An engineering approach to modelling, decision support and control for sustainable systems
Identifieur interne : 000188 ( Ncbi/Merge ); précédent : 000187; suivant : 000189An engineering approach to modelling, decision support and control for sustainable systems
Auteurs : W. Day ; E. Audsley ; A. R FrostSource :
- Philosophical Transactions of the Royal Society B: Biological Sciences [ 0962-8436 ] ; 2007.
Abstract
Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability—all essential to sustainable systems.
Url:
DOI: 10.1098/rstb.2007.2168
PubMed: 17656345
PubMed Central: 2610168
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<author><name sortKey="Audsley, E" sort="Audsley, E" uniqKey="Audsley E" first="E" last="Audsley">E. Audsley</name>
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<author><name sortKey="Frost, A R" sort="Frost, A R" uniqKey="Frost A" first="A. R" last="Frost">A. R Frost</name>
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<author><name sortKey="Day, W" sort="Day, W" uniqKey="Day W" first="W" last="Day">W. Day</name>
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<author><name sortKey="Audsley, E" sort="Audsley, E" uniqKey="Audsley E" first="E" last="Audsley">E. Audsley</name>
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<author><name sortKey="Frost, A R" sort="Frost, A R" uniqKey="Frost A" first="A. R" last="Frost">A. R Frost</name>
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<series><title level="j">Philosophical Transactions of the Royal Society B: Biological Sciences</title>
<idno type="ISSN">0962-8436</idno>
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<front><div type="abstract" xml:lang="en"><p>Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability—all essential to sustainable systems.</p>
</div>
</front>
</TEI>
<pmc article-type="research-article" xml:lang="EN"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Philos Trans R Soc Lond B Biol Sci</journal-id>
<journal-id journal-id-type="publisher-id">RSTB</journal-id>
<journal-title>Philosophical Transactions of the Royal Society B: Biological Sciences</journal-title>
<issn pub-type="ppub">0962-8436</issn>
<issn pub-type="epub">1471-2970</issn>
<publisher><publisher-name>The Royal Society</publisher-name>
<publisher-loc>London</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">17656345</article-id>
<article-id pub-id-type="pmc">2610168</article-id>
<article-id pub-id-type="publisher-id">rstb20072168</article-id>
<article-id pub-id-type="doi">10.1098/rstb.2007.2168</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>An engineering approach to modelling, decision support and control for sustainable systems</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Day</surname>
<given-names>W</given-names>
</name>
<xref ref-type="corresp" rid="cor1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Audsley</surname>
<given-names>E</given-names>
</name>
<xref ref-type="author-notes" rid="fn1">†</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Frost</surname>
<given-names>A.R</given-names>
</name>
</contrib>
</contrib-group>
<aff><institution>Silsoe Research Institute, Wrest Park, Silsoe</institution>
<addr-line>Bedford MK45 4HS, UK</addr-line>
</aff>
<author-notes><corresp id="cor1"><label>*</label>
Author for correspondence (<email>bill.day@silsoeresearch.org.uk</email>
)</corresp>
<fn id="fn1"><label>†</label>
<p>Present address: Natural Resources Management Institute, Building 42a, Cranfield University, Bedford MK43 0AL, UK.</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>26</day>
<month>7</month>
<year>2007</year>
</pub-date>
<pub-date pub-type="ppub"><day>12</day>
<month>2</month>
<year>2008</year>
</pub-date>
<volume>363</volume>
<issue>1491</issue>
<issue-title>Theme Issue ‘Sustainable agriculture I’ compiled by Chris Pollock, Jules Pretty, Ian Crute, Chris Leaver and Howard Dalton</issue-title>
<fpage>527</fpage>
<lpage>541</lpage>
<permissions><copyright-statement>© 2007 The Royal Society</copyright-statement>
<copyright-year>2007</copyright-year>
</permissions>
<abstract xml:lang="EN"><p>Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability—all essential to sustainable systems.</p>
</abstract>
<kwd-group><kwd>engineering</kwd>
<kwd>systems models</kwd>
<kwd>modelling</kwd>
<kwd>sensors</kwd>
<kwd>process control</kwd>
<kwd>agriculture</kwd>
</kwd-group>
</article-meta>
</front>
<floats-wrap><fig id="fig1" position="float"><label>Figure 1</label>
<caption><p>The linkages in the Silsoe whole farm model.</p>
</caption>
<graphic xlink:href="rstb20072168f01"></graphic>
</fig>
<fig id="fig2" position="float"><label>Figure 2</label>
<caption><p>The effect on profit of encouraging decreased herbicide use (filled symbols, blackgrass; open symbols, wild oats), either by taxation (each point on the solid lines represents 100, 200 and 300% herbicide price increases) or by land users making decisions that put increasing weighting on reduced use (dotted line), for a typical sandy loam soil, arable and roots farm.</p>
</caption>
<graphic xlink:href="rstb20072168f02"></graphic>
</fig>
<fig id="fig3" position="float"><label>Figure 3</label>
<caption><p>The key determinants of the weed control in an arable system.</p>
</caption>
<graphic xlink:href="rstb20072168f03"></graphic>
</fig>
<fig id="fig4" position="float"><label>Figure 4</label>
<caption><p>Hierarchy of models used in the WDM to lead to optimal decisions on disease control.</p>
</caption>
<graphic xlink:href="rstb20072168f04"></graphic>
</fig>
<fig id="fig5" position="float"><label>Figure 5</label>
<caption><p>The main user interface screen of the WDM, with explanation of main features.</p>
</caption>
<graphic xlink:href="rstb20072168f05"></graphic>
</fig>
<fig id="fig6" position="float"><label>Figure 6</label>
<caption><p>Model-based control for broiler production.</p>
</caption>
<graphic xlink:href="rstb20072168f06"></graphic>
</fig>
<fig id="fig7" position="float"><label>Figure 7</label>
<caption><p>Processed image of a pig showing areas identified and measured by the image analysis system.</p>
</caption>
<graphic xlink:href="rstb20072168f07"></graphic>
</fig>
<fig id="fig8" position="float"><label>Figure 8</label>
<caption><p>Biosensors offer a key opportunity to introduce engineering control to a wide range of biological processes.</p>
</caption>
<graphic xlink:href="rstb20072168f08"></graphic>
</fig>
<table-wrap id="tbl1" position="float"><label>Table 1</label>
<caption><p>A typical outcome of an LCA analysis of a single commodity: bread wheat production.</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th valign="bottom" align="left" rowspan="1" colspan="1">impacts (per tonne bread wheat produced)</th>
<th valign="bottom" align="left" rowspan="1" colspan="1">conventional</th>
<th valign="bottom" align="left" rowspan="1" colspan="1">organic</th>
</tr>
</thead>
<tbody><tr><td rowspan="1" colspan="1">energy used, MJ</td>
<td rowspan="1" colspan="1">2361</td>
<td rowspan="1" colspan="1">1736</td>
</tr>
<tr><td rowspan="1" colspan="1">global-warming-potential, kg 100 year CO<sub>2</sub>
equiv.</td>
<td rowspan="1" colspan="1">422</td>
<td rowspan="1" colspan="1">481</td>
</tr>
<tr><td rowspan="1" colspan="1">eutrophication potential, kg <inline-formula><inline-graphic xlink:href="rstb20072168e02.jpg" alternate-form-of="M2"></inline-graphic>
<mml:math id="M2"><mml:mrow><mml:msubsup><mml:mrow><mml:mtext>PO</mml:mtext>
</mml:mrow>
<mml:mn>4</mml:mn>
<mml:mrow><mml:mn>3</mml:mn>
<mml:mo>−</mml:mo>
</mml:mrow>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula>
equiv.</td>
<td rowspan="1" colspan="1">2.9</td>
<td rowspan="1" colspan="1">8.6</td>
</tr>
<tr><td rowspan="1" colspan="1">acidification potential, kg SO<sub>2</sub>
equiv.</td>
<td rowspan="1" colspan="1">3.1</td>
<td rowspan="1" colspan="1">3.3</td>
</tr>
<tr><td rowspan="1" colspan="1">pesticides used, dose ha<sup>−1</sup>
</td>
<td rowspan="1" colspan="1">2.0</td>
<td rowspan="1" colspan="1">0</td>
</tr>
<tr><td rowspan="1" colspan="1">abiotic depletion, kg antimony equiv.</td>
<td rowspan="1" colspan="1">1.4</td>
<td rowspan="1" colspan="1">1.2</td>
</tr>
<tr><td rowspan="1" colspan="1">land use, ha grade 2</td>
<td rowspan="1" colspan="1">0.14</td>
<td rowspan="1" colspan="1">0.44</td>
</tr>
</tbody>
</table>
</table-wrap>
</floats-wrap>
</pmc>
<affiliations><list></list>
<tree><noCountry><name sortKey="Audsley, E" sort="Audsley, E" uniqKey="Audsley E" first="E" last="Audsley">E. Audsley</name>
<name sortKey="Day, W" sort="Day, W" uniqKey="Day W" first="W" last="Day">W. Day</name>
<name sortKey="Frost, A R" sort="Frost, A R" uniqKey="Frost A" first="A. R" last="Frost">A. R Frost</name>
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