130,511 research outputs found
Andamento meteorologico e stato nutrizionale dei meleti e vigneti trentini: analisi dei dati del decennio 1987-1996
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Thirteen years of leaf analysis applied to Italian viticulture, olive and fruit growing
No full textIn 1987 a project to develop an Italian national centre for research on the use of leaf analyses was initiated in order to undertake and interpret leaf analyses on behalf of fruit and grape grower advisory services, and to allow the management of research both for sampling techniques and data collection in the field and in laboratory analyses. Leaves were sampled by technicians of the advisory services from different regions according to the method recommended by our laboratory. All leaf analyses were collected automatically in a data bank which recorded the data reported on the sample label (location, variety, rootstock, vegetative and productive status of the planting) and the nutrient concentrations. More than 12,500 leaf analyses have been gathered in a thirteen year period, from twelve regions from northern, central and southern Italy. Seven tree crop species were mainly included: grapevines, apple trees, peach trees, kiwi vines, olive trees, pear trees and sweet cherry trees. The following main outcomes were developed: local standards for leaf analysis interpretation; certification for low input fertilisation farming; use of leaf analysis in land evaluation and agro-ecological zoning; nutritional aspects of eco-physiological and cultural researches; studies on the relations among mineral nutrition and crop quality; field trials to test fertiliser design and products; and new analytical and diagnostic methods
A method to assess and manage leaf analysis standards according to genetic and environmental variability
No full textA simple and robust statistical method to process data collected in a Leaf Analysis Data Bank which allows to establish reference standards according to the main environmental, genetic and cultural factors affecting the plant nutritional status is presented. The method also permits to determine quickly and easily new tentative standards and to adjust yearly standards already defined
Thermal conductivity equations of pure fluids in an heuristic extended corresponding states framework. II. Application to two fluids.
No full textThermal conductivity equations of pure fluids in an heuristic extended corresponding states framework. I. Modelling techniques.
No full textDifferential effects of canopy manipulation and shading of Vitis vinifera L. cv. Cabernet Sauvignon: plant nutritional status
No full textAn extended equation of state modeling method. II. Mixtures.
No full textThis work is the extension of previous work dedicated to pure fluids. The same method is extended to the representation of thermodynamic properties of a mixture through a fundamental equation of state in terms of Helmholtz energy. The proposed technique exploits the extended corresponding states concept of distorting the independent variables of a dedicated equation of state for a reference fluid using suitable scale factor functions to adapt the equation to experimental data of a target system. An equation of state for the target mixture is used instead of an equation for the reference fluid, completely avoiding the need for a reference fluid. In particular, a Soave-Redlich-Kwong cubic equation with van der Waals mixing rules is chosen. The scale factors, that are functions of temperature, density, and composition of the target mixture, are expressed in the form of a multilayer feedforward neural network, whose coefficients are regressed by minimizing a suitable objective function involving different kinds of mixture thermodynamic data. As a preliminary test, the model is applied to five binary and two ternary haloalkane mixtures, using data generated from existing dedicated equations of state for the selected mixtures. The results show that the method is robust and straightforward for the effective development of a mixture-specific equation of state directly from experimental data
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
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