Disjunctive Kriging in Agriculture View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1989

AUTHORS

R. Webster , M. A. Oliver

ABSTRACT

Farmers apply fertilizers, treat their land or livestock with trace elements and apply remedial treatments for salinity on the basis of estimates from soil samples. If the estimates are less than specified thresholds (for plant or animal nutrients) or more (for salt concentration) then farmers are advised to act. Such estimates are subject to error, and farmers should be better equipped to make their decisions and avoid risks if they know the probabilities of deficiency or toxicity. Disjunctive kriging should be valuable in these circumstances, and this paper describes feasibility studies of its application to agriculture. The paper presents variograms of the phosphorus status of an arable farm in eastern England, cobalt deficiency in the soil of southeast Scotland which causes poor health in sheep and cattle there, and salinity in the Jordan Valley of Israel. It maps the estimated concentrations of these in the soil and the conditional probabilities that the true values are less than the recommended minima for phosphorus and cobalt, and exceed the recommended maximum for salinity. More... »

PAGES

421-432

References to SciGraph publications

  • 1976. A Simple Substitute for Conditional Expectation : The Disjunctive Kriging in ADVANCED GEOSTATISTICS IN THE MINING INDUSTRY
  • Book

    TITLE

    Geostatistics

    ISBN

    978-94-015-6846-3
    978-94-015-6844-9

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-94-015-6844-9_32

    DOI

    http://dx.doi.org/10.1007/978-94-015-6844-9_32

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1021422935


    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/2008/0503", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Soil Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/05", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Environmental Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Rothamsted Research", 
              "id": "https://www.grid.ac/institutes/grid.418374.d", 
              "name": [
                "Rothamsted Experimental Station, Harpenden, Hertfordshire, England"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Webster", 
            "givenName": "R.", 
            "id": "sg:person.01175533525.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01175533525.40"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Department of Geography, The University, Birmingham, England"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Oliver", 
            "givenName": "M. A.", 
            "id": "sg:person.010076772773.20", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010076772773.20"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/978-94-010-1470-0_14", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031348717", 
              "https://doi.org/10.1007/978-94-010-1470-0_14"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1029/wr022i005p00615", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033759352"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1365-2389.1986.tb00392.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034300981"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/jsfa.2740380203", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045985715"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1051/agro:19821010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056943276"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "1989", 
        "datePublishedReg": "1989-01-01", 
        "description": "Farmers apply fertilizers, treat their land or livestock with trace elements and apply remedial treatments for salinity on the basis of estimates from soil samples. If the estimates are less than specified thresholds (for plant or animal nutrients) or more (for salt concentration) then farmers are advised to act. Such estimates are subject to error, and farmers should be better equipped to make their decisions and avoid risks if they know the probabilities of deficiency or toxicity. Disjunctive kriging should be valuable in these circumstances, and this paper describes feasibility studies of its application to agriculture. The paper presents variograms of the phosphorus status of an arable farm in eastern England, cobalt deficiency in the soil of southeast Scotland which causes poor health in sheep and cattle there, and salinity in the Jordan Valley of Israel. It maps the estimated concentrations of these in the soil and the conditional probabilities that the true values are less than the recommended minima for phosphorus and cobalt, and exceed the recommended maximum for salinity.", 
        "editor": [
          {
            "familyName": "Armstrong", 
            "givenName": "Margaret", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-94-015-6844-9_32", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-94-015-6846-3", 
            "978-94-015-6844-9"
          ], 
          "name": "Geostatistics", 
          "type": "Book"
        }, 
        "name": "Disjunctive Kriging in Agriculture", 
        "pagination": "421-432", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-94-015-6844-9_32"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "66119c323070679a89e69d933ce7a33a0ee6335707e97a9682c4ce468bfac279"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1021422935"
            ]
          }
        ], 
        "publisher": {
          "location": "Dordrecht", 
          "name": "Springer Netherlands", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-94-015-6844-9_32", 
          "https://app.dimensions.ai/details/publication/pub.1021422935"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T21:01", 
        "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_8690_00000256.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-94-015-6844-9_32"
      }
    ]
     

    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.10.1007/978-94-015-6844-9_32'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-94-015-6844-9_32'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-94-015-6844-9_32'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-94-015-6844-9_32'


     

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

    90 TRIPLES      23 PREDICATES      32 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-94-015-6844-9_32 schema:about anzsrc-for:05
    2 anzsrc-for:0503
    3 schema:author Na82964289f47423da3910652cdf80cbd
    4 schema:citation sg:pub.10.1007/978-94-010-1470-0_14
    5 https://doi.org/10.1002/jsfa.2740380203
    6 https://doi.org/10.1029/wr022i005p00615
    7 https://doi.org/10.1051/agro:19821010
    8 https://doi.org/10.1111/j.1365-2389.1986.tb00392.x
    9 schema:datePublished 1989
    10 schema:datePublishedReg 1989-01-01
    11 schema:description Farmers apply fertilizers, treat their land or livestock with trace elements and apply remedial treatments for salinity on the basis of estimates from soil samples. If the estimates are less than specified thresholds (for plant or animal nutrients) or more (for salt concentration) then farmers are advised to act. Such estimates are subject to error, and farmers should be better equipped to make their decisions and avoid risks if they know the probabilities of deficiency or toxicity. Disjunctive kriging should be valuable in these circumstances, and this paper describes feasibility studies of its application to agriculture. The paper presents variograms of the phosphorus status of an arable farm in eastern England, cobalt deficiency in the soil of southeast Scotland which causes poor health in sheep and cattle there, and salinity in the Jordan Valley of Israel. It maps the estimated concentrations of these in the soil and the conditional probabilities that the true values are less than the recommended minima for phosphorus and cobalt, and exceed the recommended maximum for salinity.
    12 schema:editor N7f7fe9c477904568a5524baa558654b1
    13 schema:genre chapter
    14 schema:inLanguage en
    15 schema:isAccessibleForFree false
    16 schema:isPartOf Ne924548f454d48418adb8cc3de3ac421
    17 schema:name Disjunctive Kriging in Agriculture
    18 schema:pagination 421-432
    19 schema:productId N19cdebeffaf54fc3a8dd060a90aaf306
    20 N6cad228b91ab4c91beb1945b0cc02404
    21 N85909a0499534c1b8e9a055c49247183
    22 schema:publisher N633e3b78cd184cb2af7cd56b18336c6e
    23 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021422935
    24 https://doi.org/10.1007/978-94-015-6844-9_32
    25 schema:sdDatePublished 2019-04-15T21:01
    26 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    27 schema:sdPublisher Nac122ac7478e4086bb05e314ef9e21c1
    28 schema:url http://link.springer.com/10.1007/978-94-015-6844-9_32
    29 sgo:license sg:explorer/license/
    30 sgo:sdDataset chapters
    31 rdf:type schema:Chapter
    32 N19cdebeffaf54fc3a8dd060a90aaf306 schema:name doi
    33 schema:value 10.1007/978-94-015-6844-9_32
    34 rdf:type schema:PropertyValue
    35 N51426bb5846c4d2d86fce9cf350cad03 rdf:first sg:person.010076772773.20
    36 rdf:rest rdf:nil
    37 N633e3b78cd184cb2af7cd56b18336c6e schema:location Dordrecht
    38 schema:name Springer Netherlands
    39 rdf:type schema:Organisation
    40 N6cad228b91ab4c91beb1945b0cc02404 schema:name dimensions_id
    41 schema:value pub.1021422935
    42 rdf:type schema:PropertyValue
    43 N7f7fe9c477904568a5524baa558654b1 rdf:first Nd85dd5dc2fc545e5844f9d291c6257ba
    44 rdf:rest rdf:nil
    45 N85909a0499534c1b8e9a055c49247183 schema:name readcube_id
    46 schema:value 66119c323070679a89e69d933ce7a33a0ee6335707e97a9682c4ce468bfac279
    47 rdf:type schema:PropertyValue
    48 Na82964289f47423da3910652cdf80cbd rdf:first sg:person.01175533525.40
    49 rdf:rest N51426bb5846c4d2d86fce9cf350cad03
    50 Nac122ac7478e4086bb05e314ef9e21c1 schema:name Springer Nature - SN SciGraph project
    51 rdf:type schema:Organization
    52 Nd85dd5dc2fc545e5844f9d291c6257ba schema:familyName Armstrong
    53 schema:givenName Margaret
    54 rdf:type schema:Person
    55 Ne924548f454d48418adb8cc3de3ac421 schema:isbn 978-94-015-6844-9
    56 978-94-015-6846-3
    57 schema:name Geostatistics
    58 rdf:type schema:Book
    59 Nef0dd0d8e4b340e69254fe89444b59f4 schema:name Department of Geography, The University, Birmingham, England
    60 rdf:type schema:Organization
    61 anzsrc-for:05 schema:inDefinedTermSet anzsrc-for:
    62 schema:name Environmental Sciences
    63 rdf:type schema:DefinedTerm
    64 anzsrc-for:0503 schema:inDefinedTermSet anzsrc-for:
    65 schema:name Soil Sciences
    66 rdf:type schema:DefinedTerm
    67 sg:person.010076772773.20 schema:affiliation Nef0dd0d8e4b340e69254fe89444b59f4
    68 schema:familyName Oliver
    69 schema:givenName M. A.
    70 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010076772773.20
    71 rdf:type schema:Person
    72 sg:person.01175533525.40 schema:affiliation https://www.grid.ac/institutes/grid.418374.d
    73 schema:familyName Webster
    74 schema:givenName R.
    75 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01175533525.40
    76 rdf:type schema:Person
    77 sg:pub.10.1007/978-94-010-1470-0_14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031348717
    78 https://doi.org/10.1007/978-94-010-1470-0_14
    79 rdf:type schema:CreativeWork
    80 https://doi.org/10.1002/jsfa.2740380203 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045985715
    81 rdf:type schema:CreativeWork
    82 https://doi.org/10.1029/wr022i005p00615 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033759352
    83 rdf:type schema:CreativeWork
    84 https://doi.org/10.1051/agro:19821010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056943276
    85 rdf:type schema:CreativeWork
    86 https://doi.org/10.1111/j.1365-2389.1986.tb00392.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1034300981
    87 rdf:type schema:CreativeWork
    88 https://www.grid.ac/institutes/grid.418374.d schema:alternateName Rothamsted Research
    89 schema:name Rothamsted Experimental Station, Harpenden, Hertfordshire, England
    90 rdf:type schema:Organization
     




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


    ...