This study examines the apiculture sector in Türkiye between 2004 and 2024 using data from the Turkish Statistical Institute, focusing on temporal, spatial, and relational dimensions. Time-series analyses, spatial visualizations, productivity comparisons, and correlation assessments were applied to reveal the structural transformation of the sector. The findings indicate a steady increase in modern hive numbers alongside a gradual decline in traditional hives. While overall honey production has grown, per-hive productivity has not improved significantly, suggesting that modernization alone is insufficient. Spatial analyses revealed that provinces such as Ordu, Mugla, and Adana remain dominant in production, yet substantial regional inequalities persist. Comparative and relational analyses highlighted a strong positive relationship between modern hive adoption and honey output, whereas traditional hives contributed little. The study concludes that Turkish apiculture is undergoing a modernization-driven transformation of hive structures and production practices, but efficiency stagnation and regional disparities necessitate complementary policies and practices to ensure sustainable development.

The aim of this article is to present a scientific approach for the determination of the income loss resulting from easement expropriation on land allocated to annual crops. In the article, easement expropriation on land was discussed in terms of legislation and technical aspects firstly, and then determination of the easement value was explained with an example. According to the Expropriation Law, the easement value is determined by taking into account the net income obtained from the land same as in property expropriation. The facilities subject to easement expropriation have been constructed below and above the ground for permanently and temporarily. In the easement expropriation, the easement value is a negative net income calculated by subtracting the net income before the easement from the net income after the easement. For this reason, the determination of the net income according to scientific criteria and using the correct method in determination of the easement have great importance. Even if the easement expropriation is done only on a part of the land, the easement value should be determined by considering all over the land. It is expected that the article will provide useful information for appraisal commissions and experts working in expropriation cases.

This study aims to evaluate the impacts of climate change on agricultural production in Siirt Province, located in the Southeastern Anatolia Region of Türkiye, based on agroclimatic indicators. The analysis is based on long-term temperature and precipitation records for the period 1939-2024, as well as hourly temperature data from 2020-2024. Meteorological observations from the stations of Siirt, Kurtalan, Tillo, Eruh, Pervari, and Sirvan were used. The methodology included the calculation of growing degree days (GDD), temperature thresholds, vegetation period length, and the standardized precipitation evapotranspiration index (SPEI). In addition, agricultural thermal suitability projections were developed for 2050 and 2100 according to the sixth assessment report of the Intergovernmental Panel on Climate Change (IPCC) and its Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). The findings reveal a significant increase in the frequency of temperature thresholds being exceeded. The number of days above 27 °C increased from about 70 days in 1939 to over 100 days in the post-2020 period. Days above 30 °C showed an average annual increase of +0.26 days, while the number of days exceeding 33 °C reached around 20 days per year after 2000. Hourly temperature analyses showed a concentration of values above 35 °C particularly during 11:00-17:00 hours in the summer months (June-August). The cumulative annual GDD, based on a 10 °C base temperature, was calculated as approximately 2250 °C-days. According to future projections, this value is expected to rise to ~3050 °C-days under SSP2-4.5 and ~3450 °C-days under SSP5-8.5 by the end of the century. This indicates that crops such as maize, cotton, Zivzik pomegranate, and Siirt pistachio will reach their developmental thresholds earlier than in the past. The vegetation period, which averaged about 290 days in 1939, has extended to 330-340 days in recent decades. Differences among districts are notable. In lowland areas such as Kurtalan and Aydinlar, the growing season extends up to 8-9 months, while in highland areas such as Pervari it remains limited to 150-200 days. Drought analyses combining SPEI-3, SPEI-6, and SPEI-12 indicated that short-term droughts intensified after 1980, while severe and prolonged droughts became more widespread after 2000. Particularly in 1999, 2007, 2014, and 2021, SPEI values below -2 highlighted critical drought years. In conclusion, the increase in GDD accumulation and the extension of the vegetation period provide production advantages for certain crops, but the more frequent exceedance of high-temperature thresholds and intensified drought cycles increase risks of yield loss and water stress, especially for water-demanding crops. Therefore, crop patterns should be redesigned in accordance with changing climate conditions, irrigation infrastructure should be strengthened, and long-term adaptation policies should be implemented to ensure agricultural sustainability.

The aim of this study is to determine the feed quality of buckwheat (Fagopyrum esculentum Moench.) bran. The material used in this study was the “Günes” variety of buckwheat. The bran part of the plant, separated from the seeds, was ground and prepared for analysis. Wheat bran was used as a control. In this study, dry matter (DM) content, pH, propionic acid (PA), ash content (AC), crude fat (CF) content, acid detergent fiber (ADF), neutral detergent fiber (NDF), crude protein (CP) content, sodium, magnesium, phosphorus, potassium, calcium, iron, copper, zinc, and selenium contents were determined. The CF content of buckwheat bran was 1.15%, while that of wheat bran was 5.56%. Buckwheat bran contained more PA (0.381%) than wheat bran (0.056%). The CP content of the brans was found to be 14.70% for buckwheat and 15.30% for wheat. The ADF and NDF contents of buckwheat bran were 23.52% and 39.78%, respectively, while wheat bran was 14.01% and 38.79%. The DM and AC contents of buckwheat and wheat bran in the study were determined as 90.19%-2.74% and 87.73%-4.56%, respectively. Buckwheat bran exhibited lower values than wheat bran in most nutrient elements; however, all the nutrient elements in buckwheat were within the required levels for animal feed. The study concluded that the feed quality of buckwheat bran is good and, therefore, it should be added to animal rations.

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This study investigates the impact of various land use types on soil organic carbon (SOC) and total nitrogen (N) stocks within the boundaries of Sarikum National Park, a protected coastal ecosystem located along the Black Sea coast of Türkiye. The study area comprises heterogeneous land cover classes including forests, reedbeds, agropastoral systems, hazelnut orchards, sand dunes, and settlement areas. A total of 44 surface soil samples were collected from a 0-30 cm depth and analyzed using standardized physical and chemical methods. SOC and N stocks (ton ha-1) were calculated based on parameters such as bulk density, organic matter content, and coarse fragment ratio. The results revealed that SOC stocks ranged between 0.50-118.47 ton ha-1, while N stocks varied from 0.66-26.61 ton ha-1. Highest stocks were observed in reedbeds and agropastoral lands characterized by high organic matter accumulation and hydromorphic conditions. In contrast, sand dunes and settlement areas exhibited the lowest value due to shallow profiles and limited organic inputs. Findings emphasize that soil depth, clay content, horizon development, and land use configuration significantly influence the spatial distribution of SOC and N stocks. In this context, it has been emphasized how critical the carbon sink potential of protected natural and semi-natural ecosystems is in terms of sustainable land management and climate change mitigation strategies.

This study aims to develop a phenology-aware machine learning framework for accurately predicting wheat yields in Türkiye’s Central Anatolia Region. The research integrates provincial wheat yield data from the Turkish Statistical Institute (TurkStat) (2004-2023) with fourteen agro-climatic and soil parameters retrieved from the National Aeronautics and Space Administration’s Prediction of Worldwide Energy Resources (NASA POWER) platform (2003-2023). To enhance model sensitivity, all variables were segmented into five key phenological stages of wheat growth, and for each stage, the minimum, maximum, and mean values were calculated. Three classical machine learning algorithms-Gradient Boosting (GB), Random Forest (RF), and Multilayer Perceptron (MLP)-were implemented using Python (Scikit-learn and TensorFlow libraries) under a “global training-local testing” strategy. The results show that GB consistently achieved the highest predictive accuracy across all provinces, with R2 values ranging from 0.96 to 0.99, mean absolute error (MAE) between 3.6 and 6.8 kg da-1, and root mean square error (RMSE) below 7.1 kg da-1. The RF model performed slightly lower (R2= 0.81-0.90) yet remained robust in most regions. In contrast, the global MLP model exhibited heterogeneous performance, particularly in Karaman Province, where non-climatic management factors dominate (R2= -1.25; MAE ˜ 26 kg da-1). When retrained with local data, the MLP model’s accuracy improved substantially, raising R2 to 0.79 and reducing MAE to approximately 10-15 kg da-1. These findings confirm that integrating phenological segmentation within ensemble learning approaches-particularly Gradient Boosting-substantially enhances wheat yield forecasting performance. The study highlights the importance of local calibration to capture irrigation and management effects and provides a robust methodological foundation for developing climate-resilient agricultural decision-support systems.

In this study, it was aimed to examine academic publications on egg consumption in Türkiye published in the TR Index database between 2000 and 2025 through bibliometric analysis, revealing research trends and scientific impact. In this context, the distribution of publications by year, the number of authors, the most productive authors and institutions were evaluated, and the most cited studies were revealed. Additionally, trends in research topics were analyzed with the help of keyword cloud and co-word analysis; regional research trends and potential gaps were revealed with the research region analysis. The findings indicate that research on egg consumption has focused primarily on nutrition, consumption, and consumer habits and behavior. In addition, the regional analysis revealed that research activities were concentrated in the Marmara and Central Anatolia regions of Türkiye, while they were more limited in the Eastern Anatolia region. The study will provide an overview of the existing literature, guiding future research.

COBL genes play an important role in the biosynthesis of cellulose, the main component of the cell wall. This study aimed to identify and characterize members of the COBL gene family that have not been characterized in the spinach genome. Eleven COBL members carrying the COBRA and/or COBL domains were found in the spinach genome. Among the So-COBL proteins, So-COBL1 and So-COBL2 are unstable. All So-COBL proteins are hydrophilic and, with aliphatic indices below 100, are not heat-stable. Both tandem and segmental duplications have occurred during the evolution of So-COBL genes. Because the Ka/Ks ratio is less than one, they have been subjected to purifying selection throughout evolution, eliminating deleterious variants. So-COBL genes contain cis elements in their promoter region that respond to many environmental stimuli, particularly hormone and light responses. Phylogeny analysis of spinach, Arabidopsis, and quinoa COBL genes revealed two groups, COBRA and COBL7-like. The intron-exon organization, motif, and domain structure of the genes grouped in the same group are similar. Synteny analysis revealed further orthology between quinoa and spinach. This study highlights the importance of COBL genes for future studies.

The aim of this article is to reveal how to determine the easement expropriation value on land allocated to perennial crops with an example. In the determination of the easement expropriation value, the net income obtained from the land is considered as defined by the Expropriation Law. The facilities subject to easement expropriation have been constructed below and above the ground for permanently and temporarily. The easement value is a negative net income calculated by subtracting the net income before the easement from the net income after the easement. Incorrect determination of the easement value will not only lead to unfairness between the parties, but will also cause increases in investment cost, prolong cases, and delays investments. In this respect, using the correct method in determination of the easement value has great importance. The net income becomes negative during the establishment period in fruit trees and until the cutting age period in non-fruit trees. Furthermore, net income shows differences among years during the production period in fruit trees. In perennial crops, the easement value varies significantly depending on the age of the orchard in the year the easement expropriation begins. Therefore, determination of the easement value for perennial crops is more difficult and complex compared to annual crops. In the easement expropriation on perennial crops, cultivation of annual crops is usually allowed. In this case, the authority conducting the easement expropriation will pay a lower easement value, and the landowner will continue agricultural production. In this context, determination of an easement value that maintains the balance of interests between the authority conducting the easement expropriation and landowner is important. It is expected that this article will help to take away different evaluations concerning the method used for determination of the easement value.

This review discusses advanced technologies widely used in field crop production, including geographic information systems, remote sensing, unmanned aerial vehicles, variable rate application systems, yield monitoring technologies, agricultural robots, artificial intelligence, machine learning, the Internet of Things, and digital image processing. It examines the contributions of these technologies to agricultural production processes through practical applications. The agricultural sector faces various challenges such as the growing global population, climate change, limited natural resources, and increasing input costs. In this context, the integration of smart agricultural technologies has become inevitable to ensure the sustainability of production and to manage resource utilization in the most efficient way. Current findings indicate that smart agricultural technologies increase productivity, optimize production costs, and reduce environmental impacts as well as dependency on labor. Furthermore, these technologies strengthen agricultural decision support systems and contribute significantly to the development of production models aligned with sustainable development goals. The findings emphasize the necessity of digital transformation in field crop cultivation and demonstrate that the widespread adoption of these technologies has the potential to enhance agricultural competitiveness.

Climate change resulting from anthropogenic global warming has led to significant environmental challenges. According to the World Meteorological Organization (WMO), 2024 was recorded as the hottest year with a global temperature increase of 1.5 °C. The 2025 data indicate that the global average temperature is approximately 1.55 ± 0.13 °C higher than the pre-industrial period (1850-1900). The Food and Agriculture Organization reports that the livestock sector contributes about 7.1 gigatons of carbon dioxide equivalent (CO2-eq) greenhouse gas emissions annually, representing roughly 14.5% of total anthropogenic emissions. Approximately 44% of total greenhouse gas emissions come from methane (CH4) produced by enteric fermentation in ruminant animals, 23.3% come from CH4 and nitrous oxide (N2O) resulting from inadequate manure management practices, and 9% come from emissions related to feed production and land use. Among farm animals, cattle account for the highest share of emissions (62%), followed by pigs (14%), chickens (9%), buffalo (8%), and sheep and goats (7%). The lower emissions from sheep and goats are related to extensive grazing and reliance on natural pastures. Climate change causes yield losses due to heat stress, a decrease in the nutritional quality of animal products, a decline in reproductive performance in animals, negative effects on animal welfare, an increase in zoonotic diseases, and creates conditions conducive to the vector-borne spread of these diseases. It also leads to multifaceted negative consequences such as deterioration in pasture quality, reduction in forage crops, and threats to economic agricultural sustainability and global food security. While climate change negatively affects animal production, greenhouse gas emissions from animal production also directly trigger climate change, creating a two-way causal relationship. This dialectical relationship highlights the need for structural transformation in industrial livestock systems and necessitates a transition to ecologically based, natural production models. The aim of this study is to assess the effects of climate change on animal production and the contribution of livestock-related greenhouse gas emissions to global warming from a holistic perspective.