İkBal Aygün

In this paper, a new image filtering method is proposed using nonlinear symbolic functions. In this way, feature extraction from images is achieved using a small number of filters and parameters. Nonlinear symbolic functions are determined by an optimization method and different approaches are proposed to increase the filtering speed. Nonlinear functions also act as a regression layer and more efficient design is achieved by moving the image to nonlinear space. In sustainable agriculture, artificial intelligence has been recently utilized to pre-detect diseases and determine their severity to perform spraying more accurately in site-specific applications for human health and soil ingredients. Therefore, a new dataset for detecting the disease root rot severity of Arugula (Eruca vesicaria) was created and labeled for the image classification such that there is a significant decrease in production yield every year due to root rot disease. The proposed CNN model with nonlinear symbolic function filtering was produced %86.92 accuracy for the classification of disease severity whereas conventional 4-layer CNN model and pre-trained large image classification models such as VGG16, VGG19, ResNet50, ResNet101, InceptionV3, DenseNet, EfficientNetV2S, MobileNet, MobileNetV2 and Xception have been fine-tuned and classification accuracy is provided between 57-92% without preprocessing of images. Between the designed models, MobileNet model with less computational time and high accuracy can be a potential for future application in drone-based spraying systems. However, the proposed model with less number of parameters is also promising for future applications. The application results of image classification facilitate variable-rate spraying for sustainable agricultural production, ultimately protecting both human and soil health.

The rapid advancement of smart agricultural technologies has transformed modern farming practices, enhancing productivity, precision, and sustainability while introducing new ergonomic challenges. This study aimed to evaluate and prioritize ergonomic criteria associated with three major smart agricultural technologies—GPS-guided tractors, agricultural drones, and automatic irrigation systems—within a multi-stakeholder decision-making framework. The Analytic Hierarchy Process (AHP) was applied to data collected from 53 experts representing four stakeholder groups: academia, operators/farmers, manufacturers, and sectoral organizations. Five ergonomic criteria—physical workload reduction, task duration, user safety, training requirement, and cost/applicability—were analyzed to determine their relative importance. The results indicate that user safety emerged as the most influential ergonomic factor for academia, farmers, and sectoral organizations, highlighting the importance of risk reduction and operator protection in smart farming environments. In contrast, manufacturers prioritized cost and applicability, reflecting economic feasibility considerations in technology development and deployment. These findings demonstrate that ergonomic priorities differ across stakeholder groups and emphasize the need for human-centered design approaches in the development of smart agricultural systems. The proposed multi-stakeholder AHP framework provides a practical and evidence-based decision-support tool for integrating ergonomic considerations into agricultural technology design, implementation, and policy development.

It is estimated that the world population will be ten billion in 2050, and Türkiye’s population will be 105 million. In order to supply the nutritional needs of the increasing population, new techniques, machine usage/mechanization and technologies are needed in agricultural production. In order for plant production to be conducted at the desired efficiency, the usage of machinery is one of top priority, and the first and most intensive stage is tillage. As a result of the contact and interaction with the soil of the machines used in tillage, some negative situations such as abrasion occur. In order to reduce wear as much as possible, value-added processes are applied to the tillage active elements. The most basic process is to provide the hardness values at the technically desired level by applying regional or general heat treatment to the active elements. The hardness limits of the machines are specified in the Agricultural Machinery and Tractors Test Principles. In this study, the hardness values obtained as a result of the static hardness test conducted in accordance with the standards on 469 active elements belonging to different types of tillage machines were evaluated. The hardness values of the tillage elements of these machines, such as shares, discs, teeth and blades, were examined and the average hardness and standard deviation values were calculated. According to the results, shares of the mouldboard plows (50.7±3.2 HR-C), discs of disc plows (48.5±2.1 HR-C), discs of disc harrows (47.8±2.4 HR-C) and theet of toothed harrows (47.78±2.4 HR-C) are within the limits specified in the principles. The cultivator shares (41.2±6.0 HR-C), subsoiler shares (42.3±3.8 HR-C) and rotary tiller blades (43.8±2.8 HR-C) values are below the limits specified in the principles.

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 was carried out to determine the effects of some tillage methods; it included conventional tillage and conservation tillage with some weed control applications on weed manifestation in organic vineyards. The organic vineyard experiment area was designed as main and sub-plots. The effects of some methods of conventional tillage, no-tillage, and conservation tillage on weed coverage, densities, fresh weight, and dry weight were determined in the organic vineyard experiment area. These tillage methods were applied in the main plots. A chisel and heavy-duty disk harrow were used for conservation tillage methods. The plough and disc harrow were also applied as conventional methods. Other allelopathic methods (olive mill wastewater, radish (Raphanus sativus L.), and broccoli (Brassica oleracea L.) were applied as sub-plots in the experiment area. As a result of the statistical analysis of the values obtained in the study, the most effective method, the application of the plough and disc harrow, was determined for weed coverage and fresh and dry weight weeds in the main plots. The olive mill wastewater was also determined as the most effective application in the sub-plots. In terms of grape yield, the most effective method in the main plots was the plough + disc harrow application (6.8068 kg vinestock‒1). The planting of broccoli (6.4485 kg vinestock‒1) was determined as the most effective sub-plot application for grape yield.

Ergonomi, insan ile iş arasındaki uyum koşullarını inceleyen, fizyolojik, psikolojik ve sosyolojik insani sınırları dikkate alarak çalışma ortamlarında verimlilik ile iş güvenliğini artırmayı hedefleyen çok disiplinli bir bilim dalıdır. İkinci Dünya Savaşı esnasında askeri ve teknolojik gereksinimlerle önemi giderek artan ergonomi, Türkiye'de akademinin yanı sıra ulusal kongreler, lisans ve lisansüstü eğitim programları ile belirgin bir gelişim göstermiştir. Tarım sektörü, insan-iş etkileşiminin son derece yüksek seviyede olduğu, ağır fiziksel zorlanmalar ve sürekli tekrarlı hareketler içeren dinamik bir üretim alanıdır. Tarımsal üretim süreçlerinde karşılaşılan başlıca ergonomik riskler arasında kas-iskelet sistemi rahatsızlıklarına, bel, sırt ve omuz ağrılarına yol açan elle yük taşıma, uygunsuz çalışma duruşları, sürekli ayakta durma ve eğilerek yapılan zorlu işler yer almaktadır. Yürütülen çeşitli bilimsel araştırmalar; akıllı tarla pülverizatörlerinin kullanımı, ergonomik el aleti tasarımları, yüklerin güvenli taşınması, mekanizasyon desteği ve mola sürelerinin düzenlenmesi gibi uygulamaların çalışanların bedensel yükünü ve yaralanma risklerini belirgin şekilde azalttığını ortaya koymaktadır. Sonuç olarak, artan mekanizasyon seviyesi ile birlikte tarımda ergonomik risk farkındalığının oluşturulması, mevzuat düzenlemeleri ve karar destek sistemlerinin geliştirilmesi, hem çalışan sağlığının ve konforunun korunması hem de üretimde verimlilik ve gıda arz güvenliğinin sürdürülebilir kılınması açısından kritik önem taşımaktadır. Ergonomics is a multidisciplinary branch of science that examines the conditions of harmony between humans and work, aiming to increase productivity and occupational safety in working environments by considering physiological, psychological, and sociological human limits. Gaining importance during World War II due to military and technological requirements, ergonomics has shown significant development in Turkey through national congresses, undergraduate, and graduate education programs alongside academia. The agricultural sector is a dynamic production field where human-work interaction is at an extremely high level, involving heavy physical strain and repetitive movements. The primary ergonomic risks encountered in agricultural production processes include manual load handling, improper working postures, continuous standing, and strenuous tasks performed while bending over, which lead to musculoskeletal disorders as well as lower back, upper back, and shoulder pain. Various scientific studies demonstrate that applications such as the use of smart field sprayers, ergonomic hand tool designs, safe load handling, mechanization support, and rest break scheduling significantly reduce workers' physical burden and injury risks. Consequently, alongside increasing mechanization levels, creating awareness of ergonomic risks in agriculture, introducing regulatory frameworks, and developing decision support systems are of critical importance for protecting worker health and comfort, as well as ensuring productivity and food supply security.