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Multivariate analyses to determine fungicide efficacy on Ecuadorian bananas for consumption

  • Ascencio-Moreno, José [1] ; Hinojosa-Ramos, Miriam Vanessa [1] ; Ruiz-Barzola, Omar [1] ; Jiménez-Feijoó, María Isabel [1] ; Galindo-Villardón, María Purificación [2] ; Ramos-Barberán, Miriam [1]
    1. [1] Escuela Superior Politecnica del Litoral

      Escuela Superior Politecnica del Litoral

      Guayaquil, Ecuador

    2. [2] Universidad de Salamanca

      Universidad de Salamanca

      Salamanca, España

  • Localización: Espirales. Revista multidisciplinaria de investigación, ISSN-e 2550-6862, Vol. 4, Nº. 34, 2020 (Ejemplar dedicado a: July-September), págs. 2-2
  • Idioma: inglés
  • DOI: 10.31876/er.v4i34.750
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  • Resumen
    • Half maximal effective concentration EC50 is considered the main reference for evaluating the efficacy of the products in any plantation using doses and inhibition percentages from laboratory data. However, EC50 is not the best representation when other relevant variables and their relationships could be involved. As an agricultural case study, fungicide sensitivity of Pseudocercospora fijiensis, the causal agent of black sigatoka, was evaluated on bananas’ plantations in three provinces of Ecuador. In this study, multivariate statistical process control was adjusted to a fungicide efficacy evaluation case considering multiple data tables from different locations and years at the same time. The threshold conveyed by inhibition percentages, related to the EC , along with locations and years allowed the multivariate analyses carried out in the proposal. The multivariate statistical control techniques applied were Multilinear Principal Component Analysis (MPCA) and Dual STATIS-Parallel Coordinates approach (DS-PC). A comparison was developed and showed that both methods discriminate correctly between the normal and anomalous conditions within plantations along years, validating the ability of the novel method DS-PC for exhibiting better signaling of anomalous plantations and performing variable-wise analysis to find out possible causes of this behavior in an easier time-saving graphical framework.


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