Abstract: Ultraviolet (UV) radiation, particularly in the UV-A + B range (280-400 nm) is a fraction of the solar spectrum that regulates almost every aspect of insect behaviour, including orientation towards hosts, alighting, arrestment and feeding behaviour. To study the role of UV radiation on the flight activity of five insect species of agricultural importance (pests Myzus persicae, Bemisia tabaci and Tuta absoluta, and natural enemies Aphidius colemani and Sphaerophoria rueppellii), one-chamber tunnels were covered with six cladding materials with different light transmittance properties ranging from 2% to 83% UV and 54% to 85% photosynthetically active radiation (PAR). Inside each tunnel, insects were released from tubes placed in a platform suspended from the ceiling. Specific targets varying with insect species were placed at different distances from the platform. Evaluation parameters were designed for each insect and tested separately. The ability of insects to leave the platform was assessed, as well as the number of captures, eggs or mummies in each target, either sticky traps or plants. Our results suggest differences in flight activity among insect species and UV-blocking nets. The UV-opaque film drastically prevented aphids, and whiteflies from flying outside the tubes whereas T. absoluta, syrphids and parasitoids were not affected. Aphid flight behaviour was affected by the UV-opaque film compared to the other nets, especially in the furthest target of the tunnel. Fewer aphids reached distant traps under UV-absorbing nets, and significantly more aphids could fly to the end of tunnels covered with non-UV-blocking materials. Orientation of B. tabaci and T. absoluta was also negatively affected by the UV-opaque film although in a different trend. Unlike aphids, differences in B. tabaci captures were mainly found in the closest targets. UV transmittance did not have any effects on parasitoids, and S. rueppellii, implying cues other than visual for these insects under our experimental conditions. Further effects of photoselective enclosures on greenhouse pests and their natural enemies are discussed.

Abstract: The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DailyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet) x two soil types (sandy and clayey) x two feeding systems (grass only and grass/maize). The milk yield per cow, follower cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO(2)e)/ha per year, with a range of 1.9 t CO(2)e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.

Abstract: The numerical crop growth model Italian Vineyard Integrated Numerical model for Estimating physiological values (IVINE) was developed in order to evaluate environmental forcing effects on vine growth. The IVINE model simulates vine growth processes with parameterizations, allowing the understanding of plant conditions at a vineyard scale. It requires a set of meteorology data and soil water status as boundary conditions. The primary model outputs are main phenological stages, leaf development, yield, and sugar concentration. The model requires setting some variety information depending on the cultivar: At present, IVINE is optimized for Vitis vinifera L. Nebbiolo, a variety grown mostly in the Piedmont region (northwestern Italy). In order to evaluate the model accuracy, IVINE was validated using experimental observations gathered in Piedmontese vineyards, showing performances similar or slightly better than those of other widely used crop models. The results of a sensitivity analysis performed to highlight the effects of the variations of air temperature and soil water potential input variables on IVINE outputs showed that most phenological stages anticipated with increasing temperatures, while berry sugar content saturated at about 25.5 °Bx. Long-term (60 years, in the period 1950–2009) simulations performed over a Piedmontese subregion showed statistically significant variations of most IVINE output variables, with larger time trend slopes referring to the most recent 30-year period (1980–2009), thus confirming that ongoing climate change started influencing Piedmontese vineyards in 1980.