Towards a multiscale crop modelling framework for climate change adaptation assessment

B Peng, K Guan, J Tang, EA Ainsworth, S Asseng… - Nature plants, 2020‏ - nature.com
Predicting the consequences of manipulating genotype (G) and agronomic management (M)
on agricultural ecosystem performances under future environmental (E) conditions remains …

Decomposing crop model uncertainty: A systematic review

R Chapagain, TA Remenyi, RMB Harris… - Field Crops …, 2022‏ - Elsevier
Crop models are essential tools for analysing the effects of climate variability, change on
crop growth and development and the potential impact of adaptation strategies. Despite their …

Maize yield and nitrate loss prediction with machine learning algorithms

M Shahhosseini, RA Martinez-Feria, G Hu… - Environmental …, 2019‏ - iopscience.iop.org
Pre-growing season prediction of crop production outcomes such as grain yields and
nitrogen (N) losses can provide insights to farmers and agronomists to make decisions …

[HTML][HTML] Effects of shade and deficit irrigation on maize growth and development in fixed and dynamic AgriVoltaic systems

IA Ramos-Fuentes, Y Elamri, B Cheviron… - Agricultural Water …, 2023‏ - Elsevier
Maize production is essential for global food security and represents a major supply in
several value chains. However, the projected effects of climate change are likely to decrease …

Predicting crop yields and soil‐plant nitrogen dynamics in the US Corn Belt

SV Archontoulis, MJ Castellano, MA Licht… - Crop …, 2020‏ - Wiley Online Library
Abstract We used the Agricultural Production Systems sIMulator (APSIM) to predict and
explain maize and soybean yields, phenology, and soil water and nitrogen (N) dynamics …

No perfect storm for crop yield failure in Germany

H Webber, G Lischeid, M Sommer… - Environmental …, 2020‏ - iopscience.iop.org
Large-scale crop yield failures are increasingly associated with food price spikes and food
insecurity and are a large source of income risk for farmers. While the evidence linking …

Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios

C Müller, J Franke, J Jägermeyr… - Environmental …, 2021‏ - iopscience.iop.org
Concerns over climate change are motivated in large part because of their impact on human
society. Assessing the effect of that uncertainty on specific potential impacts is demanding …

Soil organic matter as catalyst of crop resource capture

AE King, GA Ali, AW Gillespie… - Frontiers in …, 2020‏ - frontiersin.org
The positive effect of soil organic matter (SOM) on crop yield has historically been attributed
to the ability of SOM to supply crops with nitrogen and water. Whether management-induced …

[HTML][HTML] Mixing process-based and data-driven approaches in yield prediction

B Maestrini, G Mimić, PAJ van Oort, K **do… - European Journal of …, 2022‏ - Elsevier
Yield prediction models can be divided between data-driven and process-based models
(crop growth models). The first category contains many different types of models with …

Substantial differences in crop yield sensitivities between models call for functionality‐based model evaluation

C Müller, J Jägermeyr, JA Franke, AC Ruane… - Earth's …, 2024‏ - Wiley Online Library
Crop models are often used to project future crop yield under climate and global change and
typically show a broad range of outcomes. To understand differences in modeled responses …