Yeast species associated with the spontaneous fermentation of cider

This paper reports the influence of cider-making technology (pneumatic and traditional pressing) on the dynamics of wild yeast populations. Yeast colonies isolated from apple juice before and throughout fermentation at a cider cellar of Asturias (Spain), during two consecutive years were studied. The yeast strains were identified by restriction fragment length polymorphism analysis of the 5.8S rRNA gene and the two flanking internal transcribed sequences (ITS). The musts obtained by pneumatic pressing were dominated by non-Saccharomyces yeasts (Hanseniaspora genus and Metschnikowia pulcherrima) whereas in the apple juices obtained by traditional pressing Saccharomyces together with non-Saccharomyces, were always present. The species Saccharomyces present were S. cerevisiae and S. bayanus. Apparently S. bayanus, was the predominant species at the beginning and the middle fermentation steps of the fermentation process, reaching a percentage of isolation between 33% and 41%, whereas S. cerevisiae took over the process in the final stages of fermentation. During the 2001 harvest, with independence of cider-making technology, the species Hanseniaspora valbyensis was always isolated at the end of fermentations.     

Recent advances in edible coatings for fresh and minimally processed fruits

The development of new edible coatings with improved functionality and performance for fresh and minimally processed fruits is one of the challenges of the post harvest industry. In the past few years, research efforts have focused on the design of new eco-friendly coatings based on biodegradable polymers, which not only reduce the requirements of packaging but also lead to the conversion of by-products of the food industry into value added film-forming components. This work reviews the different coating formulations and applications available at present, as well as the main results of the most recent investigations carried out on the topic. Traditionally, edible coatings have been used as a barrier to minimize water loss and delay the natural senescence of coated fruits through selective permeability to gases. However, the new generation of edible coatings is being especially designed to allow the incorporation and/or controlled release of antioxidants, vitamins, nutraceuticals, and natural antimicrobial agents by means of the application of promising technologies such as nanoencapsulation and the layer-by-layer assembly.     

Photoenzymatic Reduction of CC Double Bonds

A simplified procedure for cell‐free biocatalytic reductions of conjugated CC double bonds using old yellow enzymes (OYEs) is reported. Instead of indirectly regenerating YqjM (an OYE homologue from B. subtilis) or NemA (N‐ethylmaleimide reductase from E. coli) via regeneration of reduced nicotinamide cofactors, we demonstrate that direct regeneration of catalytically active reduced flavins is an efficient and convenient approach. Reducing equivalents are provided from simple sacrificial electron donors such as ethylenediaminetetraacetate (EDTA), formate, or phosphite via photocatalytic oxidation. This novel photoenzymatic reaction scheme was characterized. Up to 65% rates of the NADH‐driven reaction were obtained while preserving enantioselectivity. The chemoselectivity of the novel approach was exclusive. Even when using crude cell extracts as biocatalyst preparations, only CC bond reduction was observed while ketone and aldehyde groups remained unaltered. Overall, a simple and practical approach for photobiocatalytic reductions is presented.     

Fiber from fruit pomace: A review of applications in cereal-based products

Fruit pomace is a by-product of the fruit processing industry composed of cell wall compounds, stems, and seeds of the fruit; after washing, drying, and milling, a material high in fiber and bioactive compounds is obtained. In bakery products, dried fruit pomace can be added to replace flour, sugar, or fat and thus reduce energy load while enhancing fiber and antioxidant contents. The high fiber content of fruit pomace, however, results in techno-functional interactions that affect physicochemical and sensory properties. In this article, different sources of fruit pomace are discussed along with their application in bread, brittle and soft bakery products, and extrudates.     

Reducing Capacity,Chlorogenic Acid Content and Biological Activity in a Collection of Scarlet (Solanum aethiopicum) and Gboma (S. macrocarpon) Eggplants

Scarlet (Solanum aethiopicum) and gboma (S. macrocarpon) eggplants are important vegetables in Sub-Saharan Africa. Few studies have been made on these crops regarding the diversity of phenolic content and their biological activity. We have studied the reducing activity, the chlorogenic acid and other phenolic acid contents in a collection of 56 accessions of scarlet eggplant, including the four cultivated groups (Aculeatum, Gilo, Kumba, Shum) and the weedy intermediate S. aethiopicum-S. anguivi types, as well as in eight accessions of gboma eggplant, including the cultivated S. macrocarpon and its wild ancestor, S. dasyphyllum. A sample of the accessions evaluated in this collection has been tested for inhibition of nitric oxide (NO) using macrophage cell cultures. The results show that there is a great diversity in both crops for reducing activity, chlorogenic acid content and chlorogenic acid peak area (% of total phenolic acids). Heritability (H²) for these traits was intermediate to high in both crops. In all samples, chlorogenic acid was the major phenolic acid and accounted for more than 50% of the chromatogram peak area. Considerable differences were found among and within groups for these traits, but the greatest values for total phenolics and chlorogenic acid content were found in S. dasyphyllum. In most groups, reducing activity was positively correlated (with values of up to 0.904 in the Aculeatum group) with chlorogenic acid content. Inhibition of NO was greatest in samples having a high chlorogenic acid content. The results show that both crops are a relevant source of chlorogenic acid and other phenolic acids. The high diversity found also indicates that there are good prospects for breeding new scarlet and gboma eggplant cultivars with improved content in phenolics and bioactive properties.     

Gas barrier changes and morphological alterations induced by retorting in ethylene vinyl alcohol–based food packaging structures

Ethylene vinyl alcohol (EVOH)–based packaging structures were analyzed in terms of both barrier properties and morphological alterations after a retorting process and as functions of ethylene content. From the results, it was found that the samples do have a substantial decrease in oxygen barrier properties and that the kinetics of recovery strongly depends on the copolymer ethylene fraction. A morphological deterioration was also observed as a result of retorting, particularly for packaging structures composed of EVOH copolymers of low ethylene contents. However, the polymer morphology and barrier properties were restored after a dry thermal treatment of the retorted samples. Interestingly, preannealing of copolymers of low ethylene content rendered them more resistant to the retorting process by means of promoting both a more robust crystallinity and a lower water sorption capacity. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 2192–2202, 2005     

Peak height pattern in dichloro-rhodamine and energy transfer dye terminator sequencing

Establishing the pattern in peak heights within local sequence contexts improves the accuracy of base calling and the identification of DNA sequence variations in dye-terminator cycle sequencing. We have systematically examined pairs of sequence-tagged sites (STSs) that vary at only a single nucleotide to determine how base changes influence the peak heights of neighboring bases in sequencing traces generated by two recently commercialized dye-terminator chemistries, the dichloro-rhodamine (dRhodamine) and the energy transfer (BigDye) terminators. For sequencing traces generated with the dRhodamine terminators, the peak height of a particular base in 28 of 64 possible 3-base windows (44%) can be predicted by knowing just one or two bases 5' to the base in question. For those generated with the BigDye terminators, the peak height of a particular base in 23 of 64 possible 3-base windows (36%) can be predicted by knowing the local sequence context. When the peak heights are binned slightly differently, 75% (48 out of 64 cases) of the base peaks generated by both dRhodamine and BigDye terminators fall in the middle half, confirming that the peak patterns of these two new dye terminator chemistries are much more even than those found in the original rhodamine dye terminator sequences.     

Fuzzy method to disclose behaviour patterns in a Tagged World

The main objective of the Ubiquitous computing is to include technology on the user life without modifying their daily routine. A lot of kinds of applications base their operations on using sensors situated on a Tagged World, which is a smart area that serves to recognize user’s behaviour using information about their daily activity. It manages information collected by sensors to identify the user behaviour and to provide some services according to inferred behaviours. In this paper, we present a specific method to extract behaviour patterns on time from the collected sensor signals. The method is based on frequent itemsets that represent the common actions of the user. After, we obtain sequence patterns from these extracted itemsets. Our method should pay attention to the user activities because these have non-random imprecision by definition. Thus, we have designed a method to handle this imprecision, through establishing a temporal constraint that is called Fuzzy Temporal Window.     

A review of feature selection methods on synthetic data

With the advent of high dimensionality, adequate identification of relevant features of the data has become indispensable in real-world scenarios. In this context, the importance of feature selection is beyond doubt and different methods have been developed. However, with such a vast body of algorithms available, choosing the adequate feature selection method is not an easy-to-solve question and it is necessary to check their effectiveness on different situations. Nevertheless, the assessment of relevant features is difficult in real datasets and so an interesting option is to use artificial data. In this paper, several synthetic datasets are employed for this purpose, aiming at reviewing the performance of feature selection methods in the presence of a crescent number or irrelevant features, noise in the data, redundancy and interaction between attributes, as well as a small ratio between number of samples and number of features. Seven filters, two embedded methods, and two wrappers are applied over eleven synthetic datasets, tested by four classifiers, so as to be able to choose a robust method, paving the way for its application to real datasets.     

A new convex objective function for the supervised learning of single-layer neural networks

This paper proposes a novel supervised learning method for single-layer feedforward neural networks. This approach uses an alternative objective function to that based on the MSE, which measures the errors before the neuron's nonlinear activation functions instead of after them. In this case, the solution can be easily obtained solving systems of linear equations, i.e., requiring much less computational power than the one associated with the regular methods. A theoretical study is included to proof the approximated equivalence between the global optimum of the objective function based on the regular MSE criterion and the one of the proposed alternative MSE function.Furthermore, it is shown that the presented method has the capability of allowing incremental and distributed learning. An exhaustive experimental study is also presented to verify the soundness and efficiency of the method. This study contains 10 classification and 16 regression problems. In addition, a comparison with other high performance learning algorithms shows that the proposed method exhibits, in average, the highest performance and low-demanding computational requirements.