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.

The basic need of humanity is food. The agricultural sector has had to use new technologies in food production in recent years. The increase in the world population has necessitated the agricultural sector to produce more. Therefore, in recent years, the use of technology in agriculture has increased and new developments have occurred. Especially Industry 4.0 technologies have become preferred by manufacturers with the convenience and added values they provide. In this research, participants’ views on their expectations from technology in agriculture, their views on the use of drones in agriculture, farmers’ views on technology use, and farmers’ views on the agricultural technology context were examined. In the research, information management systems in agriculture and a survey to determine students’ interest in agricultural projects were used as data collection tools. Rapidly developing technology in recent years makes the work of producers easier in the field of agriculture and offers researchers the opportunity to research new topics. Within the scope of this research, it is important to create this research in order to determine the needs and reveal the current situation. According to the research, the participants do not see themselves as having sufficient knowledge about technology in agriculture. The research results show that the participants do not follow the developments in agriculture in the digital environment. It is seen that the participants have partially sufficient knowledge about the use of drones in agriculture, that the use of drones will be beneficial and that the use of drones will replace the use of traditional agricultural tools.

The water hammer pump presents a promising solution for water supply in water-scarce regions. In Mexico, despite abundant overall water resources, many arid areas still lack access to reliable water. This study focused on optimizing the design and performance of low-cost water hammer pumps, which are powered by river currents and require minimal maintenance. While these pumps offer a sustainable solution, they face challenges such as water wastage, noise, and potential for low efficiency. Specifically, this research aimed to evaluate the impact of air chamber design on pump performance. The materials used in the prototype included steel pipes, steel plates, connectors, and lift valves for the air chambers. The pump itself utilized steel reducers, elbows, bronze waste valves, and a steel frame. Testing materials comprised plastic hoses, a digital stopwatch, an overhead tank, graduated cylinders, and plastic buckets. During the design phase, water flow rate, head height, and pipe diameters were taken into account. The Michaud-Venso formula and Allievi's equation were used to calculate pressure and wave velocity. A prototype featuring welded air chambers and waste valves was fabricated for functional testing. Laboratory performance tests were conducted using a 0.15 m³ tank at 1.0 m and 1.2 m heights, with 52 mm and 76 mm inlet pipe diameters. The pump's power output was not measured. Specifically, air chamber sizes of approximately 2690 cm³ resulted in a 15% increase in performance. The lowest efficiency, 5%, for a 76 mm waste valve, occurred with an 880 cm³ air chamber, while the highest efficiency (17.0%) was achieved with a 6108 cm³ air chamber. The volume of water collected at the outlet was dependent on the air chamber size. As the air chamber volume increased, the flow rate at the inlet valve also increased. Therefore, optimally sizing both air chambers and waste valves is significant to maximizing pump efficiency.

Kivi (Actinidia spp.), küresel olarak önemli ekonomik değere sahip bir meyve ürünüdür. 2010'dan önce, kiviyi etkileyen virüslere sınırlı ilgi gösterilmekteydi. Ancak o zamandan beri, bu ürünü enfekte eden 20'den fazla virüs tanımlanmıştır. Bu virüsler, yapraklarda sararma, mozaik desenleri, nekroz ve halkalı lekeler gibi ciddi simptomlara neden olabilmekte ve meyve kalitesi ile verimini önemli ölçüde etkileyebilmektedirler. Bu virüslerin birçoğu yaygın bir dağılıma sahiptir. Bu derleme, kivi virüslerinin tanımlanması, genomik değişkenliği, dağılımı, taşınması, tespiti, yaygınlığı ve mücadelesi konusundaki son gelişmeleri vurgulamaktadır. Ayrıca, gelecekte kivi virüsleri ile ilgili mücadele programlarının oluşturulabilmesi için önerileri de kapsamaktadır.  Virüsten ari çoğaltma materyallerinin kullanımı, kivi virüsleri ile mücadele için en uygun maliyetli ve güvenilir strateji olmaya devam etmektedir.

The aim of this study was to synthesize silver nanoparticles (Ag@NPs) by green synthesis method using Cuminum cyminum (Cumin) plant extract. Green synthesis is preferred more than chemical and physical methods because it is a biological method in which nanoparticles are easily and rapidly obtained, as well as being environmentally friendly and cost-effective. The Ag@NPs obtained from the reaction were characterized by UV-visible spectrophotometer (UV-vis), Fourier-transformed infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy and energy dispersive X-ray (SEM-EDX). Ag@NPs were found to have maximum absorbance in the range of 400-500 nm. Functional groups involved in the reduction of Ag@NPs were identified by FTIR analysis. The spherical appearance of Ag@NPs was determined by transmission electron microscopy. The antimicrobial effect of the synthesized AgNPs was tested on gram-positive and gram-negative bacteria using the minimum inhibitory concentration (MIC) method. The results show that Ag@NPs obtained from Cuminum cyminum (Cc) seeds have effective antimicrobial activity. The use of plant-derived materials is considered to be a promising strategy for the green synthesis of Ag@NPs and could be more widely used in the bio-medical field.