Advances in farming systems analysis and intervention
Identifieur interne : 000C74 ( Istex/Corpus ); précédent : 000C73; suivant : 000C75Advances in farming systems analysis and intervention
Auteurs : B. A Keating ; R. L MccownSource :
- Agricultural Systems [ 0308-521X ] ; 2001.
Abstract
In this paper, we recognize two key components of farming systems, namely the bio-physical ‘Production System’ of crops, pastures, animals, soil and climate, together with certain physical inputs and outputs, and the ‘Management System’, made up of people, values, goals, knowledge, resources, monitoring opportunities, and decision making. Utilising upon these constructs, we review six types of farming systems analysis and intervention that have evolved over the last 40 years, namely: (1) economic decision analysis based on production functions, (2) dynamic simulation of production processes, (3) economic decision analysis linked to biophysical simulation, (4) decision support systems, (5) expert systems, and (6) simulation-aided discussions about management in an action research paradigm. Biophysical simulation modelling features prominently in this list of approaches and considerable progress has been made in both the scope and predictive power of the modelling tools. We illustrate some more recent advances in increasing model comprehensiveness in simulating farm production systems via reference to our own group's work with the Agricultural Production Systems Simulator (APSIM). Two case studies are discussed, one with broad-scale commercial agriculture in north-eastern Australia and the other with resource poor smallholder farmers in Africa. We conclude by considering future directions for systems analysis efforts directed at farming systems. We see the major challenges and opportunities lying at the interface of ‘hard’, scientific approaches to the analysis of biophysical systems and ‘soft’, approaches to intervention in social management systems.
Url:
DOI: 10.1016/S0308-521X(01)00059-2
Links to Exploration step
ISTEX:93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title>Advances in farming systems analysis and intervention</title><author><name sortKey="Keating, B A" sort="Keating, B A" uniqKey="Keating B" first="B. A" last="Keating">B. A Keating</name><affiliation><mods:affiliation>E-mail: brian.keating@cse.csiro.au</mods:affiliation></affiliation><affiliation><mods:affiliation>APSRU/CSIRO Sustainable Ecosystems, 120 Meiers Road, Indooroopilly, Brisbane, 4068 Australia</mods:affiliation></affiliation></author><author><name sortKey="Mccown, R L" sort="Mccown, R L" uniqKey="Mccown R" first="R. L" last="Mccown">R. L Mccown</name><affiliation><mods:affiliation>APSRU/CSIRO Sustainable Ecosystems, 102 Tor Street, Toowoomba, Queensland, Australia</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96</idno><date when="2001" year="2001">2001</date><idno type="doi">10.1016/S0308-521X(01)00059-2</idno><idno type="url">https://api.istex.fr/document/93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000C74</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000C74</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a">Advances in farming systems analysis and intervention</title><author><name sortKey="Keating, B A" sort="Keating, B A" uniqKey="Keating B" first="B. A" last="Keating">B. A Keating</name><affiliation><mods:affiliation>E-mail: brian.keating@cse.csiro.au</mods:affiliation></affiliation><affiliation><mods:affiliation>APSRU/CSIRO Sustainable Ecosystems, 120 Meiers Road, Indooroopilly, Brisbane, 4068 Australia</mods:affiliation></affiliation></author><author><name sortKey="Mccown, R L" sort="Mccown, R L" uniqKey="Mccown R" first="R. L" last="Mccown">R. L Mccown</name><affiliation><mods:affiliation>APSRU/CSIRO Sustainable Ecosystems, 102 Tor Street, Toowoomba, Queensland, Australia</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Agricultural Systems</title><title level="j" type="abbrev">AGSY</title><idno type="ISSN">0308-521X</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2001">2001</date><biblScope unit="volume">70</biblScope><biblScope unit="issue">2–3</biblScope><biblScope unit="page" from="555">555</biblScope><biblScope unit="page" to="579">579</biblScope></imprint><idno type="ISSN">0308-521X</idno></series><idno type="istex">93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96</idno><idno type="DOI">10.1016/S0308-521X(01)00059-2</idno><idno type="PII">S0308-521X(01)00059-2</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0308-521X</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this paper, we recognize two key components of farming systems, namely the bio-physical ‘Production System’ of crops, pastures, animals, soil and climate, together with certain physical inputs and outputs, and the ‘Management System’, made up of people, values, goals, knowledge, resources, monitoring opportunities, and decision making. Utilising upon these constructs, we review six types of farming systems analysis and intervention that have evolved over the last 40 years, namely: (1) economic decision analysis based on production functions, (2) dynamic simulation of production processes, (3) economic decision analysis linked to biophysical simulation, (4) decision support systems, (5) expert systems, and (6) simulation-aided discussions about management in an action research paradigm. Biophysical simulation modelling features prominently in this list of approaches and considerable progress has been made in both the scope and predictive power of the modelling tools. We illustrate some more recent advances in increasing model comprehensiveness in simulating farm production systems via reference to our own group's work with the Agricultural Production Systems Simulator (APSIM). Two case studies are discussed, one with broad-scale commercial agriculture in north-eastern Australia and the other with resource poor smallholder farmers in Africa. We conclude by considering future directions for systems analysis efforts directed at farming systems. We see the major challenges and opportunities lying at the interface of ‘hard’, scientific approaches to the analysis of biophysical systems and ‘soft’, approaches to intervention in social management systems.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>B.A Keating</name><affiliations><json:string>E-mail: brian.keating@cse.csiro.au</json:string><json:string>APSRU/CSIRO Sustainable Ecosystems, 120 Meiers Road, Indooroopilly, Brisbane, 4068 Australia</json:string></affiliations></json:item><json:item><name>R.L McCown</name><affiliations><json:string>APSRU/CSIRO Sustainable Ecosystems, 102 Tor Street, Toowoomba, Queensland, Australia</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>Farming systems</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Modelling</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Decision support</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>DSS</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>FARMSCAPE</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>APSIM</value></json:item></subject><language><json:string>eng</json:string></language><originalGenre><json:string>Full-length article</json:string></originalGenre><abstract>In this paper, we recognize two key components of farming systems, namely the bio-physical ‘Production System’ of crops, pastures, animals, soil and climate, together with certain physical inputs and outputs, and the ‘Management System’, made up of people, values, goals, knowledge, resources, monitoring opportunities, and decision making. Utilising upon these constructs, we review six types of farming systems analysis and intervention that have evolved over the last 40 years, namely: (1) economic decision analysis based on production functions, (2) dynamic simulation of production processes, (3) economic decision analysis linked to biophysical simulation, (4) decision support systems, (5) expert systems, and (6) simulation-aided discussions about management in an action research paradigm. Biophysical simulation modelling features prominently in this list of approaches and considerable progress has been made in both the scope and predictive power of the modelling tools. We illustrate some more recent advances in increasing model comprehensiveness in simulating farm production systems via reference to our own group's work with the Agricultural Production Systems Simulator (APSIM). Two case studies are discussed, one with broad-scale commercial agriculture in north-eastern Australia and the other with resource poor smallholder farmers in Africa. We conclude by considering future directions for systems analysis efforts directed at farming systems. We see the major challenges and opportunities lying at the interface of ‘hard’, scientific approaches to the analysis of biophysical systems and ‘soft’, approaches to intervention in social management systems.</abstract><qualityIndicators><score>7.796</score><pdfVersion>1.2</pdfVersion><pdfPageSize>544 x 743 pts</pdfPageSize><refBibsNative>true</refBibsNative><keywordCount>6</keywordCount><abstractCharCount>1677</abstractCharCount><pdfWordCount>10121</pdfWordCount><pdfCharCount>62286</pdfCharCount><pdfPageCount>25</pdfPageCount><abstractWordCount>233</abstractWordCount></qualityIndicators><title>Advances in farming systems analysis and intervention</title><pii><json:string>S0308-521X(01)00059-2</json:string></pii><genre><json:string>research-article</json:string></genre><host><volume>70</volume><pii><json:string>S0308-521X(00)X0080-7</json:string></pii><pages><last>579</last><first>555</first></pages><issn><json:string>0308-521X</json:string></issn><issue>2–3</issue><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><title>Agricultural Systems</title><publicationDate>2001</publicationDate></host><categories><wos><json:string>science</json:string><json:string>agriculture, multidisciplinary</json:string></wos><scienceMetrix><json:string>applied sciences</json:string><json:string>agriculture, fisheries & forestry</json:string><json:string>agronomy & agriculture</json:string></scienceMetrix></categories><publicationDate>2001</publicationDate><copyrightDate>2001</copyrightDate><doi><json:string>10.1016/S0308-521X(01)00059-2</json:string></doi><id>93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96</id><score>0.041554533</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">Advances in farming systems analysis and intervention</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>ELSEVIER</publisher><availability><p>ELSEVIER</p></availability><date>2001</date></publicationStmt><notesStmt><note type="content">Fig. 1: A ‘cybernetic’ framework for thinking about a farm as a purposeful, managed system (adapted from Sorrensen and Kristensen, 1992). (a) Highlighting the concepts of monitoring and adjustment linking production and management systems (b) Highlighting the place for a ‘Systems Analysis and Intervention’ element.</note><note type="content">Fig. 2: A model of the FARMSCAPE methodology (a) and (b) are sequential, linked by step 7). After McCown et al., 1998.</note><note type="content">Fig. 3: Cumulative distribution function for gross margin associated with four steps in a proposed development pathway (after Keating et al., 1991). See text for detail of Steps 1–4.</note><note type="content">Fig. 4: Average grain production for the six scenarios explored in Natural Region II in Zimbabwe, expressed in terms of grain produced from the whole farm (with 4 ha of cropping) per year. After: Keating et al., 2000.</note><note type="content">Table 1: Approaches to systems analysis and intervention that have been applied to farming systems</note><note type="content">Table 2: Some key developments in farming systems simulation over the past 20 years</note><note type="content">Table 3: Capabilities needed in simulators of farming systems, over and above that traditionally found in crop models</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a">Advances in farming systems analysis and intervention</title><author xml:id="author-1"><persName><forename type="first">B.A</forename><surname>Keating</surname></persName><email>brian.keating@cse.csiro.au</email><note type="correspondence"><p>Corresponding author</p></note><affiliation>APSRU/CSIRO Sustainable Ecosystems, 120 Meiers Road, Indooroopilly, Brisbane, 4068 Australia</affiliation></author><author xml:id="author-2"><persName><forename type="first">R.L</forename><surname>McCown</surname></persName><affiliation>APSRU/CSIRO Sustainable Ecosystems, 102 Tor Street, Toowoomba, Queensland, Australia</affiliation></author></analytic><monogr><title level="j">Agricultural Systems</title><title level="j" type="abbrev">AGSY</title><idno type="pISSN">0308-521X</idno><idno type="PII">S0308-521X(00)X0080-7</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2001"></date><biblScope unit="volume">70</biblScope><biblScope unit="issue">2–3</biblScope><biblScope unit="page" from="555">555</biblScope><biblScope unit="page" to="579">579</biblScope></imprint></monogr><idno type="istex">93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96</idno><idno type="DOI">10.1016/S0308-521X(01)00059-2</idno><idno type="PII">S0308-521X(01)00059-2</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2001</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>In this paper, we recognize two key components of farming systems, namely the bio-physical ‘Production System’ of crops, pastures, animals, soil and climate, together with certain physical inputs and outputs, and the ‘Management System’, made up of people, values, goals, knowledge, resources, monitoring opportunities, and decision making. Utilising upon these constructs, we review six types of farming systems analysis and intervention that have evolved over the last 40 years, namely: (1) economic decision analysis based on production functions, (2) dynamic simulation of production processes, (3) economic decision analysis linked to biophysical simulation, (4) decision support systems, (5) expert systems, and (6) simulation-aided discussions about management in an action research paradigm. Biophysical simulation modelling features prominently in this list of approaches and considerable progress has been made in both the scope and predictive power of the modelling tools. We illustrate some more recent advances in increasing model comprehensiveness in simulating farm production systems via reference to our own group's work with the Agricultural Production Systems Simulator (APSIM). Two case studies are discussed, one with broad-scale commercial agriculture in north-eastern Australia and the other with resource poor smallholder farmers in Africa. We conclude by considering future directions for systems analysis efforts directed at farming systems. We see the major challenges and opportunities lying at the interface of ‘hard’, scientific approaches to the analysis of biophysical systems and ‘soft’, approaches to intervention in social management systems.</p></abstract><textClass><keywords scheme="keyword"><list><head>Keywords</head><item><term>Farming systems</term></item><item><term>Modelling</term></item><item><term>Decision support</term></item><item><term>DSS</term></item><item><term>FARMSCAPE</term></item><item><term>APSIM</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2001">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier, elements deleted: ce:floats; body; tail"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//ES//DTD journal article DTD version 4.5.2//EN//XML" URI="art452.dtd" name="istex:docType"><istex:entity SYSTEM="gr1" NDATA="IMAGE" name="gr1"></istex:entity><istex:entity SYSTEM="gr2" NDATA="IMAGE" name="gr2"></istex:entity><istex:entity SYSTEM="gr3" NDATA="IMAGE" name="gr3"></istex:entity><istex:entity SYSTEM="gr4" NDATA="IMAGE" name="gr4"></istex:entity></istex:docType><istex:document><converted-article version="4.5.2" docsubtype="fla"><item-info><jid>AGSY</jid><aid>724</aid><ce:pii>S0308-521X(01)00059-2</ce:pii><ce:doi>10.1016/S0308-521X(01)00059-2</ce:doi><ce:copyright type="unknown" year="2001"></ce:copyright></item-info><head><ce:title>Advances in farming systems analysis and intervention</ce:title><ce:author-group><ce:author><ce:given-name>B.A</ce:given-name><ce:surname>Keating</ce:surname><ce:cross-ref refid="AFFA"><ce:sup>a</ce:sup></ce:cross-ref><ce:cross-ref refid="COR1"><ce:sup>∗</ce:sup></ce:cross-ref><ce:e-address type="email">brian.keating@cse.csiro.au</ce:e-address></ce:author><ce:author><ce:given-name>R.L</ce:given-name><ce:surname>McCown</ce:surname><ce:cross-ref refid="AFFB"><ce:sup>b</ce:sup></ce:cross-ref></ce:author><ce:affiliation id="AFFA"><ce:label>a</ce:label><ce:textfn>APSRU/CSIRO Sustainable Ecosystems, 120 Meiers Road, Indooroopilly, Brisbane, 4068 Australia</ce:textfn></ce:affiliation><ce:affiliation id="AFFB"><ce:label>b</ce:label><ce:textfn>APSRU/CSIRO Sustainable Ecosystems, 102 Tor Street, Toowoomba, Queensland, Australia</ce:textfn></ce:affiliation><ce:correspondence id="COR1"><ce:label>∗</ce:label><ce:text>Corresponding author</ce:text></ce:correspondence></ce:author-group><ce:date-accepted day="30" month="3" year="2001"></ce:date-accepted><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>In this paper, we recognize two key components of farming systems, namely the bio-physical ‘Production System’ of crops, pastures, animals, soil and climate, together with certain physical inputs and outputs, and the ‘Management System’, made up of people, values, goals, knowledge, resources, monitoring opportunities, and decision making. Utilising upon these constructs, we review six types of farming systems analysis and intervention that have evolved over the last 40 years, namely: (1) economic decision analysis based on production functions, (2) dynamic simulation of production processes, (3) economic decision analysis linked to biophysical simulation, (4) decision support systems, (5) expert systems, and (6) simulation-aided discussions about management in an action research paradigm. Biophysical simulation modelling features prominently in this list of approaches and considerable progress has been made in both the scope and predictive power of the modelling tools. We illustrate some more recent advances in increasing model comprehensiveness in simulating farm production systems via reference to our own group's work with the Agricultural Production Systems Simulator (APSIM). Two case studies are discussed, one with broad-scale commercial agriculture in north-eastern Australia and the other with resource poor smallholder farmers in Africa. We conclude by considering future directions for systems analysis efforts directed at farming systems. We see the major challenges and opportunities lying at the interface of ‘hard’, scientific approaches to the analysis of biophysical systems and ‘soft’, approaches to intervention in social management systems.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords class="keyword"><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Farming systems</ce:text></ce:keyword><ce:keyword><ce:text>Modelling</ce:text></ce:keyword><ce:keyword><ce:text>Decision support</ce:text></ce:keyword><ce:keyword><ce:text>DSS</ce:text></ce:keyword><ce:keyword><ce:text>FARMSCAPE</ce:text></ce:keyword><ce:keyword><ce:text>APSIM</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>Advances in farming systems analysis and intervention</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>Advances in farming systems analysis and intervention</title></titleInfo><name type="personal"><namePart type="given">B.A</namePart><namePart type="family">Keating</namePart><affiliation>E-mail: brian.keating@cse.csiro.au</affiliation><affiliation>APSRU/CSIRO Sustainable Ecosystems, 120 Meiers Road, Indooroopilly, Brisbane, 4068 Australia</affiliation><description>Corresponding author</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">R.L</namePart><namePart type="family">McCown</namePart><affiliation>APSRU/CSIRO Sustainable Ecosystems, 102 Tor Street, Toowoomba, Queensland, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="Full-length article"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">2001</dateIssued><copyrightDate encoding="w3cdtf">2001</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">In this paper, we recognize two key components of farming systems, namely the bio-physical ‘Production System’ of crops, pastures, animals, soil and climate, together with certain physical inputs and outputs, and the ‘Management System’, made up of people, values, goals, knowledge, resources, monitoring opportunities, and decision making. Utilising upon these constructs, we review six types of farming systems analysis and intervention that have evolved over the last 40 years, namely: (1) economic decision analysis based on production functions, (2) dynamic simulation of production processes, (3) economic decision analysis linked to biophysical simulation, (4) decision support systems, (5) expert systems, and (6) simulation-aided discussions about management in an action research paradigm. Biophysical simulation modelling features prominently in this list of approaches and considerable progress has been made in both the scope and predictive power of the modelling tools. We illustrate some more recent advances in increasing model comprehensiveness in simulating farm production systems via reference to our own group's work with the Agricultural Production Systems Simulator (APSIM). Two case studies are discussed, one with broad-scale commercial agriculture in north-eastern Australia and the other with resource poor smallholder farmers in Africa. We conclude by considering future directions for systems analysis efforts directed at farming systems. We see the major challenges and opportunities lying at the interface of ‘hard’, scientific approaches to the analysis of biophysical systems and ‘soft’, approaches to intervention in social management systems.</abstract><note type="content">Fig. 1: A ‘cybernetic’ framework for thinking about a farm as a purposeful, managed system (adapted from Sorrensen and Kristensen, 1992). (a) Highlighting the concepts of monitoring and adjustment linking production and management systems (b) Highlighting the place for a ‘Systems Analysis and Intervention’ element.</note><note type="content">Fig. 2: A model of the FARMSCAPE methodology (a) and (b) are sequential, linked by step 7). After McCown et al., 1998.</note><note type="content">Fig. 3: Cumulative distribution function for gross margin associated with four steps in a proposed development pathway (after Keating et al., 1991). See text for detail of Steps 1–4.</note><note type="content">Fig. 4: Average grain production for the six scenarios explored in Natural Region II in Zimbabwe, expressed in terms of grain produced from the whole farm (with 4 ha of cropping) per year. After: Keating et al., 2000.</note><note type="content">Table 1: Approaches to systems analysis and intervention that have been applied to farming systems</note><note type="content">Table 2: Some key developments in farming systems simulation over the past 20 years</note><note type="content">Table 3: Capabilities needed in simulators of farming systems, over and above that traditionally found in crop models</note><subject><genre>Keywords</genre><topic>Farming systems</topic><topic>Modelling</topic><topic>Decision support</topic><topic>DSS</topic><topic>FARMSCAPE</topic><topic>APSIM</topic></subject><relatedItem type="host"><titleInfo><title>Agricultural Systems</title></titleInfo><titleInfo type="abbreviated"><title>AGSY</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">200111</dateIssued></originInfo><identifier type="ISSN">0308-521X</identifier><identifier type="PII">S0308-521X(00)X0080-7</identifier><part><date>200111</date><detail type="volume"><number>70</number><caption>vol.</caption></detail><detail type="issue"><number>2–3</number><caption>no.</caption></detail><extent unit="issue pages"><start>353</start><end>640</end></extent><extent unit="pages"><start>555</start><end>579</end></extent></part></relatedItem><identifier type="istex">93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96</identifier><identifier type="DOI">10.1016/S0308-521X(01)00059-2</identifier><identifier type="PII">S0308-521X(01)00059-2</identifier><recordInfo><recordContentSource>ELSEVIER</recordContentSource></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Agronomie/explor/SisAgriV1/Data/Istex/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000C74 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Corpus/biblio.hfd -nk 000C74 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Agronomie
|area= SisAgriV1
|flux= Istex
|étape= Corpus
|type= RBID
|clé= ISTEX:93AB8FFA14FB42CBFE07107A596FAE6BEB2E5E96
|texte= Advances in farming systems analysis and intervention
}}
| This area was generated with Dilib version V0.6.28. |  |