Machine Learning Approaches for Forecasting the Best Microbial Strains to Alleviate Drought Impact in Agriculture
Tymoteusz Miller(University of Szczecin), Adam Brysiewicz(Institute of Technology and Life Sciences), Danuta Cembrowska-Lech(University of Szczecin), Dominika Paliwoda(West Pomeranian University of Technology in Szczecin), Lidia Sas‐Paszt(Instytut Ogrodnictwa – Państwowy Instytut Badawczy), Agnieszka Kozioł(Institute of Technology and Life Sciences), Grzegorz Mikiciuk(West Pomeranian University of Technology in Szczecin), Małgorzata Mikiciuk(West Pomeranian University of Technology in Szczecin), Adrianna Krzemińska(University of Szczecin), Anna Kisiel(University of Szczecin)
Cited by 26
Related Papers
The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies
|Sensors|2025|151
Integrating Artificial Intelligence Agents with the Internet of Things for Enhanced Environmental Monitoring: Applications in Water Quality and Climate Data
|Electronics|2025|141
An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture
|Biology|2023|138
IoT in Water Quality Monitoring—Are We Really Here?
|Sensors|2023|90
Navigating the Sea of Data: A Comprehensive Review on Data Analysis in Maritime IoT Applications
|Applied Sciences|2023|74