Abstract

FERNANDEZ-CHUAIREY, Lucía et al. Analysis of Main Components, an Effective Tool in Agricultural Technical Sciences. Rev Cie Téc Agr [online]. 2022, vol.31, n.1  Epub Nov 12, 2021. ISSN 2071-0054.

Currently there is a wide range of multivariate techniques, which are used in different areas of research. The present work focuses on the Principal Components Method and aims to establish a set of methodological criteria for the processing and interpretation of results in the use of this technique on mathematical-statistical bases. An example associated with post-harvest studies of the pineapple (variety Cayena Lisa) is developed. A sequence of steps is proposed that includes: previous analysis of correlation between variables, determination of the number of components to be selected (compromise between the different criteria), weight of variables in each component, biological interpretation and graphs that validate the results obtained in reference to components and individuals. The study had the variables: weight loss in g (PP), firmness, color index (IC), soluble solids content (SSC) and pH. The variables were grouped into two components that explain 88.36% of the variation in the data. A positive relationship was observed among PP, SSC and pH and the negative relationship of firmness with these variables. It is shown that the highest PP and pH are reached from the sixth day and the highest firmness, in the first two days, aspects to take into account in making timely decisions for storage, transportation and marketing. It is concluded that the use of multivariate techniques and, particularly, the analysis of principal components constitutes an efficient and non-destructive way in monitoring the quality of fruits in storage.

Keywords : Main Components; Agricultural Engineering; Multivariate Methods.

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