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 …

Climate variability and vulnerability to climate change: a review

PK Thornton, PJ Ericksen, M Herrero… - Global change …, 2014 - Wiley Online Library
The focus of the great majority of climate change impact studies is on changes in mean
climate. In terms of climate model output, these changes are more robust than changes in …

The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution

H Badouin, J Gouzy, CJ Grassa, F Murat, SE Staton… - Nature, 2017 - nature.com
The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for
climate change adaptation, because it can maintain stable yields across a wide variety of …

A meta-analysis of crop yield under climate change and adaptation

AJ Challinor, J Watson, DB Lobell, SM Howden… - Nature climate …, 2014 - nature.com
Feeding a growing global population in a changing climate presents a significant challenge
to society,. The projected yields of crops under a range of agricultural and climatic scenarios …

Climate change impacts on crop yields: A review of empirical findings, statistical crop models, and machine learning methods

T Hu, X Zhang, S Khanal, R Wilson, G Leng… - … Modelling & Software, 2024 - Elsevier
Understanding crop responses to climate change is crucial for ensuring food security. Here,
we reviewed∼ 230 statistical crop modeling studies for major crops and summarized recent …

Agriculture in West Africa in the twenty-first century: climate change and impacts scenarios, and potential for adaptation

B Sultan, M Gaetani - Frontiers in plant science, 2016 - frontiersin.org
West Africa is known to be particularly vulnerable to climate change due to high climate
variability, high reliance on rain-fed agriculture, and limited economic and institutional …

A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level

H Jiang, H Hu, R Zhong, J Xu, J Xu… - Global change …, 2020 - Wiley Online Library
Understanding large‐scale crop growth and its responses to climate change are critical for
yield estimation and prediction, especially under the increased frequency of extreme climate …

Ozone pollution will compromise efforts to increase global wheat production

G Mills, K Sharps, D Simpson, H Pleijel… - Global change …, 2018 - Wiley Online Library
Introduction of high‐performing crop cultivars and crop/soil water management practices that
increase the stomatal uptake of carbon dioxide and photosynthesis will be instrumental in …

[HTML][HTML] Contribution of remote sensing on crop models: a review

DA Kasampalis, TK Alexandridis, C Deva… - Journal of …, 2018 - mdpi.com
Crop growth models simulate the relationship between plants and the environment to predict
the expected yield for applications such as crop management and agronomic decision …

Can farmers' adaptation to climate change be explained by socio-economic household-level variables?

TB Below, KD Mutabazi, D Kirschke, C Franke… - Global environmental …, 2012 - Elsevier
A better understanding of processes that shape farmers' adaptation to climate change is
critical to identify vulnerable entities and to develop well-targeted adaptation policies …