Genetic gains in physic nut using selection indexes
By L. Bhering, B. Laviola, C. C. Salgado, C. F. B. Sánchez, T. Rosado, A. Alves. 2012
51 citations recorded by the source corpus.
Abstract – The objective of this work was to estimate genetic gains in physic nut ( Jatropha curcas ) using selection indexes and to establish the best selection strategy for the species. Direct and indirect selection was carried out using different selection indexes, totalizing 14 strategies. One hundred and seventy five families from the active germplasm bank of Embrapa Agroenergy, Brasilia, Brazil, were analyzed in a randomized complete block design with two replicates. The evaluated traits were: grain yield; seeds per fruit; endosperm/seed ratio; seed weight, length, width, and thickness; branches per plant at 0.5, 1.0, and 1.5 m; plant height; stem diameter; canopy projection on rows and between lines; canopy volume; juvenility (days to the first flowering); and height of the first inflorescence. Evaluations were done during the second year of cultivation. The use of selection indexes is relevant to maximize the genetic gains in physic nut, favoring a better distribution of desirable traits. The multiplicative and restrictive indexes are considered the most promising for selection.Index terms:
Subfields: Food Science, Forestry, Plant Science
View Paper: https://www.semanticscholar.org/paper/ec2832fee5bdece3d12f6219843b379add01220f
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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, background): “As advanced in breeding techniques adoption of multi-trait selection index [18,19], most of the plant breeders are not interested in adopting this index either for initial trials [48] or advanced plant breeding trials [49] that are usually demonstrated in diverse environmental conditions [23,50–52].”
- MGIDI: towards an effective multivariate selection in biological experiments (2020, methodology): “A widely-used base linear phenotypic selection index (Bhering et al., 2012; Bizari et al., 2017; Jahufer and Casler, 2015; Burdon and Li, 2019) is the Smith-Hazel (SH) index (Smith, 1936; Hazel, 1943).”