scispace - formally typeset
Search or ask a question
Institution

University of Almería

EducationAlmería, Spain
About: University of Almería is a education organization based out in Almería, Spain. It is known for research contribution in the topics: Population & Context (language use). The organization has 4674 authors who have published 10905 publications receiving 233036 citations. The organization is also known as: University of Almeria & Universidad de Almería.


Papers
More filters
Journal ArticleDOI
TL;DR: The amounts of n-3 VLCPUFA in Hermetia larvae could be altered by dietary manipulation in a short period of time and therefore a lower n-6:n-3 ratio than those of the control insect meal.

140 citations

Journal ArticleDOI
TL;DR: The water soluble ruthenium complexes (C5R5)RuCl(PTA)2] were synthesized and characterised in this paper, and their evaluation as regioselective catalysts for hydrogenation of unsaturated ketones in aqueous biphasic conditions was briefly presented.

140 citations

Journal ArticleDOI
TL;DR: The most productive institutions in terms of number of documents dealing with nitrate leaching research, h-index and total citations, were located in the United States, China and the Netherlands, followed by China, the United Kingdom and Germany.

139 citations

Journal ArticleDOI
TL;DR: In this paper, the principal extraction and clean-up methodologies (e.g., liquid-liquid extraction, solid-phase extraction, pressurized liquid extraction, QuEChERS (quick, easy, cheap, effective, rugged and safe), gel-permeation chromatography and supercritical-fluid extraction) are compared.
Abstract: Rice consumption has increased worldwide over recent decades, as it has become one of the most common foods. Although the analysis of environmental samples coming from rice areas has been well documented, there is less information regarding the analysis of pesticide residues in rice-grain samples. Rice (paddy, brown and white) can be considered a complex matrix, leading to difficulties in the application of the different multiresidue methods described in the literature. This review addresses and compares the principal extraction and clean-up methodologies [e.g., liquid-liquid extraction, solid-phase extraction, pressurized-liquid extraction, QuEChERS (quick, easy, cheap, effective, rugged and safe), gel-permeation chromatography and supercritical-fluid extraction – with QuEChERS-based methods being the most frequently employed]. Traditionally, the determination of pesticide residues in rice has been based on gas chromatography with mass spectrometry (MS). But the application of new classes of pesticides has driven laboratories to increase the use of liquid chromatography with tandem MS. The limits of detection and quantification are in the ranges 0.09–90 μg/kg and 1–297 μg/kg, respectively, for the methodologies reported. These values agree with the current internationally-accepted maximum residue limits (MRLs). Based on the European Union (EU) database, more than 3000 analyses of pesticide residues in rice have been performed by official EU laboratories over the past decade. Of these, 6% reported pesticide residues above the MRLs. Physico-chemical properties can explain the occurrence of pesticides in rice commodities: lipophilic pesticides are frequently found in brown rice, whereas fungicides are mainly found in milled rice. Carbendazim, malathion, iprodione, tebuconazole, quinclorac and tricyclazole are the pesticides most frequently found in white rice, while buprofezin, hexaconazole, chlorpyrifos and edifenphos are most commonly found in paddy rice. Pesticide-residue concentrations can be affected during rice processing – with concentrations generally lower in the final products. However, few studies focusing on primary processing have addressed the setting of precise values applicable for the processing factors.

138 citations

Journal ArticleDOI
TL;DR: In this paper, an alternative expression to calculate the variance inflation factor (VIF) in ridge regression is presented. But the expression does not necessarily lead to values of VIFs equal to or greater than 1.
Abstract: Ridge regression has been widely applied to estimate under collinearity by defining a class of estimators that are dependent on the parameter k. The variance inflation factor (VIF) is applied to detect the presence of collinearity and also as an objective method to obtain the value of k in ridge regression. Contrarily to the definition of the VIF, the expressions traditionally applied in ridge regression do not necessarily lead to values of VIFs equal to or greater than 1. This work presents an alternative expression to calculate the VIF in ridge regression that satisfies the aforementioned condition and also presents other interesting properties.

138 citations


Authors

Showing all 4758 results

NameH-indexPapersCitations
Amadeo R. Fernández-Alba8331821458
Sixto Malato8031524216
Francisco Rodríguez7974824992
Yusuf Chisti7634733979
José Luis García7345317504
Anne-Marie Caminade6958015814
Elias Fereres6823618751
David Mecerreyes6632416822
Berta Martín-López6417716136
Ana Agüera6316812280
Alberto Fernández-Gutiérrez6231213557
Mary F. Mahon5953914258
José María Carazo5930912499
Claudio Bianchini5736813412
Manuel Marquez5512612237
Network Information
Related Institutions (5)
University of Granada
59.2K papers, 1.4M citations

95% related

University of Valencia
65.6K papers, 1.7M citations

92% related

Complutense University of Madrid
90.2K papers, 2.1M citations

91% related

University of Barcelona
108.5K papers, 3.7M citations

89% related

Autonomous University of Madrid
52.8K papers, 1.6M citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202345
2022127
2021881
2020892
2019729
2018647