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SYSTEM FOR TEMPORAL ANALYSIS OF PLANT DISEASES (SiTemp)

Om SYSTEM FOR TEMPORAL ANALYSIS OF PLANT DISEASES (SiTemp)

The aim of this book is to describe the development stages of the website Sistema de Análise Temporal de Doenças em Plantas (SiTemp), available at [http://sitav.pga.uem.br]. The web tool is aimed at agronomists, who have technical and scientific knowledge of the temporal analysis of diseases. Registration information and data observed in the field or laboratory on the severity of plant diseases are stored in the SiTemp database, generating a history, which, using Artificial Intelligence (AI) techniques, processes the observed data using the Logistic, Monomolecular and Gompertz mathematical models, choosing the model that presents the best solution to explain the data set and calculating the temporal analysis and the shape of the Area Under the Disease Progress Curve (AACPD). The result of the temporal analysis is generated in the form of texts, variables, tables and graphs, and it is the agronomist's responsibility to analyze the information, which will serve as a technical-scientific basis for their final decision on crop management.Keywords: Web, disease management, epidemiology.

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  • Språk:
  • Engelska
  • ISBN:
  • 9786206543039
  • Format:
  • Häftad
  • Sidor:
  • 88
  • Utgiven:
  • 10. oktober 2023
  • Mått:
  • 150x6x220 mm.
  • Vikt:
  • 149 g.
  Fri leverans
Leveranstid: 2-4 veckor
Förväntad leverans: 20. december 2024
Förlängd ångerrätt till 31. januari 2025

Beskrivning av SYSTEM FOR TEMPORAL ANALYSIS OF PLANT DISEASES (SiTemp)

The aim of this book is to describe the development stages of the website Sistema de Análise Temporal de Doenças em Plantas (SiTemp), available at [http://sitav.pga.uem.br]. The web tool is aimed at agronomists, who have technical and scientific knowledge of the temporal analysis of diseases. Registration information and data observed in the field or laboratory on the severity of plant diseases are stored in the SiTemp database, generating a history, which, using Artificial Intelligence (AI) techniques, processes the observed data using the Logistic, Monomolecular and Gompertz mathematical models, choosing the model that presents the best solution to explain the data set and calculating the temporal analysis and the shape of the Area Under the Disease Progress Curve (AACPD). The result of the temporal analysis is generated in the form of texts, variables, tables and graphs, and it is the agronomist's responsibility to analyze the information, which will serve as a technical-scientific basis for their final decision on crop management.Keywords: Web, disease management, epidemiology.

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