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Open AccessArticle

Genomic Selection for Optimum Index with Dry Biomass Yield, Dry Mass Fraction of Fresh Material, and Plant Height in Biomass Sorghum

1
CREA Research Center for Cereals and Industrial Crops, via di Corticella 133, 40128 Bologna, Italy
2
Crop, Soil, and Microbial Sciences Department, Michigan State University, 1066 Bogue St, East Lansing, MI 42824, USA
3
Department of Field Crops, Faculty of Agricultural and Natural Sciences, Abant Izzet Baysal University, 14030 Bolu, Turkey
*
Author to whom correspondence should be addressed.
Genes 2020, 11(1), 61; https://doi.org/10.3390/genes11010061
Received: 2 December 2019 / Revised: 19 December 2019 / Accepted: 1 January 2020 / Published: 5 January 2020
(This article belongs to the Special Issue Genetic Improvement of Cereals and Grain Legumes)
Sorghum is one of the world’s major crops, expresses traits for resilience to climate change, and can be used for several purposes including food and clean fuels. Multiple-trait genomic prediction and selection models were implemented using genotyping-by-sequencing single nucleotide polymorphism markers and phenotypic data information. We demonstrated for the first time the efficiency genomic selection modelling of index selection including biofuel traits such as aboveground biomass yield, plant height, and dry mass fraction of the fresh material. This work also sheds light, for the first time, on the promising potential of using the information from the populations grown from seed to predict the performance of the populations regrown from the rhizomes—even two winter seasons after the original trial was sown. Genomic selection modelling of the optimum index selection including the three traits of interest (plant height, aboveground dry biomass yield, and dry mass fraction of fresh mass material) was the most promising. Since the plant characteristics evaluated herein are routinely measured in cereal and other plant species of agricultural interest, it can be inferred that the findings can be transferred in other major crops. View Full-Text
Keywords: Sorghum bicolor; Sorghum halepense; genomic selection; genomic prediction; optimum index; index selection; biomass; yield; plant height; GBS SNP Sorghum bicolor; Sorghum halepense; genomic selection; genomic prediction; optimum index; index selection; biomass; yield; plant height; GBS SNP
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Habyarimana, E.; Lopez-Cruz, M.; Baloch, F.S. Genomic Selection for Optimum Index with Dry Biomass Yield, Dry Mass Fraction of Fresh Material, and Plant Height in Biomass Sorghum. Genes 2020, 11, 61.

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