Vineyard zone delineation by cluster classification based on annual grape and vine characteristics View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-08

AUTHORS

Ana Belén González-Fernández, José Ramón Rodríguez-Pérez, Enoc Sanz Ablanedo, Celestino Ordoñez

ABSTRACT

This study describes a method for vineyard zone delineation based on spatial interpolation of data on annual monitoring of grape and vine growth from 2007 to 2012 for four commercial vines (Cabernet Sauvignon, Mencía, Merlot and Tempranillo) located in the Bierzo Denomination of Origen (NW Spain). A sampled grid of 20 × 29 m (14 vines/ha) was defined for each vineyard and data were collected for ten soil, six grape composition, three grape production and five vine vigour variables. Continuous maps of each variable were created by spatial interpolation from the sampled points. Several zone delineations were obtained by clustering—using the iterative self-organizing data analysis (ISODATA) algorithm—according to different combinations of the studied variables. The resulting zone delineations were analysed (ANOVA) in order to determine whether the variables in the two cluster classifications for two or three zones were statistically different from each other. The selected delineation was the cluster that included total soluble solids, titratable acidity, total phenolic content, pH, mean cluster weight and length of the internode in two zones. The results point to the feasibility of this approach to vineyard zone delineation. Further research is necessary to confirm the effectiveness of this approach for other locations and evaluate the usefulness of introducing new grape and vine variables. More... »

PAGES

525-573

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11119-016-9475-4

DOI

http://dx.doi.org/10.1007/s11119-016-9475-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006586931


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/2008/0706", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Horticultural Production", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/07", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Agricultural and Veterinary Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Leon", 
          "id": "https://www.grid.ac/institutes/grid.4807.b", 
          "name": [
            "Geomatics Engineering Research Group, University of Le\u00f3n, Av. Astorga s/n, 24401, Ponferrada, Le\u00f3n, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gonz\u00e1lez-Fern\u00e1ndez", 
        "givenName": "Ana Bel\u00e9n", 
        "id": "sg:person.013727366654.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013727366654.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Leon", 
          "id": "https://www.grid.ac/institutes/grid.4807.b", 
          "name": [
            "Geomatics Engineering Research Group, University of Le\u00f3n, Av. Astorga s/n, 24401, Ponferrada, Le\u00f3n, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rodr\u00edguez-P\u00e9rez", 
        "givenName": "Jos\u00e9 Ram\u00f3n", 
        "id": "sg:person.016624005375.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016624005375.90"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Leon", 
          "id": "https://www.grid.ac/institutes/grid.4807.b", 
          "name": [
            "Geomatics Engineering Research Group, University of Le\u00f3n, Av. Astorga s/n, 24401, Ponferrada, Le\u00f3n, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ablanedo", 
        "givenName": "Enoc Sanz", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Oviedo", 
          "id": "https://www.grid.ac/institutes/grid.10863.3c", 
          "name": [
            "Department of Mining Exploitation and Prospecting, University of Oviedo, C/Gonzalo Guti\u00e9rrez Quir\u00f3s, s/n., 33600, Mieres, Oviedo, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ordo\u00f1ez", 
        "givenName": "Celestino", 
        "id": "sg:person.01202030713.84", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01202030713.84"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1023/a:1009925919134", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002153303", 
          "https://doi.org/10.1023/a:1009925919134"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11119-012-9282-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002956090", 
          "https://doi.org/10.1007/s11119-012-9282-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11119-008-9073-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004375659", 
          "https://doi.org/10.1007/s11119-008-9073-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-12-381468-5.00004-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016519923"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/ajgw.12075", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017411717"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1755-0238.2004.tb00006.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017998024"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1755-0238.2004.tb00006.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017998024"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1590/s1516-89132012000200003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018264330"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1590/s0103-84782009005000162", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020539846"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11119-011-9254-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020761897", 
          "https://doi.org/10.1007/s11119-011-9254-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1533/9781845699284.3.445", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021078016"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11119-012-9268-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021222730", 
          "https://doi.org/10.1007/s11119-012-9268-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1755-0238.2005.tb00277.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025914636"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11119-011-9219-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026009021", 
          "https://doi.org/10.1007/s11119-011-9219-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11119-013-9328-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029186362", 
          "https://doi.org/10.1007/s11119-013-9328-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1559/152304083783914958", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032468281"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1755-0238.2011.00151.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033981376"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.foodchem.2010.06.093", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034865979"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11119-014-9354-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035507599", 
          "https://doi.org/10.1007/s11119-014-9354-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/molecules20022061", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046611041"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/molecules20022061", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046611041"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.scienta.2012.09.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047224028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1755-0238.2005.tb00273.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048583109"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5344/ajev.2011.10116", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051610082"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/molecules190913683", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052361186"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/molecules190913683", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052361186"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0504770", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055903670"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0504770", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055903670"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1255/jnirs.679", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064521422"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1255/jnirs.679", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064521422"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.13031/2013.29556", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064896231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.20870/oeno-one.2008.42.4.808", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068804858"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.20870/oeno-one.2009.43.1.804", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068804865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5424/sjar/2009074-1092", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072841506"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5424/sjar/2012102-370-11", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072841878"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/9781420025293", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095905275"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-08", 
    "datePublishedReg": "2017-08-01", 
    "description": "This study describes a method for vineyard zone delineation based on spatial interpolation of data on annual monitoring of grape and vine growth from 2007 to 2012 for four commercial vines (Cabernet Sauvignon, Menc\u00eda, Merlot and Tempranillo) located in the Bierzo Denomination of Origen (NW Spain). A sampled grid of 20 \u00d7 29 m (14 vines/ha) was defined for each vineyard and data were collected for ten soil, six grape composition, three grape production and five vine vigour variables. Continuous maps of each variable were created by spatial interpolation from the sampled points. Several zone delineations were obtained by clustering\u2014using the iterative self-organizing data analysis (ISODATA) algorithm\u2014according to different combinations of the studied variables. The resulting zone delineations were analysed (ANOVA) in order to determine whether the variables in the two cluster classifications for two or three zones were statistically different from each other. The selected delineation was the cluster that included total soluble solids, titratable acidity, total phenolic content, pH, mean cluster weight and length of the internode in two zones. The results point to the feasibility of this approach to vineyard zone delineation. Further research is necessary to confirm the effectiveness of this approach for other locations and evaluate the usefulness of introducing new grape and vine variables.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11119-016-9475-4", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1135929", 
        "issn": [
          "1385-2256", 
          "1573-1618"
        ], 
        "name": "Precision Agriculture", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "18"
      }
    ], 
    "name": "Vineyard zone delineation by cluster classification based on annual grape and vine characteristics", 
    "pagination": "525-573", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "1f5fadc72d4fd376e4cac2ebef433d31c4971371ca83f926180bddaecc7a3225"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11119-016-9475-4"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1006586931"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11119-016-9475-4", 
      "https://app.dimensions.ai/details/publication/pub.1006586931"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T10:00", 
    "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/v90/0000000347_0000000347/records_89816_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs11119-016-9475-4"
  }
]
 

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/s11119-016-9475-4'

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/s11119-016-9475-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11119-016-9475-4'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11119-016-9475-4'


 

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

185 TRIPLES      21 PREDICATES      58 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11119-016-9475-4 schema:about anzsrc-for:07
2 anzsrc-for:0706
3 schema:author N4f2717cd5a0543f28fbf209c8a910843
4 schema:citation sg:pub.10.1007/s11119-008-9073-1
5 sg:pub.10.1007/s11119-011-9219-4
6 sg:pub.10.1007/s11119-011-9254-1
7 sg:pub.10.1007/s11119-012-9268-3
8 sg:pub.10.1007/s11119-012-9282-5
9 sg:pub.10.1007/s11119-013-9328-3
10 sg:pub.10.1007/s11119-014-9354-9
11 sg:pub.10.1023/a:1009925919134
12 https://doi.org/10.1016/b978-0-12-381468-5.00004-x
13 https://doi.org/10.1016/j.foodchem.2010.06.093
14 https://doi.org/10.1016/j.scienta.2012.09.009
15 https://doi.org/10.1021/jf0504770
16 https://doi.org/10.1111/ajgw.12075
17 https://doi.org/10.1111/j.1755-0238.2004.tb00006.x
18 https://doi.org/10.1111/j.1755-0238.2005.tb00273.x
19 https://doi.org/10.1111/j.1755-0238.2005.tb00277.x
20 https://doi.org/10.1111/j.1755-0238.2011.00151.x
21 https://doi.org/10.1201/9781420025293
22 https://doi.org/10.1255/jnirs.679
23 https://doi.org/10.13031/2013.29556
24 https://doi.org/10.1533/9781845699284.3.445
25 https://doi.org/10.1559/152304083783914958
26 https://doi.org/10.1590/s0103-84782009005000162
27 https://doi.org/10.1590/s1516-89132012000200003
28 https://doi.org/10.20870/oeno-one.2008.42.4.808
29 https://doi.org/10.20870/oeno-one.2009.43.1.804
30 https://doi.org/10.3390/molecules190913683
31 https://doi.org/10.3390/molecules20022061
32 https://doi.org/10.5344/ajev.2011.10116
33 https://doi.org/10.5424/sjar/2009074-1092
34 https://doi.org/10.5424/sjar/2012102-370-11
35 schema:datePublished 2017-08
36 schema:datePublishedReg 2017-08-01
37 schema:description This study describes a method for vineyard zone delineation based on spatial interpolation of data on annual monitoring of grape and vine growth from 2007 to 2012 for four commercial vines (Cabernet Sauvignon, Mencía, Merlot and Tempranillo) located in the Bierzo Denomination of Origen (NW Spain). A sampled grid of 20 × 29 m (14 vines/ha) was defined for each vineyard and data were collected for ten soil, six grape composition, three grape production and five vine vigour variables. Continuous maps of each variable were created by spatial interpolation from the sampled points. Several zone delineations were obtained by clustering—using the iterative self-organizing data analysis (ISODATA) algorithm—according to different combinations of the studied variables. The resulting zone delineations were analysed (ANOVA) in order to determine whether the variables in the two cluster classifications for two or three zones were statistically different from each other. The selected delineation was the cluster that included total soluble solids, titratable acidity, total phenolic content, pH, mean cluster weight and length of the internode in two zones. The results point to the feasibility of this approach to vineyard zone delineation. Further research is necessary to confirm the effectiveness of this approach for other locations and evaluate the usefulness of introducing new grape and vine variables.
38 schema:genre research_article
39 schema:inLanguage en
40 schema:isAccessibleForFree false
41 schema:isPartOf N400fc6f01d854e4faf6352da438a87b0
42 N53e97e3908ea430ebd92b72e7eee2885
43 sg:journal.1135929
44 schema:name Vineyard zone delineation by cluster classification based on annual grape and vine characteristics
45 schema:pagination 525-573
46 schema:productId N42a69dc0f99c453b946b3fa8d2089648
47 Ndbf2ed3afde742f7835b9e7750e95b3a
48 Nf63ad8e510d74f7892d8691cb16f6ba4
49 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006586931
50 https://doi.org/10.1007/s11119-016-9475-4
51 schema:sdDatePublished 2019-04-11T10:00
52 schema:sdLicense https://scigraph.springernature.com/explorer/license/
53 schema:sdPublisher N6db06dc3c12b4024b464d6f284ff24e3
54 schema:url https://link.springer.com/10.1007%2Fs11119-016-9475-4
55 sgo:license sg:explorer/license/
56 sgo:sdDataset articles
57 rdf:type schema:ScholarlyArticle
58 N27ed0b35872d4247b170df0ae1c4d6bb rdf:first sg:person.016624005375.90
59 rdf:rest N63850eb865be422ea771916e4a22f0ef
60 N400fc6f01d854e4faf6352da438a87b0 schema:issueNumber 4
61 rdf:type schema:PublicationIssue
62 N42a69dc0f99c453b946b3fa8d2089648 schema:name readcube_id
63 schema:value 1f5fadc72d4fd376e4cac2ebef433d31c4971371ca83f926180bddaecc7a3225
64 rdf:type schema:PropertyValue
65 N4f2717cd5a0543f28fbf209c8a910843 rdf:first sg:person.013727366654.35
66 rdf:rest N27ed0b35872d4247b170df0ae1c4d6bb
67 N53e97e3908ea430ebd92b72e7eee2885 schema:volumeNumber 18
68 rdf:type schema:PublicationVolume
69 N5b24028df0074bed97cc23a7c9a55e76 rdf:first sg:person.01202030713.84
70 rdf:rest rdf:nil
71 N63850eb865be422ea771916e4a22f0ef rdf:first Nfa9093194bda4a41bf876431da3bf094
72 rdf:rest N5b24028df0074bed97cc23a7c9a55e76
73 N6db06dc3c12b4024b464d6f284ff24e3 schema:name Springer Nature - SN SciGraph project
74 rdf:type schema:Organization
75 Ndbf2ed3afde742f7835b9e7750e95b3a schema:name dimensions_id
76 schema:value pub.1006586931
77 rdf:type schema:PropertyValue
78 Nf63ad8e510d74f7892d8691cb16f6ba4 schema:name doi
79 schema:value 10.1007/s11119-016-9475-4
80 rdf:type schema:PropertyValue
81 Nfa9093194bda4a41bf876431da3bf094 schema:affiliation https://www.grid.ac/institutes/grid.4807.b
82 schema:familyName Ablanedo
83 schema:givenName Enoc Sanz
84 rdf:type schema:Person
85 anzsrc-for:07 schema:inDefinedTermSet anzsrc-for:
86 schema:name Agricultural and Veterinary Sciences
87 rdf:type schema:DefinedTerm
88 anzsrc-for:0706 schema:inDefinedTermSet anzsrc-for:
89 schema:name Horticultural Production
90 rdf:type schema:DefinedTerm
91 sg:journal.1135929 schema:issn 1385-2256
92 1573-1618
93 schema:name Precision Agriculture
94 rdf:type schema:Periodical
95 sg:person.01202030713.84 schema:affiliation https://www.grid.ac/institutes/grid.10863.3c
96 schema:familyName Ordoñez
97 schema:givenName Celestino
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01202030713.84
99 rdf:type schema:Person
100 sg:person.013727366654.35 schema:affiliation https://www.grid.ac/institutes/grid.4807.b
101 schema:familyName González-Fernández
102 schema:givenName Ana Belén
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013727366654.35
104 rdf:type schema:Person
105 sg:person.016624005375.90 schema:affiliation https://www.grid.ac/institutes/grid.4807.b
106 schema:familyName Rodríguez-Pérez
107 schema:givenName José Ramón
108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016624005375.90
109 rdf:type schema:Person
110 sg:pub.10.1007/s11119-008-9073-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004375659
111 https://doi.org/10.1007/s11119-008-9073-1
112 rdf:type schema:CreativeWork
113 sg:pub.10.1007/s11119-011-9219-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026009021
114 https://doi.org/10.1007/s11119-011-9219-4
115 rdf:type schema:CreativeWork
116 sg:pub.10.1007/s11119-011-9254-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020761897
117 https://doi.org/10.1007/s11119-011-9254-1
118 rdf:type schema:CreativeWork
119 sg:pub.10.1007/s11119-012-9268-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021222730
120 https://doi.org/10.1007/s11119-012-9268-3
121 rdf:type schema:CreativeWork
122 sg:pub.10.1007/s11119-012-9282-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002956090
123 https://doi.org/10.1007/s11119-012-9282-5
124 rdf:type schema:CreativeWork
125 sg:pub.10.1007/s11119-013-9328-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029186362
126 https://doi.org/10.1007/s11119-013-9328-3
127 rdf:type schema:CreativeWork
128 sg:pub.10.1007/s11119-014-9354-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035507599
129 https://doi.org/10.1007/s11119-014-9354-9
130 rdf:type schema:CreativeWork
131 sg:pub.10.1023/a:1009925919134 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002153303
132 https://doi.org/10.1023/a:1009925919134
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/b978-0-12-381468-5.00004-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1016519923
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.foodchem.2010.06.093 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034865979
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1016/j.scienta.2012.09.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047224028
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1021/jf0504770 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055903670
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1111/ajgw.12075 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017411717
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1111/j.1755-0238.2004.tb00006.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1017998024
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1111/j.1755-0238.2005.tb00273.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1048583109
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1111/j.1755-0238.2005.tb00277.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1025914636
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1111/j.1755-0238.2011.00151.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1033981376
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1201/9781420025293 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095905275
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1255/jnirs.679 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064521422
155 rdf:type schema:CreativeWork
156 https://doi.org/10.13031/2013.29556 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064896231
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1533/9781845699284.3.445 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021078016
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1559/152304083783914958 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032468281
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1590/s0103-84782009005000162 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020539846
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1590/s1516-89132012000200003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018264330
165 rdf:type schema:CreativeWork
166 https://doi.org/10.20870/oeno-one.2008.42.4.808 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068804858
167 rdf:type schema:CreativeWork
168 https://doi.org/10.20870/oeno-one.2009.43.1.804 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068804865
169 rdf:type schema:CreativeWork
170 https://doi.org/10.3390/molecules190913683 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052361186
171 rdf:type schema:CreativeWork
172 https://doi.org/10.3390/molecules20022061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046611041
173 rdf:type schema:CreativeWork
174 https://doi.org/10.5344/ajev.2011.10116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051610082
175 rdf:type schema:CreativeWork
176 https://doi.org/10.5424/sjar/2009074-1092 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072841506
177 rdf:type schema:CreativeWork
178 https://doi.org/10.5424/sjar/2012102-370-11 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072841878
179 rdf:type schema:CreativeWork
180 https://www.grid.ac/institutes/grid.10863.3c schema:alternateName University of Oviedo
181 schema:name Department of Mining Exploitation and Prospecting, University of Oviedo, C/Gonzalo Gutiérrez Quirós, s/n., 33600, Mieres, Oviedo, Spain
182 rdf:type schema:Organization
183 https://www.grid.ac/institutes/grid.4807.b schema:alternateName University of Leon
184 schema:name Geomatics Engineering Research Group, University of León, Av. Astorga s/n, 24401, Ponferrada, León, Spain
185 rdf:type schema:Organization
 




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


...