Browse
Submit Data
Databases
API
Help

Dataset Information

28 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Electronic nose dataset for pork adulteration in beef.

ABSTRACT: This article provides a dataset of several weight combinations from the adulteration of pork in beef using an electronic nose (e-nose). Seven combinations mixtures have been built, they were 100% pure beef, 10% mixed with pork, 25% mixed with pork, 50% mixed with pork, 75% mixed with pork, 90% mixed with pork, and 100% pure pork. By using this combination, a minimum of 10% of a mixture of pork or beef can be detected. In each experiment cycle, data were collected for 120 s using an e-nose. The availability of this dataset can enable further research about meat adulteration, Halal authentication, etc. For several cases, food adulteration is one of the main concerns in food science, for example, due to economic, religious reasons, etc. This dataset can also be utilized as the data source for several interesting topics such as signal processing, sensor selection, e-nose development, machine learning algorithms, etc.

SUBMITTER: Sarno R

PROVIDER: S-EPMC7452684 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Electronic nose dataset for pork adulteration in beef.

Sarno Riyanarto R Sabilla Shoffi Izza SI Wijaya Dedy Rahman DR Sunaryono Dwi D Fatichah Chastine C

Data in brief 20200807

This article provides a dataset of several weight combinations from the adulteration of pork in beef using an electronic nose (e-nose). Seven combinations mixtures have been built, they were 100% pure beef, 10% mixed with pork, 25% mixed with pork, 50% mixed with pork, 75% mixed with pork, 90% mixed with pork, and 100% pure pork. By using this combination, a minimum of 10% of a mixture of pork or beef can be detected. In each experiment cycle, data were collected for 120 s using an e-nose. The a ...[more]

PMID: 32904304

Similar Datasets

Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions.

Project description:In recent years, the development of a rapid, simple, and low-cost meat assessment system using an electronic nose (e-nose) has been the concern of researchers. In this data article, we provide a time series dataset that was obtained from a beef quality monitoring experiment using an e-nose in uncontrolled ambient conditions. The availability of this dataset will enable discussion on how to deal with noisy e-nose signals and non-optimum sensor array in beef quality monitoring. Hence, the development of proper signal processing and robust machine learning algorithm are several challenges that must be faced. Furthermore, this dataset can also be useful as a comparison dataset for similar e-nose applications, such as air quality monitoring, smart packaging system, and food quality monitoring.

| S-EPMC6282642 | biostudies-literature

Electronic nose dataset for detection of wine spoilage thresholds.

Project description:In this data article, we provide a time series dataset obtained for an application of wine quality detection focused on spoilage thresholds. The database contains 235 recorded measurements of wines divided into three groups and labeled as high quality (HQ), average quality (AQ) and low quality (LQ), in addition to 65 ethanol measurements. This dataset was collected using an electronic nose system (E-Nose) based on Metal Oxide Semiconductor (MOS) gas sensors, self-developed at the Universidade Federal Rural de Pernambuco (Brazil). The dataset is related to the research article entitled "Wine quality rapid detection using a compact electronic nose system: application focused on spoilage thresholds by acetic acid" by Rodriguez Gamboa et al., 2019. The dataset can be accessed publicly at the repository: https://data.mendeley.com/datasets/vpc887d53s/.

| S-EPMC6624639 | biostudies-literature

The Use of Electronic Nose in the Quality Evaluation and Adulteration Identification of Beijing-You Chicken.

Project description:The objective of this study was to reveal the secrets of the unique meat characteristics of Beijing-you chicken (BJY) and to compare the difference of quality and flavor with Luhua chicken (LH) and Arbor Acres broiler (AA) at their typical market ages. The results showed the meat of BJY was richer in essential amino acids, arachidonic acid contents, inosine monophosphate (IMP), and guanosine monophosphate (GMP). The total fatty acid and unsaturated fatty acid contents of BJY chicken and LH chicken were lower than that of AA broilers, whereas the ratios of unsaturated fatty acids/saturated fatty acids (2.31) and polyunsaturated fatty acids/monounsaturated fatty acids (1.52) of BJY chicken were the highest. The electronic nose and SPME-GC/MS analysis confirmed the significant differences among these three chickens, and the variety and relative content of aldehydes might contribute to a richer flavor of BJY chicken. The meat characteristics of BJY were fully investigated and showed that BJY chicken might be favored among these three chicken breeds with the best flavor properties and the highest nutritional value. This study also provides an alternative way to identify BJY chicken from other chickens.

| S-EPMC8953052 | biostudies-literature

Meat, the metabolites: an integrated metabolite profiling and lipidomics approach for the detection of the adulteration of beef with pork.

Project description:Adulteration of high quality food products with sub-standard and cheaper grades is a world-wide problem taxing the global economy. Currently, many traditional tests suffer from poor specificity, highly complex outputs and a lack of high-throughput processing. Metabolomics has been successfully used as an accurate discriminatory technique in a number of applications including microbiology, cancer research and environmental studies and certain types of food fraud. In this study, we have developed metabolomics as a technique to assess the adulteration of meat as an improvement on current methods. Different grades of beef mince and pork mince, purchased from a national retail outlet were combined in a number of percentage ratios and analysed using GC-MS and UHPLC-MS. These techniques were chosen because GC-MS enables investigations of metabolites involved in primary metabolism whilst UHPLC-MS using reversed phase chromatography provides information on lipophilic species. With the application of chemometrics and statistical analyses, a panel of differential metabolites were found for identification of each of the two meat types. Additionally, correlation was observed between metabolite content and percentage of fat declared on meat products' labelling.

| S-EPMC4819684 | biostudies-literature

Electronic nose homogeneous data sets for beef quality classification and microbial population prediction.

Project description:ObjectivesIn recent years, research on the use of electronic noses (e-nose) has developed rapidly, especially in the medical and food fields. Typically, e-nose is coupled with machine learning algorithms to detect or predict multiple sensory classes in a given sample. In many cases, comprehensive and complete experiments are required to ensure the generalizability of the predictive model. For this reason, homogeneous data sets are important to use. Homogeneous data sets refer to the data sets obtained from different observations in almost similar environmental condition. In this data article, e-nose homogeneous data sets are provided for beef quality classification and microbial population prediction.Data descriptionThis data set is originated from 12 type of beef cuts. The process of beef spoilage is recorded using 11 Metal-Oxide Semiconductor (MOS) gas sensors for 2220 min. The formal standards, issued by the Meat Standards Committee, are used as a reference in labeling beef quality. Based on the number of microbial populations, meat quality was grouped into four classes, namely excellent, good, acceptable, and spoiled. The data set is formatted in "xlsx" file. Each sheet represents one beef cut. Moreover, data sets are good cases for feature selection algorithm stability test, especially to solve sensor array optimization problems.

| S-EPMC9261018 | biostudies-literature

Rapid identification of adulteration in raw bovine milk with soymilk by electronic nose and headspace-gas chromatography ion-mobility spectrometry.

Project description:The adulteration of soymilk (SM) into raw bovine milk (RM) to gain profit without declaration could cause a health risk. In this study, electronic nose (E-nose) and headspace-gas chromatography ion-mobility spectrometry (HS-GC-IMS) were applied to establish a rapid and effective method to identify adulteration in RM with SM. The obtained data from HS-GC-IMS and E-nose can distinguish the adulterated samples with SM by principal component analysis. Furthermore, a quantitative model of partial least squares was established. The detection limits of E-nose and HS-GC-IMS quantitative models were 1.53% and 1.43%, the root mean square errors of prediction were 0.7390 and 0.5621, the determination coefficients of prediction were 0.9940 and 0.9958, and the relative percentage difference were 10.02 and 13.27, respectively, indicating quantitative regression and good prediction performances of SM adulteration levels in RM were achieved. This research can provide scientific information on the rapid, non-destructive and effective adulteration detection for RM.

| S-EPMC10176159 | biostudies-literature

Electronic nose dataset for COPD detection from smokers and healthy people through exhaled breath analysis.

Project description:This article presents a database which was obtained by acquiring measurements through a multisensory device called Electronic Nose (E-nose) based on a matrix of metal oxide sensors, in order to discriminate and classify a group of people affected by the respiratory disease Chronic Obstructive Pulmonary Disease (COPD), smokers and healthy control people through exhaled breath analysis. The database consists of 4 groups of measurements which were acquired through the E-nose system: 10 control samples (healthy people), 20 samples of people with COPD, 4 samples of smokers and 10 air samples, where in each group two samples of exhaled breath per person were acquired giving a total of 78 samples (40 from COPD, 20 from control, 8 from smokers and 10 from the air).

| S-EPMC7838708 | biostudies-literature

Hygienic quality, adulteration of pork and histamine production by Raoultella ornithinolytica in milkfish dumpling.

Project description:Ten milkfish dumpling products purchased from retail stores in southern Taiwan were collected to determine the occurrence of biogenic amines, histamine-forming bacteria, and adulteration of pork. This study showed the high contents of aerobic plate count (APC), total coliforms (TC) and Escherichia coli in tested milkfish dumpling samples, whereas the average content of various biogenic amines in all tested samples was < 1.6 mg/100 g (< 0.05 to 1.54 mg/100 g). Three histamine-producing bacterial strains (2 isolates of Raoultella ornithinolytica and 1 isolate of Enterobacter aerogenes) isolated from tested samples produced 276.6 ppm to 561.8 ppm of histamine in trypticase soy broth supplemented with 1.0% L-histidine (TSBH). Assay of multiplex polymerase chain reaction (PCR) revealed that the adulteration rates were 50% (5/10) for pork in milkfish dumplings. In addition, milkfish dumpling stuffing was inoculated with R. ornithinolytica at 5.0 log colony forming units (CFU)/g and stored at various temperatures from 4°C to 37°C to investigate bacterial growth and formation of histamine. The histamine contents quickly increased to higher than 50 mg/100 g in samples stored at 37°C and 25°C within 24 hours and 36 hours, respectively, as well as stored at 15°C within 48 hours. Therefore, bacterial growth and histamine formation were controlled by cold storage of the samples at 4°C.

| S-EPMC9337279 | biostudies-literature

Identification of Pork Adulteration in Processed Meat Products Using the Developed Mitochondrial DNA-Based Primers.

Project description:The identification of pork in commercially processed meats is one of the most crucial issues in the food industry because of religious food ethics, medical purposes, and intentional adulteration to decrease production cost. This study therefore aimed to develop a method for the detection of pork adulteration in meat products using primers specific for pig mitochondrial DNA. Mitochondrial DNA sequences for pig, cattle, chicken, and sheep were obtained from GenBank and aligned. The 294-bp mitochondrial DNA D-loop region was selected as the pig target DNA sequence and appropriate primers were designed using the MUSCLE program. To evaluate primer sensitivity, pork-beef-chicken mixtures were prepared as follows: i) 0% pork-50% beef-50% chicken, ii) 1% pork-49.5% beef-49.5% chicken, iii) 2% pork-49% beef-49% chicken, iv) 5% pork-47.5% beef-47.5% chicken, v) 10% pork-45% beef-45% chicken, and vi) 100% pork-0% beef-0% chicken. In addition, a total of 35 commercially packaged products, including patties, nuggets, meatballs, and sausages containing processed chicken, beef, or a mixture of various meats, were purchased from commercial markets. The primers developed in our study were able to detect as little as 1% pork in the heat treated pork-beef-chicken mixtures. Of the 35 processed products, three samples were pork positive despite being labeled as beef or chicken only or as a beef-chicken mix. These results indicate that the developed primers could be used to detect pork adulteration in various processed meat products for application in safeguarding religious food ethics, detecting allergens, and preventing food adulteration.

| S-EPMC5516074 | biostudies-literature

Bio-benchmarking of electronic nose sensors.

Project description:BackgroundElectronic noses, E-Noses, are instruments designed to reproduce the performance of animal noses or antennae but generally they cannot match the discriminating power of the biological original and have, therefore, been of limited utility. The manner in which odorant space is sampled is a critical factor in the performance of all noses but so far it has been described in detail only for the fly antenna.MethodologyHere we describe how a set of metal oxide (MOx) E-Nose sensors, which is the most commonly used type, samples odorant space and compare it with what is known about fly odorant receptors (ORs).Principal findingsCompared with a fly's odorant receptors, MOx sensors from an electronic nose are on average more narrowly tuned but much more highly correlated with each other. A set of insect ORs can therefore sample broader regions of odorant space independently and redundantly than an equivalent number of MOx sensors. The comparison also highlights some important questions about the molecular nature of fly ORs.ConclusionsThe comparative approach generates practical learnings that may be taken up by solid-state physicists or engineers in designing new solid-state electronic nose sensors. It also potentially deepens our understanding of the performance of the biological system.

| S-EPMC2712691 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data