Recep Tayyip Erdoğan Üniversitesi Kurumsal Akademik Arşivi
DSpace@RTEÜ, Recep Tayyip Erdoğan Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Molecular screening of diverse Tomato germplasm for root-knot nematode resistance using the Mi23 marker
(Elsevier, 2025) Mortazavi, Parnaz; Ali, Amjad; Tatar, Muhammed; Ölmez, Fatih; Altaf, Muhammad Tanveer; Nadeem, Muhammad Azhar; Baloch, Faheem Shehzad
Tomato (Solanum lycopersicum L.), an important vegetable and horticultural crop, provides significant health benefits. The quality and yield of tomato plants are drastically impacted by root-knot nematode (RKN) a group of obligate parasites. In the current study, 212 tomato genotypes collected from diverse geographical regions, including T & uuml;rkiye, France, Taiwan, and others, were molecularly screened using the Mi23 primer pair (Mi23-F/ Mi23-R) to detect the presence of the Mi-1.2 resistance gene. The results of the molecular screening revealed that a total of six genotypes: three homozygous genotypes, Romitel-RHT 3 (France), AVTO0102-CLN2366B, and AVTO0101-CLN2413D (Taiwan), and three heterozygous genotypes, Aysbars-F1, Italian Field (To-23), and Red Pole (To-25) (T & uuml;rkiye) amplified with a required band size of 380 bp. Notably, 206 genotypes including those from the USA Germany, and Kyrgyzstan, lacked the Mi-1.2 resistance gene, exhibiting susceptibility to RKN. These findings highlight the significance role of molecular markers in identifying and utilizing nematoderesistant genes to enhance tomato breeding programs for robust and disease-resistant cultivars.
Population structure of the invasive Asian Tiger Mosquito, Aedes albopictus, in Europe
(Wiley, 2025) Corley, Margaret K; Cosme, Luciano Veiga; Armbruster, Peter A.; Beebe, Nigel; Bega, Anna; Akıner, Muhammet Mustafa; Caccone, Adalgisa
The Asian tiger mosquito, Aedes albopictus, is currently the most widespread invasive mosquito species in the world. It poses a significant threat to human health, as it is a vector for several arboviruses. We used a SNP chip to genotype 748 Ae. albopictus mosquitoes from 41 localities across Europe, 28 localities in the native range in Asia, and 4 in the Americas. Using multiple algorithms, we examined population genetic structure and differentiation within Europe and across our global dataset to gain insight into the origin of the invasive European populations. We also compared results from our SNP data to those obtained using genotypes from 11 microsatellite loci (N = 637 mosquitoes from 25 European localities) to explore how sampling effort and the type of genetic marker used may influence conclusions about Ae. albopictus population structure. While some analyses detected more than 20 clusters worldwide, we found mosquitoes could be grouped into 7 distinct genetic clusters, with most European populations originating in East Asia (Japan or China). Interestingly, some populations in Eastern Europe did not share genetic ancestry with any populations from the native range or Americas, indicating that these populations originated from areas not sampled in this study. The SNP and microsatellite datasets found similar patterns of genetic differentiation in Europe, but the microsatellite dataset could not detect the more subtle genetic structure revealed using SNPs. Overall, data from the SNP chip offered a higher resolution for detecting the genetic structure and the potential origins of invasions.
Brewing contradictions: state intervention and commodity dynamics in tea agriculture in Turkey
(John Wiley and Sons Inc, 2025) Karaçimen, Elif; Değirmenci, Ekin
This study reevaluates the perceived decline of state involvement in agriculture and examines the contradictions of state intervention within neoliberal contexts through a commodity-specific analysis of tea production in Turkey. Based on fieldwork in Rize, which produces 65% of the country's tea and plays a central role in a nation with the highest per capita tea consumption globally, the study highlights the Turkish state's contradictory approach. This approach oscillates between aligning with the interests of capital and those of petty-commodity producers, often resulting in unsustainable outcomes and abrupt policy shifts shaped by the specificities of tea as a commodity, including its perishability, seasonality and low maintenance requirements. Labour strategies add another layer of contradiction, with the state actively facilitating migrant labour supply for harvesting when possible, while at other times turning a blind eye to irregular migration and informal labour markets controlled by brokers. This dual approach suppresses production costs and supports the continuity of smallholder tea cultivation, yet increasingly reinforces reliance on precarious and fragmented labour markets. The findings contribute to broader discussions on state involvement in agriculture, highlighting how policy, commodity traits and social class dynamics interact to shape sectoral outcomes.
The effects of ai-supported autonomous irrigation systems on water efficiency and plant quality: a case study of geranium psilostemon ledeb
(Multidisciplinary Digital Publishing Institute (MDPI, 2025) Ercan Oğuztürk, Gülcay; Murat, Caner; Yurtseven, Meryem; Oğuztürk, Türker
This study investigates the effects of an AI-supported irrigation system on the production of natural plant species and irrigation efficiency at Rize Recep Tayyip Erdoğan University. To enhance water resource efficiency while utilizing Turkey’s rich plant diversity, Geranium psilostemon Ledeb. (Black-Eyed Crane’s-Bill) was selected for cultivation. The research includes adaptation trials and growth monitoring of this perennial taxon, which naturally grows at an altitude of 2000 m. The experiments were conducted in two different environments: one utilizing an AI-supported irrigation system and the other relying on manual irrigation. The findings reveal that AI-supported irrigation systems optimize irrigation strategies, providing a more efficient and effective plant cultivation process compared to manual irrigation. The AI-supported irrigation system continuously monitors air and soil moisture levels, ensuring optimal irrigation conditions and instant adaptation to seasonal variations. This innovative approach minimizes water losses while preventing soil salinization, thereby offering a significant solution for sustainable agricultural practices. In conclusion, this study demonstrates that natural plant species can be effectively cultivated using AI-supported irrigation systems and that these systems hold great potential for water conservation and ecological balance. These findings present a crucial step toward developing effective solutions for global water challenges and promoting sustainable landscape and agricultural practices.
Mapping artificial intelligence adoption in hepatology practice and research: challenges and opportunities in MENA region
(Frontiers Media SA, 2025) El-Kassas, Mohamed; Khalifa, Rofida; Medhat, Mohammed A.; Yılmaz, Yusuf; Tumi, Ali; Labidi, Asma; AlNaamani, Khalid M.
Background: Artificial intelligence (AI) is increasingly relevant to hepatology, yet real-world adoption in the Middle East and North Africa (MENA) is uncertain. We assessed awareness, use, perceived value, barriers, and policy priorities among hepatology clinicians in the region. Methods: A cross-sectional online survey targeted hepatologists and gastroenterologists across 17 MENA countries. The survey assessed clinical and research applications of AI, perceived benefits, clinical and research use, barriers, ethical considerations, and institutional readiness. Descriptive statistics and thematic analysis were performed. Results: Of 285 invited professionals, 236 completed the survey (response rate: 82.8%). While 73.2% recognized the transformative potential of AI, only 14.4% used AI tools daily, primarily for imaging analysis and disease prediction. AI tools were used in research by 39.8% of respondents, mainly for data analysis, manuscript writing assistance, and predictive modeling. Major barriers included inadequate training (60.6%), limited AI tool access (53%), and insufficient infrastructure (53%). Ethical concerns focused on data privacy, diagnostic accuracy, and over-reliance on automation. Despite these challenges, 70.3% expressed strong interest in AI training., and 43.6% anticipating routine clinical integration within 1–3 years. Conclusion: MENA hepatologists are optimistic about AI but report limited routine use and substantial readiness gaps. Priorities include scalable training, interoperable infrastructure and standards, clear governance with human-in-the-loop safeguards, and region-specific validation to enable safe, equitable implementation.
