Assessment of Potentially Dangerous Glacial Lake Outburst Flood in Panjshir , Afghanistan Using RS and GIS

This study provides the first systematic assessment of glacial lake hazards in Panjshir Province, Afghanistan, where rapid glacier retreat has facilitated the formation and expansion of numerous glacial lakes and intensified downstream risk. Using Landsat and Sentinel-2 imagery, a 5-m DEM, and GIS-based morphometric extraction, 135 glacial lakes were identified and evaluated through a composite Glacial Lake Outburst Flood Risk Index (GLOFRI). Six key parameters—lake area, outlet slope, glacier proximity, dam type, cascade configuration, and elevation—were used to calculate normalized hazard scores. GLOFRI values ranged from 0.0162 to 0.575 and were classified by the Equal Interval method into three hazard levels. Results show that four lakes (2.96%) fall within the high-risk category, primarily characterized by relatively large surface areas, unstable moraine dams, steep outlet slopes, and direct proximity to active glaciers. Fifty-nine lakes (43.70%) were classified as medium-risk and seventy-two (53.33%) as low-risk. Spatial analysis confirms that high-risk lakes are clustered immediately downstream of glacier fronts and connected to steep, confined valleys, representing the most immediate threat to communities, infrastructure, and irrigated land in Panjshir. The resulting prioritized inventory of potentially dangerous glacial lakes provides an essential baseline for monitoring, early-warning development, and GLOF-focused disaster risk reduction, and it offers a transferable framework for glacial lake hazard assessment in other data-scarce mountain regions

Genetic Analysis and Variability Assessment of Bambara Groundnut (Vigna subterranea L.) Lines Based on Vegetative Traits

Genetic diversity is essential to a plant species' ability to survive, adapt, and thrive in a constantly shifting environment. It also forms the basis for crop development's efficient selection process. Therefore, breeding programs that present a high level of genetic variability in germplasm collections benefit significantly from an understanding of the genetic processes responsible for the inheritance of this trait. Therefore, this research aims to estimate the genetic analysis and variability of Bambara groundnut based on vegetative components using multivariate analyses. A randomized complete block design, including three replications, was utilized to evaluate five genotypes of Bambara groundnuts. The seeds were divided into three groups: large, medium, and small seed sizes. Statistical analysis was conducted in SAS version 9.4 to estimate ten vegetative characters' variance components and heritability. Most vegetative variables in the current study showed significant variations between the five genotypes, fifteen combinations of seed size and genotypes, seed size categories, and the interaction between genotype and seed size categories. The estimation of the genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) varied from 0 to 20.36%. Moreover, the high values of GCV (20.36%) and PCV (28.18%) resulted from the wide canopy trait, while moderate GCV and high PCV were registered from the number of petioles, number of leaves, number of branches, and dried biomass. The low GCV and high PCV were recorded for fresh biomass and high plant growth. More research should be conducted to enhance these Bambara genotypes in various environments

Assessing Rangeland Conditions and Sustainable Management Strategies in Bamyan, Afghanistan

Identifying effective solutions for rangeland-related challenges has become increasingly complex. Rangelands cover the majority of Bamyan province and serve as a vital source of meat and dairy production. Most farmers in the region are agro-pastoralists who depend heavily on rangelands as their primary asset, while intensive livestock farming systems remain uncommon. Given the ecological importance and the widespread degradation of natural resources, this study aimed to explore sustainable solutions to prevent further destruction of rangelands in Bamyan. Although previous research has largely focused on identifying causes of degradation, there has been limited attention to practical and localized solutions. This study employed a dual-method approach: (1) a review of library and online resources, and (2) fieldwork using observational tools, semi-structured interviews, and questionnaires based on a five-point Likert scale. Due to the absence of a complete list of farmers, simple random sampling was used to select 110 participants in 2023. The findings indicate that most Bamyan farmers are older, married, and illiterate, with primary agricultural outputs including potatoes, wheat, legumes, and fruits. Factor analysis revealed three key areas for intervention: (1) the role and support of government institutions, (2) the contribution of researchers, and (3) the internal involvement of local beneficiaries. Each of these factors encompasses a range of specific solution-oriented variables. The study highlights the importance of collaborative efforts and researcher engagement in the sustainable management of natural resources in Bamyan

Impact of Naphthalene Acetic Acid (NAA) on Growth, Quality and Yield of Eggplants

The present investigation was conducted to study the effect of Naphthalene Acetic Acid (NAA) on the growth, quality, and yield of eggplants. The research was conducted at the Agriculture Research farm of Kabul University from April to September 2024. A Randomized Complete Block Design (RCBD) with three replications and five treatments was employed: T1 (40 ppm), T2 (50 ppm), T3 (60 ppm), T4 (70 ppm), and T5 (Control). Data were collected on various growth parameters, fruit quality traits, and yield components. The recorded data were analyzed using the Statistical Tools for Agricultural Research (STAR) software. Results showed that NAA significantly enhanced eggplant growth, yield, and quality. T1 (40 ppm NAA) had the highest plant height (73.73 cm), branch number (9.20), leaf count (97), and leaf area (235.75 cm²), while the control group had the lowest values. T1 also produced the longest fruit (23.87 cm), largest diameter (4.21 cm), highest weight (186.67 g), and most fruits per plant (10.11). Similarly, T1 yielded the highest per plant (1.31 kg) and per hectare (41.9 metric tons), whereas the control recorded the lowest. Post-harvest results indicated no significant difference in shelf life. T1 had the best fruit appearance, texture, and flavor, with the highest overall acceptability (Like Moderately), while the control had the least (Neither Like nor Dislike).  The results can be concluded that spraying eggplants with 40 ppm Naphthalene Acetic Acid (NAA) at two stages (50% flowering and 20 days after the first application) can significantly improve their growth, quality, and yield. Farmers can spray this concentration of NAA to achieve vigorous growth, higher yield, and improved fruit quality

Energy Production Potential of Afghanistan: Balancing Renewable and Non-Renewable Energy for National Electrification and Energy Independence

The world is transitioning towards renewable energy sources to decarbonize the energy supply and meet the growing global energy demand. In 2023, the global investment in renewable energy reached $1.8 trillion. The progress towards renewable energy in Afghanistan is unclear, and its potential is not clearly identified when compared to non-renewable energy sources. Additionally, the country relies heavily on imported electricity, leading to numerous negative trade-offs in its energy policies and infrastructure. Therefore, this review aims to analyze Afghanistan's energy sector, encompassing demand, access, production, and development, as well as its renewable energy resources, performance, and sustainable impact on the nation. Findings show that Afghanistan has also made progress in small-scale solar projects, as the share of solar energy reached 9.64% in 2022. However, the per capita access to electricity is only 100 kWh, the lowest in the world, and only 20 percent of electricity comes from domestic resources, which are dominated by hydropower. Afghanistan's renewable energy resource potential, including solar, hydro, wind, geothermal, and biomass power, exceeds 300,000 MW. This potential not only meets domestic electricity demand but also could be exported to neighboring countries. Among all these resources, solar energy is the most efficient and cost-effective. Afghanistan is accelerating its renewable energy transition, and the country's authorities must put a strong focus on solar energy, hydropower, and natural gas power sources for a sustainable future and energy security, rather than coal-fired power sources. The information gathered will help policymakers focus on domestic renewable energy to enhance Afghanistan's energy independenc

Optimization of One-Dimensional Functions Using the Golden Section Search Method

This paper addresses the problem of one-dimensional function optimization using the Golden Section Search Method. The primary objective is to determine the point at which a given unimodal function achieves its minimum within a bounded interval. The importance of such methods lies in their applicability to various scientific and engineering problems where analytical solutions may be complex or intractable. The study aims to explore both the theoretical background and practical implementation of the method, supported by an illustrative example. The research method involves analytical derivation of conditions for extrema, an explanation of unimodality, and step-by-step application of the Golden Section technique. The expected result is an accurate approximation of the function's minimum point with a specified level of precision, demonstrating the effectiveness and efficiency of the method in minimizing unimodal functions without requiring derivative information

The Effects of Dietary Phenylalanine on Antioxidant Activity and Muscle Quality of Common Carp (Cyprinus carpio)

This study was conducted to investigate the effects of dietary phenylalanine on antioxidant capacity and muscle quality of common carp (Cyprinus carpio). The study also examined how various inclusion levels of dietary phenylalanine affect flesh quality and the expression of genes related to protein utilization and muscle development in common carp (Cyprinus carpio). Six isonitrogenous (37.92 ± 0.28% crude protein) and isolipidic (7.14 ± 0.15% crude lipid) diets were formulated with incremental levels of phenylalanine (0.38%, 0.94%, 1.32%, 1.75%, 2.23%, and 2.7%). A total of 1200 fish were divided into 24 cylindrical polypropylene tanks, with 50 individuals in each tank (initial individual weight of fish was 0.20 ± 0.07 g), and were run in four replicates in a completely randomized design for 8 weeks. Antioxidant capacity results showed that superoxide dismutase (SOD) activity was significantly higher in the 2.23% group (P<0.05), while malondialdehyde (MDA) content in the 2.23% Phe group was significantly lower than in other groups (P<0.05). Total antioxidant capacity (T-AOC) activity was significantly lower in the first two groups (0.38% and 0.94% Phe) compared to other groups (P<0.05). Dietary phenylalanine levels led to improvements in muscle texture and the expression of genes associated with protein utilization and muscle development

Effect of Climate Change on Agriculture in Nimruz Province and its Relationship with the Development of Rural Areas

Climate change poses a critical challenge to Afghanistan’s agriculture by reducing water resources, increasing temperatures, and altering rainfall patterns, all of which threaten food security and rural development. Despite the vulnerability of Afghanistan’s agricultural sector, there is limited empirical research assessing how climate change explicitly affects agriculture in Nimruz Province and its implications for rural development, leaving a critical gap in localized evidence. This study investigates the impact of climate change on agriculture in Nimruz Province. The statistical population included employees of the Department of Agriculture, the Agricultural High School, the Faculty of Agriculture at Nimruz Institute of Higher Education, and local farmers (N=100), from which 80 participants were selected using Cochran’s formula and convenience sampling. Data were collected through a 35-item questionnaire validated by agricultural experts, with a Cronbach’s alpha coefficient of 0.8 confirming strong reliability. As an applied, descriptive-analytical, and survey-based study, data were analyzed in SPSS using descriptive statistical methods. The results show that climate change has a considerable impact on agriculture in Nimruz Province, with the most potent effects observed in agricultural production and the weakest in cultivation methods. The study concludes that climate change has a significant impact on agriculture in the region, and it recommends implementing sustainable resource management, promoting modern agricultural technologies, and raising farmers’ awareness to mitigate adverse effects and enhance resilience

Systematic Review of Integrated Weed Management Strategies in Maize (Zea mays L.) Cultivation

Weeds are a major constraint in maize cultivation, causing global yield losses that average about 37%, with studies reporting a range of 20% to 80% depending on weed pressure and management. Effective weed control is therefore critical, particularly during the vulnerable period between 4 to 7 weeks after sowing. This systematic review aims to evaluate and synthesize current approaches to Integrated Weed Management (IWM) in maize cultivation to support farmers, researchers, and agricultural specialists in identifying more sustainable and effective weed control strategies. Although various weed control methods exist, comprehensive comparison of their effectiveness, sustainability, and long-term implications for soil health and productivity in maize-based systems remain limited in the literature. A systematic search was conducted across major scientific databases including Google Scholar, Web of Science, Scopus, and PubMed. Keywords such as “Integrated Weed Management,” “biological methods,” “chemical weed control,” “mechanical methods,” “cultural practices,” and “herbicide risks” were used to identify relevant studies. Articles were screened and selected based on relevance and methodological quality. The findings indicate that while chemical herbicides are widely used due to their efficiency and lower labor requirements, overreliance on them can lead to soil degradation, herbicide resistance, and environmental harm. In contrast, IWM approaches that integrate crop rotation, mechanical control, cover crops, bioherbicides, and precision agriculture techniques offer more sustainable outcomes. The review highlights the potential of herbicide-resistant maize cultivars and natural herbicides in reducing dependency on synthetic chemicals. Future research should focus on optimizing IWM combinations tailored to specific agroecological zones and improving the adoption of sustainable practices at the farm level

Modelling and Forecasting Wholesale Potato Prices in Northern India Using SARIMA

Farmers face many difficulties as a result of price fluctuation in agricultural commodities, mostly in developing nations like India. Potato prices are particularly unstable during the post-harvest period, which frequently forces farmers to sell at low prices because of urgent financial needs and delayed market information. The objective of this study is to use the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast monthly wholesale potato prices. Three important markets in Northern India i.e. Uttar Pradesh, a significant producer, Punjab, a distribution hub, and Delhi, a major consumption center were studied for price trends. The AGMARKNET portal was used to collect monthly wholesale price data from January 2010 to December 2024. The best fitted SARIMA models were determined using the lowest AIC and BIC values: SARIMA(2,0,0)(2,0,1)[12] for Uttar Pradesh, SARIMA(1,0,1)(1,1,1)[12] for Punjab, and SARIMA(1,0,1)(0,1,1)[12] for Delhi. Forecast results reveal clear seasonal patterns. Prices in Uttar Pradesh are expected to decline from Rs. 1986.61 in January to a low of Rs. 1629.92 in April, before rising again to Rs. 1821.96 in July. Similarly, the lowest forecasted prices are observed in March and April in Punjab (Rs. 1546.22) and Delhi (Rs. 1664.95), while the highest price is projected for October in Delhi (Rs. 2039.61). The observed patterns suggest that the post-harvest months, specifically from February to April, typically see a decline in prices attributed to market saturation. Conversely, prices tend to increase during the mid to late year period, likely influenced by a decrease in fresh arrivals and a heightened dependence on stored produce. The forecast emphasizes the importance of market-specific dynamics and illustrates the effectiveness of predictive models in assisting farmers marketing decisions. This enables improved planning by traders and policymakers to address seasonal price volatility. &nbsp