Abstract:ABSTRACT. For the selection of coffee plants that have favorable characteristics, it is necessary to evaluate variables related to production. Knowledge of the genetic divergence of arabica coffee is of extreme importance, as this knowledge can be associated with plant breeding programs in order to combine genetic divergence with good productive performance. The objective of this study was to evaluate the genetic divergence among 16 genotypes of Coffea arabica with the purpose of identifying the most dissimila… Show more
“…In the present work, 16 C. arabica cultivars were selected for analysis, according to their global commodity value in different countries. C. arabica lineages analyzed in this study were classified into two groups that agree with previously reported phylogenies obtained through other methods (Anthony et al, 2002;Machado et al, 2017;Steiger et al, 2002). The first group corresponds to the 'Bourbon' and 'Typica' genetic family; the most important cultivars of this group are 'Pluma Hidalgo' and 'Maragogype', which are natural mutations of 'Typica'.…”
Section: Discussionsupporting
confidence: 85%
“…In conclusion, FCM was used for the estimation of genome size and GC% content in 16 C. arabica cultivars, which allowed the identification of different groups that agree with the previously grouping described, obtained through phylogenetic and amplified fragment length polymorphism analysis (Anthony et al, 2002;Giles et al, 2019;Machado et al, 2017;Steiger et al, 2002). This information could be helpful for C. arabica breeding programs, given the paucity of genome size studies with FCM in different important C. arabica cultivars (such as the group corresponding to the 'Bourbon' and 'Typica' genetic family hybrids and artificial crosses).…”
Section: Discussionmentioning
confidence: 67%
“…Indeed, Coffea cultivars mitigate heat stress in greater CO 2 concentrations (Martins et al, , 2017Rodrigues et al, 2016). The genetic divergence in Coffea is extensively described and quantitative trait loci associated with phenotypes were identified using multivariate procedures (Giles et al, 2018;Machado et al, 2017). Knowledge of base composition in woody plants may provide additional insight into the relationship between GC% and climatic adaptability (Contreras and Shearer 2018).…”
Coffee is an important crop worldwide, grown on about 10 million hectares in tropical regions including Latin America, Africa, and Asia. The genus Coffea includes more than 100 species; most are diploid, except for C. arabica, which is allotetraploid and autogamous. The genetic diversity of commercial coffee is low, likely due to it being selfpollinating, in addition, the widespread propagation of few selected cultivars, such as Caturra, Bourbon, and Typica. One approach is the analysis of genome size in these cultivars as a proxy to study its genetic variability. In the present work, genome size of 16 cultivars was assessed through high-resolution flow cytometry (FCM). Nuclear DNA was analyzed using a modified procedure that uses propidium iodide (PI) and 4#,6#-diamino-2-phenylindole dihydrochloride hydrate (DAPI) staining. The C. arabica cultivars investigated possessed a nuclear DNA content ranging from 2.56 ± 0.016 pg for Typica, to 3.16 ± 0.033 pg for ICATU, which had the largest genome size. All cultivars measured using both fluorochromes had greater estimates with DAPI than PI. The proportion of the genome composed of guanosine and cytosine (GC%) among the cultivars evaluated in this study ranged from 37.03% to 39.22%. There are few studies of genome size by FCM of distinct important C. arabica cultivars, e.g., hybrids and artificial crosses. Thus, this work could be valuable for coffee breeding programs. The data presented here are intended to expand the genomic understanding of C. arabica and could link nuclear DNA content with evolutionary relationships such as diversification, hybridization and polyploidy.
Materials and Methods
Plant materialLeaves were collected from 16 healthy C. arabica cultivars in consideration of its
“…In the present work, 16 C. arabica cultivars were selected for analysis, according to their global commodity value in different countries. C. arabica lineages analyzed in this study were classified into two groups that agree with previously reported phylogenies obtained through other methods (Anthony et al, 2002;Machado et al, 2017;Steiger et al, 2002). The first group corresponds to the 'Bourbon' and 'Typica' genetic family; the most important cultivars of this group are 'Pluma Hidalgo' and 'Maragogype', which are natural mutations of 'Typica'.…”
Section: Discussionsupporting
confidence: 85%
“…In conclusion, FCM was used for the estimation of genome size and GC% content in 16 C. arabica cultivars, which allowed the identification of different groups that agree with the previously grouping described, obtained through phylogenetic and amplified fragment length polymorphism analysis (Anthony et al, 2002;Giles et al, 2019;Machado et al, 2017;Steiger et al, 2002). This information could be helpful for C. arabica breeding programs, given the paucity of genome size studies with FCM in different important C. arabica cultivars (such as the group corresponding to the 'Bourbon' and 'Typica' genetic family hybrids and artificial crosses).…”
Section: Discussionmentioning
confidence: 67%
“…Indeed, Coffea cultivars mitigate heat stress in greater CO 2 concentrations (Martins et al, , 2017Rodrigues et al, 2016). The genetic divergence in Coffea is extensively described and quantitative trait loci associated with phenotypes were identified using multivariate procedures (Giles et al, 2018;Machado et al, 2017). Knowledge of base composition in woody plants may provide additional insight into the relationship between GC% and climatic adaptability (Contreras and Shearer 2018).…”
Coffee is an important crop worldwide, grown on about 10 million hectares in tropical regions including Latin America, Africa, and Asia. The genus Coffea includes more than 100 species; most are diploid, except for C. arabica, which is allotetraploid and autogamous. The genetic diversity of commercial coffee is low, likely due to it being selfpollinating, in addition, the widespread propagation of few selected cultivars, such as Caturra, Bourbon, and Typica. One approach is the analysis of genome size in these cultivars as a proxy to study its genetic variability. In the present work, genome size of 16 cultivars was assessed through high-resolution flow cytometry (FCM). Nuclear DNA was analyzed using a modified procedure that uses propidium iodide (PI) and 4#,6#-diamino-2-phenylindole dihydrochloride hydrate (DAPI) staining. The C. arabica cultivars investigated possessed a nuclear DNA content ranging from 2.56 ± 0.016 pg for Typica, to 3.16 ± 0.033 pg for ICATU, which had the largest genome size. All cultivars measured using both fluorochromes had greater estimates with DAPI than PI. The proportion of the genome composed of guanosine and cytosine (GC%) among the cultivars evaluated in this study ranged from 37.03% to 39.22%. There are few studies of genome size by FCM of distinct important C. arabica cultivars, e.g., hybrids and artificial crosses. Thus, this work could be valuable for coffee breeding programs. The data presented here are intended to expand the genomic understanding of C. arabica and could link nuclear DNA content with evolutionary relationships such as diversification, hybridization and polyploidy.
Materials and Methods
Plant materialLeaves were collected from 16 healthy C. arabica cultivars in consideration of its
“…These nine clusters are considered divergent among each other regarding the foliar nutrient contents from the C. canephora genotypes cultivated at an altitude of 850 meters, where high diversity was identified in terms of foliar nutrient contents. The study of genetic diversity using multivariate techniques is important for planning and defining work strategies in breeding programs (Guedes et al, 2013;Machado et al, 2017). In fact, the use of plant material with genetic variability is determinant for successive breeding programs, providing greater gains in selection (Cruz et al, 2004).…”
The variation in the climatic conditions throughout the year can influence the foliar nutrient contents in Coffea canephora, impacting the fertilization management. We evaluated the influence of the climatic seasonality on the foliar nutrient contents of 28 C. canephora genotypes cultivated at 850 meters of altitude, in cold winter. The work was carried out in Morrinhos, State of Goiás, Brazil. A randomized complete block design in a 2 x 28 factorial arrangement was used, with two crop seasons, winter and summer, and 28 C. canephora genotypes, with four replications, each replicate composed by five plants, and a spacing of 3.5 m x 1.0 m. The third and fourth pairs of leaves, of productive branches located in the middle third of the plant, were collected in six-year-old crops. The leaves were dried, and the mineral contents were analyzed, they were, then, subjected to multivariate analysis of principal components, dissimilarity and clustering. The results reveal the existence of different nutritional contents among leaves collected in the winter and summer. There is a tendency of higher macro and micronutrient contents in leaves collected in the winter than in the summer. The nutritional diagnosis should consider the group of genotypes and the crop season.
“…The berries' anatomical variations, such as the diameter of the crown, may influence the penetration behavior of H. hampei (MACHADO et al, 2017). Chemical characteristics are also important determinants of insect behavior (BRUCE; PICKETT, 2011), especially that of the females, which can sense the different volatile compounds released by attacked and intact fruit and differentiate among them (JARAMILLO et al, 2013;BRASSIOLI-MORAES et al, 2019).…”
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.