Free choice profiling sensory analysis and principal component analysis as tools to support an apple breeding program

Abstract

The challenge for genetic improvement of apples is to develop varieties that have appealing physicochemical and sensorial qualities, good adaptation to different environments, and resistance to pests and diseases. The present study evaluated the physicochemical parameters and sensory attributes of promising genotypes and of a commercial apple variety in the breeding program of the Parana Rural Development Institute IAPAR-EMATER in two cultivation localities in Parana state, Lapa and Palmas. We proposed the use of free choice profiling (FCP) sensorial analysis and principal component analysis (PCA) as tools to aid in the genetic improvement of apples. The genotypes analyzed from Palmas were PR2.40, PR2.13, PR2.21, PR2.31, PR2.51, PR2.26, PR2.5, PR2.70, PR2.60, IAPAR75-Eva, and from Lapa were PR2.40, PR2.13, PR2.21, and IAPAR75-Eva. The physicochemical parameters analyzed were weight, height, diameter, skin and pulp firmness, color, pH, titratable acidity (TA), total soluble solids (SST), and SST/TA ratio. In FCP, 10 assessors described the appearance, aroma, taste, and texture of apples. In Palmas, genotypes PR2.13, PR2.21, PR2.26, PR2.40, PR2.60, and IAPAR75-Eva showed sensory and physicochemical characteristics that were appealing to consumers, showing promise for launch as varieties. PR2.5, PR2.31, PR2.51, and PR2.70 presented low concordance between physicochemical characteristics and sensory attributes requiring more detailed study of these genotypes. Comparison between from two localities PR2.13, PR.2.21, PR.2.40, and IAPAR75-Eva the genotypes indicated a relationship between physicochemical and sensorial characteristics, and the presence of a higher number of indicative attributes of good quality. In Palmas, however, the apples presented physicochemical characteristics of and sensory attributes of immature fruit. The application PCA contributed to the evaluation of a greater number of parameters of apple quality and showed the genotypes with high quality parameters. In addition, FCP allowed identify the attributes of genotypes grown in same local as well as identify attributes that separated same genotypes grown in two local. Therefore, these multivariate analyses were appropriated to apply in apple breeding program and aiding the breeder's decision to recommend new varieties of apples.