Developments in Geographic Information Systems and Remote Sensing (RS) technologies and innovative approaches emerging in deep learning (DL) supported analysis methods have an important place in disaster research as in every field. Convolutional neural networks such as Mask RCNN, U-NET, one of the deep learning methods for disaster damage impact assessment and classification, have started to show successful results. However, high-resolution geospatial imagery and drones provide faster and more accurate detection of structural damage.  In this study, damaged building detection was performed using Göktürk-1 satellite images from 6 February 2023 using Mask-RCNN architecture. In this study, deep learning methods were used to detect the collapsed buildings in the city of Malatya during the 6 February 2023 earthquakes. The study aims to emphasize the significance of GIS and remote sensing for the timely and efficient evaluation of building damage after a disaster. Considering this, high quality images of Malatya city before and after the earthquake were analyzed and data sets were created by masking using Mask RCNN deep learning method through ArcGIS Pro 3.4.0 software. According to the results of the research, it quickly detected damaged buildings with an accuracy rate of 70% according to satellite images after the earthquake. As a result, GIS and deep learning models were used to detect and map the initial damage after the earthquake.

Drought is regarded as one of the most significant abiotic constraints to agricultural crop output worldwide. Drought in the spring and early summer, which coincides with important reproductive stages, severely limits lupin yield in Mediterranean climate zones. The purpose of this study was to determine how different drought treatments affected seed germination and initial seedling growth in Lupinus albus L. (white or field lupin). Seed germination parameters and initial seedling growth traits were tested against five levels of drought stress induced with Polyethylene glycol-6000 (PEG6000) at concentrations of 0, 4, 8, 12, and 16%. An experiment with four replications was conducted using a completely randomized design. The results revealed that the negative effect of drought stress started at 4% (-0.03 MPa or -0.3 bar) treatment for the initial seedling growth stage; whereas, it started at 12% (-0.2 MPa or -2 bar) treatment for the germination stage. Therefore, it was determined that L. albus was more sensitive to drought stress at the initial seedling growth stage than at the germination stage. However, it was observed that the growth parameters were more sensitive in shoot growth than in root growth to drought stress. There will be a sharp loss of yield in soils with levels of drought stress imposed by 12% PEG6000 (-0.2 MPa-moderate drought-) and beyond. Therefore, it is likely that L. albus has low drought tolerance.

Okra (Abelmoschus esculentus) cultivation in regions like Ramechhap, Bagmati Province, Nepal faces challenges in improving yield and economic returns due to suboptimal agronomic practices. To address this issue, a field experiment was conducted to assess the effects of pinching and micronutrient sprays (zinc and boron) on growth, yield, and economic returns of okra. The study aimed to evaluate the impact of pinching and zinc-boron foliar application on key growth parameters, including the number of leaves, fruit length, number of fruits per plant, and total yield. Pinching significantly increased the number of leaves and fruits per plant, as well as the total yield. The application of 0.25% Zn + 0.25% B resulted in the highest fruit length, fruit weight, and total yield. The combined treatment of pinching and Zn-B spray (P1M3) recorded the highest fruit length (11.13 cm), number of fruits per plant (21.91), and yield (17.68 t ha-1). Economic analysis revealed that this combination resulted in the highest net return (NRs. 774,869.35 ha-1) and the highest benefit-cost ratio (B:C = 1.95), indicating that it could significantly improve farm income for smallholder farmers in the region. These results demonstrate the potential of integrated agronomic practices, including pinching and micronutrient application, to enhance both productivity and profitability in okra cultivation.

Agricultural lands are known not only as agricultural production areas but also as areas with high income expectations as an investment tool. In Turkey, recent fluctuations in economic indicators such as the euro, dollar, and gold, along with increasing investment demand, have caused agricultural land prices to rise uncontrollably. Controlling land price increases is important for preventing the misuse of agricultural lands. The sustainable management of agricultural lands and price stability are closely related to the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 and 15, “Sustainable Cities and Communities” and “Life on Land.” In this context, accurately predicting prices is important for minimizing price fluctuations in agricultural lands for investors and landowners and supporting sustainable development. In general, the Multiple Linear Regression (MLR) model is considered one of the effective traditional methods for predicting real estate prices. However, depending on the data, more reliable results can be obtained than with powerful deep learning models such as the Extreme Gradient Boosting (XGBoost) algorithm, which exhibits superior prediction performance. This study aims to compare the MLR and XGBoost algorithms to predict agricultural land prices in villages located in the central district of Çanakkale and to examine daily fluctuations in economic indicators such as the dollar, gold, and euro. The results showed that XGBoost (R2 = 0.66) has an advantage in terms of coefficient of determination values compared to MLR (R2 = 0.01). Accurate price prediction for agricultural lands will help control fluctuations in land prices. Additionally, it will support farmers and investors in making informed decisions for a sustainable agricultural economy.

The existing practice of using excessive mineral fertilizers for maize production not only degrades the soil quality but also poses a threat to the overall ecosystem. Thus, in our research, we attempt to investigate the influence of biofertilizers on yield and yield attributing traits of maize, as a better, alternative, cheaper, eco-friendly, and sustainable solution. A two-factorial field experiment (RCBD) was carried out in Gaindakot, Ward No. 8, Nawalpur district, to assess the effect of Azotobacter in association with other fertilizers on the growth and yield of different maize varieties. The experiment consisted of 15 treatments (3 maize varieties and 5 different nutrient sources) with 3 replications. The three maize varieties used were Local Pahelo, Rampur Composite, and Rampur Hybrid-14, while the nutrient sources included Control, Farmyard Manure (FYM) only, Azotobacter-inoculated seeds, Azotobacter + FYM, and Azotobacter + chemical fertilizers (NPK). The results obtained revealed that the optimum performance was observed in Rampur Hybrid-14 with the nutrient source being Azotobacter inoculation in combination with FYM, resulting in a Leaf Area Index (LAI) of 0.39, 15 leaves, a grain yield of 8.41 tons per hectare, dry stover weight of 0.964 kg per meter square and a root length of 32.33 cm. The results demonstrated that the use of Azotobacter in combination with FYM in the Rampur Hybrid-14 variety could result in higher yields in commercial maize production, reducing the need for excessive mineral fertilizers.

In this study, it was aimed to examine the potential therapeutic effects of Urtica dioica seed (UDS) oil on hepatorenal damage induced by methotrexate in rats. Thirty-two Wistar albino rats were divided into four groups: Control, Methotrexate (MTX, 20 mg/kg i.p.), UDS (30 ml/kg feed containing UDS), and MTX+UDS (20 mg/kg i.p. + 30 ml/kg feed containing UDS oil, respectively). At the end of the six-week study, the MTX-treated group demonstrated elevated levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) in serum and increased levels of malondialdehyde (MDA), an indicator of lipid peroxidation in liver, kidney, and blood tissues. However, reduced glutathione (GSH) levels (apart from erythrocytes) showed a significant decrease (p<0.005). The MTX group's liver and erythrocyte tissues showed a significant decrease in glutathione reductase (GR) activity compared to the control. Additionally, there was a significant decrease in the activities of glutathione peroxidase (GPx) and catalase (CAT) in the MTX group as compared to the control. The co-administration of MTX+UDS decreased liver MDA concentration and the levels of the enzymes AST, ALT, and LDH compared to the MTX group. On the other hand, there was an increase in kidney glutathione S-transferase (GST) activity and GSH levels. Histopathological investigation revealed that pellets containing UDS oil significantly reduced the degenerative and necrotic changes that MTX had generated in the liver and kidney, including parenchymal and hydropic degeneration and inflammatory cell infiltration. Immunohistochemical staining showed that caspase 3, a marker of apoptosis, decreased significantly with the administration of UDS oil. In conclusion, MTX-induced hepatorenal damage was either prevented or greatly decreased by UDS oil.

Bu çalışma, çevresel değişkenlerin, mekanize operasyonların ve kimyasal maruziyetin önemli tehditler oluşturduğu tarım sektörüne özel bir odaklanma ile yüksek riskli sektörlerde DRA uygulamasını araştırmaktadır. Sensör ağlarının, İHA (İnsansız Hava Aracı)’ların, hava durumu izleme istasyonlarının ve yapay zekâ destekli analizlerin entegrasyonu, risk değerlendirmelerinin sürekli olarak güncellenmesini sağlayarak iş güvenliği ve üretkenliğin artırılması için eyleme geçirilebilir içgörüler sağlar. Şebekeden bağımsız meyve bahçesindeki bir vaka çalışmasında, DRA uygulamasını, risk izleme ve müdahale stratejilerini optimize etmek için uydu tabanlı internet, GPS modülleri ve otomatik veri işleme sistemlerini teorik olarak birleştirerek gösterilmiştir. Bulgular, gerçek zamanlı tehlike tespiti, iyileştirilmiş işçi güvenliği ve öngörülemeyen çevresel değişikliklere karşı geliştirilmiş dayanıklılık gibi DRA'nın avantajlarını vurgulamaktadır. Çalışma ayrıca, geleneksel risk değerlendirme yöntemleri ile DRA arasında karşılaştırmalı bir SWOT analizi sunarak, öngörücü analiz ve uyarlanabilir risk yönetimindeki güçlü ve zayıf yönlerini vurgulamaktadır. Bu çalışma; yeni bir kavram olan dinamik risk analizi konusunda yazılan, tarımda teknoloji kullanımı, iş sağlığı ve güvenliği alanında, Türkçe literatürde ilk olma özelliği taşımaktadır. Çalışma kapsamında tarıma uygun riskler belirlenip tanımlanmış, düzenleyici faaliyetleri DRA ile uyumlu olarak belirlenerek, geleneksel risk izleme yöntemleriyle ile karşılaştırılmış ve SWOT analiziyle de kavramsallık ve uygulanabilirlik açısından irdeleyen teorik esaslı bir çalışmadır.

Mevcut çalışmada, coğrafi işaret tescilli Çubuk Turşusunun fermantasyon süreci ve depolama sürecindeki bazı kalite özelliklerinin değişiminin izlenmesi amaçlanmıştır. Bu amaçla, turşu örnekleri coğrafi işarete uygun şekilde, Ankara'nın Çubuk ilçesinde hazırlanmıştır. Süreç boyunca değişimler salatalık ve salamurada yapılan analizler ile gözlemlenmiştir. Salatalıklarda; ilk gün (taze salatalık), 7., 15., 21., 30., 45., 60., 90., ve 180. günlerde rutubet miktarı, kabuk (ekzokarp) ve iç (endokarp) renk (L*, a*, b*) değerleri, indirgen şeker miktarı, ve ekzokarp ve endokarp sertliği belirlenmiştir. Salamura örneklerinin ise pH, titrasyon asitliği ve tuz miktarı açısından ilk gün, 7., 15., 21., 30., 45., 60., 90., ve 180. günlerde analizleri yapılmıştır. Mineral madde içeriğinin değişimi hem salatalık, hem de salamurada; ilk gün, 7., 15., 21., 45. ve 180. günlerde incelenmiştir. Duyusal analizler ise 21., 30., 45., 60., 90., ve 180. günlerde gerçekleştirilmiştir. Fermantasyon ve depolama süresinde mineral madde içeriği İndüktif Eşleşmiş Plazma Kütle Spektroskopisi (ICP-MS) ile belirlenmiştir. Salatalık turşusu ve salamurasındaki mineral madde konsantrasyonundaki en büyük değişiklik fermantasyonun en hızlı olduğu ilk 7 günde gerçekleşmiştir. Çubuk turşusunun salatalık ekzokarp ve endokarp sertliğinin ise fermantasyon ve depolama süresi boyunca stabil kaldığı belirlenmiştir. Duyusal değerlendirme sonuçlarına göre turşular 21. günden 180. güne kadar kabul edilebilir düzeyde notlar almıştır. Tekstürel ve duyusal olarak Çubuk turşusunun kalite özelliklerini koruduğu ve sürecin stabil ilerlediği gözlemlenmiştir.

This study investigated selected quality and functional characteristics of 17 hulled wheat accessions (Triticum monococcum and Triticum dicoccum) preserved in the Türkiye Seed Gene Bank, along using four modern wheat cultivars (Triticum aestivum L. and Triticum durum Desf.). The samples were evaluated regarding grain color parameters (L*, a*, b*), thousand kernel weight, and protein content. Furthermore, total phenolic content (TPC) and antioxidant activities were were analyzed using DPPH and FRAP assays. The differences between samples were statistically significant in terms of DPPH activity and protein content. Species-wise comparison demonstrated that T. monococcum and T. dicoccum had the highest average protein levels. The highest DPPH antioxidant activity was recorded in T. monococcum sample no. 10 (859.67 µg mL⁻¹), while the lowest was in sample no. 2 (532.58 µg mL⁻¹) of the same species. Significant variation was found across the samples for L*, a*, b* color values, Chroma (C), Hue angle (h°), thousand kernel weight, total phenolic content, and FRAP antioxidant capacity. The highest TPC was detected in T. dicoccum sample no. 17 (11.23 mg GAE g⁻¹), and the highest FRAP reducing power was found in sample no. 14 of the same species (22.10 mg TE g⁻¹). These findings demonstrate notable diversity among hulled wheats regarding the evaluated traits and suggest their potential as valuable genetic resources for wheat breeding programs.

The objective of this study was to evaluate the relationship between plasma leptin levels in the early and late luteal periods of cows and conception rate. In the present study, the ovsynch + progesterone (P4) protocol was employed in 50 Holstein cows. Blood samples were collected on the 5th and 18th days following artificial insemination, and the levels of leptin and progesterone were subsequently measured. Subsequent to artificial insemination, mean leptin levels in the early (day 5) and late (day 18) luteal phases of the cows were measured as 5.96 ± 2.54 and 8.02 ± 4.14 ng/mL, respectively. Levels of leptin in the blood of pregnant cows on both day 5 (9.01 ± 4.40 ng/mL) and day 18 (12.04 ± 6.49 ng/mL) were higher than those in the blood of non-pregnant cows (4.44 ± 3.83 ng/mL and 6.01 ± 4.93 ng/mL, respectively). The findings revealed that progesterone levels on the 5th day following artificial insemination exhibited higher mean values (2.11 ± 0.64 ng/mL) in pregnant cows as compared to non-pregnant cows (1.49 ± 0.51 ng/mL). Furthermore, a higher level of progesterone was observed on day 18 in pregnant cows (8.89 ± 2.01 ng/mL) in comparison to non-pregnant cows (5.22 ± 2.21 ng/mL) (p<0.05). The study revealed that levels of the hormones leptin and progesterone were elevated in pregnant cows during the early and late luteal phase, in comparison to non-pregnant cows. However, no correlation was determined between P4 and leptin. The conclusion drawn was that, while there was a possibility that leptin levels could have an effect on the process of pregnancy and implantation, no relationship was found between progesterone and leptin levels