1,720,985 research outputs found
Anthocyanin profiles of non-V. vinifera genotypes
No full textAnthocyanins are the main compounds responsible for the color of red grapes and wine. They play a key role in determining the quality of grape berries. Today, wild Vitis genotypes represent an important source of genetic resistance to biotic and abiotic stresses. In fact, these genotypes are used in breeding programs with V. vinifera in order to improve V. vinifera cultivars resistance to phylloxera and powdery mildew diseases (Yang et al. 2014). The resulting inter-specific hybrids present diglucoside anthocyanins which are characteristic of wild Vitis genotypes. Since the acceptable limits of diglucoside contained in wine is 15 mg/L (J. A. Considine, E. Frankish 2014), the aim of this work was to study the anthocyanin profiles of 9 wild genotypes collected in four different vintages. Grape skin anthocyanins were analyzed by HPLC-DAD and twenty different anthocyanins were detected and quantified. Diglucoside derivates were not detected in all wild Vitis genotypes. Out of the nine genotypes analyzed one had no diglucoside anthocyanins. In three genotypes less than 5% of the total amount of anthocyanins detected were diglucosides (from 11,6 to 56,9 mg/kg). In the five remaining genotypes more than 50% of the total were found to be diglucosides (from 522,1 to 1829,2 mg/kg). Cluster analysis showed that each genotype had characteristic distributions of anthocyanins consistent between harvest years
The Compound Characteristics Comparison (CCC) approach: a tool for improving confidence in natural compound identification
No full textCompound identification is the main hurdle in LC-HRMS-based metabolomics, given the high number of ‘unknown’ metabolites. In recent years, numerous in silico fragmentation simulators have been developed to simplify and improve mass spectral interpretation and compound annotation. Nevertheless, expert mass spectrometry users and chemists are still needed to select the correct entry from the numerous candidates proposed by automatic tools, especially in the plant kingdom due to the huge structural diversity of natural compounds occurring in plants. In this work, we propose the use of a supervised machine learning approach to predict molecular substructures from isotopic patterns, training the model on a large database of grape metabolites. This approach, called ‘Compounds Characteristics Comparison’ (CCC) emulates the experience of a plant chemist who ‘gains experience’ from a (proof-of-principle) dataset of grape compounds. The results show that the CCC approach is able to predict with good accuracy most of the sub-structures proposed. In addition, after querying MS/MS spectra in Metfrag 2.2 and applying CCC predictions as scoring terms with real data, the CCC approach helped to give a better ranking to the correct candidates, improving users’ confidence in candidate selection. Our results demonstrated that the proposed approach can complement current identification strategies based on fragmentation simulators and formula calculators, assisting compound identification. The CCC algorithm is freely available as R package (https://github.com/lucanard/CCC) which includes a seamless integration with Metfrag. The CCC package also permits uploading additional training data, which can be used to extend the proposed approach to other systems biological matrices
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
Unravelling the effect of harvest date on Shiraz wine volatile composition by two dimensional gas chromatography and wine sensory analyses
No full textAn investigation of Shiraz wine volatile composition from four vineyards located in the Riverina region of Australia was performed by accessing wines made from sequentially harvested grapes. Vines were drip irrigated with average yields from 10.2-18.5 kg/vine in the four vineyards. Shiraz wines were vinified from 60 kg grape triplicates. Following a berry ripening model [1], the first harvest (H1) was 12 days from the plateau of berry sugar accumulation and the second harvest (H2), 24 days after the plateau.
Data acquired by HS-SPME-GC×GC-TOFMS were deconvoluted and aligned with LECO ChromaTOF Version 4.22 software at a signal to noise ratio of 100. A total of 1240 putative compounds were detected by HS-SPME-GC×GC-TOFMS in at least one of the samples. A comparison of vineyards revealed that approximately 200 of compounds were found to be at significantly different levels in at least one of the harvest dates. Principal component analyses illustrated a separation of samples based on harvest date. C5, C6 and C9 compounds, known as green leaf volatiles, were typically found in higher levels in H1 wines. Modifications of yeast metabolism of the sulfur-containing amino acid, methionine, were noticed. Methionol, methional and ethyl 3-(methylthio)-propionate were significantly lower in H2 wines whereas 2-(methylthio)-ethanol was increased. Several higher alcohol acetates were also measured at higher levels in H2 wines. Sensory evaluation revealed significant differences in wines based on the harvest date determined by berry ripening model. Wines from grapes harvested at H1 were perceived by panellists to be higher in red fruit attributes whereas wines from H2 were perceived higher in dark fruit and plum characters.
These results indicate significant modulation of wine volatiles as a consequence of harvest dates, by altering lipoxygenase derived compounds and yeast metabolism, irrespective of vineyard cultural practices, within the same warm to hot climatic region
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
Influence of yield and harvest date on Shiraz wine volatile and non-volatile composition
No full textTargeted and untargeted metabolomics was applied to wine samples in order to determine the effect of yield and harvest date on Shiraz wine volatile and non-volatile composition within the same warm-hot Australian mesoclimate. Vines were drip irrigated and trellised to open sprawling canopy with an average yield from 10.2-18.5 kg/vine/vineyard. Shiraz wines were made in triplicates from grapes harvested at two occasions 10 to 12 days apart (harvest 1; H1 and harvest 2; H2, respectively) commencing 12 days from the plateau of berry sugar accumulation.
Wine volatiles were acquired by HS-SPME-GC×GC-TOFMS. A total of 1,276 putative compounds were detected in at least one of the wine samples and 175 compounds showed significant trends related to grape maturity. The first two dimensions of the PCA accounted for 57% of the variation and separated the samples according to the harvest date, irrespective of the yield. Trained tasting panels were able to perceive differences between wines from H1 and H2. Wine polyphenols and wine pigments were quantified by LC-MS/MS. Vineyard yield had a predominant effect on wine color related pigments, whereas harvest date was of lesser importance. More than 50 quantified polyphenols in wines were poorly correlated with either harvest date or yield. In conclusion, common evolution of wine volatiles, irrespective of site particularities was noticed for Shiraz, whereas it seems that wine non-volatile composition (colour related compounds and polyphenols) is at bigger influence of site rather than harvest date in the late ripenin
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