[HTML][HTML] Machine learning in crop yield modelling: A powerful tool, but no surrogate for science

G Lischeid, H Webber, M Sommer, C Nendel… - Agricultural and Forest …, 2022‏ - Elsevier
Provisioning a sufficient stable source of food requires sound knowledge about current and
upcoming threats to agricultural production. To that end machine learning approaches were …

Similar estimates of temperature impacts on global wheat yield by three independent methods

B Liu, S Asseng, C Müller, F Ewert, J Elliott… - Nature Climate …, 2016‏ - nature.com
The potential impact of global temperature change on global crop yield has recently been
assessed with different methods. Here we show that grid-based and point-based simulations …

Global wheat production with 1.5 and 2.0° C above pre‐industrial warming

B Liu, P Martre, F Ewert, JR Porter… - Global Change …, 2019‏ - Wiley Online Library
Efforts to limit global warming to below 2° C in relation to the pre‐industrial level are under
way, in accordance with the 2015 Paris Agreement. However, most impact research on …

Can conservation agriculture increase soil carbon sequestration? A modelling approach

E Valkama, G Kunypiyaeva, R Zhapayev, M Karabayev… - Geoderma, 2020‏ - Elsevier
Conservation agriculture (CA) involves complex and interactive processes that ultimately
determine soil carbon (C) storage, making it difficult to identify clear patterns. To solve these …

Use of crop growth model to simulate the impact of climate change on yield of various wheat cultivars under different agro-environmental conditions in Khyber …

F Gul, I Ahmed, M Ashfaq, D Jan, S Fahad, X Li… - Arabian Journal of …, 2020‏ - Springer
Climate change is significantly affecting agriculture and food security. Variations in
temperature and uncertainties in rainfall patterns negatively affect the yield of crops. Crop …

Modeling the impacts of projected climate change on wheat crop suitability in semi-arid regions using the AHP-based weighted climatic suitability index and CMIP6

K Alsafadi, S Bi, HG Abdo, H Almohamad, B Alatrach… - Geoscience Letters, 2023‏ - Springer
Due to rapid population growth and the limitation of land resources, the sustainability of
agricultural ecosystems has attracted more attention all over the world. Human activities will …

To bias correct or not to bias correct? An agricultural impact modelers' perspective on regional climate model data

P Laux, RP Rötter, H Webber, D Dieng, J Rahimi… - Agricultural and Forest …, 2021‏ - Elsevier
Many open questions and unresolved issues surround the topic of bias correction (BC) in
climate change impact studies (CCIS). One question relates to the contribution of …

Calibration and validation of APSIM-Wheat and CERES-Wheat for spring wheat under rainfed conditions: Models evaluation and application

M Ahmed, MN Akram, M Asim, M Aslam… - … and Electronics in …, 2016‏ - Elsevier
Crop growth in process based crop models is controlled by different parameters. Model
calibration is necessary for application to new cultivars and environment. We applied a …

[PDF][PDF] Forecasting daily meteorological time series using ARIMA and regression models

M Murat, I Malinowska, M Gos… - International …, 2018‏ - archive.sciendo.com
The daily air temperature and precipitation time series recorded between January 1, 1980
and December 31, 2010 in four European sites (Jokioinen, Dikopshof, Lleida and Lublin) …

Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles

A Maiorano, P Martre, S Asseng, F Ewert, C Müller… - Field crops …, 2017‏ - Elsevier
To improve climate change impact estimates and to quantify their uncertainty, multi-model
ensembles (MMEs) have been suggested. Model improvements can improve the accuracy …