Holy basil, known as Tulasi in Nepali is a medicinal herb with significant potential in Nepal. Despite its significance in culture and tradition, its scientific and commercial potential is yet underexplored. This review article explores holy basil’s pharmacological characteristics emphasizing its adaptogenic, anti-bacterial and anti-inflammatory qualities. The medicinal uses of basil are attributed to its bioactive compounds including ursolic acid, rosmarinic acid and eugenol.  This review article highlights the necessity of systematic cultivation, sustainable harvesting and advanced extraction technique in order to optimize the yield and quality of these bioactive substances. It also explores holy basil’s potential in the cosmetic, pharmaceutical and nutraceutical sectors and advocates for further research and development to utilize its full potential. Basil’s commercial and industrial potential in Nepal is also glorified in this review article along with challenges in commercialization also providing future recommendations.

This article explores an intelligent and equitable approach to collective and participatory irrigation for small farmers, with an emphasis on the democratization of water use. It examines how this equitable irrigation approach can contribute to the social economy by improving irrigation efficiency and reducing costs for farmers. This work highlights the socio-economic benefits of this approach and highlights its potential to promote democratic water management particularly for small-scale farmers. To do this, we propose a collective irrigation system using a Particle Swarm Optimization (PSO) algorithm, to accurately estimate crop water needs, a method of equitable distribution of water according to needs. Additionally, we propose a novel weighted aggregation technique to establish irrigation priorities among crops, taking into account factors such as crop yield, water scarcity, and economic value.

This study evaluated and compared the antimicrobial, antioxidant, anticholinesterase, and antidiabetic activities of Matricaria chamomilla L. (chamomile), Lavandula angustifolia Mill. (lavender), Hypericum perforatum L. (St. John’s wort), Salvia officinalis L. (sage), and Foeniculum vulgare Mill. (fennel) plants and their extracts. Antioxidant activity was assessed using DPPH and ABTS assays, while α-glucosidase and α-amylase inhibition assays determined antidiabetic potential. Acetylcholinesterase and butyrylcholinesterase inhibitory activities were measured via the Ellman method, and antimicrobial activity was evaluated using the micro-well dilution test. Among the tested extracts, H. perforatum extract and H. perforatum drug exhibited the most potent biological activities. In the α-glucosidase inhibition assay, H. perforatum extract displayed the highest inhibition (95.40%, IC₅₀ = 8 µg/mL), followed by H. perforatum drug (94.71%, IC₅₀ = 27 µg/mL). The strongest α-amylase inhibition was observed with the Soothing Complex Product (60.90%), following acarbose (74.61%). The highest ABTS radical scavenging activity was noted in S. officinalis drug (99.39%) and H. perforatum drug (99.32%), while the DPPH assay showed significant activity for S. officinalis extract (46.99%) and α-tocopherol (46.99%). Antimicrobial testing revealed moderate antibacterial effects of F. vulgare drug against Staphylococcus aureus and Candida albicans (MIC = 1250 µg/mL). Overall, H. perforatum extracts demonstrated strong enzyme inhibition and antioxidant properties, highlighting their potential for medicinal and dermocosmetic applications. These findings provide valuable insights into the bioactivity of herbal extracts, supporting their potential use in over-the-counter formulations and new plant-based therapeutic products.

This study explores the significance and application potential of windbreaks as an agroforestry practice in residential areas. In the context of increasing environmental degradation, climate change, and the need for sustainable land use, windbreaks are highlighted for their multifaceted benefits to living environments. These benefits range from energy savings to ecosystem enhancements, soil conservation, and biodiversity improvement. The study examines the historical and current applications of windbreaks across different ecological regions of Turkey, emphasizing their potential contributions based on scientific data. Windbreaks established around residential areas improve microclimatic conditions, enhance quality of life, mitigate the adverse effects of strong winds and storms, and contribute to food security. Additionally, they support environmental sustainability by increasing carbon sequestration and helping to combat the impacts of climate change. For the successful implementation of windbreaks, proper species selection, precise establishment techniques, and continuous maintenance are essential. The study suggests enhancing collaboration between public and private sectors for the planning and management of windbreaks in a geographically diverse country like Turkey. Moreover, it underscores the need for awareness campaigns, educational programs, and the promotion of scientific research to scale these practices. Windbreaks demonstrate considerable potential as a sustainable land-use model and serve as a vital component for improving living standards and environmental resilience.

Population growth has increased demand and diversified use of Irish potato which have increased its demand. The crop has become a major source of food and income for many households across the world. However, despite the high potential of about 30 tonnes per hectare (ha), smallholder farmers in Kenya realize low Irish potato yields ranging from 4-8 tonnes per ha due to limited uptake of agricultural technologies. The low yields calls for a profound understanding of the factors influencing the uptake agricultural technologies. The study analyzed the effects of the adoption of agricultural technologies on Irish potato yield in Ol Kalou Sub County. The study considered chemical fertilizer, certified seeds, fungicides, and farm machinery as the four main agricultural technologies that that affect yield. A descriptive cross-sectional research design was used to obtain data from a study population of 21,942 smallholder Irish potato farmers in Ol Kalou Sub County. A multiple-stage sampling technique was employed to generate a sample size of 385 respondents who provided primary data. Data collected was analyzed using endogenous switching regression model using STATA version 17. The study found that the average treatment effect on treated (ATT) was 10.21 bags per acre. In addition, the Endogenous switching regression model showed that the expected yield for the adopter increased by 51.83%. Out of the four technologies, the use of chemical fertilizers had the highest effect of 37% on yield. The study concluded that the adoption of agricultural technologies increases the yield of Irish potatoes. The study recommends that national and county governments should develop policy regulations such as training and extension services, market access, price support and public-private partnerships encouraging farmers to uptake agricultural technologies. The study also recommends that both levels of government should subsidize agricultural technologies, hence reducing the cost of adoption.

One of the cornerstones of a developed economy is undoubtedly the agricultural sector. Agriculture is at the center of both human nutrition and economic activities. The use of drones, especially in the process of spraying fields, has the potential to increase the efficiency of agricultural production. Drones can be programmed to scan the field and spray pesticides on these areas. This allows farmers to manage the processes of protecting their crops and removing pests more effectively. Spraying with drones minimizes the negative effects encountered in spraying with tractor-drawn machines. Drones can easily reach places that tractor-drawn machine cannot reach and can spray more precisely. In addition, thanks to drones, the need for labor is also reduced, so that one person can spray a large area in a short time. In this study, the process of spraying with drones was observed in detail by a company with an unmanned aerial vehicle-2 (UAV) license for agricultural spraying. This modern spraying method using drones was meticulously evaluated step by step. In traditional methods, farmers or workers may be directly exposed to pesticides while spraying with tractor-drawn machines, but thanks to drones, this exposure is minimized, which provides a great advantage in terms of occupational health and safety (OHS). In addition, the speed of the work process, less use of water and pesticides, and the need for labor are among the advantages. However, the problem of not being able to connect to GPS, accidents that may occur under the command of the drone, and limitations such as adverse weather conditions can be considered disadvantages of drone spraying. The findings reveal how drone spraying has transformed agriculture.

This study comprehensively examines the applicability of the 5S methodology as a tool for enhancing efficiency, occupational safety, and sustainability in the agricultural sector. The 5S methodology, predicated on the principles of sorting, organising, cleaning, standardising, and sustaining, aims to create safer and more productive workplaces. The research investigates its effects on both indoor agricultural machinery manufacturing processes and outdoor crop production practices. The analysis reveals notable advantages in manufacturing processes, including reduced waste, enhanced occupational safety, and improved product quality, particularly in production, assembly, and quality control processes. However, the methodology faces limitations in outdoor agricultural practices due to seasonal variations and open-field conditions, which challenge the cleaning, sorting, and organising stages. However, its application in maintenance, repair, and equipment storage processes has been shown to prolong the lifespan of machinery and ensure safer working conditions. The 5S methodology aligns with the United Nations Sustainable Development Goals, serving as a practical approach to enhancing efficiency, workplace safety, and resource management in the agricultural sector. This study underscores the 5S methodology's promise as a sustainable solution for enhancing productivity and safety in agriculture.

This study proposes a reliable and easy understandable statistical solution for the selection of varieties in the balanced and partially balanced lattice experiments, which are widely used in plant breeding studies. For this purpose, the Analysis of Means (ANOM) was adapted to the balanced, simple and triple lattice designs and an R function is developed for it. The adapted ANOM approach was compared with the Tukey, Duncan and Fisher’s LSD tests with respect to the actual type I error rate in all of the balanced, simple and triple lattice designs. In addition to this, the ANOM approach and Tukey test were examined comparatively using a hypothetical example. According to the simulation results, LSD and Duncan could not maintain the actual type I error rate at 5.00% under any conditions. This situation became more dramatic with the increase in the number of groups. While the actual type I error rate for LSD and Duncan tests varied between 54.36%-100.00% and 37.49%-99.96%, respectively, for ANOM and Tukey tests it varied between 4.64%-6.08% and 4.62%-6.45%, respectively. ANOM and Tukey tests were quite successful in terms of maintaining the actual type I error rate. However, since the number of groups in lattice designs was quite high, the given hypothetical example showed that it would be more understandable to use the ANOM method.

Araştırmada farklı illerdeki topraklardan izole edilmiş bakterilerin kadmiyum (Cd) ile kirletilmiş topraklarda yetiştirilen mısır bitkisinin gelişimi ve besin elementi alımına etkilerini belirlemek amaçlanmıştır. Sera koşullarında yürütülen çalışmada 3 kg kapasiteli saksılar kullanılmış ve tesadüf parselleri deneme desenine göre üç yinelemeli olarak saksı denemesi yürütülmüştür. Araştırmada Ordu (B1), Hatay (B2), Sivas (B3), Adana (B4), Isparta (B5) ve Antalya (B6) illerinden izole edilmiş bakteriler kullanılmıştır. Kadmiyum uygulamaları 0 mg Cd kg-1 ve 5 mg Cd kg-1 olarak uygulanmıştır. Araştırma sonuçları, bakteri uygulamalarının mısır bitkisinin kuru madde üretimini arttırdığını ve en yüksek kuru madde üretiminin 57,6 g saksı-1 ile Cd0 uygulamasında B2 aşılamasında olduğunu göstermiştir. Araştırmada hem Cd0 hem de Cd5 uygulamasında bütün bakteri aşılamaları kontrole oranla bitkinin kuru madde üretimini arttırmıştır. Aynı durum azot (N) konsantrasyonu için de geçerlidir. Araştırmada ortalama değerler incelendiğinde, fosfor (P), kalsiyum (Ca), demir (Fe), bakır (Cu), mangan (Mn) ve çinko (Zn) konsantrasyonları özellikle Cd ile kirletilmiş topraklarda bakteri aşılaması ile bitkide artmıştır. Bu durum, Cd ile kirlenmiş topraklarda bakteri aşılaması ile bitki yetiştirmenin önemli bir strateji olabileceğini düşündürmektedir.

Tarım sektöründe bitki hastalıklarının erken teşhisi ve sınıflandırılması, ürün kayıplarının azaltılması ve verimliliğin artırılması açısından büyük önem taşımaktadır. Özellikle nar meyvesi, ekonomik değeri yüksek olan bir ürün olup hastalıkları hem kaliteyi hem de üretimi ciddi şekilde etkileyebilmektedir. Bu bağlamda, nar meyvesinin çeşitli hastalıklarının teşhisi ve sınıflandırılması için makine öğrenmesi ve derin öğrenme yöntemlerinin kullanımı araştırılmaktadır. Çalışmada, Hindistan’ın Karnataka eyaletindeki çiftliklerden toplanan 5099 nar görüntüsü kullanılmıştır. Görüntüler; Kahverengi Leke Hastalığı, Kara Leke Hastalığı, Bakteriyel Yanıklık, Yaprak Lekesi Hastalığı ve Sağlıklı olmak üzere beş sınıfa ayrılmıştır. Veri seti Destek Vektör Makineleri (DVM), Karar Ağaçları (KA) ve Evrişimli Sinir Ağları (ESA) kullanılarak sınıflandırılmıştır. Bulgular, ESA modellerinin nar hastalıklarının tespitinde diğer makine öğrenme yöntemlerine göre yüksek doğruluk oranları sağladığını göstermektedir. Özellikle, iki konvolüsyon katmanlı ESA modeli %88 doğruluk oranı ile en iyi performansı sergilemiştir. Karar ağaçları ise diğer modellere kıyasla daha düşük doğruluk oranlarına sahip olmuştur. Derin öğrenme ve makine öğrenmesi modellerinin bitki hastalıklarının teşhisinde etkin bir şekilde kullanılabileceği ve tarım sektöründe verimliliği artırabileceği ortaya konmuştur.