M. I. Mínguez

Radiation interception and use, and spectral reflectance of contrasting canopies of autumn sown faba beans and semi-leafless peas

Abstract Water deficits in faba bean produced a change in leaf angle that lowered the fraction of photosynthetically active radiation intercepted ( R pi ) by the canopy, when compared to irrigated faba beans. This response was not found in a semi-leafless pea crop for its canopy structure was maintained rigid by tendrils. These contrasting behaviours were quantified by changes in photosynthetically active radiation ( R p ) extinction coefficients ( K ). For irrigated faba beans, an average value for K of 0.78 is proposed for R p interception modelling. In the case of water stressed faba beans, the possibility of using a water stress dependent K is raised. The canopy architecture of semi-leafless peas may allow the use of one K (0.50) for the two water regimes. Radiation use efficiency (RUE) showed a two phase behaviour: before (RUEbg) and after (RUEag) the beginning of grain filling. In addition, changes in RUE were also due to water supply and affected RUEag values, although in a different way in peas than in faba beans. The reflectance properties of these canopies allowed for an evaluation of crop biomass and also enhanced their contrasting characteristics. The Soil Adjusted Vegetation Index (SAVI2) was used here as a means to estimate R pi . The relationships between SAVI2 and R pi were near-linear in faba beans and linear in peas. Crop biomass was then estimated with these relationships and with the acquired information on the two phase RUE of each species and water regime.

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management.