Skip to main content
Log in

Development of a web tool for action threshold evaluation in table grape pest management

  • Published:
Precision Agriculture Aims and scope Submit manuscript

Abstract

Pest control is a major issue in agricultural management due to crop yield losses caused by pests. In this context, integrated pest management aims to suppress pest populations below an action threshold to minimize their impact. This paper presents the development of a web tool based on the Spanish regulations for the integrated pest management of table grapes; this provides decision support for evaluating when a particular pest action threshold has been crossed thus affecting table grape crops. The tool was built using a model-driven software development approach that enables software system generation from the problem’s knowledge model. The design of the knowledge bases which contain the system’s decision rules is also described. It is divided into knowledge bases that contain general knowledge related to the table grape crop as well as several specific knowledge bases (one per pest) containing the reasoning model that deduces the risk associated with a particular pest. The software has been designed by applying the model-driven development method thus making the system flexible, easy to evolve and adaptable whenever a new pest has to be incorporated into the software.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Notes

  1. http://aims.fao.org/standards/agrovoc.

References

  • Angele, J., Fensel, D., Landes, D., & Studer, R. (1998). Developing knowledge-based systems with MIKE. Automated Software Engineering, 5(4), 389–418. doi:10.1023/A:1008653328901.

    Article  Google Scholar 

  • Beck, H. W., Kim, S., & Hagan, D. (2005). A crop-pest ontology for extension publications. In: J. Boaventura Cunha, & R. Morais (Eds.), Proceedings of the EFITA/WCCA 2005 joint conference (pp. 1169–1176). Vila Real, Portugal: Universidade De Tras-os-Montes e Alto Douro.

  • Boyer, M. J., & Mili, H. (2011). IBM websphere ilog jrules. In Agile business rule development (pp. 215–242). Berlin, Germany: Springer. doi:10.1007/978-3-642-19041-4_8.

  • Browne, P. (2009). JBoss drools business rules. Mumbai, India: Packt Publishing Ltd.

    Google Scholar 

  • Cañadas, J., Palma, J., & Túnez, S. (2011). Defining the semantics of rule-based web applications through model-driven development. International Journal of Applied Mathematics and Computer Science, 21(1), 41–55. doi:10.2478/v10006-011-0003-4.

    Article  Google Scholar 

  • Cockburn, A. (2000). Writing effective use cases. Boston, USA: Addison-Wesley Professional.

    Google Scholar 

  • Cuena, J., & Molina, M. (1997). KSM: an environment for design of structured knowledge models. In S. G. Tzafestas (Ed.), Knowledge-based systems: Advanced concepts, techniques and applications (pp. 217–245). Singapore: World Scientific Publishing.

    Chapter  Google Scholar 

  • del Águila, I. M., Cañadas, J., & Túnez, S. (2015). Decision making models embedded into a web-based tool for assessing pest infestation risk. Biosystems Engineering, 133, 102–115. doi:10.1016/j.biosystemseng.2015.03.006.

    Article  Google Scholar 

  • del Sagrado, J., Túnez, S., del Águila, I., & Orellana, F. J. (2013). Architectural model for agrarian software management with decision support features. Advanced Science Letters, 19(10), 2958–2961. doi:10.1166/asl.2013.5077.

    Article  Google Scholar 

  • Directive, E. U. (2009a). 128/EC of the European parliament and of the council of 21 October 2009 establishing a framework for community action to achieve the sustainable use of pesticides. Official Journal of European Union, 52, 71–86.

    Google Scholar 

  • Directive, E. U. (2009b). Regulation (EC) No 1107/2009 of the European parliament and of the council of 21 October 2009 concerning the placing of plant protection products on the market and repealing council directives 79/117/EEC and 91/414/EEC. Official Journal of European Union, 52, 1–50.

    Google Scholar 

  • Durkin, J. (1993). Expert systems: catalog of applications. Akron, OH, USA: Intelligent Computer Systems Inc.

    Google Scholar 

  • Farrar, J. J., Baur, M. E., & Elliott, S. F. (2016). Adoption of IPM practices in grape, tree fruit, and nut production in the Western United States. Journal of Integrated Pest Management, 7(1), 8. doi:10.1093/jipm/pmw007.

    Article  Google Scholar 

  • Feng, J., Wang, J., Zhang, X., Zhao, F., Kanianska, R., & Tian, D. (2015). Design and implementation of emergy-based sustainability decision assessment system for protected grape cultivation. Sustainability, 7(10), 14002–14025. doi:10.3390/su71014002.

    Article  Google Scholar 

  • Forgy, C. L. (1982). Rete: A fast algorithm for the many pattern/many object pattern match problem. Artificial Intelligence, 19(1), 17–37. doi:10.1016/0004-3702(82)90020-0.

    Article  Google Scholar 

  • Friedman-Hill, E. (2003). Jess in action: Java rule-based systems. Greenwich, CT, USA: Manning Publications.

    Google Scholar 

  • Geary, D., & Horstmann, C. S. (2007). Core javaserver faces (2nd ed.). Delhi, India: Prentice Hall.

    Google Scholar 

  • Giarratano, J. C., & Riley, G. D. (2004). Expert systems: Principles and programming, (4th ed.). Boston, USA: Course Technology Thomson Career & Professional Group.

    Google Scholar 

  • Gil, E., Llorens, J., Landers, A., Llop, J., & Giralt, L. (2011). Field validation of dosaviña, a decision support system to determine the optimal volume rate for pesticide application in vineyards. European Journal of Agronomy, 35(1), 33–46. doi:10.1016/j.eja.2011.03.005.

    Article  Google Scholar 

  • Gómez-Pérez, A., Fernández-López, M., & Corcho, O. (2004). Ontological engineering. London, UK: Springer.

    Google Scholar 

  • JBoss. (2009). RichFaces. JBoss Community. Retrieved July 10, 2016, from http://richfaces.jboss.org/.

  • Kogut, P., Cranefield, S., Hart, L., Dutra, M., Baclawski, K., Kokar, M., et al. (2002). UML for ontology development. The Knowledge Engineering Review, 17(01), 61–64. doi:10.1017/S0269888902000358.

    Article  Google Scholar 

  • Léger, B., & Naud, O. (2009). Experimenting statecharts for multiple experts knowledge elicitation in agriculture. Expert Systems with Applications, 36(8), 11296–11303. doi:10.1016/j.eswa.2009.03.052.

    Article  Google Scholar 

  • Liao, J., Li, L., & Liu, X. (2015). An integrated, ontology-based agricultural information system. Information Development, 31(2), 150–163. doi:10.1177/0266666913510716.

    Article  Google Scholar 

  • Ligęza, A., & Nalepa, G. J. (2011). A study of methodological issues in design and development of rule-based systems: proposal of a new approach. Wiley Interdisciplinary Reviews, 1(2), 117–137. doi:10.1002/widm.11.

    Google Scholar 

  • Lucas-Espadas, A., & Martín-Gil, Á. (2014). Guía de gestión integrado de plagas. Uva de mesa (Guide for integrated pest management of table grapes). Madrid, Spain: Ministerio de Agricultura, Alimentación y Medio Ambiente.

  • Lucas-Espadas, A. (2008). Plagas y enfermedades de la vid en la Region de Murcia. (Pests and diseases of grapevine in Murcia region). Murcia, Spain: Consejería de Agricultura y Agua. Servicio de Sanidad Vegetal.

  • Maliappis, M. T. (2009). Applying an agricultural ontology to web-based applications. International Journal of Metadata, Semantics and Ontologies, 4(1–2), 133–140. doi:10.1504/IJMSO.2009.026261.

    Article  Google Scholar 

  • Mellor, S. J., Clark, A. N., & Futagami, T. (2003). Model-driven development—guest editor’s introduction. IEEE Software, 20(5), 14–18. doi:10.1109/MC.2006.58.

    Article  Google Scholar 

  • Molitor, D., Augenstein, B., Mugnai, L., Rinaldi, P. A., Sofia, J., Hed, B., et al. (2015). Composition and evaluation of a novel web-based decision support system for grape black rot control. European Journal of Plant Pathology, 124(4), 1–14. doi:10.1007/s10658-015-0835-0.

    Google Scholar 

  • Nalepa, G. J., & Bobek, S. (2014). Rule-based solution for context-aware reasoning on mobile devices. Computer Science and Information Systems, 11(1), 171–193. doi:10.2298/CSIS130209002N.

    Article  Google Scholar 

  • Norris, R. F., Caswell-Chen, E. P., & Kogan, M. (2003). Concepts in integrated pest management. New Jersey, USA: Prentice Hall PTR.

    Google Scholar 

  • Nutter, F. W. (1993). Terms and concepts for yield, crop loss, and disease thresholds. Plant Disease, 77, 211–215. doi:10.1094/PD-77-211.

    Google Scholar 

  • Object Management Group. (2003). MDA guide version 1.0.1. Retreived July 10, 2016, from http://www.omg.org/.

  • OIV. (2016, June). International organisation of vine and wine. Retreived July 10, 2016, from http://www.oiv.int/.

  • Orellana, F. J., Del Sagrado, J., & del Águila, I. M. (2011). SAIFA: A web-based system for integrated production of olive cultivation. Computers and Electronics in Agriculture, 78(2), 231–237. doi:10.1016/j.compag.2011.07.014.

    Article  Google Scholar 

  • Papajorgji, P., Clark, R., & Jallas, E. (2009). The model driven architecture approach: A framework for developing complex agricultural systems. In P. Pardalos & P. Papajorgji (Eds.) Advances in modeling agricultural systems (pp. 1–18). New York, USA: Springer, doi:10.1007/978-0-387-75181-8_1.

  • Papajorgji, P. J., & Pardalos, P. M. (2014). Software engineering techniques applied to agricultural systems (Vol. 93). Boston, MA, USA: Springer.

  • Rajbhandari, S., & Keizer, J. (2012). The AGROVOC concept scheme—a walkthrough. Journal of Integrative Agriculture, 11(5), 694–699. doi:10.1016/S2095-3119(12)60058-6.

    Article  Google Scholar 

  • Rossi, V., Salinari, F., Poni, S., Caffi, T., & Bettati, T. (2014). Addressing the implementation problem in agricultural decision support systems: the example of vite.net®. Computers and Electronics in Agriculture, 100, 88–99. doi:10.1016/j.compag.2013.10.011.

    Article  Google Scholar 

  • Russell, S. J., & Norvig, P. (1995). Artificial intelligence: a modern approach. Upper Saddle River, NJ, USA: Prentice-Hall Inc.

    Google Scholar 

  • Schreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N., de Velde, W. V., et al. (2000). Knowledge engineering and management: The commonKADS methodology. Cambridge, MA, USA: The MIT Press.

    Google Scholar 

  • Shadbolt, N., Motta, E., & Rouge, A. (1993). Constructing knowledge-based systems. Software, IEEE, 10(6), 34–38. doi:10.1109/52.241964.

    Article  Google Scholar 

  • Zheng, Y.-L., He, Q.-Y., Qian, P., & Ze, L. I. (2012). Construction of the ontology-based agricultural knowledge management system. Journal of Integrative Agriculture, 11(5), 700–709. doi:10.1016/S2095-3119(12)60059-8.

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank the Consejería de Agricultura y Agua, Servicio de Sanidad Vegetal of Región de Murcia, especially Mr. Alfonso Lucas Espadas for his collaboration in the knowledge elicitation. His knowledge and experience have formed the basis of this work. This research has been partially supported by Data, Knowledge and Software Engineering (DKSE) research group (TIC-181) of the University of Almería.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joaquín Cañadas.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cañadas, J., del Águila, I.M. & Palma, J. Development of a web tool for action threshold evaluation in table grape pest management. Precision Agric 18, 974–996 (2017). https://doi.org/10.1007/s11119-016-9487-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-016-9487-0

Keywords

Navigation