Junior Hilton Lopes, Rocha Rodrigo Barros, Kolln Alana Mara, Silva Ramiciely Nunes de Paula, Alves Enrique Anastácio, Teixeira Alexsandro Lara, Espíndula Marcelo Curitiba
Legal Amazon Biodiversity and Biotechnology Network (Bionorte), Federal University of Rondônia (UNIR), Porto Velho 76801-058, RO, Brazil.
Federal Institute of Education, Science and Technology of Rondônia (IFRO), Jaru 76890-000, RO, Brazil.
Plants (Basel). 2024 Oct 4;13(19):2780. doi: 10.3390/plants13192780.
The objective of this study was to characterize the genetic divergence and selection gains of the physicochemical grains traits of 68 genotypes of most cultivated in the Western Amazon. For this purpose, the following characteristics were evaluated over two harvests: aqueous extract, ash, acidity, pH, protein, ether extract, soluble solids, phenolic compounds, soluble sugars, reducing sugars, and non-reducing sugars. The genotype × measurement interaction effect was significant for all characteristics, with a predominant simple interaction, resulting in smaller changes in the ranking of genotypes. Out of a total of 45 genotypic correlation estimates, 8 were significant, of which 5 were related to acidity. The dispersion of the first two components associated with reference points shows that the genotypes BRS3193, AS1, AS2, AS3, N16, CA1, and AS7 were closest to the ideal type of higher performance. Selection for the main characteristic of soluble sugars resulted in estimates of genetic progress lower than those observed using selection indices. The genetic materials present high genetic diversity, allowing the selection of reference plants with high levels of sugars (BRS3193, AS3, GJ25, and LB30), proteins (BRS2357), lipids (GJ30), and phenolic compounds in their green beans (BRS3193) and high water solubility (AS2).
本研究的目的是表征西亚马逊地区种植最广泛的68个基因型的物理化学籽粒性状的遗传差异和选择增益。为此,在两个收获季对以下特性进行了评估:水提取物、灰分、酸度、pH值、蛋白质、乙醚提取物、可溶性固形物、酚类化合物、可溶性糖、还原糖和非还原糖。基因型×测量交互效应对于所有特性均显著,主要为简单交互,导致基因型排名变化较小。在总共45个基因型相关性估计中,8个显著,其中5个与酸度相关。与参考点相关的前两个成分的离散度表明,基因型BRS3193、AS1、AS2、AS3、N16、CA1和AS7最接近高性能的理想类型。对可溶性糖主要特性的选择导致遗传进展估计低于使用选择指数观察到的结果。遗传材料具有高度的遗传多样性,允许选择在青豆中具有高水平糖类(BRS3193、AS3、GJ25和LB30)、蛋白质(BRS2357)、脂质(GJ30)和酚类化合物(BRS3193)以及高水溶性(AS2)的参考植株。