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Each sample was done in triplicates. Tentative identification of the volatile compounds was achieved by comparing mass spectrum and RIs with the Nist05a. Some compounds were identified by injecting the authentic compounds into the GC-MS system, while the RI of the compounds was calculated using an n -alkane series under the same conditions according to Van Den Dool and Kratz equation [ 11 ].
Semiquantitative determinations were performed accord-ing to Xiao [ 10 ]. The antioxidant activities of samples were expressed as TEAC values, defined as the concentration of standard trolox with the same antioxidant capacity as those of the samples. Linearity was studied by quantification of the correlation coefficients. Heat map visualization of data was performed using the TBtools v0. Data was log-transformed dividing the values of relative peak areas of each volatile compound by mean to perform heat maps.
Ethical approval: The conducted research is not related to either human or animal use. Compositions of aroma compounds and their calculated RI values from the four functional liquors are listed in Table 1. A total of 61 volatile compounds were tentatively identified and categorized into the following seven groups: esters 28 , alcohols 8 , fatty acids 3 , carbonyl compound including aldehydes and ketones 11 , hydrocarbons 7 , phenols 1 , and other compositions 3.
The relatively low standard deviations obtained for most compounds confirmed the authenticity and validity of the volatile profile of the four liquors. In other words, most of the volatile compounds contributed significantly to the overall aroma of the liquor. As shown in Figure 1 , the similarity and difference of volatile compounds in four functional liquors were analyzed using Venn diagram.
From left to right, the common compounds and different compounds of L1, L2, L3, and L4 were grouped. There were 60 different components including 1 acid octanoic acid , 1 alcohol isoamyl alcohol , 1 aldehyde acetaldehyde , and 7 esters ethyl acetate, ethyl butyrate, isoamyl acetate, ethyl valerate, ethyl hexanoate, ethyl heptanoate, and ethyl octanoate.
L1, L2, L3, and L4 have 2, 11, 10, and 6 components respectively and large difference in taste was observed between L2 and L3. Esters were shown to be the dominant group in the four liquors accounted for Esters are important family of aroma compounds in liquors. They are commonly formed by esterification of alcohols and acids followed by dehydration.
In general, esters were divided into two categories: acetate esters and ethyl esters. Ethyl esters of fatty acids were produced during the alcoholic fermentation and endowed the fruity aromas.
Ethyl hexanoate, ethyl acetate, and ethyl octanoate were the major components in ester group of the four samples. Their presence contributed to the pleasant, fruity fragrance notes of the liquors.
Ethyl octanoate generated pineapple, pear, and sweet fruit aroma was reported to be the most abundant compound in white wines [ 14 ]. Other dominant compounds in ester groups were ethyl butyrate, isoamyl acetate, ethyl pentanoate, ethyl heptanoate, ethyl lactate, and ethyl decanoate.
Their presence commonly contributed to the fruity bouquet notes of the alcoholic drinks. Ethyl lactate produced rum, fruit, and cream aroma.
Hexyl hexanoate with apple peel and peach aroma were detected in L3 7. Ethyl nonanoate with floral and fruity aroma were found only in L3 5. Four of them ethyl hexanoate, ethyl pentanoate, ethyl heptanoate, and ethyl octanoate showed high values of OAV over 1,, especially ethyl hexanoate, which correlates with a green apple odor. Eight alcohols were detected in the functional liquors and served as one of the decisive factors for the flavor of liquors.
Isoamyl alcohol was the most abundant alcohol in all samples from It contributed to a whiskey, malt, and burned aroma. Acids were responsible for fruity, cheese, fatty, and rancid notes. Short-chain acids had the aroma of sour and rancid, and could suppress and cover other aroma in liquors, so appropriate concentration of them in liquor was preferred.
Hexanoic and octanoic acid produced a cheese flavor at low concentrations and harsh and rancid odors at high concentrations [ 16 ]. Butyric acid contributed a cheese aroma at low concentrations while yielding rancid and sweat odors at high concentrations.
It was only detected in L3 Kediri – Pemerintah Kota Kediri, Jawa Timur, memaksimalkan peran Forum Anak dengan menggandeng lembaga perlindungan anak sebagai upaya memenuhi hak anak agar bisa terealisasi lebih optimal. Anak-anak yang ikut dalam forum mendapatkan bekal untuk peningkatan kapasitas, pemahaman, pengetahuan, kesadaran dan perannya sebagai pelopor dan pelapor 2P pemenuhan hak anak.
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Kegiatan ini dilakukan untuk mengimplementasikan peran dari forum anak kelurahan dengan baik dalam upaya pemenuhan hak-hak anak. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent.
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Use this page to find a source and view associated metrics. Use qualitative as well as quantitative metrics when presenting your research impact. Always use more than one quantitative metric. QOAM is a market place for scientific and scholarly journals which publish articles in open access. Quality scoring of the journals in QOAM is based on academic crowd sourcing; price information includes institutional licensed pricing.
Reden wir offen Till Kreutzer und Prof. Folge 1: Reden wir offen ORCID iDs help authors disambiguate their work and display records for funding and grant applications. Since the Helmholtz Open Science Coordination Office supports scientists and their respective Helmholtz Centres in the implementation of open science.
These openly accessible databases contain a significant and steadily growing share of the scientific output of the Helmholtz Association. The following regularly updated overview by ZB MED contains a selection of webinars dealing with open access, open data, open science, open educational resources, horizon , rights and licenses, FAIR data, repositories, peer review, altmetrics, research data management, predatory publishing.
Learn more about finding a journal for publication, open access, predatory journals, your copyright as an author via Toolkit Publish your Paper [ZBW Kiel].
The aim of this toolkit is to support researchers in finding a journal that publishes their paper and optimally promotes the visibility of their research.
The “Guidelines on the Handling of Research Data” put the framework stipulated by the Principles into a concrete form in the DFG’s funding arrangements. This toolkit addresses research data management. This topic is a burden for many in the research routine. For researchers, however, it promises to be of great benefit if they document, secure and finally share their research data. When starting a new project and creating a Data Management Plan – DMP, one of the first considerations to make should be to decide, in advance, which file formats to use.
However, this has the negative consequence of making these data less interoperable. Moreover, file formats can be either lossless or lossy: that is, whether data is uncompressed such as TIFF for images or compressed such as JPEG for images to remove redundant information and thus reduce file size.
It is common practice to do analyses on lossy data but this does not necessarily mean that these data should be the ones that should be kept for long-term storage. In this context, it is highly likely that the most important file to consider for long-term storage through its curation lifecycle is either the first file that which was initially captured from an instrument or a direct lossless standard file format version from this one.
Why is it necessary? How to deal with it? Raw data: By raw data we mean the original data that has been collected from a source and not yet processed or analysed. Raw data will provide the foundation for any downstream analyses. In many cases the captured or collected data may be unique and impossible to reproduce, such as time points in weather measurements and interviews.
For this reason, they should be safeguarded from any possible loss. Moreover, raw data will typically be lossless – i. For example, Leica microscopes use a proprietary data format but is also a container for lossless data – the container contains metadata specific to the Leica microscopes that allows reading, writing and analysis through Leica software.
See also our guide “Data formats for preservation” see link before. Data backup 3. Versioning 4. DFG] will be required to develop several versions of a Data Management Plan DMP , in which they will specify what data will be kept for the longer term. Other projects are invited to submit a Data Management Plan if it is relevant for their planned research. First steps 3. What is it: Not all research data are digital.
Most researchers keep handwritten laboratory notebooks, journals and other materials, examples of which may be surveys, paintings, fossils, minerals and tissue. However, non-digital data can be converted to a digital source in a variety of ways. Why digitize data 3. Digitizing versus Born digital 4. Golden copy 5. Retention period 6. Text digitizing 7. What is sensitive data: What is the best way of managing access to sensitive data? This is not a straightforward question as it involves ethical, legal and technical issues to be tackled.
This guide will help you on your way to preserve your sensitive data safely. It explains the different types of sensitive data, how to prepare them for storage and the possible cost involved in the process. How to prepare sensitive data for storage and sharing 3. It is developed with funding from the DFG, can now be used free of charge by researchers for the preparation of text-based research materials.
Users of the QualiAnon tool can highlight words or text passages and replace it with text pertinent to the category of information, on different levels of abstraction.
Standardized lists can be used, and replacements can be made on a case- and study-specific basis. QualiAnon documents the replacements and allows for data exports of varying sensitivity. The participation of over people from several countries indicates strong interest in the tool.
Among the participants were researchers from different disciplines, research data managers, representatives of research data centers, repositories, authorities and institutions. The further development of the Qualiservice anonymization tool was mainly aimed at enabling it to be used outside of a particularly protected working environment of a research data center such as Qualiservice. What is required? Horizonrequirements 2. Are data publishing costs supported? What are these repository certificates based on?
Introduction: Are you at the start of your project and planning to create research data? Read on to find out how to make it more findable, accessible, interoperable and reusable via the FAIR principles.
Why are the FAIR principles needed? The increasing availability of online resources means that data need to be created with longevity in mind. Providing other researchers with access to your data facilitates knowledge discovery and improves research transparency. What is FAIR data 3.