Akaike Information Criterion (AIC) and stepwise regression method to select the areca nut population as across parent material

Abstract

Abstract Areca nut is widely distributed in tropical areas, including Indonesia. Areca nut has a genetic source for hybrid development. Areca nut is a cross-pollinated plant, so the gene constitution is expected to be heterogeneous and heterozygous. A stepwise regression approach can be utilized to identify the best model of several characters for selection. This study aimed to find out the suitable model and selection characters for selecting a potential population of Areca for use as a cross-parent material. The study was conducted at the Kayuwatu Experimental Garden using the Local Areca Accession Population. The research used a single block with 7 local accessions of areca nut and the vegetative and generative characters of 10 plants from each accession were observed. The results showed that the best model for estimating whole fruit weight (y) = 86586 - 498 stem circumference* + 11158 Fruits Per Bunch* + 4738 Number of Leaves + 38.9 Number of Fruits Per Bunch** + 58.8 fruit equatorial circumference* + 1545 fruit polar circumference *. Based on stepwise regression, only stem circumference, fruit equatorial circumference, fruit polar circumference, and the number of fruits per bunch might be used as the selection criteria to determine the best population.