Search Results - Sliven~

Transforming soil quality index predictions in the Nile River Basin using hybrid stacking machine learning techniques by Singha, Chiranjit, Sahoo, Satiprasad, Govind, Ajit

“…Soil Quality Index (SQI) was assessed in Egypt’s Nile River Basin using 266 surface samples (0–30 cm depth) collected between 2021 and 2022. Eleven key soil quality indicators such as bulk density (BD), sand, silt, clay, pH, electrical conductivity (EC), organic carbon (OC), calcium (Ca), nitrogen (N), phosphorus (P), and potassium (K) were analyzed to estimate the observed SQI (SQIobs) using a PCA-based scoring method and geostatistical techniques. …”
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Options for methane mitigation in China's rice sector by Yang, Jintao, Zhang, Yumei, Zhang, Ruizeng, Fan, Shenggen, Zhou, Sheng, Li, Yangyang, Wang, Bin, Yang, Xiaoguang, Chen, Kevin Z.

“…Model simulations indicate that, due to a declining population and reduced rice consumption, methane emissions could decline by 15.9% in 2035 and by 35.4% in 2060, even without improvements in emission intensity reduction, driven primarily by a reduction in the cultivated area. …”
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Understanding Farmer Preferences through Citizen Science: Insights on Potato Varieties in Nigeria by Sharma, K., Atieno, E., Sousa, K. de, Etten, Jacob van, Nyawade, S.

“…This study highlights the value of participatory, data-driven breeding that integrates local knowledge to enhance adoption, resilience, and food security.…”
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Incorporating dynamic crop area in hydrological model to address interannual variability in water withdrawal and implication of sustainable water management by Umer, M., Hanasaki, N., Gopalan, S. P., Ali, Zeshan, Oki, T.

“…Water security assessments are critical for policymakers in agriculture-dominated regions, where water demand and withdrawals continuously change due to crop area variations driven by farmers’ decisions. However, hydrological models often assume fixed crop areas, resulting in unrealistic estimates of water demand, withdrawals, and related scarcity. …”
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Prevalence and antimicrobial resistance in enterococci isolated from semi-intensive and free-range poultry farms in peri-urban Wakiso and rural Soroti, Uganda by Ochieng, Linnet, Ayebare, Dreck, Ndoboli, Dickson, Mbatidde, Irene, Tenhagen, B.-A., Roesel, Kristina, Wampande, E., Moodley, Arshnee

“…Only 3.3% of the isolates were multidrug-resistant. Eleven acquired resistance genes were detected, with <i>tetL</i> and <i>tetM</i> showing significant distribution differences between systems. …”
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Tackling irrigation development and water management crises in Africa by Zemadim, Birhanu, Haileslassie, Amare, Dirwai, Tinashe Lindel, Gebrezgabher, Solomie A., Akpoti, Komlavi, Osei-Amponsah, Charity, Cofie, Olufunke O., Hafeez, Mohsin, Smith, Mark

“…Addressing Africa’s irrigation development and water management crises requires an integrated approach that combines technological innovation, robust policy reforms, and farmer-led or community-driven water stewardship, with a focus on inclusion to build resilience against the impacts of climate variability.…”
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Technological innovations in freeze drying: Enhancing efficiency, sustainability, and food quality by Al Faruq, Abdulla, Farahnaky, Asgar, Dokouhaki, Mina, Khatun, Husne Ara, Trujillo, Francisco J., Majzoobi, Mahsa

“…Recent trends also include the application of artificial intelligence (AI) and machine learning to model, monitor, and optimise FD processes, enabling data-driven decision-making and improved process control. …”
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Thermal bioclimatic transformations in the coastal regions of Ganges delta: insights from CMIP6 multi-model ensemble by Islam, H. M. Touhidul, Mainuddin, Mohammed, Affan, Abu, Ahmed, Sharif, Rahman, Md. Abiar, Sadeque, Abdus, Almazroui, Mansour, Rahman, S. M. Hasibur, Kamruzzaman, Mohammad

“…This study employs a multi-model ensemble of sixteen CMIP6 global climate models to assess future changes in eleven TBIs under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. …”
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Opportunities, challenges, and interventions for agriculture 4.0 adoption by Vijayakumar, Shanmugam, Murugaiyan, Varunseelan, Ilakkiya, S., Kumar, Virender, Sundaram, Raman Meenakshi, Kumar, Rapolu Mahender

“…Agriculture 4.0, a data-driven transformation, addresses these issues through modern technologies like Internet of Things (IoT), artificial intelligence (AI), big data analytics, unmanned aerial vehicles (UAVs), and agricultural robots. …”
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Testing and piloting the landscape management tracking system in the Central and South Regions of Ethiopia. Activity Report by Adimassu, Zenebe, Tibebe, Degefie, Kebede, Fikiru, Abera, Wuletawu, Demeke, Getamesay, Gizaw, Solomon, Balcha, Matewos, Tamene, Lulseged

“…Overall, the pilot demonstrated the digital tracking system’s potential to enhance SWC/CSA monitoring, improve data accuracy, and empower local users through technology-driven solutions.…”
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Assessment of combined nutrients and pesticides grey water footprint in a Sub-Saharan African lake catchment by Onyango, J., Simaika, John, Kitaka, N., Irvine, K.

“…These findings highlight pollution hotspots in low-flow sub-catchments, driven by intensive farming and settlements, and underscore the urgent need for integrated water quality standards and advanced monitoring strategies to safeguard aquatic ecosystems and promote sustainable water management in sub-Saharan Africa.…”
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COVID-19 and rural livelihoods: Lessons from a longer-term assessment and the path to recovery by Berrospi, Maria Lucia, Ceballos, Francisco, Hernandez, Manuel A., Paz, Cynthia

“…The households that were initially more affected in terms of food security and nutrition but recovered faster include those located in one of the three studied departments and families living above the poverty line, while smallholders affected by hurricanes, non-coffee producers, and indigenous populations took longer to recover. …”
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Building institutional synergies for agricultural research and development in Ghana: The case of the cropping calendar agro-advisory by Amankwaa-Yeboah, Patricia, Ofosu-Ampong, Kingsley, Masoud, Jalaludeen, Jizorkuwie, Abdul-latif Baamonyor, Wilson, Michael, Ampadu-Boakye, Theresa, Abera, Wuletawu

“…This paper presents the co-development and early scaling of a dynamic cropping calendar and bundled agro-advisory tool, a partnership-driven innovation led by CSIR-INSTI, CSIR-CRI, CSIR-Soil Research Institute, the Ministry of Food and Agriculture (MoFA), and the Alliance of Bioversity International and CIAT, under the CGIAR Excellence in Agronomy Initiative. …”
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Contrasting carbon and water flux dynamics in an East African rangeland and cropland by Odongo, Vincent O., Leitner, Sonja, Dowling, T.P.F., Gluecks, Ilona V., Jackowicz-Korczynski, M., Rinne, J., Wooster, M.J., Merbold, Lutz

“…Cropland demonstrated higher carbon use efficiency (CUE), driven by efficient C allocation for crop growth, supported by fertilizers, pesticides, and minimum tillage practices. …”
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Environmental and social considerations in hydropower development in the South Asian Himalayas: a NEXUS perspective by Bhandari, R., Neupane, N., Shrestha, Shisher, Chauhan, D., Pokharel, D., Xue, W.

“…Even though climate change has significantly altered river flow regimes and heightened the risks of glacial lake outburst floods (GLOFs), the study finds that the integration of robust climate risk assessments across the region remains in its infancy and is often regarded as unnecessary. Sedimentation, driven by Himalayan geology, and climate-induced erosion, reduces reservoir capacity and damage turbines with studies indicating up to 25% capacity loss in projects like Kulekhani, Nepal due to inadequate sediment management. …”
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Why AWD isn't taking off: Understanding barriers and pathways for scaling in gravity-fed irrigation systems in rice landscape by Evangelista, Gio Karlo, Samoy-Pascual, Kristine, Cabangon, Romeo J., Regalado, Manuel J., Enriquez, Yuji, Lampayan, Rubenito, Rala, Arnel, Yadav, Sudhir

“…However, adoption was constrained by elevation-driven water flow patterns, clay distribution, tenant-operated plots, and rigid rotational schedules. …”
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Comparing a multi-item Rasch scale for purchase intentions with preference elicitation using experimental auctions for consumer acceptance of biofortified food: An in-store study i... by Lagerkvist, C., Okello, J.J., Ojwang, S., Mwizerwa, H., Nshimiyimana, J.C., Ndirigwe, J., Shingiro, J.B., Low, J.W.

“…Including the measurement uncertainty reverses the extent to which the choice to bid and the bid amount within the BDM are driven by separate processes. Moreover, while actual liking helped predict purchase intentions, no evidence was found of such association for nutritional beliefs. …”
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Water insecurity in Sri Lanka, 2024-2025: Evidence from the 2024-2025 BRIGHT survey by Stifel, Elizabeth, Headey, Derek D., Hülsen, Vivien, Munasinghe, Dilusha, Ranucci, Immacolata, Sabai, Moe, van Asselt, Joanna, Weerasinghe, Krishani

“…Estate sector households show the greatest relative improvement, with the share using improved water sources increasing by approximately five percentage points. This shift is driven primarily by a 15-percentage-point rise in the use of protected wells, although nearly half (49%) of estate households continue to rely on rivers, springs, or tank water. • Most households in Sri Lanka report few insecurity experiences, and are therefore mostly water secure, with 90% not experiencing water insecurity. • Differences between groups are subtle and occur mainly between marginal and low levels of water security, rather than between fully secure and insecure households. • 68% of estate households (households on plantations), experienced at least water insecurity experience compared to only 28% of urban households and 33% of rural households. • Households in dry agroecological zones face slightly higher risks water insecurity (11%) com-pared to 9% of in both intermediate and wet zones. • Poverty is a key predictor of water insecurity. …”
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Hydrological modelling for a resilient future: innovations at the water-climate nexus by Sikka, Alok, Yadav, Shweta, Alam, Mohammad Faiz, Ghosh, Surajit, Bhatpuria, Dhyey, Padhee, Suman Kumar, Sahana, V., Pandey, Shivam, Sena, Dipaka Ranjan

“…The session showcased cutting-edge modelling tools, data-driven approaches, and interdisciplinary methods to tackle emerging water challenges under climate change. …”
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Measuring smallholder dairy farmers’ social valuation of climate mitigation: A case study from Kenya by Florez, Jesus Fernando, Gonzalez Quintero, Ricardo, Pazos Cardenas, Mateo, Triana Ángel, Natalia, Enciso, Valentina, Waluse, Kenneth, Notenbaert, An, Burkart, Stefan

“…Support for improved forages is nonetheless strong, driven by perceived gains in productivity and environmental sustainability. …”
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