1,720,977 research outputs found
Effetto dei trattamenti di termoterapia sulla produzione di etanolo e acetaldeide in frutti di agrumi
No full textOptimizing genetic parameters of CSM-CERES wheat and CSM-CERES maize for durum wheat, common wheat, and maize in Italy
No full textThe expected increase in population and the pressure posed by climate change on agricultural production require the assessment of future yield levels and the evaluation of the most suitable management options to minimize climate risk and promote sustainable agricultural production. Crop simulation models are widely applied tools to predict crop development and production under different management practices and environmental conditions. The aim of this study was to parameterize CSM-CERES-Wheat and CSM-CERES-Maize models, implemented in the Decision Support System for Agrotechnology Transfer (DSSAT) software, to predict phenology and grain yield of durum wheat, common wheat, and maize in different Italian environments. A 10- year (2001-2010) dataset was used to optimize the genetic parameters for selected varieties of each species and to evaluate the models considering several statistical indexes. The generalized likelihood uncertainty estimation method, and trial and error approach were used to optimize the cultivar-specific parameters of these models. Results show good model performances in reproducing crop phenology and yield for the analyzed crops, especially with the parameters optimized with the trial and error procedure. Highly significant (p ≤ 0.001) correlations between observed and simulated data were found for both anthesis and yield in model calibration and evaluation (p ≤ 0.01 for grain yield of maize in model evaluation). Root mean square error (RMSE) values range from six to nine days for anthesis and from 1.1 to 1.7 t ha-1 for crop yield and index of agreement (d-index) from 0.96 to 0.98 for anthesis and from 0.8 to 0.87 for crop yield. The set of genetic parameters obtained for durum wheat, common wheat, and maize may be applied in further analyses at field, regional, and national scales to guide operational (farmers), strategic, and tactical (policy makers) decisions
Modeling high-resolution climate change impacts on wheat and maize in Italy
Full text linkThe Mediterranean basin has been identified as a prominent hotspot of climate change, with expected negative impacts on crop productivity, among others. Given the primary role that agriculture has to sustain cultural values, economic opportunities, and food security, it is crucial to identify specific risks in agriculture due to climate change, which can address more effective adaptation strategies and policies to cope with climate change. This study aims to evaluate the high-resolution impacts of climate change on the length of the growing cycle and yield of durum wheat, common wheat, and maize in Italy by using the CERES-Wheat and CERES-Maize crop models implemented in the Decision Support System for Agrotechnology Transfer (DSSAT) software. A digital platform (GIS-DSSAT) was developed to couple crop simulation models with dynamically downscaled climate projections at high resolution for Italy, which can better represent the Italian landscape complexity and the spatial distribution of different pedological and crop management features, providing more detailed information on the expected impacts on crops respect to previous studies at a coarser resolution. The projections have been extended for two climate change scenarios and accounting for uncertainty, either considering or not the potential direct effects of increasing atmospheric CO2 concentrations ([CO2]). Results show that climate change may affect Italian cereal production in the medium to long term periods. Maize is the main affected crop, with yield reductions homogeneously distributed from North to South Italy. Wheat yield is expected to decrease mainly in southern Italy, while northern Italy may benefit from higher precipitation regimes. Higher levels of atmospheric CO2 concentrations may partially offset the negative impact posed by climate change and increase the benefits in the northern regions, especially for common and durum wheat
Assessing climate risk for cereals and livestock to inform adaptation planning at regional and local scale
No full textClimate change is strongly affecting Mediterranean agriculture, prompting urgent adaptation actions to cope with its negative impacts and to enhance the resilience of agricultural systems. Detailed climate risk analyses are essential to inform and guide decision-making on priority actions to be implemented in each territory, tailored on specific local needs. This work applied the impact chain approach to assess the climate-related risks for cereals and livestock sectors in Sardinia, Italy. Impact chains allow analysing and understanding the interrelationships between climate drivers and the related risks, supporting the development of adaptation strategies and plans. In this study, statistical socio-economic indicators were integrated with results from dynamic crop simulation models and climate change scenarios to investigate the risk components, following the IPCC framework, for the agricultural sector by 2050. The results show higher negative impacts for cereals than for livestock, with durum wheat being less climate sentitive than common wheat and maize. Overall, Sardinia has low exposure for both cereals and livestock, while adaptive capacity is criticality low, highlighting the need for urgent action. The outcomes of the analysis were elaborated at both the regional and municipal level, to provide user-friendly information for policy-makers at different administrative levels. The assessed level of risks, in terms of hazard, exposure, and vulnerability, has been used to develop the Regional Adaptation Strategy to Climate Change (SRACC) for the Sardinia region. These results may leed decision making and help planning and programming interventions also at municipal level
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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