966 resultados para Antinutritional substances


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Pós-graduação em Alimentos e Nutrição - FCFAR

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Moringa oleifera Lam, is a leguminous plant, originally from Asia, which is cultivated in Brazil because of its low production cost. Although some people have used this plant as food, there is little information about its chemical and nutritional characteristics. The objective of this study was to characterise the leaves of M. oleifera in terms of their chemical composition, protein fractions obtained by solubility in different systems and also to assess their nutritional quality and presence of bioactive substances. The whole leaf flour contained 28.7% crude protein, 7.1% fat, 10.9% ashes, 44.4% carbohydrate and 3.0 mg 100 g(-1) calcium and 103.1 mg 100 g(-1) iron. The protein profile revealed levels of 3.1% albumin, 0.3% globulins, 2.2% prolamin, 3.5% glutelin and 70.1% insoluble proteins. The hydrolysis of the protein from leaf flour employing sodium dodecyl sulfate (SDS) and 2-mercaptoethanol (ME) resulted in 39.5% and 29.5%, respectively. The total protein showed low in vitro digestibility (31.8%). The antinutritional substances tested were tannins (20.7 mg g(-1)), trypsin inhibitor (1.45 TIU mg g(-1)), nitrate (17 mg g(-1)) and oxalic acid (10.5 mg g(-1)), besides the absence of cyanogenic compounds. beta-Carotene and lutein stood out as major carotenoids, with concentrations of 161.0 and 47.0 mu g g(-1) leaf, respectively. Although M. oleifera leaves contain considerable amount of crude protein, this is mostly insoluble and has low in vitro digestibility, even after heat treatment and chemical attack. In vivo studies are needed to better assess the use of this leaf as a protein source in human feed. (C) 2013 Elsevier Ltd. All rights reserved.

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An increasing number of studies are highlighting the alarming proportion of motorists that drive after having consumed illicit drugs. However presently, little attention has focused on the factors that may facilitate drug driving from a criminogenic paradigm. This study evaluated the contribution of deterrence, defiance, and deviance theories on intentions to drug drive to determine factors that might facilitate or reduce this behaviour. A total of 922 individuals completed a questionnaire that assessed frequency of drug use and a variety of perceptions on deterrence, defiance, and deviance constructs. The analysis showed that the defiance constructs (i.e., experiencing feelings of shame and believing in the legitimacy of sanctioning authority) and the deviance constructs (i.e., moral attachment to the norm and having a criminal conviction) were predictive of drug driving intentions. The facets of deterrence theory were not found to be significant predictors. Ultimately, this study illustrates that a range of behavioural and perceptual factors have the capacity to influence decisions to drug drive. As a result, there appears the need to extend the focus of research endeavours beyond legal sanctions to examine other factors that may be utilised to both understand the aetiology of drug driving as well as increase the possibility of compliance with the corresponding legislation.

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Deep Raman Spectroscopy is a domain within Raman spectroscopy consisting of techniques that facilitate the depth profiling of diffusely scattering media. Such variants include Time-Resolved Raman Spectroscopy (TRRS) and Spatially-Offset Raman Spectroscopy (SORS). A recent study has also demonstrated the integration of TRRS and SORS in the development of Time-Resolved Spatially-Offset Raman Spectroscopy (TR-SORS). This research demonstrates the application of specific deep Raman spectroscopic techniques to concealed samples commonly encountered in forensic and homeland security at various working distances. Additionally, the concepts behind these techniques are discussed at depth and prospective improvements to the individual techniques are investigated. Qualitative and quantitative analysis of samples based on spectral data acquired from SORS is performed with the aid of multivariate statistical techniques. By the end of this study, an objective comparison is made among the techniques within Deep Raman Spectroscopy based on their capabilities. The efficiency and quality of these techniques are determined based on the results procured which facilitates the understanding of the degree of selectivity for the deeper layer exhibited by the individual techniques relative to each other. TR-SORS was shown to exhibit an enhanced selectivity for the deeper layer relative to TRRS and SORS whilst providing spectral results with good signal-to-noise ratio. Conclusive results indicate that TR-SORS is a prospective deep Raman technique that offers higher selectivity towards deep layers and therefore enhances the non-invasive analysis of concealed substances from close range as well as standoff distances.

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Corporate social responsibility is imperative for manufacturing companies to achieve sustainable development. Under a strong environmental information disclosure system, polluting companies are disadvantaged in terms of market competitiveness, because they lack an environmentally friendly image. The objective of this study is to analyze productive inefficiency change in relation to toxic chemical substance emissions for the United States and Japan and their corresponding policies. We apply the weighted Russell directional distance model to measure companies productive inefficiency, which represents their production technology. The data encompass 330 US manufacturing firms observed from 1999 to 2007, and 466 Japanese manufacturing firms observed from 2001 to 2008. The article focuses on nine high-pollution industries (rubber and plastics; chemicals and allied products; paper and pulp; steel and non-ferrous metal; fabricated metal; industrial machinery; electrical products; transportation equipment; precision instruments) categorized into two industry groups: basic materials industries and processing and assembly industries. The results show that productive inefficiency decreased in all industrial sectors in the United States and Japan from 2001 to 2007. In particular, that of the electrical products industry decreased rapidly after 2002 for both countries, possibly because of the enforcement of strict environmental regulations for electrical products exported to European markets.

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A novel combined near- and mid-infrared (NIR and MIR) spectroscopic method has been researched and developed for the analysis of complex substances such as the Traditional Chinese Medicine (TCM), Illicium verum Hook. F. (IVHF), and its noxious adulterant, Iuicium lanceolatum A.C. Smith (ILACS). Three types of spectral matrix were submitted for classification with the use of the linear discriminant analysis (LDA) method. The data were pretreated with either the successive projections algorithm (SPA) or the discrete wavelet transform (DWT) method. The SPA method performed somewhat better, principally because it required less spectral features for its pretreatment model. Thus, NIR or MIR matrix as well as the combined NIR/MIR one, were pretreated by the SPA method, and then analysed by LDA. This approach enabled the prediction and classification of the IVHF, ILACS and mixed samples. The MIR spectral data produced somewhat better classification rates than the NIR data. However, the best results were obtained from the combined NIR/MIR data matrix with 95–100% correct classifications for calibration, validation and prediction. Principal component analysis (PCA) of the three types of spectral data supported the results obtained with the LDA classification method.