A B S T R A C TIn this paper we explore the new possibilities for early crop yield assessment at the local scale arising from the availability of dynamic crop growth models and of downscaled multi-model ensemble seasonal forecasts. We compare the use of the latter with other methods, based on crop growth models driven by observed climatic data only. The soil water balance model developed and used at ARPA Emilia-Romagna (CRITERIA) was integrated with crop growth routines from the model WOFOST 7.1. Some validation runs were first carried out and we verified with independent field data that the new integrated model satisfactorily simulated above-ground biomass and leaf area index. The model was then used to test the feasibility of using downscaled multi-model ensemble seasonal hindcasts, coming from the DEMETER European research project, in order to obtain early (i.e. 90, 60 and 30 d before harvest) yield assessments for winter wheat in northern Italy. For comparison, similar runs with climatology instead of hindcasts were also carried out. For the same purpose, we also produced six simple linear regression models of final crop yields on within season (end of March, April and May) storage organs and above-ground biomass values. Median yields obtained using downscaled DEMETER hindcasts always outperformed the simple regression models and were substantially equivalent to the climatology runs, with the exception of the June experiment, where the downscaled seasonal hindcasts were clearly better than all other methods in reproducing the winter wheat yields simulated with observed weather data. The crop growth model output dispersion was almost always significantly lower than the dispersion of the downscaled ensemble seasonal hindcast used as input for crop simulations.
In this paper we explore the new possibilities for early crop yield assessment at the local scale arising from the availability of dynamic crop growth models and of downscaled multi‐model ensemble seasonal forecasts. We compare the use of the latter with other methods, based on crop growth models driven by observed climatic data only. The soil water balance model developed and used at ARPA Emilia‐Romagna (CRITERIA) was integrated with crop growth routines from the model WOFOST 7.1. Some validation runs were first carried out and we verified with independent field data that the new integrated model satisfactorily simulated above‐ground biomass and leaf area index. The model was then used to test the feasibility of using downscaled multi‐model ensemble seasonal hindcasts, coming from the DEMETER European research project, in order to obtain early (i.e. 90, 60 and 30 d before harvest) yield assessments for winter wheat in northern Italy. For comparison, similar runs with climatology instead of hindcasts were also carried out. For the same purpose, we also produced six simple linear regression models of final crop yields on within season (end of March, April and May) storage organs and above‐ground biomass values. Median yields obtained using downscaled DEMETER hindcasts always outperformed the simple regression models and were substantially equivalent to the climatology runs, with the exception of the June experiment, where the downscaled seasonal hindcasts were clearly better than all other methods in reproducing the winter wheat yields simulated with observed weather data. The crop growth model output dispersion was almost always significantly lower than the dispersion of the downscaled ensemble seasonal hindcast used as input for crop simulations.
Alternative methods to animal testing are considered as promising tools to support the prediction of toxicological risks from environmental exposure. Among the alternative testing methods, the cell transformation assay (CTA) appears to be one of the most appropriate approaches to predict the carcinogenic properties of single chemicals, complex mixtures and environmental pollutants. The BALB/c 3T3 CTA shows a good degree of concordance with the in vivo rodent carcinogenesis tests. Whole-genome transcriptomic profiling is performed to identify genes that are transcriptionally regulated by different kinds of exposures. Its use in cell models representative of target organs may OPEN ACCESS Sustainability 2014, 6 5266 help in understanding the mode of action and predicting the risk for human health. Aiming at associating the environmental exposure to health-adverse outcomes, we used an integrated approach including the 3T3 CTA and transcriptomics on target cells, in order to evaluate the effects of airborne particulate matter (PM) on toxicological complex endpoints. Organic extracts obtained from PM 2.5 and PM 1 samples were evaluated in the 3T3 CTA in order to identify effects possibly associated with different aerodynamic diameters or airborne chemical components. The effects of the PM 2.5 extracts on human health were assessed by using whole-genome 44 K oligo-microarray slides. Statistical analysis by GeneSpring GX identified genes whose expression was modulated in response to the cell treatment. Then, modulated genes were associated with pathways, biological processes and diseases through an extensive biological analysis. Data derived from in vitro methods and omics techniques could be valuable for monitoring the exposure to toxicants, understanding the modes of action via exposure-associated gene expression patterns and to highlight the role of genes in key events related to adversity.
A study was conducted on the effects of different mulching materials on Tuber uncinatum (the Burgundy truffle) ectomycorrhizas in a 6-yearold experimental truffière. The mulching materials were wheat straw, an aluminised cloth, a black mulching cloth, and a sub-watering cloth. Three years after the start of the experiment the mulches significantly influenced the degree of ectomycorrhizal colonisation in the upper 0-15 cm of soil. The sub-watering cloth stimulated T. uncinatum colonisation and depressed the development of the contaminant ectomycorrhizal fungi that were promoted by the black mulch. Both straw and the black mulch depressed T. uncinatum infection. The mulches appear to have had their effects on ectomycorrhizal colonisation via their impact on soil temperature and moisture.
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