Simulation of pest effects on crops using coupled pest-crop models: the potential for decision support View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1998

AUTHORS

P. S. Teng , W. D. Batchelor , H. O. Pinnschmidt , G. G. Wilkerson

ABSTRACT

Pest management decision support systems have evolved from rudimentary single decision rules to multiple criteria optimization software. In its simplest form, a decision support tool could be a pest management threshold calculated using empirical relations and field data on a calculator. A sophisticated form would be interactive computer systems that utilize simulation models, databases, and decision algorithms, in an integrated manner, to address normative problems. Central to the decision making process in pest (insect, disease, weed) management is information on the effect that a particular pest population has on the economic output of the crop. This effect depends on crop development stage, the prevailing environment, and the crop genotype’s yield potential and ability to compensate for pest injury. In this paper, we present a conceptual framework for linking pest effects to crop models, and detail the coupling techniques used in linking pest and crop models and demonstrate, with examples, how this provides output for decision support. The crop models belonging to the CERES and CROPGRO families are used to exemplify situations for linking pest effects to crop growth and development via twenty-one links (CROPGRO) and twenty for CERES­RICE. Methods are described for representing pest dynamics, since these affect the pest-crop interaction, and the kind of pest data required for input into pest-crop combination models. Five basic methods of quantifying pest dynamics are proposed — (a) Field assessment, (b) A priori assumptions, (c) Analytic modeling, (d) Pest simulation models, and (e) Use of pest simulation models interlinked with crop models. The concept and techniques for using common coupling points in multiple-pest situations are described. More... »

PAGES

221-266

References to SciGraph publications

  • 1993. Decision support systems for agricultural development in SYSTEMS APPROACHES FOR AGRICULTURAL DEVELOPMENT
  • 1993. Pest damage relations at the field level in SYSTEMS APPROACHES FOR AGRICULTURAL DEVELOPMENT
  • Book

    TITLE

    Understanding Options for Agricultural Production

    ISBN

    978-90-481-4940-7
    978-94-017-3624-4

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_12

    DOI

    http://dx.doi.org/10.1007/978-94-017-3624-4_12

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1048674618


    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/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "name": [
                "Division of Entomology and Plant Pathology, International Rice Research Institute, P.O. Box 933, Manila, The Philippines"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Teng", 
            "givenName": "P. S.", 
            "id": "sg:person.012254557523.28", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012254557523.28"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Iowa State University", 
              "id": "https://www.grid.ac/institutes/grid.34421.30", 
              "name": [
                "Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, Iowa\u00a050011-3080, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Batchelor", 
            "givenName": "W. D.", 
            "id": "sg:person.010022005423.23", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010022005423.23"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Giessen", 
              "id": "https://www.grid.ac/institutes/grid.8664.c", 
              "name": [
                "Tropeninstitut, Abt. Phytopathologie und Angew. Entomologie, Justus-Liebig-Universitaet, Bismarckstr. 16, D-35390\u00a0Giessen, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Pinnschmidt", 
            "givenName": "H. O.", 
            "id": "sg:person.014152656727.25", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014152656727.25"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "North Carolina State University", 
              "id": "https://www.grid.ac/institutes/grid.40803.3f", 
              "name": [
                "Department of Crop Sciences, North Carolina State University, Raleigh, NC\u00a027695-2647, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wilkerson", 
            "givenName": "G. G.", 
            "id": "sg:person.07417323263.92", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07417323263.92"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/0308-521x(94)00012-g", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002028087"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.py.23.090185.002323", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004461095"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1071/pp9840277", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004463515"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1365-3180.1992.tb01906.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006727927"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1365-3180.1988.tb01606.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010597380"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0308-521x(90)90100-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011425313"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0308-521x(90)90100-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011425313"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1365-3180.1988.tb00829.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011897899"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0308-521x(96)00038-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011991982"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4039/ent1091457-11", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015849004"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-011-2842-1_28", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016474665", 
              "https://doi.org/10.1007/978-94-011-2842-1_28"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-011-2842-1_28", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016474665", 
              "https://doi.org/10.1007/978-94-011-2842-1_28"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0308-521x(91)90145-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024635472"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0308-521x(91)90145-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024635472"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0261-2194(86)90087-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028991063"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0261-2194(86)90087-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028991063"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.py.26.090188.001151", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032304099"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0002-1571(80)90009-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033103409"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0002-1571(80)90009-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033103409"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-011-2842-1_16", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033115059", 
              "https://doi.org/10.1007/978-94-011-2842-1_16"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-011-2842-1_16", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033115059", 
              "https://doi.org/10.1007/978-94-011-2842-1_16"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0308-521x(92)90023-h", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033747637"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0308-521x(92)90023-h", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033747637"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0261-2194(90)90003-p", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036528576"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0261-2194(90)90003-p", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036528576"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00221589.1992.11516267", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037528707"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.py.23.090185.002031", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047714965"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/s001447970002408x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053754943"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1094/pd-68-539", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060082675"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1094/phyto-73-1581", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060106874"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1094/phyto-73-89", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060107047"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1094/phyto-81-611", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060109108"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.13031/2013.28665", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064895862"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.13031/2013.32748", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064898770"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2134/agronj1990.00021962008200050033x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068992607"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2134/agronj1991.00021962008300020030x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068992731"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2135/cropsci1991.0011183x003100050041x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1069023065"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2307/2404463", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1069914053"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "1998", 
        "datePublishedReg": "1998-01-01", 
        "description": "Pest management decision support systems have evolved from rudimentary single decision rules to multiple criteria optimization software. In its simplest form, a decision support tool could be a pest management threshold calculated using empirical relations and field data on a calculator. A sophisticated form would be interactive computer systems that utilize simulation models, databases, and decision algorithms, in an integrated manner, to address normative problems. Central to the decision making process in pest (insect, disease, weed) management is information on the effect that a particular pest population has on the economic output of the crop. This effect depends on crop development stage, the prevailing environment, and the crop genotype\u2019s yield potential and ability to compensate for pest injury. In this paper, we present a conceptual framework for linking pest effects to crop models, and detail the coupling techniques used in linking pest and crop models and demonstrate, with examples, how this provides output for decision support. The crop models belonging to the CERES and CROPGRO families are used to exemplify situations for linking pest effects to crop growth and development via twenty-one links (CROPGRO) and twenty for CERES\u00adRICE. Methods are described for representing pest dynamics, since these affect the pest-crop interaction, and the kind of pest data required for input into pest-crop combination models. Five basic methods of quantifying pest dynamics are proposed \u2014 (a) Field assessment, (b) A priori assumptions, (c) Analytic modeling, (d) Pest simulation models, and (e) Use of pest simulation models interlinked with crop models. The concept and techniques for using common coupling points in multiple-pest situations are described.", 
        "editor": [
          {
            "familyName": "Tsuji", 
            "givenName": "Gordon Y.", 
            "type": "Person"
          }, 
          {
            "familyName": "Hoogenboom", 
            "givenName": "Gerrit", 
            "type": "Person"
          }, 
          {
            "familyName": "Thornton", 
            "givenName": "Philip K.", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-94-017-3624-4_12", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-90-481-4940-7", 
            "978-94-017-3624-4"
          ], 
          "name": "Understanding Options for Agricultural Production", 
          "type": "Book"
        }, 
        "name": "Simulation of pest effects on crops using coupled pest-crop models: the potential for decision support", 
        "pagination": "221-266", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-94-017-3624-4_12"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "e7e077214ea34405cbf3d421f2504b08066791bce834fdc56c1e47b922eef9da"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1048674618"
            ]
          }
        ], 
        "publisher": {
          "location": "Dordrecht", 
          "name": "Springer Netherlands", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-94-017-3624-4_12", 
          "https://app.dimensions.ai/details/publication/pub.1048674618"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T19:12", 
        "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_8684_00000273.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-94-017-3624-4_12"
      }
    ]
     

    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.10.1007/978-94-017-3624-4_12'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_12'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_12'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_12'


     

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

    196 TRIPLES      23 PREDICATES      57 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-94-017-3624-4_12 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author Nb08353ea976b4d82b6322836d9ce3ff2
    4 schema:citation sg:pub.10.1007/978-94-011-2842-1_16
    5 sg:pub.10.1007/978-94-011-2842-1_28
    6 https://doi.org/10.1016/0002-1571(80)90009-6
    7 https://doi.org/10.1016/0261-2194(86)90087-6
    8 https://doi.org/10.1016/0261-2194(90)90003-p
    9 https://doi.org/10.1016/0308-521x(90)90100-5
    10 https://doi.org/10.1016/0308-521x(91)90145-z
    11 https://doi.org/10.1016/0308-521x(92)90023-h
    12 https://doi.org/10.1016/0308-521x(94)00012-g
    13 https://doi.org/10.1016/s0308-521x(96)00038-8
    14 https://doi.org/10.1017/s001447970002408x
    15 https://doi.org/10.1071/pp9840277
    16 https://doi.org/10.1080/00221589.1992.11516267
    17 https://doi.org/10.1094/pd-68-539
    18 https://doi.org/10.1094/phyto-73-1581
    19 https://doi.org/10.1094/phyto-73-89
    20 https://doi.org/10.1094/phyto-81-611
    21 https://doi.org/10.1111/j.1365-3180.1988.tb00829.x
    22 https://doi.org/10.1111/j.1365-3180.1988.tb01606.x
    23 https://doi.org/10.1111/j.1365-3180.1992.tb01906.x
    24 https://doi.org/10.1146/annurev.py.23.090185.002031
    25 https://doi.org/10.1146/annurev.py.23.090185.002323
    26 https://doi.org/10.1146/annurev.py.26.090188.001151
    27 https://doi.org/10.13031/2013.28665
    28 https://doi.org/10.13031/2013.32748
    29 https://doi.org/10.2134/agronj1990.00021962008200050033x
    30 https://doi.org/10.2134/agronj1991.00021962008300020030x
    31 https://doi.org/10.2135/cropsci1991.0011183x003100050041x
    32 https://doi.org/10.2307/2404463
    33 https://doi.org/10.4039/ent1091457-11
    34 schema:datePublished 1998
    35 schema:datePublishedReg 1998-01-01
    36 schema:description Pest management decision support systems have evolved from rudimentary single decision rules to multiple criteria optimization software. In its simplest form, a decision support tool could be a pest management threshold calculated using empirical relations and field data on a calculator. A sophisticated form would be interactive computer systems that utilize simulation models, databases, and decision algorithms, in an integrated manner, to address normative problems. Central to the decision making process in pest (insect, disease, weed) management is information on the effect that a particular pest population has on the economic output of the crop. This effect depends on crop development stage, the prevailing environment, and the crop genotype’s yield potential and ability to compensate for pest injury. In this paper, we present a conceptual framework for linking pest effects to crop models, and detail the coupling techniques used in linking pest and crop models and demonstrate, with examples, how this provides output for decision support. The crop models belonging to the CERES and CROPGRO families are used to exemplify situations for linking pest effects to crop growth and development via twenty-one links (CROPGRO) and twenty for CERES­RICE. Methods are described for representing pest dynamics, since these affect the pest-crop interaction, and the kind of pest data required for input into pest-crop combination models. Five basic methods of quantifying pest dynamics are proposed — (a) Field assessment, (b) A priori assumptions, (c) Analytic modeling, (d) Pest simulation models, and (e) Use of pest simulation models interlinked with crop models. The concept and techniques for using common coupling points in multiple-pest situations are described.
    37 schema:editor N4edd600f28cb4b1ba5bd7d25c04b2725
    38 schema:genre chapter
    39 schema:inLanguage en
    40 schema:isAccessibleForFree false
    41 schema:isPartOf N80545e2dd8744eecbef4b31984681b7d
    42 schema:name Simulation of pest effects on crops using coupled pest-crop models: the potential for decision support
    43 schema:pagination 221-266
    44 schema:productId N7c3d4318b12c4da6a706f2b5a8016858
    45 Nd99949a1f501491e98577b47f3ae856b
    46 Nea6b8554e9314785a73115d9d9c0e723
    47 schema:publisher Na120f33d5d0a480fae283b69587217a6
    48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048674618
    49 https://doi.org/10.1007/978-94-017-3624-4_12
    50 schema:sdDatePublished 2019-04-15T19:12
    51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    52 schema:sdPublisher Nc89090eee627465a9c5ec74d448e8da7
    53 schema:url http://link.springer.com/10.1007/978-94-017-3624-4_12
    54 sgo:license sg:explorer/license/
    55 sgo:sdDataset chapters
    56 rdf:type schema:Chapter
    57 N157e1715a81c4a42bad5a148e68880d5 schema:name Division of Entomology and Plant Pathology, International Rice Research Institute, P.O. Box 933, Manila, The Philippines
    58 rdf:type schema:Organization
    59 N18882128badb4d29b3f7cf12a64a0b76 rdf:first sg:person.014152656727.25
    60 rdf:rest N1ff91186ea7c49b09999cba9fba6bde0
    61 N1ff91186ea7c49b09999cba9fba6bde0 rdf:first sg:person.07417323263.92
    62 rdf:rest rdf:nil
    63 N4edd600f28cb4b1ba5bd7d25c04b2725 rdf:first N77f4b6f4a54e4758aba1ceeb4d31e590
    64 rdf:rest N6f81c2ae0a7c4345b56f02f5673c9140
    65 N6f81c2ae0a7c4345b56f02f5673c9140 rdf:first Ncc4b3764492847a8bc68ef59d56a0b9d
    66 rdf:rest Nfeecb3f0735f422f96ff270b213fdeb1
    67 N77f4b6f4a54e4758aba1ceeb4d31e590 schema:familyName Tsuji
    68 schema:givenName Gordon Y.
    69 rdf:type schema:Person
    70 N7c3d4318b12c4da6a706f2b5a8016858 schema:name doi
    71 schema:value 10.1007/978-94-017-3624-4_12
    72 rdf:type schema:PropertyValue
    73 N80545e2dd8744eecbef4b31984681b7d schema:isbn 978-90-481-4940-7
    74 978-94-017-3624-4
    75 schema:name Understanding Options for Agricultural Production
    76 rdf:type schema:Book
    77 Na120f33d5d0a480fae283b69587217a6 schema:location Dordrecht
    78 schema:name Springer Netherlands
    79 rdf:type schema:Organisation
    80 Nb08353ea976b4d82b6322836d9ce3ff2 rdf:first sg:person.012254557523.28
    81 rdf:rest Nce992f8e2316401cb2c3506e65131232
    82 Nc89090eee627465a9c5ec74d448e8da7 schema:name Springer Nature - SN SciGraph project
    83 rdf:type schema:Organization
    84 Ncc4b3764492847a8bc68ef59d56a0b9d schema:familyName Hoogenboom
    85 schema:givenName Gerrit
    86 rdf:type schema:Person
    87 Nce992f8e2316401cb2c3506e65131232 rdf:first sg:person.010022005423.23
    88 rdf:rest N18882128badb4d29b3f7cf12a64a0b76
    89 Nd99949a1f501491e98577b47f3ae856b schema:name dimensions_id
    90 schema:value pub.1048674618
    91 rdf:type schema:PropertyValue
    92 Nde4670a5d15b4b9fb57c3fecbe497e29 schema:familyName Thornton
    93 schema:givenName Philip K.
    94 rdf:type schema:Person
    95 Nea6b8554e9314785a73115d9d9c0e723 schema:name readcube_id
    96 schema:value e7e077214ea34405cbf3d421f2504b08066791bce834fdc56c1e47b922eef9da
    97 rdf:type schema:PropertyValue
    98 Nfeecb3f0735f422f96ff270b213fdeb1 rdf:first Nde4670a5d15b4b9fb57c3fecbe497e29
    99 rdf:rest rdf:nil
    100 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    101 schema:name Information and Computing Sciences
    102 rdf:type schema:DefinedTerm
    103 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    104 schema:name Artificial Intelligence and Image Processing
    105 rdf:type schema:DefinedTerm
    106 sg:person.010022005423.23 schema:affiliation https://www.grid.ac/institutes/grid.34421.30
    107 schema:familyName Batchelor
    108 schema:givenName W. D.
    109 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010022005423.23
    110 rdf:type schema:Person
    111 sg:person.012254557523.28 schema:affiliation N157e1715a81c4a42bad5a148e68880d5
    112 schema:familyName Teng
    113 schema:givenName P. S.
    114 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012254557523.28
    115 rdf:type schema:Person
    116 sg:person.014152656727.25 schema:affiliation https://www.grid.ac/institutes/grid.8664.c
    117 schema:familyName Pinnschmidt
    118 schema:givenName H. O.
    119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014152656727.25
    120 rdf:type schema:Person
    121 sg:person.07417323263.92 schema:affiliation https://www.grid.ac/institutes/grid.40803.3f
    122 schema:familyName Wilkerson
    123 schema:givenName G. G.
    124 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07417323263.92
    125 rdf:type schema:Person
    126 sg:pub.10.1007/978-94-011-2842-1_16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033115059
    127 https://doi.org/10.1007/978-94-011-2842-1_16
    128 rdf:type schema:CreativeWork
    129 sg:pub.10.1007/978-94-011-2842-1_28 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016474665
    130 https://doi.org/10.1007/978-94-011-2842-1_28
    131 rdf:type schema:CreativeWork
    132 https://doi.org/10.1016/0002-1571(80)90009-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033103409
    133 rdf:type schema:CreativeWork
    134 https://doi.org/10.1016/0261-2194(86)90087-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028991063
    135 rdf:type schema:CreativeWork
    136 https://doi.org/10.1016/0261-2194(90)90003-p schema:sameAs https://app.dimensions.ai/details/publication/pub.1036528576
    137 rdf:type schema:CreativeWork
    138 https://doi.org/10.1016/0308-521x(90)90100-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011425313
    139 rdf:type schema:CreativeWork
    140 https://doi.org/10.1016/0308-521x(91)90145-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1024635472
    141 rdf:type schema:CreativeWork
    142 https://doi.org/10.1016/0308-521x(92)90023-h schema:sameAs https://app.dimensions.ai/details/publication/pub.1033747637
    143 rdf:type schema:CreativeWork
    144 https://doi.org/10.1016/0308-521x(94)00012-g schema:sameAs https://app.dimensions.ai/details/publication/pub.1002028087
    145 rdf:type schema:CreativeWork
    146 https://doi.org/10.1016/s0308-521x(96)00038-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011991982
    147 rdf:type schema:CreativeWork
    148 https://doi.org/10.1017/s001447970002408x schema:sameAs https://app.dimensions.ai/details/publication/pub.1053754943
    149 rdf:type schema:CreativeWork
    150 https://doi.org/10.1071/pp9840277 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004463515
    151 rdf:type schema:CreativeWork
    152 https://doi.org/10.1080/00221589.1992.11516267 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037528707
    153 rdf:type schema:CreativeWork
    154 https://doi.org/10.1094/pd-68-539 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060082675
    155 rdf:type schema:CreativeWork
    156 https://doi.org/10.1094/phyto-73-1581 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060106874
    157 rdf:type schema:CreativeWork
    158 https://doi.org/10.1094/phyto-73-89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060107047
    159 rdf:type schema:CreativeWork
    160 https://doi.org/10.1094/phyto-81-611 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060109108
    161 rdf:type schema:CreativeWork
    162 https://doi.org/10.1111/j.1365-3180.1988.tb00829.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011897899
    163 rdf:type schema:CreativeWork
    164 https://doi.org/10.1111/j.1365-3180.1988.tb01606.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1010597380
    165 rdf:type schema:CreativeWork
    166 https://doi.org/10.1111/j.1365-3180.1992.tb01906.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1006727927
    167 rdf:type schema:CreativeWork
    168 https://doi.org/10.1146/annurev.py.23.090185.002031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047714965
    169 rdf:type schema:CreativeWork
    170 https://doi.org/10.1146/annurev.py.23.090185.002323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004461095
    171 rdf:type schema:CreativeWork
    172 https://doi.org/10.1146/annurev.py.26.090188.001151 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032304099
    173 rdf:type schema:CreativeWork
    174 https://doi.org/10.13031/2013.28665 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064895862
    175 rdf:type schema:CreativeWork
    176 https://doi.org/10.13031/2013.32748 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064898770
    177 rdf:type schema:CreativeWork
    178 https://doi.org/10.2134/agronj1990.00021962008200050033x schema:sameAs https://app.dimensions.ai/details/publication/pub.1068992607
    179 rdf:type schema:CreativeWork
    180 https://doi.org/10.2134/agronj1991.00021962008300020030x schema:sameAs https://app.dimensions.ai/details/publication/pub.1068992731
    181 rdf:type schema:CreativeWork
    182 https://doi.org/10.2135/cropsci1991.0011183x003100050041x schema:sameAs https://app.dimensions.ai/details/publication/pub.1069023065
    183 rdf:type schema:CreativeWork
    184 https://doi.org/10.2307/2404463 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069914053
    185 rdf:type schema:CreativeWork
    186 https://doi.org/10.4039/ent1091457-11 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015849004
    187 rdf:type schema:CreativeWork
    188 https://www.grid.ac/institutes/grid.34421.30 schema:alternateName Iowa State University
    189 schema:name Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, Iowa 50011-3080, USA
    190 rdf:type schema:Organization
    191 https://www.grid.ac/institutes/grid.40803.3f schema:alternateName North Carolina State University
    192 schema:name Department of Crop Sciences, North Carolina State University, Raleigh, NC 27695-2647, USA
    193 rdf:type schema:Organization
    194 https://www.grid.ac/institutes/grid.8664.c schema:alternateName University of Giessen
    195 schema:name Tropeninstitut, Abt. Phytopathologie und Angew. Entomologie, Justus-Liebig-Universitaet, Bismarckstr. 16, D-35390 Giessen, Germany
    196 rdf:type schema:Organization
     




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


    ...