Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-15T23:22:22.215Z Has data issue: false hasContentIssue false
  • English
  • Français

A Relational Database as Decision Support System in Chemical Weed Control

Published online by Cambridge University Press:  12 June 2017

Lucia Stigliani ,
Giuseppe Santospirito ,
Nicola Cardinale  and
Cosimo Resina
Lucia Stigliani
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
Giuseppe Santospirito
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
Nicola Cardinale
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
Cosimo Resina
Affiliation:
Computer Sci. Dep., Metapontum Agrobios-I-75010 Metaponto (MT), Italy
Get access Rights & Permissions [Opens in a new window]

Abstract

Decision making in weed control is complex and time-consuming. Moreover, the structure of the available information does not facilitate the comparison of different herbicides. Indeed, information format can be the limiting factor in the performance of sophisticated computer programs intended to supply appropriate advice on weed control treatments. A relational database for decision support on chemical weed control has been developed. It uses a detailed structure by subdividing the information where possible. The database includes programs for entering, updating, and printing data, as well as programs for retrieving information and giving treatment advice. The information access on herbicides is organized around searches based on a specific crop and multiple weed species at their respective growth stages. Optimization of the selected herbicides is carried out and supplies the lowest number of herbicides controlling all the chosen weeds. Information on critical parameters for herbicide application such as varietal restrictions, rotational crops, and compatibility with other products is also interactively available.

Keywords

Computerherbicide optimization
Type
Research
Information
Weed Technology , Volume 10 , Issue 4 , December 1996 , pp. 781 - 794
Copyright
Copyright © 1996 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

1. Atzeni, P. and Torlone, R. 1991. Le Strutture COMPLESSE nei Modelli per Basi di Dati. Riv. Informat. 21:43–58.Google Scholar
2. Baldoni, R. and Giardini, L. 1981. Coltivazioni Erbacee. Patron, Bologna, p. 15–119.Google Scholar
3. Capurro, R. and Concaro, G. 1990. Una Banca Dati per la Gestione dei Fitofarmaci Utilizzabili sulle Colture Erbacee. L'Inf. Agr. 46(7): 120–122.Google Scholar
4. Conti, G. G. and Carminucci, D. 1989. Banca Dati Fitofarmaci: Una Corretta Informazione per un Uso Razionale. L'Inf. Agr. 45(36): 71–72.Google Scholar
5. Fabricatore Amici, J. 1988. Sostanze Attive Autorizzate in Agricoltura, ovvero, la Difesa delle Piante nel Rispetto dell'Uomo e dell'Ambiente. Italian Agriculture Ministry, Roma, p. 125–301.Google Scholar
6. Ferrari, C., Baldoni, G., and Tei, F. 1987. Lo Studio della Vegetazione Infestante le Colture Agrarie. Proc. VI S.I.L.M. ‘Societa’ Italiana Lotta alle Malerbe) Symp., Milano, p. 89.Google Scholar
7. Hafliger, E. and Brun, J. 1981. Tables of the Weeds. Ciba Geigy, Basic, Switzerland.Google Scholar
8. Hanway, I. I. 1986. How a Corn Plant Develops. Spec. Rep. no. 48. Iowa State Univ. Sci. Technol. Press, Ames, Iowa. p. 3.Google Scholar
9. Linker, H. M., York, A. C., and Wilhite, D. R. Jr. 1990. WEEDS—A System for Developing a Computer-based Herbicide Recommendation Program. Weed Technol. 4:380–385.CrossRefGoogle Scholar
10. Muccinelli, M. 1992. Prontuario dei Fitofarmaci, 4th Edit. Edagricole, Bologna, p. 374–582.Google Scholar
11. Mueller-Warrant, G. W. 1991. Format of a Weed Control Database. Weed Technol. 5:221–228.CrossRefGoogle Scholar
12. Pignatti, S. 1982. Flora d'Italia, Edagricole, Bologna, 3 Vol., 780 p.Google Scholar
13. Resina, C., Vanadia, S., Basile, G., Longo, A., and Stigliani, L. 1989. Data base sul diserbo chimico. Proc. 7th Simposio Chimica degli Antiparassitari. Agricoltura e Informatica, Piacenza, Italy, p. 141–154.Google Scholar
14. Schmidt, J. W. and Brodie, M. L. Relational Database System: Analysis and Comparison. Springer-Verlag, Berlin Heidelberg, p. 6–8.Google Scholar
15. Tottman, D. R. and Makepeace, R. J. 1979. An Explanation of the Decimal Code for the Growth Stage of Cereals, with illustrations. Ann. Appl. Biol. 93:221–234.CrossRefGoogle Scholar
16. Wilkerson, G. G., Coble, H. D., and Modena, S. A. 1987. A postemergenceherbicide decision model for soybeans. Weed Sci. Soc. Am. 27:95.Google Scholar