Modelling predicts that heat stress and not drought will limit wheat yield in Europe

Global warming is characterised by shifts in weather patterns and increases in extreme weather events. New crop cultivars with specific physiological traits will therefore be required if climate change is not to result in losses of yield and food shortages. However, the intrinsic uncertainty of climate change predictions poses a challenge to plant breeders and crop scientists who have limited time and resources and must select the most appropriate traits for improvement. Modelling is, therefore, a powerful tool to identify future threats to crop production and hence targets for improvement. Wheat is the most important crop in temperate zones, including Europe, and is the staple food crop for many millions of humans and their livestock. However, its production is highly sensitive to environmental conditions, with increased temperature and incidence of drought associated with global warming posing potential threats to yield in Europe. We have therefore predicted the future impacts of these environmental changes on wheat yields using a wheat simulation model combined with climate scenarios based on fifteen global climate models from the IPCC AR4 multi-model ensemble. Despite the lower summer precipitation predicted for Europe, the impact of drought on wheat yields is likely to be smaller than at present, because the warmer conditions will result in earlier maturation before drought becomes severe later in the summer. By contrast, the probability of heat stress around flowering is predicted to increase significantly which is likely to result in considerable yield losses for heat sensitive wheat cultivars commonly grown in north Europe. Breeding strategies should therefore focus on the development of wheat varieties which are tolerant to high temperature around flowering, rather than on developing varieties resistant to drought which may be required for other parts of the world

Ro-vibrational Quenching of CO (\u3cem\u3ev\u3c/em\u3e = 1) by He Impact in a Broad Range of Temperatures: A Benchmark Study Using Mixed Quantum/Classical Inelastic Scattering Theory

The mixed quantum/classical approach is applied to the problem of ro-vibrational energy transfer in the inelastic collisions of CO(v = 1) with He atom, in order to predict the quenching rate coefficient in a broad range of temperatures 5 \u3c T \u3c 2500 K. Scattering calculations are done in two different ways: direct calculations of quenching cross sections and, alternatively, calculations of the excitation cross sections plus microscopic reversibility. In addition, a symmetrized average-velocity method of Billing is tried. Combination of these methods allows reproducing experiment in a broad range of temperatures. Excellent agreement with experiment is obtained at 400 \u3c T \u3c 2500 K (within 10%), good agreement in the range 100 \u3c T \u3c 400 K (within 25%), and semi-quantitative agreement at 40 \u3c T \u3c 100 K(within a factor of 2). This study provides a stringent test of the mixed quantum/classical theory, because the vibrational quantum in CO molecule is rather large and the quencher is very light (He atom). For heavier quenchers and closer to dissociation limit of the molecule, the mixed quantum/classical theory is expected to work even better

Russian Language Neural Net Chatbot with Natural Language Processing

In this paper, we consider a chatbot, which can reply to various user commands and uses natural language processing. Moreover, the most common employee's working processes were automated. This solution can work under any corporate local or global networks. Although, in this article, used tools, software and libraries are explained as well. As a result, chatbot prototype is presented

Modelling predicts that heat stress, not drought, will increase vulnerability of wheat in Europe

New crop cultivars will be required for a changing climate characterised by increased summer drought and heat stress in Europe. However, the uncertainty in climate predictions poses a challenge to crop scientists and breeders who have limited time and resources and must select the most appropriate traits for improvement. Modelling is a powerful tool to quantify future threats to crops and hence identify targets for improvement. We have used a wheat simulation model combined with local-scale climate scenarios to predict impacts of heat stress and drought on winter wheat in Europe. Despite the lower summer precipitation projected for 2050s across Europe, relative yield losses from drought is predicted to be smaller in the future, because wheat will mature earlier avoiding severe drought. By contrast, the risk of heat stress around flowering will increase, potentially resulting in substantial yield losses for heat sensitive cultivars commonly grown in northern Europe

Investigating the effects of inter-annual weather variation (1968- 2016) on the functional response of cereal grain yield to applied nitrogen, using data from the Rothamsted Long-Term experiments

The effect of weather on inter-annual variation in the crop yield response to nitrogen (N) fertilizer for winter wheat (Triticum aestivvum L.) and spring barley (Hordeum vulgare L.) was investigated using yield data from the Broadbalk Wheat and Hoosfield Spring Barley long-term experiments at Rothamsted Research. Grain yields of crops from 1968 to 2016 were modelled as a function of N rates using a linear-plus-exponential (LEXP) function. The extent to which inter-annual variation in the parameters of these responses was explained by variations in weather (monthly summarized temperatures and rainfall), and by changes in the cultivar grown, was assessed. The inter-annual variability in rainfall and underlying temperature influenced the crop N response and hence grain yields in both crops. Asymptotic yields in wheat were particularly sensitive to mean temperature in November, April and May, and to total rainfall in October, February and June. In spring barley asymptotic yields were sensitive to mean temperature in February and June, and to total rainfall in April to July inclusive and September. The method presented here explores the separation of agronomic and environmental (weather) influences on crop yield over time. Fitting N response curves across multiple treatments can support an informative analysis of the influence of weather variation on the yield variability. Whilst there are issues of the confounding and collinearity of explanatory variables within such models, and that other factors also influence yields over time, our study confirms the considerable impact of weather variables at certain times of the year. This emphasizes the importance of including weather temporal variation when evaluating the impacts of climate change on crops

Vulnerability of horticultural crop production to extreme weather events

The potential impact of future extreme weather events on horticultural crops was evaluated. A review was carried out of the sensitivities of a representative set of crops to environmental challenges. It confirmed that a range of environmental factors are capable of causing a significant impact on production, either as yield or quality loss. The most important of these were un-seasonal temperature, water shortage or excess,and storms. Future scenarios were produced by the LARS-WG1, a stochastic weather generator linked with UKCIP02 projections of future climate. For the analyses, 150 years of synthetic weather data were generated for baseline, 2020HI and 2050HI scenarios at defined locations. The output from the weather generator was used in case studies, either to estimate the frequency of a defined set of circumstances known to have impact on cropping, or as inputs to models of crop scheduling or pest phenology or survival. The analyses indicated that episodes of summer drought severe enough to interrupt the continuity of supply of salads and other vegetables will increase while the frequency of autumns with sufficient rainfall to restrict potato lifting will decrease. They also indicated that the scheduling of winter cauliflowers for continuity of supply will require the deployment of varieties with different temperature sensitivities from those in use currently. In the pest insect studies, the number of batches of Agrotis segetum (cutworm) larvae surviving to third instar increased with time, as did the potential number of generations of Plutella xylostella (diamond-back moth) in the growing season, across a range of locations. The study demonstrated the utility of high resolution scenarios in predicting the likelihood of specific weather patterns and their potential effect on horticultural production. Several limitations of the current scenarios and biological models were also identified