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CROP BREEDING, GENETICS & CYTOLOGY

Multivariate Analyses to Display Interactions between Environment and General or Specific Combining Ability in Hybrid Crops

^a Advanta Semillas S.A.I.C., Ruta Nac. 33 Km 636, CC 559, (2600) Venado Tuerto, Argentina
^b CSIRO Plant Industry, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Qld 4067, Australia

^* Corresponding author (avega{at}waycom.com.ar)

Estimates of general combining ability (GCA) and specific combining ability (SCA) help plant breeders devise breeding and selection strategies. The objective of this paper was to apply two-mode principal component analysis (PCA) to environment-centered and normalized female (F) or male (M) x environment (E) tables and three-mode PCA on F x M x E tables to display the variability associated with GCA, SCA, and their interactions with environments. A sunflower (Helianthus annuus L.) North Carolina Design II (4 females x 4 males) was grown in 11 environments in Argentina. Site regression (SREG2) and additive main effects and multiplicative interaction (AMMI2) models identified lines with high GCA and SCA. The two- and three-mode PCAs revealed GCA x E and SCA x E interactions and were able to identify the best tester for either broad or specific adaptation. Two combinations of analyses accounted for all sources of variation. In Strategy 1 (explaining 59% of the genotype (G) + G x E interaction), two-mode PCA displayed GCA + SCA while three-mode PCA displayed GCA x E + SCA x E interactions. Strategy 2 (77%) used two-mode PCA to display GCA + GCA x E interaction and three-mode PCA to display SCA + SCA x E interaction. Both strategies were suitable approaches to understand the combining ability of the core germplasm of a hybrid crop breeding program and allowed decisions to be made about the required focus on line development within sub-regions encompassed by the program.

Abbreviations: AMMI, additive main effects and multiplicative interaction • BLUE, best linear unbiased estimate • E, environment • F, female • G, genotype • GCA, general combining ability • M, male • NCII, North Carolina Experiment II • PC, principal component • PCA, principal component analysis • SCA, specific combining ability • REML, restricted maximum likelihood • SREG, site regression