Multitrait index based on factor analysis and ideotype‐design: proposal and application on elephant grass breeding for bioenergy
By João Romero do Amaral Santos de Carvalho Rocha, J. C. Machado, P. Carneiro. 2018
168 citations recorded by the source corpus.
This study proposes a new multitrait index based on factor analysis and ideotype‐design (FAI‐BLUP index), and validates its potential on the selection of elephant grass genotypes for energy cogeneration. Factor analysis was carried out, and afterwards, factorial scores of each ideotype were designed according to the desirable and undesirable factors, and the spatial probability was estimated based on genotype‐ideotype distance, enabling genotype ranking. In order to quantify the potential of the FAI‐BLUP index, genetic gains were predicted and compared with the Smith‐Hazel classical index. The FAI‐BLUP index allows ranking the genotypes based on multitrait, free from multicollinearity, and it does not require assigning weights, as in the case of the Smith‐Hazel classical index and its derived indices. Furthermore, the genetic correlation ‐ positive or negative ‐ within each factor was taken into account, preserving their traits relationship, and giving biological meaning to the ideotypes. The FAI‐BLUP index indicated the 15 elephant grass with the highest performance for conversion to bioenergy via combustion, and predicted balanced and desirable genetic gains for all traits. In addition, the FAI‐BLUP index predicted gains of approximately 62% of direct selection, simultaneously for all traits that are desired to be increased, and approximately 33% for traits which are desired to be decreased. The genotypes selected by the FAI‐BLUP index have potential to improve all traits simultaneously, while the Smith‐Hazel classical index predicted gains of 66% for traits that are desired to be increased, and −32% for traits that are desired to be decreased, and it does not have potential to improve all traits simultaneously. The FAI‐BLUP index provides an undoubtable selection process and can be used in any breeding programme aiming at selection based on multitrait.
Subfields: Agronomy and Crop Science, Genetics, Plant Science
View Paper: https://www.semanticscholar.org/paper/27b81d98bfa3b1d52ec71a019a2adecbdca856f5
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Citations in the corpus
- A Framework for Identification of Stable Genotypes Basedon MTSI and MGDII Indexes: An Example in Guar (Cymopsis tetragonoloba L.) (2021, unknown): “As the efficiency of multivariate techniques to solve the multicollinearity issues seems to be high when dealing with multi-traits [21,23,53], therefore, to bridge the gaps in traditional methods of stability analysis, Olivoto and Nardino [24] developed an index that can overcome the defects of all ”
- MGIDI: towards an effective multivariate selection in biological experiments (2020, methodology): “2) to assess the performance of the MGIDI index and compare it with the classical Smith-Hazel (SH) index (Smith, 1936; Hazel, 1943), and the modern FAI-BLUP index (Rocha et al., 2018) in terms of percentage of success in selecting traits with desired gains.”