Analysis and characterization of edible oils by chemometric methods View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2006-04

AUTHORS

Liliana M. Giacomelli, Miguel Mattea, Claudio D. Ceballos

ABSTRACT

Chemometric techniques have been used to group samples with similar features as well as to discriminate among experimental data on edible oils. The objective of this study was to provide a simple method for differentiating vegetable oil types and to classify unknown samples using analytical techniques commonly used in the edible oil industry. We used principal component analysis to study the relationship between FA composition, tocopherol levels, CIF (Commission Internationale de l'Eclairage) parameters, and a photometric color index. The total variance in the original data matrix was established mainly by three principal components. Data processing allowed the oil samples to be identified and created a 2-D map as a fingerprint of the oil types. This analysis can be used successfully to differentiate vegetable oil types and classify them as crude or refined oils. More... »

PAGES

303-308

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11746-006-1204-0

DOI

http://dx.doi.org/10.1007/s11746-006-1204-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022561969


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0301", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Analytical Chemistry", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National University of R\u00edo Cuarto", 
          "id": "https://www.grid.ac/institutes/grid.412226.1", 
          "name": [
            "Departamento de Tecnolog\u00eda Qu\u00edmica, Facultad de Ingenier\u00eda, Universidad Nacional de R\u00edo Cuarto, Ruta Nacional 36 Km. 601, R\u00edo Cuarto (X5804BYA), C\u00f3rdoba, Argentina"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Giacomelli", 
        "givenName": "Liliana M.", 
        "id": "sg:person.01357051024.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01357051024.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National University of R\u00edo Cuarto", 
          "id": "https://www.grid.ac/institutes/grid.412226.1", 
          "name": [
            "Departamento de Tecnolog\u00eda Qu\u00edmica, Facultad de Ingenier\u00eda, Universidad Nacional de R\u00edo Cuarto, Ruta Nacional 36 Km. 601, R\u00edo Cuarto (X5804BYA), C\u00f3rdoba, Argentina"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mattea", 
        "givenName": "Miguel", 
        "id": "sg:person.01026355015.31", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026355015.31"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National University of R\u00edo Cuarto", 
          "id": "https://www.grid.ac/institutes/grid.412226.1", 
          "name": [
            "Departamento de Tecnolog\u00eda Qu\u00edmica, Facultad de Ingenier\u00eda, Universidad Nacional de R\u00edo Cuarto, Ruta Nacional 36 Km. 601, R\u00edo Cuarto (X5804BYA), C\u00f3rdoba, Argentina"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ceballos", 
        "givenName": "Claudio D.", 
        "id": "sg:person.014370674365.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014370674365.33"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s11746-003-0686-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008951274", 
          "https://doi.org/10.1007/s11746-003-0686-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tifs.2003.07.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011277758"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tifs.2003.07.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011277758"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0308-8146(01)00370-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012267651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0925-4005(03)00101-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013148406"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0925-4005(03)00101-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013148406"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0021-9673(01)01502-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013471207"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0003-2670(00)01289-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014131568"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0003-2670(97)00574-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017903313"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11746-997-0093-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019081229", 
          "https://doi.org/10.1007/s11746-997-0093-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11746-997-0172-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022846481", 
          "https://doi.org/10.1007/s11746-997-0172-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0021-9673(00)00389-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026127062"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11746-000-0100-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042372379", 
          "https://doi.org/10.1007/s11746-000-0100-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0003-2670(99)00540-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042807418"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.chroma.2003.10.032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046132053"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2116/analsci.20.935", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049519874"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2006-04", 
    "datePublishedReg": "2006-04-01", 
    "description": "Chemometric techniques have been used to group samples with similar features as well as to discriminate among experimental data on edible oils. The objective of this study was to provide a simple method for differentiating vegetable oil types and to classify unknown samples using analytical techniques commonly used in the edible oil industry. We used principal component analysis to study the relationship between FA composition, tocopherol levels, CIF (Commission Internationale de l'Eclairage) parameters, and a photometric color index. The total variance in the original data matrix was established mainly by three principal components. Data processing allowed the oil samples to be identified and created a 2-D map as a fingerprint of the oil types. This analysis can be used successfully to differentiate vegetable oil types and classify them as crude or refined oils.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11746-006-1204-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1082739", 
        "issn": [
          "0003-021X", 
          "1558-9331"
        ], 
        "name": "Journal of the American Oil Chemists' Society", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "83"
      }
    ], 
    "name": "Analysis and characterization of edible oils by chemometric methods", 
    "pagination": "303-308", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6b7d8faf803f47ddc6faddc8cbacbad97a08005f1d84d7a1eb0581878b37ec72"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11746-006-1204-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1022561969"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11746-006-1204-0", 
      "https://app.dimensions.ai/details/publication/pub.1022561969"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T02:07", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8700_00000521.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs11746-006-1204-0"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11746-006-1204-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11746-006-1204-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11746-006-1204-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11746-006-1204-0'


 

This table displays all metadata directly associated to this object as RDF triples.

121 TRIPLES      21 PREDICATES      41 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11746-006-1204-0 schema:about anzsrc-for:03
2 anzsrc-for:0301
3 schema:author Nb6b37cb79c4843f0952ccf8000b393f4
4 schema:citation sg:pub.10.1007/s11746-000-0100-y
5 sg:pub.10.1007/s11746-003-0686-0
6 sg:pub.10.1007/s11746-997-0093-1
7 sg:pub.10.1007/s11746-997-0172-3
8 https://doi.org/10.1016/j.chroma.2003.10.032
9 https://doi.org/10.1016/j.tifs.2003.07.001
10 https://doi.org/10.1016/s0003-2670(00)01289-7
11 https://doi.org/10.1016/s0003-2670(97)00574-6
12 https://doi.org/10.1016/s0003-2670(99)00540-1
13 https://doi.org/10.1016/s0021-9673(00)00389-7
14 https://doi.org/10.1016/s0021-9673(01)01502-3
15 https://doi.org/10.1016/s0308-8146(01)00370-3
16 https://doi.org/10.1016/s0925-4005(03)00101-1
17 https://doi.org/10.2116/analsci.20.935
18 schema:datePublished 2006-04
19 schema:datePublishedReg 2006-04-01
20 schema:description Chemometric techniques have been used to group samples with similar features as well as to discriminate among experimental data on edible oils. The objective of this study was to provide a simple method for differentiating vegetable oil types and to classify unknown samples using analytical techniques commonly used in the edible oil industry. We used principal component analysis to study the relationship between FA composition, tocopherol levels, CIF (Commission Internationale de l'Eclairage) parameters, and a photometric color index. The total variance in the original data matrix was established mainly by three principal components. Data processing allowed the oil samples to be identified and created a 2-D map as a fingerprint of the oil types. This analysis can be used successfully to differentiate vegetable oil types and classify them as crude or refined oils.
21 schema:genre research_article
22 schema:inLanguage en
23 schema:isAccessibleForFree false
24 schema:isPartOf N1d44a69fe0494a15af026ba5a5f6636f
25 N6ecc9f3f00224401b225703f0d412b45
26 sg:journal.1082739
27 schema:name Analysis and characterization of edible oils by chemometric methods
28 schema:pagination 303-308
29 schema:productId N152ceb9ec21a445fa2b6bec1dd91d1a8
30 N80a26aca411d4aeca2be628b4ffd93e7
31 Nf11a21c783764361a4d1e360586a8ec2
32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022561969
33 https://doi.org/10.1007/s11746-006-1204-0
34 schema:sdDatePublished 2019-04-11T02:07
35 schema:sdLicense https://scigraph.springernature.com/explorer/license/
36 schema:sdPublisher Nce5f71c9ef7140988613abddeefa0625
37 schema:url http://link.springer.com/10.1007%2Fs11746-006-1204-0
38 sgo:license sg:explorer/license/
39 sgo:sdDataset articles
40 rdf:type schema:ScholarlyArticle
41 N152ceb9ec21a445fa2b6bec1dd91d1a8 schema:name readcube_id
42 schema:value 6b7d8faf803f47ddc6faddc8cbacbad97a08005f1d84d7a1eb0581878b37ec72
43 rdf:type schema:PropertyValue
44 N1d44a69fe0494a15af026ba5a5f6636f schema:issueNumber 4
45 rdf:type schema:PublicationIssue
46 N60cbe06dc9bb46419eab93722f634717 rdf:first sg:person.014370674365.33
47 rdf:rest rdf:nil
48 N658f691c77754a1485b4286b2ab23c6e rdf:first sg:person.01026355015.31
49 rdf:rest N60cbe06dc9bb46419eab93722f634717
50 N6ecc9f3f00224401b225703f0d412b45 schema:volumeNumber 83
51 rdf:type schema:PublicationVolume
52 N80a26aca411d4aeca2be628b4ffd93e7 schema:name dimensions_id
53 schema:value pub.1022561969
54 rdf:type schema:PropertyValue
55 Nb6b37cb79c4843f0952ccf8000b393f4 rdf:first sg:person.01357051024.37
56 rdf:rest N658f691c77754a1485b4286b2ab23c6e
57 Nce5f71c9ef7140988613abddeefa0625 schema:name Springer Nature - SN SciGraph project
58 rdf:type schema:Organization
59 Nf11a21c783764361a4d1e360586a8ec2 schema:name doi
60 schema:value 10.1007/s11746-006-1204-0
61 rdf:type schema:PropertyValue
62 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
63 schema:name Chemical Sciences
64 rdf:type schema:DefinedTerm
65 anzsrc-for:0301 schema:inDefinedTermSet anzsrc-for:
66 schema:name Analytical Chemistry
67 rdf:type schema:DefinedTerm
68 sg:journal.1082739 schema:issn 0003-021X
69 1558-9331
70 schema:name Journal of the American Oil Chemists' Society
71 rdf:type schema:Periodical
72 sg:person.01026355015.31 schema:affiliation https://www.grid.ac/institutes/grid.412226.1
73 schema:familyName Mattea
74 schema:givenName Miguel
75 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026355015.31
76 rdf:type schema:Person
77 sg:person.01357051024.37 schema:affiliation https://www.grid.ac/institutes/grid.412226.1
78 schema:familyName Giacomelli
79 schema:givenName Liliana M.
80 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01357051024.37
81 rdf:type schema:Person
82 sg:person.014370674365.33 schema:affiliation https://www.grid.ac/institutes/grid.412226.1
83 schema:familyName Ceballos
84 schema:givenName Claudio D.
85 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014370674365.33
86 rdf:type schema:Person
87 sg:pub.10.1007/s11746-000-0100-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1042372379
88 https://doi.org/10.1007/s11746-000-0100-y
89 rdf:type schema:CreativeWork
90 sg:pub.10.1007/s11746-003-0686-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008951274
91 https://doi.org/10.1007/s11746-003-0686-0
92 rdf:type schema:CreativeWork
93 sg:pub.10.1007/s11746-997-0093-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019081229
94 https://doi.org/10.1007/s11746-997-0093-1
95 rdf:type schema:CreativeWork
96 sg:pub.10.1007/s11746-997-0172-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022846481
97 https://doi.org/10.1007/s11746-997-0172-3
98 rdf:type schema:CreativeWork
99 https://doi.org/10.1016/j.chroma.2003.10.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046132053
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1016/j.tifs.2003.07.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011277758
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1016/s0003-2670(00)01289-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014131568
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1016/s0003-2670(97)00574-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017903313
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1016/s0003-2670(99)00540-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042807418
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1016/s0021-9673(00)00389-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026127062
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/s0021-9673(01)01502-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013471207
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1016/s0308-8146(01)00370-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012267651
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/s0925-4005(03)00101-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013148406
116 rdf:type schema:CreativeWork
117 https://doi.org/10.2116/analsci.20.935 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049519874
118 rdf:type schema:CreativeWork
119 https://www.grid.ac/institutes/grid.412226.1 schema:alternateName National University of Río Cuarto
120 schema:name Departamento de Tecnología Química, Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Ruta Nacional 36 Km. 601, Río Cuarto (X5804BYA), Córdoba, Argentina
121 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...