Main content area

Genetic Parameters and Prediction of Breeding Values in Switchgrass Bred for Bioenergy

Edmé, Serge, Mitchell, Robert, Sarath, Gautam
Crop science 2017 v.57 no.3 pp. 1464-1474
Panicum virgatum, bioenergy, breeding value, dry matter accumulation, ethanol, genetic correlation, genetic improvement, genetic variation, heritability, lignin, linear models, monitoring, multivariate analysis, plant breeding, prediction, recurrent selection, seedlings, Nebraska
Estimating genetic parameters is an essential step in breeding by recurrent selection to maximize genetic gains over time. This study evaluated the effects of selection on genetic variation across two successive cycles (C1 and C2) of a ‘Summer’x‘Kanlow’ switchgrass (Panicum virgatum L.) population. Two progeny tests were planted in 2007 and 2011 near Mead, NE and respectively analyzed for 2 and 4 yr. Each test was a randomized complete block design, with four replicates of 34 halfsib families in single-row plots of 10 seedlings in C1 and with three replicates of 111 halfsib families in single-row plots of five seedlings in C2. The C2 test included C0, C1, and parental populations for comparison. Multivariate mixed linear models revealed ample additive genetic variation for dry matter yield (DMY), Klason lignin (KL), and predicted ethanol yield (ETOH) in both cycles, with heritability ranging from 0.40±0.18 to 0.5±0.14 at the family level, from 0.22±0.17 to 0.36±0.22 at the individual level, and from 0.25 to 0.31 within family in C1. Matching values in C2 were: from 0.42±0.09 to 0.63±0.07, from 0.10±0.07 to 0.34±0.13, and from 0.12 to 0.48. More opportunity exists to improve DMY, with a coefficient of additive genetic variation of 11 to 32%, than KL (3–5%) or ETOH (3–6%). The traits were properly aligned for joint improvement for high DMY and reduced KL in C1, owing to favorable genetic correlations (rA=−0.33±0.11) and each having respective rA of 0.60±0.05 and −0.62±0.07 with ETOH. In C2, the rA between DMY and KL (−0.19±0.10) or ETOH (0.04±0.04) decreased towards zero, and that between KL and ETOH was moderately less negative (−0.35±0.15). These results suggest a strong genetic basis for improvement of the traits and monitoring of their patterns every cycle to find the proper weights that maximize the breeding goal of designing the ideal bioenergy switchgrass.