The aim of this study was to estimate variability, broad sense heritability, and genetic advance for dry matter yield (DMY), days to anthesis (ANTH), plant height (HT), in-vitro fiber digestibility-30h (IVFD), lignin (LIGN), starch (STAR %), crude protein content (CP %), acid detergent fiber (ADF) and neutral detergent fiber (NDF) in spring triticale genotypes. Eighteen genotypes were tested at the Field Crop Development Centre (FCDC) in Lacombe, Alberta in 2010-2011 and 2011-2012 growing season. The experimental design was randomized complete block design with 3 replicates. Combined analysis of variance was carried out using SAS Enterprise 4.2 statistical package. Heritability was estimated following the variance component method. Simple correlation coefficients were determined among all traits using two years average data. The genotype mean squares were significant (P ≤ 0.05) for DMY, ANTH, HT, IFVD, ADF, NDF, STAR %, LIGN, and CP %. The effect of year was also highly significant on all studied traits. The phenotypic coefficient of variation was higher than the genetic coefficient of variation for all traits, indicating high influence of the environment on these traits. The significant genetic variability and the high heritability combined with high genetic advance of HT, STAR% and ADF in triticale genotypes suggested that selection could be successfully practiced for those traits. Correlation analysis showed significant and positive correlation of DMY with ANTH and HT, indicating that late and tall genotypes are more suitable as a forage type and they tend to produce more biomass yield. However, DMY did not show any significant correlation with the digestibility. IVFD and STAR % were negatively correlated with LIGN. In general, these results indicated that breeding for low lignin and high starch content will improve the digestibility in triticale genotypes. The preliminary results of this study were promising. Further research must include more diverse genotypes evaluated under multiple locations and years to better understand the variance components and heritability in key agronomic and quality traits.

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