The disc angles, vertical loads, soil type, and residue conditions have a significant effect on the performance of a single disc-type no-till seeder furrow opener. Disc angles are divided into two as the disc and tilt angle, and they play an important role on parameters such as the furrow profile, residue distribution, the cross-sectional area of furrow and spoiled soil area on the furrow edges. In this research, which was conducted with a soil bin, 5 disc angles (0°, 5°, 10°, 15°, and 20°), 5 tilt angles (0°, 2.5°, 5°, 7.5°, and 10°), 3 vertical loads (50, 100, and 150 kg), and 3 different residue conditions (wheat, corn, and no-residue soil) were used. Better results were obtained for the furrow profile, distance of the dragged residue, and the amount of dragged and cut residue at a disc angle of 0°. In addition, a higher residue coverage rate of 63% was achieved with a disc angle of 0°. The dragging of wheat and corn residue increased as the disc angle increased; however, the effect of the tilt angle on residue dragging was the opposite of that of the disc angle. In addition, the cutting performance of the single disc opener was better for corn residue (64.5%) than wheat residue (35.3%). While the amount of residue cut at a disc angle of 0° was 60%, this value decreased to 40% when the disc angle was 20°. This shows that a wide disc angle is a significant disadvantage in terms of cutting the residue. Increasing the vertical load applied on the disc opener increased the furrow width, furrow cross-sectional area, spoiled soil area, distance of the dragged residue, dragged and buried residue, and depth of the buried residue. It was concluded that a vertical load of 50 kg was sufficient for a single disc furrow opener under the existing conditions. As the disc angle increased, significant increases occurred in the cross-sectional area of the furrow by 6 times and on the spoiled soil by 17 times, which is undesirable for no-

Bu çalışma, Konya Ovası Projesi (KOP) Bölgesi‘nin 2009-2018 yılları arasındaki tarım alet ve makina varlığı ile tarımsal mekanizasyon özelliklerindeki değişimin saptanması amacıyla ele alınmıştır. Çalışmanın materyalini KOP Bölgesi‘ndeki illerin 2009-2018 yılları arasındaki tarım alet ve makinaları istatistiksel verileri oluşturmuştur. 2009-2018 yıllarına ait traktör sayısı, traktör güç dağılımı ve tarım alanı değerlerinden yararlanılarak tarımsal mekanizasyon özellikleri ile bu özellikler arası ilişkiler belirlenmiş ve karşılaştırmalar yapılmıştır. Karşılaştırmalarda; ortalama traktör gücü (kW), birim alana düşen traktör gücü (kW/ha), 1000 hektar tarım alanına düşen traktör sayısı (adet/1000 ha) ve bir traktöre düşen tarım alanı (ha/traktör) kriterleri esas alınmıştır. Elde edilen sonuçlara göre, KOP Bölgesi‘nin 2009 ve 2018 yılları verileri sırasıyla, ortalama traktör gücü 38,21 kW ve 38,91 kW, birim alana düşen traktör gücü 1,21 kW/ha ve 1,56 kW/ha, 1000 hektar alana düşen traktör sayısı 31,75 adet/1000 ha ve 40,09 adet/1000 ha ve bir traktöre düşen tarım alanı 31,50 ha/traktör ve 24,94 ha/traktör olarak belirlenmiştir.

The aim of this study was to determine the effects of different shank types, tine types, and tractor forward speeds on the power and fuel consumption of chisel plows, stubble cover, soil surface roughness, and penetration resistance. In addition, using the obtained results, the draft power, fuel consumption, soil surface roughness, and soil stubble cover rate were modeled using Deep Learning Neural Network (DLNN) architectures and sensitivity analysis of these models were performed. Four different shank types (rigid, semi-spring, spring, and vibrating) and two different tine types (conventional and winged) were used at three different tractor forward speeds (4.5, 5.4 and 6.3 km.h^− 1) were tested to this end. The obtained results indicated that the maximum draft power was achieved with the rigid type shank. The highest soil surface roughness values were observed for the vibrating shank type and winged tine type. Sixteen different network architectures were conducted using deep learning neural network methods and draft power, fuel consumption, soil surface roughness, and percent stubble cover were modeled. Sensitivity analyses were performed to indicate which modeled parameters were more sensitive to the factors using the obtained models. Draft power was modeled with 97.7% accuracy using the DLNN9 network architecture. Additionally, fuel consumption and soil roughness were best modeled with the DLNN13 network architecture, R² values for those targets were 0.929 and 0.930 respectively. According to the sensitivity analysis, draft power, fuel consumption, soil roughness, and stubble cover rate were significantly affected by changes in the physical properties of the soil.

Soil temperature is a crucial factor affecting soil's physical, chemical, and biological processes. In particular, the rate of biochemical activities and the soil-plant-water balance are affected by soil temperature. Soil temperature has an important role in many issues such as soil management, water movement in the soil, and planting time determination. Therefore, to know the soil temperature and make predictions about its change in the coming years, the soil temperature trend must also be known. Today, there are many studies on soil temperature. However, studies on the trend of soil temperature are limited, especially in Türkiye. In this study, soil temperature trends over the period between 1981 and 2021 were analyzed on a monthly scale at 5 and 20 cm depths using 73 meteorological stations in Türkiye. Also, the relationships between air and soil temperature were examined during the same period. The results yielded a high correlation between air and soil temperature. According to the monthly trend analysis of soil temperature, there was a predominance of positive trends at both soil depths. For 5 cm and 20 cm-depths, the distribution of significant positive trends was the highest in March (78.08% and 83.56%, respectively), while significant negative trend distribution was the highest in June (9.59%) and July (4.11%), respectively. Increasing soil temperatures will affect many soil characteristics and agricultural production processes. It should be noted that the increase in soil temperature may positively affect plant germination and root development, but soil moisture balance and biochemical negatively affect soil properties. Planning sustainable soil management practices, including soil tillage, to reduce the increase in soil temperatures has become necessary. Therefore, activities that may cause an increase in soil temperature should be controlled and monitored.

This study investigated the effects of different drying temperatures (50, 60, and 70°C) in the oven and microwave pre-treatment on the drying behavior, effective diffusion values, energy parameters, and color characteristics of purple carrots. The results showed that microwave pre-treatment increased drying rates and accelerated the drying process at all temperatures. Effective diffusion values varied depending on drying temperature and pre-treatment, with higher values obtained at lower temperatures. According to energy analysis results, samples dried at 60°C were found to be more efficient in terms of energy parameters, exhibiting higher specific moisture absorption and lower specific energy consumption values. Color analysis revealed that samples dried with microwave pre-treatment at 60°C retained color characteristics closest to those of the fresh product. Overall, it was concluded that microwave pretreatment improves drying performance and that its application in conjunction with a 60°C drying temperature is a suitable method for drying purple carrots in terms of quality and energy efficiency.