Combining climate change, crop growth and crop disease models to predict impacts of climate change on crop diseases can guide planning of climate change adaptation strategies to ensure future food security. This review summarises recent developments in modelling climate change impacts on crop diseases, emphasises some major challenges and highlights recent trends. The use of multi-model ensembl...

Goals of the Crop Modelers during this Workshop: 1) to calibrate and intercompare multiple crop models (APSIM, DSSAT, INFOCROP, and STICS) against rice and wheat data at sites in South Asia, 2) to simulate growth and yield sensitivity of those four crop models for rice and wheat to temperature and carbon dioxide levels, and 3) to demonstrate the process of predicting district-level yield of pea...

In the context of the GEOLAND EC FP6 project the comparison of different remote sensing based approaches for yield forecasting over large areas in Europe are tested and results inter-compared. In particular the methods tested include the ones in use within the MARS-Crop Yield Forecasting System as the results from the Crop Growth Monitoring System model and vegetation indicators derived from Lo...

Process-based crop simulation models require employment of new knowledge for continuous improvement. To simulate growth and development of different genotypes of a given crop, most models use empirical relationships or parameters defined as genetic coefficients to represent the various cultivar characteristics. Such a loose introduction of different cultivar characteristics can result in bias w...

Better irrigation management and more efficient management of crop production require modeling of plant growth and crop yield. More applicable models are usually simple and requires less and accessible inputs. The objective of this study was to develop a model for growth and yield prediction of saffron under various irrigation regimes. In this modeling soil water budget and other simple rel...

Correct estimation of above-ground biomass (AGB) is necessary for accurate crop growth monitoring and yield prediction. We estimated AGB based on images obtained with a snapshot hyperspectral sensor (UHD 185 firefly, Cubert GmbH, Ulm, Baden-Württemberg, Germany) mounted on an unmanned aerial vehicle (UAV). The UHD 185 images were used to calculate the crop height and hyperspectral reflectance o...