Frontiers in Remote Sensing, 2023 The fast and accurate yield estimates with the increasing availability and variety of global satellite products and the rapid development of new algorithms remain a goal for precision agriculture and food security.
Maninder Singh Dhillon +6 more
doaj +2 more sources
Crop science experiments designed to inform crop modeling [PDF]
Agricultural and Forest Meteorology, 2013 Crop growth simulation models are a useful tool to assess the impact of environment, crop management, genetics and breeding strategies, as well as climate change and variability on growth and yield. Any crop science experiment that measures key physiological processes, tests these productive processes, their interaction with other processes ...
Craufurd, Peter Q. +4 more
openaire +3 more sources
Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt. [PDF]
Sci Rep, 2021 This study investigates whether coupling crop modeling and machine learning (ML) improves corn yield predictions in the US Corn Belt. The main objectives are to explore whether a hybrid approach (crop modeling + ML) would result in better predictions ...
Shahhosseini M +3 more
europepmc +3 more sources
A time-dependent parameter estimation framework for crop modeling. [PDF]
Sci Rep, 2021 The performance of crop models in simulating various aspects of the cropping system is sensitive to parameter calibration. Parameter estimation is challenging, especially for time-dependent parameters such as cultivar parameters with 2–3 years of ...
Akhavizadegan F +4 more
europepmc +2 more sources
Combining machine learning and remote sensing-integrated crop modeling for rice and soybean crop simulation. [PDF]
Front Plant SciMachine learning (ML) techniques offer a promising avenue for improving the integration of remote sensing data into mathematical crop models, thereby enhancing crop growth prediction accuracy.
Ko J, Shin T, Kang J, Baek J, Sang WG.
europepmc +2 more sources
Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling. [PDF]
Front Plant Sci, 2018 Heliaphen is an outdoor platform designed for high-throughput phenotyping. It allows the automated management of drought scenarios and monitoring of plants throughout their lifecycles. A robot moving between plants growing in 15-L pots monitors the plant
Gosseau F +12 more
europepmc +2 more sources
Integrating Plant Science and Crop Modeling: Assessment of the Impact of Climate Change on Soybean and Maize Production. [PDF]
Plant Cell Physiol, 2017 Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world.
Fodor N +6 more
europepmc +2 more sources
Lessons from climate modeling on the design and use of ensembles for crop modeling. [PDF]
Clim Change, 2016 Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer ...
Wallach D +4 more
europepmc +2 more sources
Cropbox: a declarative crop modeling framework
bioRxiv, 2022 Crop models mirror our knowledge on crops in silico. Therefore, crop modeling inherits common issues of software engineering and often suffers from technical debts.
Kyungdahm Yun, Soo-Hyung Kim
semanticscholar +1 more source
A comprehensive uncertainty quantification of large-scale process-based crop modeling frameworks
Environmental Research Letters, 2021 Regional and global impact assessment tools are increasingly used to explore and evaluate the impact of climate change and extreme events on crop yield and environmental externalities.
Hamze Dokoohaki +4 more
semanticscholar +1 more source