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A Framework for Agricultural Model Development

A Framework for Agricultural Model Development. Kei Tanaka NARC-NARO. Contents of Presentation. Background of model development Framework Efficiency of using framework Conclusions. Background of Agricultural Model Development. Developed several agricultural models

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A Framework for Agricultural Model Development

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  1. A Framework for Agricultural Model Development Kei Tanaka NARC-NARO

  2. Contents of Presentation • Background of model development • Framework • Efficiency of using framework • Conclusions

  3. Background of Agricultural Model Development • Developed several agricultural models • Plant growth models (rice, pear, …) • Disease prediction models (wheat, pear, …) • Executable in an web pagehttp://cse.naro.affrc.go.jp/ketanaka/model/

  4. Java • APIs: Network, GUI, … • Cross-platform: Windows, Linux, Mac OS, … • Applet: If JRE is installed, additional installation work is not necessary. • Execution easily is important to popularize a model • Secure programming

  5. MetBroker • A middleware between weather databases and agricultural models • Provides consistent methods to access various weather databases through the Internet

  6. Framework • Framework • Program library summarized to reuse for the specific purpose application. • Advantages of using a Framework • Offers implementation→ Development productivity improves • Specifies a development method→ Quality of application is kept high

  7. Frameworks • Web MVC • Struts, Tapestry, JSF, Spring MVC, Web Work • O/R Mapping • Hibernate, PriDE, O/R Broker, Mr.Persister • Testing • JUnit, TestNG, JTiger • SOA (Service Oriented Architecture) • Celtix, Beehive, JBoss jBPM

  8. Common Features of Agricultural Models • Management of data • Sequential value: Air Temp., Rain, … • Numerical value: Weight, Threshold, … • Date: Transplant date, … • Boolean value: Use or Not use • Weather data acquisition from a MetBroker or a user’s local file • Result display in a table or a chart

  9. Example 1 Data Source Setup import net.agmodel.data.*; import net.agmodel.datareader.*; … public class PearDuthieData extends ExecutionDataImpl{ public BlastamData(){ //Setup for parameters and sequential data addValueElement(LEAF_WETNESS_THRESHOLD); //Declaration of a parameter setValue_(LEAF_WETNESS_THRESHOLD, 80.0); //Set of the initial value of a parameter addSequenceElement(AIRTEMPERATURE); //Declaration of a sequential data addSequenceElement(LEAFWETNESS); DataSourceAttribute dsAttrAirTemp = getDataSourceAttribute(AIRTEMPERATURE); DataSourceAttribute dsAttrLeafWet = getDataSourceAttribute(LEAFWETNESS); //Set of the data source of sequential data dsAttrAirTemp.addUsableDataSource(DataSourceElement.MET_BROKER); //MetBroker dsAttrAirTemp.addUsableDataSource(DataSourceElement.USER_DATA); //User Data dsAttrLeafWet.addUsableDataSource(DataSourceElement.MET_BROKER); dsAttrLeafWet.addUsableDataSource(DataSourceElement.USER_DATA); dsAttrLeafWet.addUsableDataSource(DataSourceElement.ESTIMATED_DATA); //Estimated Data … } public UserDataReader getUserDataReader(){ //Setup to aquire user’s local file data UserDataReaderImpl udReader = new UserDataReaderImpl(); udReader.addTextDataElement(new TextDataElement(AIRTEMPERATURE, AIRTEMPERATURE.toString(), "C")); udReader.addTextDataElement(new TextDataElement(LEAFWETNESS, LEAFWETNESS.toString(), "")); return udReader; } … }

  10. public class PearDuthieData extends ExecutionDataImpl{ public BlastamData(){ addValueElement(LEAF_WETNESS_THRESHOLD); setValue_(LEAF_WETNESS_THRESHOLD, 80.0); addSequenceElement(AIRTEMPERATURE); addSequenceElement(LEAFWETNESS); DataSourceAttribute dsAttrAirTemp = getDataSourceAttribute(AIRTEMPERATURE); DataSourceAttribute dsAttrLeafWet = getDataSourceAttribute(LEAFWETNESS); //Set of the data source of sequential data dsAttrAirTemp.addUsableDataSource(DataSourceElement.MET_BROKER); dsAttrAirTemp.addUsableDataSource(DataSourceElement.USER_DATA); dsAttrLeafWet.addUsableDataSource(DataSourceElement.MET_BROKER); dsAttrLeafWet.addUsableDataSource(DataSourceElement.USER_DATA); dsAttrLeafWet.addUsableDataSource(DataSourceElement.ESTIMATED_DATA); … } public UserDataReader getUserDataReader(){ //Setup to aquire user’s local file data UserDataReaderImpl udReader = new UserDataReaderImpl(); udReader.addTextDataElement(new TextDataElement(AIRTEMPERATURE, AIRTEMPERATURE.toString(), "C")); udReader.addTextDataElement(new TextDataElement(LEAFWETNESS, LEAFWETNESS.toString(), "")); return udReader; } … }

  11. Example 2 Result Display public class PearDuthieTableUI extends net.agmodel.gui.ModelTableFrame{ //Display result data in a table protected SequenceTM[] createSequenceTM(ResultData data){ JigsawQuantityFormat jqf = new JigsawQuantityFormat("0", DEVOID); //Number format to display Sequence wetness = data.getSequence(WETNESS_DURATION); Sequence infection = data.getSequence(INFECTION_RATE); return new SequenceTM[]{ //Array of sequential data displayed in a table new SequenceTM((MetSequence)data.getSequence(AIRTEMPERATURE)), new SequenceTM((MetSequence)data.getSequence(LEAFWETNESS)), new SequenceTM(data.getSequence(WETNESS_DURATION), WETNESS_DURATION.toString(), "h", SummaryKind.AVERAGE, jqf), new SequenceTM(data.getSequence(INFECTION_RATE), INFECTION_RATE.toString(), "", SummaryKind.MAXIMUM, jqf)}; } //Display result data in a chart protected SequenceC[] createSequenceC(ResultData data){ Interval in = data.getResultInterval(); Duration re = data.getResolution(); return new SequenceC[]{ //Array of sequential data displayed in a chart new SequenceC((MetSequence)data.getSequence(AIRTEMPERATURE), in, re), new SequenceC((MetSequence)data.getSequence(LEAFWETNESS), in, re), new SequenceC(new SequenceU(data.getSequence(INFECTION_RATE), SummaryKind.MAXIMUM), INFECTION_RATE.toString(), null, null, in, re)}; } //Display result data in a map protected net.agmodel.gui.MultipleStationResultMap createMap(double latitude, double longitude){ return new PearDuthieMap((ResultData[])allData, latitude, longitude, 1000000, INFECTION_RATE.toString()); } }

  12. public class BlastamTableUI extends net.agmodel.gui.ModelTableFrame{ //Display result data in a table protected SequenceTM[] createSequenceTM(ResultData data){ //Number format to display JigsawQuantityFormat jqf = new JigsawQuantityFormat("0", DEVOID); //Array of sequential data displayed in a table return new SequenceTM[]{ new SequenceTM((MetSequence)data.getSequence(AIRTEMPERATURE)), new SequenceTM((MetSequence)data.getSequence(RAIN)), new SequenceTM((MetSequence)data.getSequence(WIND)), new SequenceTM((MetSequence)data.getSequence(SUNSHINE))}; } //Display result data in a chart protected SequenceC[] createSequenceC(ResultData data){ Interval in = data.getResultInterval(); Duration re = data.getResolution(); return new SequenceC[]{ //Array of sequential data displayed in a chart new SequenceC((MetSequence)data.getSequence(AIRTEMPERATURE), in, re), new SequenceC((MetSequence)data.getSequence(RAIN), in, re), new SequenceC((MetSequence)data.getSequence(WIND), in, re), new SequenceC((MetSequence)data.getSequence(SUNSHINE), in, re)}; } //Display result data in a map protected net.agmodel.gui.MultipleStationResultMap createMap(double latitude, double longitude){ return new BlastamMap((ResultData[])allData, latitude, longitude, 1000000, INFECTION_RATE.toString()); } }

  13. public class BlastamTableUI extends net.agmodel.gui.ModelTableFrame{ //Display result data in a table protected SequenceTM[] createSequenceTM(ResultData data){ //Number format to display JigsawQuantityFormat jqf = new JigsawQuantityFormat("0", DEVOID); //Array of sequential data displayed in a table return new SequenceTM[]{ new SequenceTM((MetSequence)data.getSequence(AIRTEMPERATURE)), new SequenceTM((MetSequence)data.getSequence(RAIN)), new SequenceTM((MetSequence)data.getSequence(WIND)), new SequenceTM((MetSequence)data.getSequence(SUNSHINE))}; } //Display result data in a chart protected SequenceC[] createSequenceC(ResultData data){ Interval in = data.getResultInterval(); Duration re = data.getResolution(); //Array of sequential data displayed in a chart return new SequenceC[]{ new SequenceC((MetSequence)data.getSequence(AIRTEMPERATURE), in, re), new SequenceC((MetSequence)data.getSequence(RAIN), in, re), new SequenceC((MetSequence)data.getSequence(WIND), in, re), new SequenceC((MetSequence)data.getSequence(SUNSHINE), in, re)}; } //Display result data in a map protected net.agmodel.gui.MultipleStationResultMap createMap(double latitude, double longitude){ return new BlastamMap((ResultData[])allData, latitude, longitude, 1000000, INFECTION_RATE.toString()); } }

  14. public class BlastamTableUI extends net.agmodel.gui.ModelTableFrame{ //Display result data in a table protected SequenceTM[] createSequenceTM(ResultData data){ //Number format to display JigsawQuantityFormat jqf = new JigsawQuantityFormat("0", DEVOID); //Array of sequential data displayed in a table return new SequenceTM[]{ new SequenceTM((MetSequence)data.getSequence(AIRTEMPERATURE)), new SequenceTM((MetSequence)data.getSequence(RAIN)), new SequenceTM((MetSequence)data.getSequence(WIND)), new SequenceTM((MetSequence)data.getSequence(SUNSHINE))}; } //Display result data in a chart protected SequenceC[] createSequenceC(ResultData data){ Interval in = data.getResultInterval(); Duration re = data.getResolution(); return new SequenceC[]{ //Array of sequential data displayed in a chart new SequenceC((MetSequence)data.getSequence(AIRTEMPERATURE), in, re), new SequenceC((MetSequence)data.getSequence(RAIN), in, re), new SequenceC((MetSequence)data.getSequence(WIND), in, re), new SequenceC((MetSequence)data.getSequence(SUNSHINE), in, re)}; } //Display result data in a map protected net.agmodel.gui.MultipleStationResultMap createMap(double latitude, double longitude){ return new BlastamMap((ResultData[])allData, latitude, longitude, 1000000, INFECTION_RATE.toString()); } }

  15. Agricultural Models developed by using Framework

  16. Efficiency of using Framework • MetBLASTAM (Rice blast forecasting model) • 2,000 lines was developed for the model • 25,000 lines provided by the framework was called from the model program • Calculation part (main part of the model) is 45% of the model program→ Developer can use much time to develop main part, not Data acquisition, GUI.

  17. Conclusions • Developed the framework for agricultural models • Several models developed by using the framework • Program for weather data acquisition and result display only lists data names • Model developer can use much time to develop main part

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