Abstract: Ultraviolet (UV) radiation directly regulates a multitude of herbivore life processes, in addition to indirectly affecting insect success via changes in plant chemistry and morphogenesis. Here we looked at plant and insect (aphid and whitefly) exposure to supplemental UV-A radiation in the glasshouse environment and investigated effects on insect population growth. Glasshouse grown peppers and eggplants were grown from seed inside cages covered by novel plastic filters, one transparent and the other opaque to UV-A radiation. At a 10-true leaf stage for peppers (53 days) and 4-true leaf stage for eggplants (34 days), plants were harvested for chemical analysis and infested by aphids and whiteflies, respectively. Clip-cages were used to introduce and monitor the insect fitness and populations of the pests studied. Insect pre-reproductive period, fecundity, fertility and intrinsic rate of natural increase were assessed. Crop growth was monitored weekly for 7 and 12 weeks throughout the crop cycle of peppers and eggplants, respectively. At the end of the insect fitness experiment, plants were harvested (68 days and 18-true leaf stage for peppers, and 104 days and 12-true leaf stage for eggplants) and leaves analysed for secondary metabolites, soluble carbohydrates, amino acids, total proteins and photosynthetic pigments. Our results demonstrate for the first time, that UV-A modulates plant chemistry with implications for insect pests. Both plant species responded directly to UV-A by producing shorter stems but this effect was only significant in pepper whilst UV-A did not affect the leaf area of either species. Importantly, in pepper, the UV-A treated plants contained higher contents of secondary metabolites, leaf soluble carbohydrates, free amino acids and total content of protein. Such changes in tissue chemistry may have indirectly promoted aphid performance. For eggplants, chlorophylls a and b, and carotenoid levels decreased with supplemental UV-A over the entire crop cycle but UV-A exposure did not affect leaf secondary metabolites. However, exposure to supplemental UV-A had a detrimental effect on whitefly development, fecundity and fertility presumably not mediated by plant cues as compounds implied in pest nutrition – proteins and sugars – were unaltered.

Abstract: Mitigation of greenhouse gas emissions from agriculture should be assessed across cropping systems and agroclimatic regions. In this study, we investigate the ability of the FASSET model to analyze differences in the magnitude of N2O emissions due to soil, climate and management factors in cereal-based cropping systems. Forage maize was grown in a conventional dairy system at Mabegondo (NW Spain) and wheat and barley in organic and conventional crop rotations at Foulum (NW Denmark). These two European sites represent agricultural areas with high and low to moderate emission levels, respectively. Field trials included plots with and without catch crops that were fertilized with either mineral N fertilizer, cattle slurry, pig slurry or digested manure. Non-fertilized treatments were also included. Measurements of N2O fluxes during the growing cycle of all the crops at both sites were performed with the static chamber method with more frequent measurements post-fertilization and biweekly measurements when high fluxes were not expected. All cropping systems were simulated with the FASSET version 2.5 simulation model. Cumulative soil seasonal N2O emissions were about ten-fold higher at Mabegondo than at Foulum when averaged across systems and treatments (8.99 and 0.71 kg N2O-N ha(-1), respectively). The average simulated cumulative soil N2O emissions were 9.03 and 1.71 kg N2O-N ha(-1) at Mabegondo and at Foulum, respectively. Fertilization, catch crops and cropping systems had lower influence on the seasonal soil N2O fluxes than the environmental factors. Overall, in its current version FASSET reproduced the effects of the different factors investigated on the cumulative seasonal soil N2O emissions but temporally it overestimated emissions from nitrification and denitrification on particular days when soil operations, ploughing or fertilization, took place. The errors associated with simulated daily soil N2O fluxes increased with the magnitude of the emissions. For resolving causes of differences in simulated and measured fluxes more intensive and temporally detailed measurements of N2O fluxes and soil C and N dynamics would be needed. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers and plant breeders in addressing the challenges of climate change by simulating alternative roads of adaptation. They can also provide management decision support under current conditions. A drawback of existing grass models is that they do not take into account the effect of winter stresses, limiting their use for full-year simulations in areas where winter survival is a key factor for yield security. Here, we present a novel full-year PBM for grassland named BASGRA. It was developed by combining the LINGRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winter processes. We present the model and show how it was parameterized for timothy (Phleum pratense L.), the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRA simulates the processes taking place in the sward during the transition from summer to winter, including growth cessation and gradual cold hardening, and functions for simulating plant injury due to low temperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data from five different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudes from 59 degrees to 70 degrees N) and soil conditions. The total dataset included 11 variables, notably above-ground dry matter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used in the calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector from the single, Bayesian calibration, nearly all measured variables were simulated to an overall normalized root mean squared error (NRMSE) <0.5. For many site x experiment combinations, NRMSE was <0.3. The temporal dynamics were captured well for most variables, as evaluated by comparing simulated time courses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robust model, allowing for simulation of growth and several important underlying processes with acceptable accuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be tested further using independent data from a wide range of growing conditions. Finally we show an example of application of the model, comparing overwintering risks in two climatically different sites, and discuss future model applications. Further development work should include improved simulation of the dynamics of C reserves, and validation of winter tiller dynamics against independent data. (C) 2016 Elsevier B.V. All rights reserved.