Improved phenomenological model for an isothermal winemaking fermentation

An improved phenomenological model of the varietals must fermentation in a batch bioreactor under controlled bench-scale conditions is presented. The model allows predicting satisfactorily the behavior of the main bioprocess variables to adjust potential deviations from a predefined trajectory. It avoids possible discontinuities when it is used equations like the Blackman’s type for modelling bioprocesses, allowing a more accurate and smooth approximation to the experimental data. The cellular growth term is modeled as a variant of the Verlhurst’s logistic equation. The validation with own and published experimental data and, an exhaustive sensitivity analysis about its properties are presented. The model shows an excellent performance for the main variables and great potential to be used as biomass state estimator into control strategies to avoid abnormal fermentations and, tracks predefined trajectories.     

Volatile compounds contribution of Hanseniaspora guilliermondii and Hanseniaspora uvarum during red wine vinifications

This work aims to investigate the contribution of a selected non-Saccharomyces yeast species, Hanseniaspora guilliermondii, to higher alcohols, esters, fatty acids and heavy sulphur compounds composition of red wine. Red grape must vinifications of 100 l were performed and an inoculated fermentation with H. guilliermondii was compared to a spontaneous fermentation. The presence of apiculate yeasts was observed in both fermentations; however, Hanseniaspora uvarum was the only apiculate yeast isolated from the spontaneous fermentation. Apiculate yeasts dominated the fermentation until an ethanol concentration of 6% (v/v) was attained and remained in considerable high levels for an ethanol concentration of 12.5% (v/v). The grape must inoculated with H. guilliermondii led to the production of wine with higher concentrations of 1-propanol, 2-phenylethyl acetate and 3-(methylthio)propionic acid, and lower amounts of ethyl hexanoate, pentanoic acid, free fatty acids, 2-methyltetrahydrothiophen-3-one and acetic acid-3-(methylthio)propyl ester, than wine resulting from the spontaneous fermentation. The present study shows that the use of specific apiculate yeasts in grape must fermentations may lead to the production of wines with different chemical profiles, emphasising the importance of Hanseniaspora yeasts as mixed starter cultures with Saccharomyces cerevisiae, in winemaking.     

复杂储层测井评价数据挖掘方法研究

数据挖掘是应对石油勘探开发未来挑战的10项关键技术之一。提出了一种将预测性数据挖掘技术应用于复杂储层测井评价的方法。将遗传算法应用于特征子集选择和建模参数优化,利用重复交叉验证得到泛化误差的无偏估计,并从选定的多学习算法建模结果中优选出最终预测模型。以克拉玛依油田六中区克下组油藏水淹级别划分为例,在该方法框架内对比研究了8种特征子集方案和决策树、神经网络、支持向量机、贝叶斯网络、组合学习等5种分类方法12种预测模型。结果表明支持向量机预测准确率最高,达91.47%,选择其作为最终预测模型,而决策树模型容易理解,作为辅助参考模型。利用该数据挖掘方法解决油、气、水层识别和岩性划分等问题时,能够获得高性能的分类模型,从而将有效地提高解释精度和符合率。     

数据挖掘技术

数据挖掘技术作为一个新兴的技术在许多领域都取得了成功的应用。介绍了数据挖掘技术的基本情况,讨论了主要的数据挖掘问题如数据分类、关联规则挖掘、数据汇总和路径遍历模式识别等。最后展望了数据挖掘技术的发展和今后的研究工作。     

Use of starter cultures in fermentation on a household scale

An overview on the role and potential of microorganisms in traditional food fermentations is given. Prospects for the implementation of starter cultures for homescale food fermentations are discussed against the background of the present situation, socio-economic and rural/logistic constraints, and the potential for improvement of traditional processes. Special attention is given to the African situation and the well-accepted lactic fermented, traditional foods. Perspectives are given on the improvement of the nutritional value and the overall product safety, with reference to strain selection on the basis of particular phenotypic and technical features.     

从学科高度看核测井

彭琥．从学科高度看核测井．测井技术，１９９４，１８（５）：３１８～３２５本文试图在核测井领域内．从其发展历史、方法和仪器分类，以及信息流三方面入手，以认识和思想方法为重点，响应和补充对我国测井学科发展的讨论。本文认为核测井研究可分为地质—物理基础原理、测量方法和仪器、应用方法和资料处理解释三大部分，它们以解决实际问题为共同出发点和归宿。我国核测井仪器研制与国际水平的差距在６０年代曾缩短到５年，但近年来却拉大到了十多年。投产仪器的内在质量和刻度标准化体系的差距更大。按辐射源、被测射线和信息采集分析方法来命名和分类．提供了一个把所有的核测井方法和仪器进行横向比较的方法，从中可体会到发展核测井仪应该综合运用空间、时间、能量等分析手段，以介质固有的核物理参数或岩石物理参数为仪器输出值，通过刻度（试验）井和数值模拟，建立仪器输出值—地层核物理参数—岩石物理参数之间的准确的定量转换及影响因素校正关系。核测井信息流程图提供了对核测井进行纵向分析的线索。研究和认识核测井应该全面完成其正演问题和反演问题的研究，而反演问题存在着更多的困难。在核测井信息流转的每一步骤上都有过成功，也都还存在问题。这对核测井工作者既是挑战，又是机     

DMOS工业优化软件在催化裂化装置吸收稳定单元上的应用

利用基于数据挖掘的有效工具DMOS工业优化软件对催化裂化装置吸收稳定单元稳定汽油蒸气压过高的问题进行分析、处理,得到优化方案,并在生产上进行实施,成功地降低了稳定汽油蒸气压。     

地下盐穴储气库快速建槽技术及其应用

我国地下盐穴储气库为层状盐层建库,盐岩品位低且夹层多,盐穴的建槽速度慢,腔体底部抬升较快,不能满足我国地下储气库建设的需要,迫切需要寻求新的建槽技术加快盐穴储气库的建槽速度。为此,介绍了盐穴储气库溶腔机理,提出了优化造腔参数、扩眼、使用快速工具促溶3种快速建槽技术：①通过数值模拟对造腔循环方式、管柱提升次数、注水排量等造腔工艺参数进行优化;②采用扩眼法加快建槽速度;③应用喷射式、延伸喷射式和软管式3种造腔工具加快建槽速度。现场应用效果表明：快速建槽技术能够加快盐穴储气库的建槽速度,缩短盐穴建库周期,提高盐穴建库效益。     

基于突现自组织映射的数据挖掘：测井岩性识别新方法

提出一种基于突现自组织映射的测井岩性识别数据挖掘方法。采用大规模神经元和无边界环面映射,用U矩阵进行可视化,最后通过人工交互进行聚类和分类。将该方法用于准噶尔盆地陆东一五彩湾地区的火山岩岩性识别,效果良好,准确率达90％以上。该方法能有效发现高维数据中隐藏的模式,尤其适合复杂岩性的测井识别。     

Microbial quality and yeast population dynamics in cracked green table olives’ fermentations

Cracked green table olives, from the Manzanilla variety, are a fermented food produced and consumed in Portugal. The objective of the present work was to study the microbiological characteristics and yeast population evolution during the fermentation of cracked green olives. The predominant microorganisms were yeasts while lactic acid bacteria were not detected and a clear decrease of the mould population was observed. At the end of the fermentations, no viable counts of Enterobacteriaceae were found. Yeast isolates were identified by the 5.8S rRNA-ITS region restriction analysis and by sequencing the D1/D2 region of the 26S rRNA gene. During the initial phases of the fermentations a great diversity of yeasts was observed. However, as the processes evolved the biodiversity decreased with the fermentative yeasts Citeromyces matritensis, Zygotorulaspora mrakii and Saccharomyces cerevisiae becoming the dominant species. The presence of these fermentative yeasts at the end of the production process is associated to a risk of spoilage. The results obtained represent a first attempt towards the comprehension of the microbiota of this type of “Natural olives” that constitute an important component of the Mediterranean diet.     

油气勘探开发常用数据挖掘算法优选

迈入大数据时代的石油工业,需要充分挖掘石油工业大数据的巨大潜在价值。虽然数据挖掘已经在许多行业取得了丰硕的成果,但在油气勘探开发领域的应用还处于初始阶段,这主要由于油气勘探开发的数据及其应用具有自己的特殊性。数据挖掘常用的算法可分为回归、分类、聚类、估计、预测、关联分析等。其中的回归、分类是最成熟、应用最多的算法。但是对于具体的研究对象、不同的研究问题和数据源,不同的回归和分类算法又具有各自的适用性,因此需要针对具体问题优选适合该数据集的算法。以塔河油田的试油数据为例,以地层系数和油层分类为分析挖掘对象,详细解析了常用回归、分类算法的适用性。研究发现,对于常见的石油行业数据和研究对象：1最优的回归算法是反向传播神经网络（BPNN）,其次为支持向量机回归（R-SVM）和多元回归分析（MRA）;2最优的分类算法是支持向量机分类（C-SVM）,其次为贝叶斯逐步判别（BAYSD）;3 MRA和BAYSD可以用于数据降维,BAYSD的降维效果更好;4 R型聚类分析（RCA）可以用于数据降维,Q型聚类分析（QCA）可以用于样本约简;5在做具体的数据挖掘应用研究时一定要针对具体数据集对所用算法进行优选。     

ID3算法及应用

目前,数据发掘技术的研究已引起各个领域的注意,随着数据库中信息量的增加,数据发掘技术在市场分析、决策支持等各个方面,将会给人类带来不可估量的益处。本文主要介绍数据发掘算法中ID3算法及在实际系统中的应用,从而实现数据库的数据查询分析。     

Kinetics of traditional Turkish sausage quality aspects during fermentation

Changes in chemical (pH, moisture, salt, ash, fat, protein, free fatty acids (FFA), thiobarbituric acid reactive substances (TBARS) and residual nitrite contents), colour (Hunter L*, a* and b*, hue angle, chroma (saturation index), browning index (BI) and total colour difference (ΔE)) and microbiological (total mesophilic aerobic bacterial (TMAB), lactic acid bacteria (LAB), total Enterobacteriaceae (TE) and Staphylococcus and Micrococcus (SM)) quality characteristics of traditional fermented sausage “sucuk” during fermentation were investigated and kinetic modeling of these parameters were performed, in this study. The fermentation of the sucuk lasted 9 days. Analysis of the quality parameters was run on the beginning of the fermentation and on the 1st, 2nd, 3rd, 4th, 5th and 9th days of the fermentation process. Changes in the chemical and colour parameters were represented by zero, first and second order kinetic models. Microbial increments were represented by linear (first order kinetic) models and reductions were represented by both linear and Weibull distribution models.     

Authentication of protected designation of origin artichokes by spectroscopy methods

Artichoke samples with the protected designation of origin (PDO) ‘Alcachofa de Benicarló’ were discriminated from those produced in other towns surrounding Valencia and Murcia, outside the PDO frame. Inductively coupled plasma (ICP-OES), near infrared (NIR) and X-ray fluorescence (XRF) were assayed in order to achieve a correct sample classification of the three different origin sample groups (Benicarló, Valencia and Murcia). Chemometrics was used to compare the ability of classification of artichoke from their origin by using concentration data of mineral elements, determined by ICP-OES, NIR spectra and XRF spectra. Multivariate analysis tools, as principal component analysis (PCA), hierarchical cluster analysis (HCA) and partial least square discriminant analysis (PLSDA), were used for chemometric data treatment. This study evidenced that the mineral profile of artichokes is a good way for the correct identification of sample origin and that the direct use of XRF spectra of the lyophilised edible part of artichoke can be used as a cheap and green alternative for the authentication of samples produced in the PDO ‘Alcachofa de Benicarló’ and to differentiate from those produced in near areas.     

Molecular characterisation and antimicrobial activity of bacteria associated with submerged lactic acid cassava fermentation

Molecular identification of microorganisms associated with submerged cassava fermentation was carried out and isolates of lactic acid bacteria (LAB) were examined for antimicrobial activity, including ability to produce antimicrobial peptides as a first step to define starter cultures for controlled cassava fermentations. A total of 75 isolates, including 41 LAB, 31 aerobic bacteria (AB) and three anaerobic bacteria were isolated from unfermented and fermenting cassava roots, cassava leaves and fermented cassava dough and identified by a combination of phenotypic tests and sequencing of 16S rRNA, rpoA, rpoB and pheS genes. Microbial diversity at interspecies and intraspecies level was screened by, respectively, PCR amplification of the 16S-23S rDNA intergenic transcribed spacer (ITS-PCR) and repetitive sequence based PCR (rep-PCR). Antimicrobial activity of LAB cultures and supernatants against indicator bacteria; Escherichia coli, Salmonella enterica serotype Typhimurium (S. Typhimurium), Bacillus cereus and Staphylococcus aureus was studied using agar diffusion tests. Furthermore, inactivation of indicator bacteria was investigated in both liquid medium and during controlled cassava fermentation. Results revealed a diversity of bacterial genera, species and subspecies associated with submerged cassava fermentation. DNA sequencing enabled identification of LAB isolates as Lactobacillus plantarum, Weissella confusa, Weissella paramesenteroides, Lactobacillus rhamnosus, Lactobacillus hilgardii, Lactobacillus paracasei, Leuconostoc mesenteroides, Enterococcus faecium, Enterococcus casseliflavus, and Pediococcus acidilactici. Lactobacillus spp. were the predominant LAB and were present in all cassava samples studied. Aerobic bacteria were predominantly Bacillus spp., including Bacillus subtilis, Bacillus amyloliquefaciens and B. cereus. Other species identified included Staphylococcus pasteuri and Clostridium beijerinkii. Cells, supernatants and cell free supernatants (CFS) of selected LAB isolates were able to inhibit both Gram positive and Gram negative pathogenic bacteria. LAB isolates inactivated all indicator organisms during controlled cassava fermentations, with a 4–6 log reduction after 48 h fermentation. The antimicrobial effect of the LAB was attributed to acid production.     

Assessment of premium organic orange juices authenticity using HPLC-HR-MS and HS-SPME-GC-MS combining data fusion and chemometrics

This study aims to develop a robust chemometric approach to make it possible to authenticate European premium organic orange juices. The metabolomic fingerprinting and the volatile profile of commercial orange juices were analyzed by HPLC-HR-MS and HS-SPME-GC-MS. These data were used for authentication (classification of orange juices) purposes, using principal component analysis, hierarchical cluster analysis and partial least squares discriminant analysis, which provided acceptable results. Some flavonoids, fatty acids, aldehydes and esters were identified as potential markers involved in the differentiation of organic juices. Data fusion strategies were tested and 'mid-level' data fusion achieved an optimal model for classifying organic or conventional orange juices with a sensitivity and specificity of 100%, thus improving the individual models. This approach, combining mass spectrometry techniques, chemometrics and data fusion, likely provides a new framework for the authentication of organic foodstuffs.     

2D-fluorescence and multivariate data analysis for monitoring of sourdough fermentation process

Sourdough is used for the manufacture of bakery products, especially rye bread and vital for the development of its typical flavor. Although the process of sourdough fermentation is known thousands of years, still it is not understood in detail. Despite, in modern bread fabrication quality requirements are very high and demand a consequent control not only for the final baking process, but also for the production of intermediates. Characteristic process variables like pH-value and the degree of acidity are typically measured off-line to receive information about the state of the fermentation process. A new approach for monitoring the actual process state is the employment of 2D-fluorescence spectroscopy. As a non-invasive, optical method it is widely used for monitoring various types of bioprocesses, e.g. yeast or bacterial cultivations. In this contribution the application of partial least squares (PLS) regression and principal component regression (PCR) models for prediction of process variables of rye sourdough fermentations are compared to an evaluation where principal component analysis (PCA) is combined with artificial neural networks (ANN) for prediction of pH-value and acidity. For the pH-value PLS regression proved as good as PCR models and the combination of PCA and ANN. The average percentage root mean square error of prediction (pRMSEP) was between 2.5 and 5.1%. For the prediction of the acidity level, the best results were obtained using PLS regression models (pRMSEP: 6.0–8.1%). Smoothing the noisy 2D-fluorescence spectra slightly decreased the errors about 0.6%. Predictions with data sets of varying dough yield and constant temperature led to about 2% better results than data sets with different temperatures and constant dough yield. These results indicate a higher sensitivity of the prediction quality with respect to varying temperature compared to varying dough yield.     

Food-related hazards in China: Consumers' perceptions of risk and trust in information sources

This paper identifies segments of Chinese consumers based on their perception of personal risk, how worried they are and their subjective knowledge about seven possible food-related hazards: additives, residues, counterfeit, inferior, genetically modified, deteriorated and nutritionally imbalanced food. Data were collected through a consumer survey conducted in Beijing (534 participants) and in Baoding (437 participants). Three clusters were identified: worried and knowledgeable consumers (60.1%), worried and ignorant consumers (21.7%) and moderately worried consumers (18.2%). The first two groups reported a high level of worry and high perception of personal risk about food-related hazards in China. The two hazards they were most worried about were counterfeit food and inferior quality food. Television, internet and personal communication were the three information channels most frequently used by participants to obtain information about food safety. Worried and ignorant consumers reported less frequent use of magazines, books and brochures compared with other consumers. Medical doctors, personal experience and research institutes were the three most trusted information sources for the first two groups of consumers. Moderately worried consumers only placed high levels of trust in medical doctors and themselves. Consumers' perceptions about the knowledge, honesty and concern of different information sources significantly and positively affected their trust in those sources. The study concludes by making recommendations as to how to improve communications with the different identified consumer segments and identifies future research required to expand its validity.     

Dynamics of microbial ecology during cocoa fermentation and drying: Towards the identification of molecular markers

This study aimed to evaluate molecular microbial markers associated with cocoa fermentation and drying steps. The dynamics of microbial populations were analyzed during postharvest processing (fermentation and sun drying) of cocoa from Ivory Coast. The variations in bacterial and yeast communities structure were monitored by a molecular technique (PCR-DGGE) using 16S rRNA and 26S rRNA profiles. Dominant microbial species were determined by sequencing. Our results showed that treatments of cocoa generated great variations in the microbial ecology in terms of number of species detected. The bacterial ecology quickly underwent dramatical changes during the fermentation step after two days. The dominance of Enterobacteria was first observed and then accompanied by Lactic acid bacteria and at the latest stages by acetic acid bacteria. Furthermore, Hanseniaspora opuntiae yeast species predominated during cocoa bean fermentation and drying processes. In addition, two bacterial species were only identified during the drying step of fermented cocoa beans and are potential candidates for biological markers of this process.     

The influence of acid and alkaline treatments on pathogens and the shelf life of poultry meat

A study was carried out to determine the influence of acid and alkaline treatments on pathogens and the shelf life of poultry meat. The following acid and alkaline substances were used: 1% lactic acid, (Purac^R), a 1% formulation of active constituents (sugars, foodstuff phosphates, ascorbic/isoascorbic acid or their inorganic salts) with lactic acid as activator (Glutamal bioactive^R) and 10% trisodium phosphate (TSP). A total of 360 poultry carcasses were collected from a poultry processing plant and subjected to spray treatments at a pressure of 300 kPa and dipping treatments using the acids and alkali. Water was used as control. The carcass rinse method was used as the method of sampling. The microbiological data obtained were subjected to statistical analyses using the multifactor analysis of variance (ANOVA). Sensory evaluations were conducted using a seven-member panel to determine the acceptability or otherwise of the treated carcasses. Mean log₁₀ reductions (cfu/ml) achieved, based on the different treatments, modes of treatment and days of storage were between 0.4 and 2.5 for APC; 0.5 and 2.7 for Enterobacteriaceae; 0.2 and 2.4 for Pseudomonas, and 0.2 and 1.1 for Lactobacillus. The dipping treatment gave the best overall reduction effect. About 60% of the carcasses examined (day 0, only) were positive for salmonella. The sensory evaluations recorded high acceptability scores. The findings show that acids and alkaline substances are viable tools for the decontamination of poultry carcasses.