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: The data set for this study comprised 1,488,474 test-day records for milk, fat, and protein yields and fat and protein percentages from 191,012 first-, second-, and third-parity Holstein cows from 484 farms. Data were collected from 2001 through 2007 and merged with meteorological data from 35 weather stations. A linear model (M1) was used to estimate the effects of the temperature-humidity index (THI) on production traits. Least squares means from M1 were used to detect the THI thresholds for milk production in all parities by using a 2-phase linear regression procedure (M2). A multiple-trait repeatability test-model (M3) was used to estimate variance components for all traits and a dummy regression variable (t) was defined to estimate the production decline caused by heat stress. Additionally, the estimated variance components and M3 were used to estimate traditional and heat-tolerance breeding values (estimated breeding values, EBV) for milk yield and protein percentages at parity 1. An analysis of data (M2) indicated that the daily THI at which milk production started to decline for the 3 parities and traits ranged from 65 to 76. These THI values can be achieved with different temperature/humidity combinations with a range of temperatures from 21 to 36°C and relative humidity values from 5 to 95%. The highest negative effect of THI was observed 4 d before test day over the 3 parities for all traits. The negative effect of THI on production traits indicates that first-parity cows are less sensitive to heat stress than multiparous cows. Over the parities, the general additive genetic variance decreased for protein content and increased for milk yield and fat and protein yield. Additive genetic variance for heat tolerance showed an increase from the first to third parity for milk, protein, and fat yield, and for protein percentage. Genetic correlations between general and heat stress effects were all unfavorable (from -0.24 to -0.56). Three EBV per trait were calculated for each cow and bull (traditional EBV, traditional EBV estimated with the inclusion of THI covariate effect, and heat tolerance EBV) and the rankings of EBV for 283 bulls born after 1985 with at least 50 daughters were compared. When THI was included in the model, the ranking for 17 and 32 bulls changed for milk yield and protein percentage, respectively. The heat tolerance genetic component is not negligible, suggesting that heat tolerance selection should be included in the selection objectives.

Abstract: Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.