were adopted in the wheat farming system in recent decades. In this review, a large number of peer-reviewed articles have been screened during the last 15 years to evaluate the potential of some environmentally friendly agricultural practices such as tillage system, biological crop protection, crop rotation, intercropping systems, and the integration of resistant varieties in achieving a high and stable wheat yield. The present investigation unveiled that embracing eco-friendly agricultural methods in the wheat farming system holds the potential to engender high and sustainable wheat yields, contingent upon a normative strategy that comprehensively addresses multiple factors. These include the intrinsic attributes of the grown wheat cultivars, plant nutritional parameters, soil agrochemical characteristics, and specific climatic conditions. Further in-depth investigations under field conditions are necessary to help in the discernment of appropriate environmentally agricultural techniques that can efficaciously optimize the yield potential of the different cultivated varieties.

Soil erosion is a major environmental challenge in Mediterranean regions, where climatic variability, steep slopes, and human activities accelerate land degradation. In the north-central region of Algeria, the Mitidja Plain faces increasing erosion pressure, threatening biodiversity, agricultural productivity, and long-term soil sustainability. This study aims to assess soil erosion risk by integrating the Revised Universal Soil Loss Equation (RUSLE), the Analytical Hierarchy Process (AHP), and Geographic Information System (GIS) techniques within a Cloud-Based Geospatial (CBG) framework using the Google Earth Engine (GEE) platform. High-resolution datasets on rainfall, topography, soil properties, and land cover were processed in GEE to derive five RUSLE factors: rainfall runoff erosivity (R E ), soil erodibility (K S ), slope length steepness (L S ), cropping management (C M ), and management practices (P C ). The analysis revealed that 41% of the Mitidja Plain is at severe erosion risk, with an average soil loss of 88.72 t ha⁻¹ yr⁻¹ and a maximum of 161.13 t ha⁻¹ yr⁻¹. Erosion hotspots correspond to areas where slopes exceed 22°, vegetation cover is sparse, and rainfall intensity is high. The AHP-weighted integration achieved strong predictive accuracy (AUC = 0.87), identifying slope characteristics as the most influential factor (weight = 0.292). Forested areas reduced erosion risk in 30% of the region, while unprotected mountainous zones covering 22% of the study area require urgent intervention. These findings demonstrate the effectiveness of CBG-enhanced modeling for mapping priority conservation areas. Recommendations include terracing, check dams, vegetation restoration, and adaptive agricultural practices to reduce soil loss, particularly in agricultural lands with moderate to high vulnerability (48% of the plain). The methodology provides a replicable framework for other Mediterranean regions facing similar erosion pressures, offering robust spatial data to guide soil management and conservation planning.

Developing high-yielding and resilient maize hybrids is essential to ensure its sustainable production with the ongoing challenges of considerable shifts in global climate. This study aimed to explore genetic diversity among exotic and local maize inbred lines, evaluate their combining ability, understand the genetic mechanisms influencing ear characteristics and grain yield, and identify superior hybrids suited for timely and late sowing conditions. Seven local and exotic maize inbred lines were genotyped using SSR (Simple Sequence Repeat) markers to assess their genetic diversity. These diverse lines were utilized to develop 21 F1 hybrids using a diallel mating design. These hybrids, alongside a high-yielding commercial check (SC-10), were evaluated under field conditions across two growing seasons under timely and late sowing conditions. The results showed that sowing date, assessed hybrids, and their interaction significantly influenced all measured agronomic traits. Notably, late sowing reduced plant height, ear characteristics, and, ultimately, grain yield. Several hybrids, particularly L101 × L103, L101 × L105, L104 × L105, and L104 × L107 under timely sowing, and L101 × L105 and L104 × L107 under late sowing, surpassed the agronomic performance of check commercial hybrid. Inbred lines L101 and L103 emerged as superior combiners for ear traits and yield, while line L106 showed promise for breeding shorter-stature plants. Hybrid combinations L101 × L105, L104 × L107, and L106 × L107 were identified as specific good combiners for grain yield and related traits under both sowing conditions, indicating their potential for commercial development. Strong positive associations were observed between grain yield and certain agronomic traits highlighting their utility for indirect selection in early breeding generations.

The issue of soil contamination is one of the most important subjects that interests decision-makers all over the world. It is also related to soil fertility and food security. The soils adjacent to the drains in Egypt suffer from increasing concentration of heavy metals, which negatively affects soil and crop quality. Precise spatial distribution maps of heavy metals are an essential key to mitigating the negative impacts on the ecosystem. Sixty random soil locations adjacent to the El-Moheet drainage were chosen on the west side of the Nile River, El-Minia governorate, Egypt. Six heavy metals (Cr, Co, Cu, Cd, Pb, and Zn) were selected to generate their spatial pattern maps using ordinary Kriging (OK). Principal component analysis (PCA) and contamination factors (CF) were applied to evaluate soil contamination levels in the study area. The results showed that the Gaussiang model was a high fit for soil pH, and Pb, the Exponential model was fit for EC, Stable model was fit for OC, Co, Cu, and Cd. In addition, the Spherical model was fit for both Cr and Zn. The MSE values were close to zero in all selected metals, while the values of RMSSE were close to one. The results showed that the soil heavy metal concentrations were grouped into two clusters using PCA. Furthermore, three contamination degrees were obtained (moderate, considerable, and very high), with about 70.7% of the study area characterized by considerable heavy metals concentration, where the average heavy metals concentration (mg kg−1) in this degree was 91.23 ± 19.5, 29.44 ± 5.2, 53.83 ± 10.2, 1.12 ± 0.3, 36.04 ± 18.0, and 101.29 ± 35 for Cr, Co, Cu, Cd, Pb, and Zn, respectively. The current results reflect the mismanagement and use of low-quality water for irrigation in the study area, which increased the toxic element concentration in soil surface layers. In the end, the results of spatial distribution maps of pollutants and their degrees could support decision-makers as a basis for developing appropriate mitigation plans for heavy metals.