Optimization of soybean heat-treating using a fluidized bed dryer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2013-12

AUTHORS

Marcela L. Martínez, María A. Marín, Pablo D. Ribotta

ABSTRACT

This study was designed to optimize drying and inactivation of heat-labile inhibitors conditions of soybean by using a fluidized bed dryer, in order to shorten treatment time and to reduce losses in end-product quality such as soy flour color and soy protein solubility. The independent variables were initial moisture of soybeans, heating time and temperature of air entering the fluidization chamber. The response variables studied were final moisture of soybeans, inactivation of urease, soy flour color and soy protein solubility. Response surface methodology was able to model the response of the different studied variables. For each response group, relevant terms were included into an equation; the behavior of response was predicted within the experimental area and was presented as a response surface. The results suggested that a combination of soybean initial moisture of 0.14 g/g (wb), treatment time of 3.4 min and hot-air temperature of 136.5 °C could be a good processing combination of parameters for heating soybean using hot-air in order to reduce treatment time and quality losses in soybean flour. Thus, fluidized bed drying technology may be used as an alternative industrial method to eliminate the antinutritional factors. More... »

PAGES

1144-1150

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13197-011-0434-9

DOI

http://dx.doi.org/10.1007/s13197-011-0434-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1014818885

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24426027


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/2008/0907", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Environmental Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "IMBIV (CONICET-UNC), ICTA- FCEFyN-UNC, Av. V\u00e9lez S\u00e1rsfield 1611, CPAX5016GCA, C\u00f3rdoba, Argentina"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mart\u00ednez", 
        "givenName": "Marcela L.", 
        "id": "sg:person.011420256027.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011420256027.43"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "ICTA- FCEFyN-UNC, Av. V\u00e9lez S\u00e1rsfield 1611, CPAX5016GCA, C\u00f3rdoba, Argentina"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mar\u00edn", 
        "givenName": "Mar\u00eda A.", 
        "id": "sg:person.016376776174.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016376776174.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "CONICET/Departamento de Qu\u00edmica Industrial y Aplicada, FCEFyN-UNC, Av. Velez S\u00e1rsfield 1611, CPAX5016GCA, C\u00f3rdoba, Argentina"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ribotta", 
        "givenName": "Pablo D.", 
        "id": "sg:person.01012320373.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012320373.51"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/s0022-474x(00)00015-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010229975"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.2478/s11535-006-0039-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012065185", 
          "https://doi.org/10.2478/s11535-006-0039-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00217-008-0838-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015836329", 
          "https://doi.org/10.1007/s00217-008-0838-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00217-008-0838-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015836329", 
          "https://doi.org/10.1007/s00217-008-0838-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10408399409527649", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020859172"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jfoodeng.2004.01.036", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024064221"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0927-7765(03)00040-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025499778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0927-7765(03)00040-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025499778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.aca.2007.07.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031376299"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0308-8146(94)90188-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034606241"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0308-8146(94)90188-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034606241"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13197-010-0082-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038939404", 
          "https://doi.org/10.1007/s13197-010-0082-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13197-010-0082-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038939404", 
          "https://doi.org/10.1007/s13197-010-0082-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.lwt.2005.05.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044394290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foodchem.2008.09.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045922123"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11947-008-0080-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050056675", 
          "https://doi.org/10.1007/s11947-008-0080-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jsfa.1915", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051788287"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/fstl.1997.0247", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054487951"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0009246", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055896283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0009246", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055896283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2527/1991.6972918x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070878250"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3382/ps.0600393", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071244083"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3382/ps.0642314", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071246085"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3382/ps.0691749", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071247759"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/122.1.151", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1077371348"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-12", 
    "datePublishedReg": "2013-12-01", 
    "description": "This study was designed to optimize drying and inactivation of heat-labile inhibitors conditions of soybean by using a fluidized bed dryer, in order to shorten treatment time and to reduce losses in end-product quality such as soy flour color and soy protein solubility. The independent variables were initial moisture of soybeans, heating time and temperature of air entering the fluidization chamber. The response variables studied were final moisture of soybeans, inactivation of urease, soy flour color and soy protein solubility. Response surface methodology was able to model the response of the different studied variables. For each response group, relevant terms were included into an equation; the behavior of response was predicted within the experimental area and was presented as a response surface. The results suggested that a combination of soybean initial moisture of 0.14\u00a0g/g (wb), treatment time of 3.4\u00a0min and hot-air temperature of 136.5\u00a0\u00b0C could be a good processing combination of parameters for heating soybean using hot-air in order to reduce treatment time and quality losses in soybean flour. Thus, fluidized bed drying technology may be used as an alternative industrial method to eliminate the antinutritional factors. ", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s13197-011-0434-9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1006305", 
        "issn": [
          "0022-1155", 
          "0975-8402"
        ], 
        "name": "Journal of Food Science and Technology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "50"
      }
    ], 
    "name": "Optimization of soybean heat-treating using a fluidized bed dryer", 
    "pagination": "1144-1150", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "469a280a6a1ff96d91449c94bd559064dac7cc2df526934ba56467d2f6be2a50"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "24426027"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "0056471"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s13197-011-0434-9"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1014818885"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s13197-011-0434-9", 
      "https://app.dimensions.ai/details/publication/pub.1014818885"
    ], 
    "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%2Fs13197-011-0434-9"
  }
]
 

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/s13197-011-0434-9'

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/s13197-011-0434-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13197-011-0434-9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13197-011-0434-9'


 

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

150 TRIPLES      21 PREDICATES      49 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s13197-011-0434-9 schema:about anzsrc-for:09
2 anzsrc-for:0907
3 schema:author N097d42739db14c34aef508be53a53e66
4 schema:citation sg:pub.10.1007/s00217-008-0838-6
5 sg:pub.10.1007/s11947-008-0080-z
6 sg:pub.10.1007/s13197-010-0082-5
7 sg:pub.10.2478/s11535-006-0039-x
8 https://doi.org/10.1002/jsfa.1915
9 https://doi.org/10.1006/fstl.1997.0247
10 https://doi.org/10.1016/0308-8146(94)90188-0
11 https://doi.org/10.1016/j.aca.2007.07.011
12 https://doi.org/10.1016/j.foodchem.2008.09.021
13 https://doi.org/10.1016/j.jfoodeng.2004.01.036
14 https://doi.org/10.1016/j.lwt.2005.05.013
15 https://doi.org/10.1016/s0022-474x(00)00015-1
16 https://doi.org/10.1016/s0927-7765(03)00040-7
17 https://doi.org/10.1021/jf0009246
18 https://doi.org/10.1080/10408399409527649
19 https://doi.org/10.1093/jn/122.1.151
20 https://doi.org/10.2527/1991.6972918x
21 https://doi.org/10.3382/ps.0600393
22 https://doi.org/10.3382/ps.0642314
23 https://doi.org/10.3382/ps.0691749
24 schema:datePublished 2013-12
25 schema:datePublishedReg 2013-12-01
26 schema:description This study was designed to optimize drying and inactivation of heat-labile inhibitors conditions of soybean by using a fluidized bed dryer, in order to shorten treatment time and to reduce losses in end-product quality such as soy flour color and soy protein solubility. The independent variables were initial moisture of soybeans, heating time and temperature of air entering the fluidization chamber. The response variables studied were final moisture of soybeans, inactivation of urease, soy flour color and soy protein solubility. Response surface methodology was able to model the response of the different studied variables. For each response group, relevant terms were included into an equation; the behavior of response was predicted within the experimental area and was presented as a response surface. The results suggested that a combination of soybean initial moisture of 0.14 g/g (wb), treatment time of 3.4 min and hot-air temperature of 136.5 °C could be a good processing combination of parameters for heating soybean using hot-air in order to reduce treatment time and quality losses in soybean flour. Thus, fluidized bed drying technology may be used as an alternative industrial method to eliminate the antinutritional factors.
27 schema:genre research_article
28 schema:inLanguage en
29 schema:isAccessibleForFree true
30 schema:isPartOf N1bc37dade5254fb4b0a3b4605ff7788c
31 N2d9a2d2e35534e3b91968e4e7babe37c
32 sg:journal.1006305
33 schema:name Optimization of soybean heat-treating using a fluidized bed dryer
34 schema:pagination 1144-1150
35 schema:productId N0327fd4fded24f46982c417dcdfb8c9e
36 N73d6969293014db6a8bfe017ead97bd7
37 Nb144f90cd4874782846d7d6c8f9c9512
38 Nb761104fe43747b1b7c76aeaf0c5a75b
39 Ne7431a78172c4652a6bd90e43acb9416
40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014818885
41 https://doi.org/10.1007/s13197-011-0434-9
42 schema:sdDatePublished 2019-04-11T02:07
43 schema:sdLicense https://scigraph.springernature.com/explorer/license/
44 schema:sdPublisher N6a7370ec01724b1b976b120819e28eef
45 schema:url http://link.springer.com/10.1007%2Fs13197-011-0434-9
46 sgo:license sg:explorer/license/
47 sgo:sdDataset articles
48 rdf:type schema:ScholarlyArticle
49 N0189963e417a43e78ed3ec12dc0a050c rdf:first sg:person.01012320373.51
50 rdf:rest rdf:nil
51 N0327fd4fded24f46982c417dcdfb8c9e schema:name readcube_id
52 schema:value 469a280a6a1ff96d91449c94bd559064dac7cc2df526934ba56467d2f6be2a50
53 rdf:type schema:PropertyValue
54 N06359fd7545e4f06a40f1c4f4cfd02db schema:name IMBIV (CONICET-UNC), ICTA- FCEFyN-UNC, Av. Vélez Sársfield 1611, CPAX5016GCA, Córdoba, Argentina
55 rdf:type schema:Organization
56 N097d42739db14c34aef508be53a53e66 rdf:first sg:person.011420256027.43
57 rdf:rest Ncba6d7c295d8420aa6dda81ff34d1553
58 N1bc37dade5254fb4b0a3b4605ff7788c schema:issueNumber 6
59 rdf:type schema:PublicationIssue
60 N2775bc9397154ea0ad73c1297ecefded schema:name ICTA- FCEFyN-UNC, Av. Vélez Sársfield 1611, CPAX5016GCA, Córdoba, Argentina
61 rdf:type schema:Organization
62 N2d9a2d2e35534e3b91968e4e7babe37c schema:volumeNumber 50
63 rdf:type schema:PublicationVolume
64 N55e3e17c8c014364b6808db88823e9cd schema:name CONICET/Departamento de Química Industrial y Aplicada, FCEFyN-UNC, Av. Velez Sársfield 1611, CPAX5016GCA, Córdoba, Argentina
65 rdf:type schema:Organization
66 N6a7370ec01724b1b976b120819e28eef schema:name Springer Nature - SN SciGraph project
67 rdf:type schema:Organization
68 N73d6969293014db6a8bfe017ead97bd7 schema:name doi
69 schema:value 10.1007/s13197-011-0434-9
70 rdf:type schema:PropertyValue
71 Nb144f90cd4874782846d7d6c8f9c9512 schema:name nlm_unique_id
72 schema:value 0056471
73 rdf:type schema:PropertyValue
74 Nb761104fe43747b1b7c76aeaf0c5a75b schema:name dimensions_id
75 schema:value pub.1014818885
76 rdf:type schema:PropertyValue
77 Ncba6d7c295d8420aa6dda81ff34d1553 rdf:first sg:person.016376776174.07
78 rdf:rest N0189963e417a43e78ed3ec12dc0a050c
79 Ne7431a78172c4652a6bd90e43acb9416 schema:name pubmed_id
80 schema:value 24426027
81 rdf:type schema:PropertyValue
82 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
83 schema:name Engineering
84 rdf:type schema:DefinedTerm
85 anzsrc-for:0907 schema:inDefinedTermSet anzsrc-for:
86 schema:name Environmental Engineering
87 rdf:type schema:DefinedTerm
88 sg:journal.1006305 schema:issn 0022-1155
89 0975-8402
90 schema:name Journal of Food Science and Technology
91 rdf:type schema:Periodical
92 sg:person.01012320373.51 schema:affiliation N55e3e17c8c014364b6808db88823e9cd
93 schema:familyName Ribotta
94 schema:givenName Pablo D.
95 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012320373.51
96 rdf:type schema:Person
97 sg:person.011420256027.43 schema:affiliation N06359fd7545e4f06a40f1c4f4cfd02db
98 schema:familyName Martínez
99 schema:givenName Marcela L.
100 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011420256027.43
101 rdf:type schema:Person
102 sg:person.016376776174.07 schema:affiliation N2775bc9397154ea0ad73c1297ecefded
103 schema:familyName Marín
104 schema:givenName María A.
105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016376776174.07
106 rdf:type schema:Person
107 sg:pub.10.1007/s00217-008-0838-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015836329
108 https://doi.org/10.1007/s00217-008-0838-6
109 rdf:type schema:CreativeWork
110 sg:pub.10.1007/s11947-008-0080-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1050056675
111 https://doi.org/10.1007/s11947-008-0080-z
112 rdf:type schema:CreativeWork
113 sg:pub.10.1007/s13197-010-0082-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038939404
114 https://doi.org/10.1007/s13197-010-0082-5
115 rdf:type schema:CreativeWork
116 sg:pub.10.2478/s11535-006-0039-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1012065185
117 https://doi.org/10.2478/s11535-006-0039-x
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1002/jsfa.1915 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051788287
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1006/fstl.1997.0247 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054487951
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/0308-8146(94)90188-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034606241
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.aca.2007.07.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031376299
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.foodchem.2008.09.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045922123
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.jfoodeng.2004.01.036 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024064221
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.lwt.2005.05.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044394290
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/s0022-474x(00)00015-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010229975
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/s0927-7765(03)00040-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025499778
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1021/jf0009246 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055896283
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1080/10408399409527649 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020859172
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1093/jn/122.1.151 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077371348
142 rdf:type schema:CreativeWork
143 https://doi.org/10.2527/1991.6972918x schema:sameAs https://app.dimensions.ai/details/publication/pub.1070878250
144 rdf:type schema:CreativeWork
145 https://doi.org/10.3382/ps.0600393 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071244083
146 rdf:type schema:CreativeWork
147 https://doi.org/10.3382/ps.0642314 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071246085
148 rdf:type schema:CreativeWork
149 https://doi.org/10.3382/ps.0691749 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071247759
150 rdf:type schema:CreativeWork
 




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


...