Biblioteca do Café
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Item Identification of morphoagronomic traits correlated with the N use efficiency in coffee(Editora UFLA, 2025-04-29) Moura, Waldenia de Melo; Ribeiro, Poliane Marcele; Soares, Luciana Gomes; Silva Júnior, Antônio Carlos da; Ferreira, Tatiane Cravo; Gravina, Geraldo de Amaral; Martinez, Hermínia Emília PrietoThe study of nutritional efficiency is an expensive process, as it requires extensive planting areas, several years of evaluation and the destruction of plants. To mitigate these difficulties, a strategy would be to identify easily measurable traits associated with nutritional efficiency in growing a nutritional solution. Thus, the objective of this study was identify morphoagronomic traits correlated with the N-efficiency indices in to assist in selecting coffee genotypes for environments with N restriction. Twenty arabica coffee genotypes were grown in a nutrient solution with a low concentration of nitrogen (1.0 mmol L-1). The experiment was conducted in a randomized block design with three replications. There was variability among the coffee genotypes for all the traits evaluated. Most of the traits evaluated showed greater genetic than environmental influence on phenotypic expression. Heritability (H2) was greater than 70% for most of the traits evaluated, with an emphasis on plant height and internode length, which also had the highest relative variation indices (RVIs). The associations between morphoagronomic traits and nutritional efficiency indices revealed greater contributions of genotypic correlation than of environmental correlation. Among the traits associated with nutritional efficiency indices, stem diameter has the potential for use in breeding programs for the selection of cultivars that present greater nitrogen efficiency in environments with nitrogen restriction.Item Morpho-agronomic and leaf anatomical traits in Coffeacanephora genotypes(Universidade Federal de Santa Maria, 2023) Silva, Larícia Olária Emerick; Schmidt, Raquel; Almeida, Rafael Nunes de; Feitoza, Rodrigo Barbosa Braga; Cunha, Maura da; Partelli, Fábio LuizGenetic variability is the basis for coffee genetic breeding. This study evaluated the potential of leaf anatomy and morpho-agronomic traits in studies of genetic variability in C. canephoracultivars. Ten genotypes were distributed in randomized block designs with three replicates. Significant differences among genotypes were detected by F-test (P < 0.05) for 13 of 15 evaluated traits. These results evidenced the heterogeneity of the studied cultivars, which is essential in composition of genetic basis in breeding programs. The Scott-Knott test detected variability among genotypes, grouped into up to four mean groups. Leaf anatomy traits presented the largest variations. Five out of seven leaf anatomy traits presented heritability higher than 80%, with emphasis on stomatal density (95.69%) and stomatal pore length (92.72%). Positive correlations were observed among morpho-agronomic and anatomic traits. Cluster analysis used the Mahalanobis general distance (D2) as a measure of genetic dissimilarity and divided the genotypes into two distinct groups. The inclusion of leaf anatomic traits to characterize C. canephoragenotypes may assist plant breeders with better genetic discrimination and with greater security in plant selection when composing cultivars.Item Morpho-agronomic and leaf anatomical traits in Coffeacanephora genotypes(Universidade Federal de Santa Maria, 2022-11-28) Silva, Larícia Olária Emerick; Schmidt, Raquel; Almeida, Rafael Nunes de; Feitoza, Rodrigo Barbosa Braga; Cunha, Maura da; Partelli, Fábio LuizGenetic variability is the basis for coffee genetic breeding. This study evaluated the potential of leaf anatomy and morpho-agronomic traits in studies of genetic variability in C. canephoracultivars. Ten genotypes were distributed in randomized block designs with three replicates. Significant differences among genotypes were detected by F-test (P < 0.05) for 13 of 15 evaluated traits. These results evidenced the heterogeneity of the studied cultivars, which is essential in composition of genetic basis in breeding programs. The Scott-Knott test detected variability among genotypes, grouped into up to four mean groups. Leaf anatomy traits presented the largest variations. Five out of seven leaf anatomy traits presented heritability higher than 80%, with emphasis on stomatal density (95.69%) and stomatal pore length (92.72%). Positive correlations were observed among morpho-agronomic and anatomic traits. Cluster analysis used the Mahalanobis general distance (D2) as a measure of genetic dissimilarity and divided the genotypes into two distinct groups. The inclusion of leaf anatomic traits to characterize C. canephoragenotypes may assist plant breeders with better genetic discrimination and with greater security in plant selection when composing cultivars.Item Environmental stratification and performance of Coffea canephora clones grown in the Western Amazon(Editora UFLA, 2021) Moraes, Marcos Santana; Rocha, Rodrigo Barros; Ferreira, Fábio Medeiros; Souza, Carolina Augusto de; Espindula, Marcelo Curitiba; Teixeira, Alexsandro LaraChange in the performance of clones grown in different environments is an important question for Coffea canephora breeding. The aim of this study was to evaluate environmental stratification and the performance of C. canephora clones grown in the Western Amazon. For that purpose, the mean yield of three crop seasons was considered to evaluate the performance of 20 genotypes grown in 6 clonal competition trials in the environments of: E1: Ouro Preto do Oeste-RO, E2: Porto Velho-RO, E3: Ariquemes-RO, E4 and E5: Rio Branco-AC and E6: Alta Floresta do Oeste-RO. The trials were conducted with a plant spacing of 3 m × 1.5 m in a complete block experimental design, with three replications of eight plants per plot. Combined analysis indicated significance of the genotype × environment (G×E) interaction and favorable conditions to obtain gains from selection. Reduction in the dimensionality estimated from climate and soil characteristics indicated that the environments of Porto Velho-RO, Rio Branco-AC and Ariquemes-RO are more similar to each other than the environments of Ouro Preto do Oeste-RO and Alta Floresta-RO of greater natural soil fertility and higher altitude. The AMMI1 biplot shows that genotypes 16, 10, and 13 had the highest mean yields, together with greater stability. In the AMMI2 scatterplot (IPCA1×IPCA2), the environ ments E4 and E5 were clustered in the same sector. Clustering based on the complex fraction of the G×E interaction coincided with the AMMI2 scatterplot that clustered the E4 and E5 environments in a single mega-environment. Except for these environments, all the others clustered as locations of different biotic and abiotic stress conditions. This result shows the importance of maintaining evaluations in these environments, which represent the conditions of the coffee fields in the region.Item Receptor-Like Kinase (RLK) as a candidate gene conferring resistance to Hemileia vastatrix in coffee(Escola Superior de Agricultura "Luiz de Queiroz", 2021) Almeida, Dênia Pires de; Castro, Isabel Samila Lima; Mendes, Tiago Antônio de Oliveira; Alves, Danúbia Rodrigues; Barka, Geleta Dugassa; Barreiros, Pedro Ricardo Rossi Marques; Zambolim, Laércio; Sakiyama, Ney Sussumu; Caixeta, Eveline TeixeiraThe biotrophic fungus Hemileia vastatrix causes coffee leaf rust (CLR), one of the most devastating diseases in Coffea arabica. Coffee, like other plants, has developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs) have been identified in certain plants as candidates for resistance (R) genes or membrane receptors that activate the R genes. The RGAs identified in different plants possess conserved domains that play specific roles in the fight against pathogens. Despite the importance of RGAs, in coffee plants these genes and other molecular mechanisms of disease resistance are still unknown. This study aimed to sequence and characterize candidate genes from coffee plants with the potential for involvement in resistance to H. vastatrix. Sequencing was performed based on a library of bacterial artificial chromosomes (BAC) of the coffee clone ‘Híbrido de Timor’ (HdT) CIFC 832/2 and screened using a functional marker. Two RGAs, HdT_ LRR_RLK1 and HdT_LRR_RLK2, containing the motif of leucine-rich repeat-like kinase (LRR-RLK) were identified. Based on the presence or absence of the HdT_LRR_RLK2 RGA in a number of differential coffee clones containing different combinations of the rust resistance gene, these RGAs did not correspond to any resistance gene already characterized (SH1-9). These genes were also analyzed using qPCR and demonstrated a major expression peak at 24 h after inoculation in both the compatible and incompatible interactions between coffee and H. vastatrix. These results are valuable information for breeding programs aimed at developing CLR-resistant cultivars, in addition to enabling a better understanding of the interactions between coffee and H. vastatrix.Item Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms(Escola Superior de Agricultura "Luiz de Queiroz", 2021) Sousa, Ithalo Coelho de; Nascimento, Moysés; Silva, Gabi Nunes; Nascimento, Ana Carolina Campana; Cruz, Cosme Damião; Silva, Fabyano Fonseca e; Almeida, Dênia Pires de; Pestana, Kátia Nogueira; Azevedo, Camila Ferreira; Zambolim, Laércio; Caixeta, Eveline TeixeiraGenomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic merit. In general, such methodologies require certain assumptions about the data, such as the normality of the distribution of phenotypic values. To circumvent the non-normality of phenotypic values, the literature suggests the use of Bayesian Generalized Linear Regression (GBLASSO). Another alternative is the models based on machine learning, represented by methodologies such as Artificial Neural Networks (ANN), Decision Trees (DT) and related possible refinements such as Bagging, Random Forest and Boosting. This study aimed to use DT and its refinements for predicting resistance to orange rust in Arabica coffee. Additionally, DT and its refinements were used to identify the importance of markers related to the characteristic of interest. The results were compared with those from GBLASSO and ANN. Data on coffee rust resistance of 245 Arabica coffee plants genotyped for 137 markers were used. The DT refinements presented equal or inferior values of Apparent Error Rate compared to those obtained by DT, GBLASSO, and ANN. Moreover, DT refinements were able to identify important markers for the characteristic of interest. Out of 14 of the most important markers analyzed in each methodology, 9.3 markers on average were in regions of quantitative trait loci (QTLs) related to resistance to disease listed in the literature.Item Trait selection using procrustes analysis for the study of genetic diversity in Conilon coffee(Editora da Universidade Estadual de Maringá - EDUEM, 2020) Pontes, Daiana Salles; Rosado, Renato Domiciano Silva; Cruz, Cosme Damião; Nascimento, Moysés; Oliveira, Ana Maria Cruz; Pensky, Scott MichaelTrait selection is occasionally necessary to save money and time, as well as accelerate breeding program processes. This study aimed to propose two criteria to select traits based on a Procrustes analysis that are poorly explored in genetic breeding: Criterion 1 (backward algorithm) and Criterion 2 (exhaustive algorithm). Then, these two criteria were further compared with Jolliffe’s criterion, which has often been used to select traits in genetic diversity studies. Sixteen agronomic traits were considered, and 40 Conilon coffee (Coffea canephora) accessions were evaluated. This study showed that the flexibility in selecting traits by researcher preference, graphical visualization, and Procrustes statistic through criteria 1 and 2 is a fast and reliable alternative for decision-making. These decisions are based on the removal and addition of traits for phenotyping in studies of Conilon coffee diversity that can be applied to other crops. Other relevant aspects of selection traits criteria were also discussed.Item Resistance of new Coffea canephora clones to root-knot nematode (Meloidogyne incognita) in the western amazon(Editora UFLA, 2020) Rudnick, Vaneide Araújo de Sousa; Vieira Junior, José Roberto; Fernandes, Cleberson de Freitas; Rocha, Rodrigo Barros; Teixeira, Alexsandro Lara; Ramalho, André Rostand; Espindula, Marcelo Curitiba; Santos, Anderson Vieira; Anjos, Elize Francisca Mendes dos; Uchôa, Francisco PaivaRoot-knot disease is among the main diseases affecting coffee crop. The plant selection to the development new resistant cultivars is among one the most efficient methods of control. The present work aimed to quantify the resistance responses of Coffea canephora clones to root-knot nematode Meloidogyne incognita in the Western Amazon. For this, 17 previously selected clones were evaluated in three experimental trials, carried out in the municipalities of Ji-Paraná and Porto Velho, Rondônia. The resistance to root-knot nematodes M. incognita were evaluated by the numbers of gall in the roots (NG) and by the reproductive factor (RF). The resistance response was also interpreted according the genetic diversity of the clones based in their morphological traits. The clones BRS3210, C12, BRS2314, BRS3137 and BRS1216 are resistant to M. incognita with RF of 0.34, 0.62, 0.79, 0.86 and 0.98, respectively. BRS3213, C125, C15, BRS2336, BRS3220 and C09 clones were classified as susceptible, with RF of 1.93, 1.95, 2.00, 2.31, 2.32 and 2.35. The BRS3193, C160 and BRS2357 clones were classified as very susceptible, with RF values of 3.03, 4.41 and 5.82, respectively. The clustering based on the genetic diversity of morphological traits indicated that genotypes more similar to the Robusta botanic variety had lower RF. The hybrid plants showed intermediate degrees of resistance indicating the segregation for the character of the M. incognita resistance. The clones BRS3210, C12, BRS2299, BRS2314, BRS3137 and BRS1216 expressed resistance responses to M. incognita with potential for growing resistant genotypes in the Western Amazon.