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Morpho-agronomic variability in rice genotypes in the Central Pacific, Costa Rica

Abstract

Rice (Oryza sativa L.) is included in the daily diet of 75% of the world population. In Costa Rica, the rice sector is a fundamental axis of attention, particularly because it is the main product within the basic food basket. Studying the morpho-agronomic variability of this cereal is a key factor for planning breeding strategies. The objective of the present investigation was to determine which morpho-agronomic traits give the greater contribution to genetics in 54 rice lines. The evaluated lines come from a collection of the germplasm bank of CIAT in Colombia, these were sent to Costa Rica through the National Rice Corporation (CONARROZ). Seven quantitative and five qualitative morphological variables were measured. For the quantitative ones, the coefficient of variation was calculated and a Principal Component Analysis (PCA) was performed, as well as a Cluster Analysis. With the qualitative ones, a Multiple Correspondence Analysis (MCA) was performed. The most heterogeneous quantitative variables according to the values ​​of the coefficient of variation were: tons per hectare, fertile stems and full grains per panicle. The PCA revealed that all the variables, except plant height, contributed to the total variance, and the MCA suggests that the qualitative variables measured in this research are discriminatory to differentiate genotypes. No correlations were reached between the quantitative variables studied. In the cluster analysis, four groups were obtained, one of which comprised the majority of the genotypes. The genotypes of this last group are characterized by having high values ​​for the variable full grains per panicle and medium and high values ​​for the rest of the variables. The results obtained are useful to choose the appropriate variables for selection. The cluster analysis allowed to establish the phylogenetic relationship between the lines for the planning of future crosses.

Keywords

PCA, MCA, Oryza sativa, Morphological characters

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