Search Results - "Artificial Intelligence"

Rice-fish coculture: Enhancing resource management and food security by Samaddar, Ayan, Kacha, Dani, Kaviraj, Anilava, Freed, Sarah Johanna, Panemangalore, Arun Padiyar, Saha, Subrata

“…Then, we analyzed the data by applying artificial intelligence and machine learning algorithms to identify the stresses and recommend guidelines to improve farmers' management and decision-making for sustainable rice-fish coculture. …”
Get full text

Business Investment Decision (BID) Tool for strengthening seed business by Jayanth, R., Rajendran, S.

“…Future development plans include expanding the web version, integrating artificial intelligence for industry comparisons and strategy formulation, incorporating real-time data, and enabling seamless integration with accounting systems. …”
Get full text

Digital framework for georeferenced multiplatform surveillance of banana wilt using human in the loop AI and YOLO foundation models by Mora, Juan Jose, Blomme, Guy, Safari, Nancy, Elayabalan, Sivalingam, Selvarajan, Ramasamy, Selvaraj, Michael Gomez

“…Human in the Loop Artificial Intelligence was also utilized to enhance the ground level model’s predictions.…”
Get full text

Machine learning based groundwater prediction in a data-scarce basin of Ghana by Siabi, E. K., Dile, Y. T., Kabo-Bah, A. T., Amo-Boateng, M., Anornu, G. K., Akpoti, Komlavi, Vuu, C., Donkor, P., Mensah, S. K., Incoom, A. B. M., Opoku, E. K., Atta-Darkwa, T.

Get full text

Water-energy-food planning and operations framework for river basins with a case study on the Blue Nile by Basheer, Mohammed, Siddig, Khalid, Ringler, Claudia

“…In this study, we develop and apply a framework for water resources planning in the Blue Nile using four steps: (1) understanding the water-energy-food nexus management landscape through stakeholder engagement and literature review; (2) developing a detailed daily simulator that captures major nexus components and objectives at a fine temporal scale; (3) linking the simulator to an Artificial intelligence-based search algorithm to design efficient agricultural and dam operation portfolios considering national and sectoral priorities; and (4) presenting the results using interactive visualization tools to facilitate dialogue and support decisions. …”
Get full text

Un plan paso a paso para integrar el conocimiento adquirido en la parcela digital y diplomados en los programas académicos. by Lizarazo, Miguel, Ramos, Gresia Dalal, Bonilla, Melissa, Munoz, Luis Armando, Jimenez, Daniel Ricardo

“…The digital transformation of the agricultural sector in Latin America has driven the adoption of innovative technologies, including IoT, artificial intelligence, and remote sensing. However, in Guatemala, small and medium-sized producers face challenges in accessing and applying these technological tools to their production systems. …”
Get full text

Review of Climate-Resilient Agriculture for Ensuring Food Security: Sustainability Opportunities and Challenges of India by Sahoo, Satiprasad, Singha, Chiranjit, Govind, Ajit, Moghimi, Armin

“…Discussions indicated that empirical studies, clear sustainability indicators, and integration of advanced technology such as artificial intelligence and geo-spatial tools are needed to improve India’s adaptation strategies to climate change. …”
Get full text

Digital descriptors sharpen classical descriptors, for improving genebank accession management: A case study on Arachis spp. and Phaseolus spp. by Conejo-Rodriguez, Diego Felipe, Gonzalez-Guzman, Juan Jose, Ramirez-Gil, Joaquín Guillermo, Wenzl, Peter, Urban, Milan

“…Functional diversity indices are recommended to genebank curators to evaluate phenotypic variability to identify accessions with unique traits or identify accessions that represent the greatest phenotypic variation of the species (functional agrobiodiversity collections). The artificial intelligence algorithms are capable of characterizing accessions which reduces costs generated by additional phenotyping. …”
Get full text

AI-enabled UAV borne hyperspectral imaging for crop-livestock farm management by Sankararao, A.U.G., Rajalakshmi, P., Choudhary, Sunita, Kholova, Jana, Jones, Christopher S.

“…Hyperspectral imaging (HSI) sensors provide enriched spectral information, enabling more precise investigations into feed quality evaluation, forage management, and livestock health. Artificial intelligence and machine learning (AI/ML) approaches can effectively analyze high-dimensional HSI data and extract meaningful insights. …”
Get full text

Building resilient urban water systems: emerging opportunities for solving long-lasting challenges by Nlend, B., Reimuth, A., Yang, L. E., Jampani, Mahesh, Cristiano, E., Dewals, B., Boyer, E., Cetinkaya, I. D., Diémé, L. P., Dutta, R., Feng, W., Grossi, G., Nasr, W. B., Obaitor, O. S., Olusola, A. O., Panchanathan, A., Rab, G., Sharma, S., Wang, C., Warter, M. M., Welty, C., Tetzlaf, D.

“…Technological breakthroughs, such as smart sensors and artificial intelligence, can enhance the efficiency and resilience of real-time water monitoring and predictions. …”
Get full text

2024 Learning and Optimization Report by CGIAR System Organization

“…. • Systems – Advance PRMS v2 as a cohesive, user-centered platform, scale up artificial intelligence (AI) and automation to reduce reporting effort and enhance QA processes. • Capacity – Expand training and peer-learning opportunities, strengthen organizational support and engagement with Centers, and build skills for PRMS v2, AI tools, and adaptive management. • Products/Outputs – Improve report usability and readability, enhance trend analysis and Portfolio comparisons, integrate return on investment (ROI) analyses and impact/results stories, and pilot AI-generated report drafts and summaries to reduce effort and better tailor outputs to decision-makers. …”
Get full text

Statistics from Space: Next-Generation Agriculture Production Information for Enhanced Monitoring of Food Security in Mozambique - Groundtruthing data collection and stakeholder en... by Centre of Excellence in Agri-Food Systems and Nutrition

“…The Statistics from Space project (SFS) seeks to support the Government of Mozambique to produce and disseminate accurate crop production statistical data leveraging satellite remote-sensing data and artificial intelligence augmented analytics. The project, funded by the Government of the Republic of Korea (Ministry of Agriculture, Food and Rural Affairs; MAFRA), aims to provide the Mozambican Ministry of Agriculture and Rural Development with production estimates of major crops across three provinces namely Gaza, Manica and Zambezia in a sufficiently timely manner so that all market participants can use the information for decision-making. …”
Get full text

Scalable database for observed climate hazards and impacts, climate finance and climate litigation cases in Africa by Engdaw, Mastawesha Misganaw, Ghosh, Aniruddha, Chilambe, Pedro Anglaze

“…In the era of rapidly evolving, data-intensive artificial intelligence, Africa must transform from being data-lacking and externally dependent to becoming a continent of data ownership and ensure its digital sovereignty. …”
Get full text

Comparative performance of the objective vs. consensual seasonal climate forecasting approaches in West Africa and the Sahel by Tanimoune, Laouali I, Nimon, Pouwereou, Ali, Abdou, Houngnibo, Mandela C M, Alhassane, Agali, Mohamed, Hamatan, Soumana, Djibo, Assoumana, Boubacar Toukal, Segnon, Alcade Christel, Zougmore, Robert Bellarmin

“…AGRHYMET RCC-AOS, through the AICCRA project, has developed objective seasonal forecasting systems, combining advanced statistics, dynamical models, and artificial intelligence algorithms improving accuracy and reliability of climate forecasts across the region. …”
Get full text

A Comparative Study of Deep Learning Frameworks Applied to Coffee Plant Detection from Close-Range UAS-RGB Imagery in Costa Rica by Arriola-Valverde, Sergio, Rimolo-Donadio, Renato, Villagra-Mendoza, Karolina, Chacón-Rodriguez, Alfonso, García-Ramirez, Ronny, Somarriba, Eduardo

“…Introducing artificial intelligence techniques in agriculture offers new opportunities for improving crop management, such as in coffee plantations, which constitute a complex agroforestry environment. …”
Get full text

Management and agricultural water productivity improvement in India and the Ganges Basin by Sharma, Bharat, Sikka, Alok, Lautze, Jonathan F., Mabhaudhi, T.

“…A matrix approach was employed to compile and review the DSS with broader segregation under (i) crop and farm-based decision support systems, (ii) DSS based on artificial intelligence, enhanced machine learning, fuzzy multi-criteria decision making, and knowledge systems, (iii) DSS for real-time operation of micro-irrigation systems, (iv) DSS for management of tanks and reservoirs for water-deficit regions, and (v) DSS for improving water productivity under canal commands and conjunctive management of surface and groundwater resources. …”
Get full text

Oportunidades y desafíos de la Inteligencia Artificial en el sistema agrobioindustrial. Un estudio exploratorio by Cornejo, Karina De Lujan

Get full text

Clustering of facial action units in horses with pain by Silventoinen, Alina

“…Facial actions have been used together with artificial intelligence in order to evaluate pain in humans. …”
Get full text

Urban Farming: Production comparison of Basil and Oak Leaf lettuce in two hydroponic growing systems : an industrial collaborated study in Sweden by Malik, Omer Hafeez

“…Further studies are needed to investigate the crop production potential on commercial scale with precision farming, integration of AI (artificial intelligence) and IOT (internet of things) along with complete control on factors like temperature, humidity, CO2 levels, light and nutrients.…”

A bibliometric analysis of solar energy forecasting studies in Africa by Zwane, N., Tazvinga, H., Botai, C., Murambadoro, M., Botai, J., Wit, J. de, Mabasa, B., Daniel, S., Mabhaudhi, Tafadzwanashe

“…Three emerging topics were identified from the thematic map analysis— namely, “solar irradiance”, “artificial intelligence” and “clear sky”, which implies that researchers are paying attention to solar irradiance, using modelling techniques that incorporate machine learning techniques. …”
Get full text