Marco Fiorentini

MineTRACE: An Evidence-Grounded Interactive Reasoning System for Mineral Prospectivity

Yiran Zhang, Jinwen Liu, Daniel Su, Yisu Chen et autres

Mineral exploration requires integrating heterogeneous geochemical, geophysical, and geological evidence, yet existing prospectivity systems often provide only opaque scores or heatmaps. We present MineTRACE, a web-based system for evidence-grounded exploration of eight commodities: Cu, Au, Ni, W, Sn, Co, Ta, and Mn. …

Late Archean Mantle Evolution Inferred From Highly Siderophile Element Geochemistry Of Komatiites And Basalts In Yilgarn Craton Western Australia

Rhys Clifford, Akira Ishikawa, Marco Fiorentini, Nicolas Thebaud et autres

Protracted Neoarchean high-temperature–moderate-pressure metamorphism recorded in the granulite-facies Katanning Gold Deposit, Southwest Yilgarn Craton, Western Australia

Jonathan Garcia, Naomi Tucker, Margaux Le Vaillant, Helen B. McFarlane et autres

The 1.33 Moz Katanning Gold Deposit (KGD) is hosted by Neoarchean granulite-facies volcanosedimentary rocks of the Katanning Greenstone Belt (KGB), Southwest Yilgarn Craton, Western Australia. The pressure–temperature-time (P-T-t) evolution of these high-grade metamorphic rocks remains poorly constrained, limiting our understanding of the …

au, fi (code pays fourni par la source)

Dataset for: Multi-Data Source-Based Machine Learning Modelling Framework for Remote Estimation of Soil Organic Carbon and Carbon Credits Validation

Marco Fiorentini, Matteo Francioni, Stefano Zenobi, Chiara Rivosecchi et autres

Dataset used for the scientific work entiled "Multi-Data Source-Based Machine Learning Modelling Framework for Remote Estimation of Soil Organic Carbon and Carbon Credits Validation" The estimation of the soil organic carbon (SOC) using remotely sensed data is playing an increasingly important role …

Dataset for: Multi-Data Source-Based Machine Learning Modelling Framework for Remote Estimation of Soil Organic Carbon and Carbon Credits Validation

Marco Fiorentini, Matteo Francioni, Stefano Zenobi, Chiara Rivosecchi et autres

Dataset used for the scientific work entiled "Multi-Data Source-Based Machine Learning Modelling Framework for Remote Estimation of Soil Organic Carbon and Carbon Credits Validation" The estimation of the soil organic carbon (SOC) using remotely sensed data is playing an increasingly important role …

Metallogenic potential of komatiites from the Shankaraghatta Complex, Western Dharwar Craton (Southern India)

Ria Mukherjee, Marco Fiorentini, Laure Martin, Robert Frei et autres

in, au, dk (code pays fourni par la source)

Geodynamic Controls on Magmatic Ni-Cu-Platinum Group Element Sulfide Mineral Systems Through Time

David A. Holwell, Daryl E. Blanks, Marco Fiorentini, Erin S. Thompson et autres

Abstract Most models for the formation of magmatic Ni-Cu-platinum group element (PGE) sulfide deposits invoke high-temperature events (e.g., plumes) to sufficiently melt enough peridotite mantle to produce MgO- and Ni-Cu-PGE–rich magmas, and the deposits are thus intrinsically linked to the emplacement of …

gb, au (code pays fourni par la source)

IoT system for Precision Viticulture: Multi-Pathogen Detection and Yield Mapping via State-Of-The-Art Object Detection Model and Georeferenced Inference

Lindo Nepi, Marco Fiorentini, Adriano Mancini, Luigi Ledda et autres

it (code pays fourni par la source)

Evaluation of the most scalable, accurate and cost trade-offs machine learning framework to estimate the Mediterranean wood-pasture yield

Marco Fiorentini, Marco Cossu, Maria Teresa Tiloca, Stefano Lupinu et autres

Abstract Purpose Sustainable grazing management requires precise knowledge of daily nutritional requirements and the quantity and quality of pasture dry matter. Combining multiple data sources with machine learning models can create accurate predictive systems to optimize feeding, cut expenses, and maintain pasture …

it (code pays fourni par la source)

Assessing climate change impacts on Mediterranean durum wheat using DSSAT-CERES-Wheat across contrasting environments

Chiara Rivosecchi, Marco Bianchini, Michele Denora, Biagio di Tella et autres

The Mediterranean basin is a climate change hotspot, and this will strongly affect key crops such as durum wheat, a staple for millions and a major commodity in southern Europe. Future productivity remains uncertain, as climate change introduces both limiting and beneficial …

it (code pays fourni par la source)

Smart Agriculture Insurance Based on Artificial Intelligence – Object Detection

Marco Fiorentini, Stefano Zenobi, Federico Mammarella, Matteo Francioni et autres

Abstract Climate change and extreme weather events, such as hailstorms, increasingly threaten high-value crops like grapes, causing substantial yield losses and economic risks for farmers. Traditional damage assessment methods, typically based on manual field inspections, are time-consuming, subjective, and error-prone, leading to …

it (code pays fourni par la source)

Multi-source data and machine learning for Mediterranean wood-pastures biomass estimation

Marco Cossu, Marco Fiorentini, Maria Teresa Tiloca, S. Lupinu et autres

The aim was to develop a machine-learning framework to predict the biomass yield of Mediterranean wood-pastures, by using a multi-data source approach composed of remote sensing and climate data. The ensemble learner was the best model to predict the dry weight biomass …

it (code pays fourni par la source)