*4.4. Multi-Trait Index Based on Factor Analysis and Genotype-Ideotype Distance (MGIDI)*

Experienced breeders often try to combine several desired traits into a new genotype to produce high performance. When measuring multiple traits, it is often difficult to select a genotype from the ideotypes. In this regard, various multivariate methods are widely used, such as principal component analysis, factor analysis, cluster analysis, and different samples to group measured traits or select test genotypes [73]. We used a two-way heat map clustering pattern and PCA to connect test genotypes and measured attributes in this study (Figures 6 and 7), however, we could not pick specific genotypes. To make the selection of genotypes with several features easier, [27] the recently introduced MGIDI (multi-trait genotype-ideotypes distance index) is a new method for genotype selection based on multiple trait information. The eggplant genotypes were ranked based on information on measured multiple traits (Figure 7). The MGIDI index selected genotypes G80, G54, G66, G120, G46, G61, G65, G108, G4, G79, G42, G77, G47, G50, G51, G43, G44, G48, and G49 as promising eggplant genotypes. Apart from these genotypes, G80 was very close to the cut point, which recommends that this genotype can exist desirable features. Hence, the researcher should pay particular attention to assessing genotypes that are very close to the cut point [27]. The application of the MGIDI index to plant crop research is predicted to grow rapidly. Similarly, This index was used to find the best strawberry genotype [74].
