Bem vindo à Biblioteca do Café
O SBICafé é um repositório temático da produção científica das instituições que integram o Consórcio Brasileiro de Pesquisa e Desenvolvimento do Café (Consórcio Pesquisa Café). Seu objetivo é unificar e facilitar o acesso à produção científica das instituições consorciadas, no que se refere a temas relacionados ao agronegócio do café, aumentando assim a visibilidade, o uso e o impacto dos resultados das pesquisas depositadas, no intuito de fortalecer os projetos desenvolvidos em torno do Programa Nacional de Pesquisa e Desenvolvimento do Café (PNP D/Café), aumentando sua produtividade, progresso e recompensas.
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Submissões Recentes
Large-scale gene expression analysis reveals the role of primary metabolism regulation in resistance to Brazilian Pseudomonas coronafaciens pv. garcae in coffee
(Instituto Agronômico (IAC), 2024-12-20) Schenk, Juliana Camargo Martinati; Rodrigues, Lucas Mateus Rivero; Arruda, Natália; Guimarães, Paula de Souza; Diniz, Leandro Cardamone; Rezende, Antonio Mauro; Destéfano, Suzete Aparecida Lanza; Padilha, Lilian; Maluf, Mirian Perez; Guerreiro Filho, Oliveiro
This study investigated the response of arabica coffee plants to the pathogen Pseudomonas coronafaciens pv. garcae using RNA-seq technology. Susceptible and resistant coffee plants were inoculated with the bacteria, and leaf samples were collected at different time points for RNA sequencing. Seven genes related to different defense pathways were chosen for expression quantification in time-course experiments using infected leaves from resistant and susceptible plants, as well as non-infiltrated and water-infiltrated leaves as controls. The results obtained revealed that response mechanisms differ between genotypes and provide insights into the genetic basis of early defense in coffee plants against P. coronafaciens pv. garcae, offering potential strategies for genetic breeding.
Rock powder application combined with bacterial inoculation enhances the early growth of coffee plants
(Editora UFLA, 2025-03-14) Corrêa, Jessiane dos Santos; Araújo, Dayane Aparecida de Oliveira; Rodrigues, Allieksiei Castelar Perim Souza; Brito, Orlando Gonçalves; Gusmão Júnior, Genilson Rodrigues; Rodrigues, Tatiana Tozzi Martins Souza
The use of rock powder combined with nutrient-solubilizing and growth-promoting bacteria represents a promising alternative for nutrient supply to the soil and improved crop development. This study aimed to evaluate the development of coffee seedlings treated with rock dust and inoculated with Bacillus species. Six types of rock powder (slate, black slate, gneiss, kamafugite, pyroxenite, and a mixture of mica schist and granite) were added to standard fertilizer in the presence or absence of a Bacillus mixture (Bacillus subtilis and Bacillus amyloliquefaciens) during coffee cultivation. We measured plant height, stem diameter, leaf number, shoot and root dry biomass, and nutrient levels in the soil and coffee leaves after. In the kamafugite treatment, adding a bacterial mixture increased plant height. When the bacterial application was considered alone, it resulted in an 85% increase in the plants’ total dry biomass. Rock powder and bacteria showed a substantial interaction effect, particularly for nutrients. Gneiss and kamafugite treatments increased phosphorus availability in the soil, whereas bacterial presence boosted calcium and magnesium content. The combination of nutrient-solubilizing and growth-promoting bacteria and rock powder improved soil chemical properties and the early development of coffee plants.
Sample size estimation of fruit maturation for Arabica’s coffee
(Instituto Agronômico (IAC), 2025-01-31) Botega, Gustavo Pucci; Abrahão, Juliana Costa de Rezende; Botelho, Thiago Tavares; Botelho, Cesar Elias; Salvador, Guilherme Soares; Gonçalves, Flávia Maria Avelar
This study aimed at establishing the ideal sample size for evaluating the maturation cycle in Coffea arabica, and investigating the errors associated with different sample sizes, in addition to verifying the possibility of using the clustering method to separate genotypes according to the maturation stage. Two experiments were analyzed: one with F2:3 progenies using visual maturation assessment through fruit counting, and another with cultivars using image processing for maturation assessment. To determine the ideal sample size for this trait, we used the estimation of the errors associated with maturation, using the bootstrap technique. Subsequently, the K-means algorithm was tested as an alternative for clustering genotypes into maturation classes. The application of the bootstrap technique in order to estimate the error associated with maturation revealed that the adoption of a 450-mL sample size resulted in an associated error of approximately 5%, indicating that it is an adequate size for character assessment. The implementation of K-means as a clustering tool offers a promising perspective for Arabica coffee plant breeding programs. A more comprehensive analysis, which not only assesses the proportion of ripe fruits, but also considers the distribution of different maturation stages, provides a more accurate understanding of the maturation process. This allows a more precise identification of genotypes with the most suitable performance for different growing conditions, as well as enabling adjustments in harvest management and post-harvest processing, optimizing coffee quality.
Contribution of mycorrhiza and phosphate-solubilizing fungi in coffee seedling growth in four soils with different fertility conditions
(Instituto Agronômico (IAC), 2025-01-17) González-Osorio, Hernan; Sadeghian, Siavosh; Mira, Beatriz Eugenia
Phosphorus (P) is a limiting nutrient for coffee seedlings. To meet this requirement, coffee growers usually apply di-ammonium phosphate (DAP), which is highly sensitive to local price fluctuations. The use of arbuscular mycorrhizal fungi (AMF) and phosphate-solubilizing fungi (PSF) has been recommended, but the results derived from their application are inconsistent and uncertain, depending on soil fertility status. The response of AMF and PSF application in the plant growth of coffee seedlings during the nursery stage was evaluated in four non-sterile soils, which represent the most abundant type of soils in the coffee regions of Colombia: Eutropept, Dystropept, Fulvudand, and Ultisol. The treatments included a commercial AMF inoculum, PSF-Phlebia subserialis-CH4, and a consortium of AMF+PSF, at four P levels (0, 0.5, 1, and 2 g.plant-1 P2O5) using DAP fertilizer. Shoot dry weight (SDW) was affected by P applications in Fulvudand. In the other soils, a P-response occurred with 0.5 g.plant-1 , whereas 1 and 2 g.plant-1 of P2O5 caused a significant reduction in SDW. AMF increased SDW by 40% in Eutropept. The negative effect of higher P amounts was mitigated (> 70%) through PSF and AMF+PSF in Ultisol and Eutropept, respectively. In plants in which microorganisms increased SDW, the P concentration was 0.17 to 0.22%. The plant growth promotion of coffee seedlings during the nursery stage with AMF and/or PSF applications varied according to soil type and P amounts applied.
Modeling nitrogen loss due to ammonia volatilization in fertilizers applied to coffee plants
(Editora da Universidade Estadual de Maringá - EDUEM, 2025-03-25) Nascimento, Leonardo de Almeida; Fernandes, Felipe Augusto; Pereira, Adriele Aparecida; Alves, Henrique José de Paula; Fernandes, Tales Jesus
The coffee tree has a strong dependence on nitrogen (N), which influences the nutritional aspect and plant productivity. The knowledge of the nutritional behavior of coffee crops, as well as the pattern of nutrient release and loss, contribute to the appropriate crop management, influencing quality, productivity and minimizing economic losses. Therefore, the objective of this article is to select the non-linear model that best describes nitrogen losses due to ammonia (NH3) volatilization, in seven conventional and increased efficiency fertilizers, applied in three installments to coffee plants and indicate the fertilizers that presented the highest and lowest nitrogen losses due to NH3 volatilization. The data come from an experiment carried out during the 2015/2016 harvest at the Coffee Innovation Agency (INOVACAFÉ) of the Federal University of Lavras, in a randomized block design with 3 replications of 7 treatments (nitrogen fertilizers). The estimation method used was the least squares method (MMQ), with the Gauss-Newton convergence algorithm as the iterative method. As diagnostic measures to determine the best model, the adjusted coefficient of determination (R2aj), residual standard deviation (RSD), Akaike information criterion (AIC) and mean absolute deviation (MAD) were used. It was verified that all models exhibited good adjustments, however, the Brody and Logistic models stood out in describing the accumulated nitrogen losses, due to ammonia volatilization, in relation to the seven treatments applied and evaluated. It was found that ammonium nitrate and ammonium sulfate fertilizers presented the lowest N losses, while Prilled Urea and Urea + anionic polymer contribute the greatest losses due to the volatilization of NH3, in the three fertilizations on coffee plants.
