ABSTRACT This study aimed to evaluate the beverage quality of Coffea canephora genotypes in different environments of the western Amazon to assist plant selection and new cultivar development. To analyze beverage quality, samples of cherry coffee beans were collected separately for each genotype from clonal competition trials installed in the municipalities of Ouro Preto do Oeste, Alta Floresta do Oeste, Porto Velho, and Ariquemes in Rondônia State and Rio Branco in Acre State (Brazil). The beverage quality was assessed using the Robusta Cupping Protocol, which attribute to each genotype a score in a range from 0 to 100, highlighting nuances. Analysis of variance and principal components using reference points were used to quantify genotype x environment interaction (G x E). The analysis of variance indicated that genotypic and G x E interaction effects were significant (p < 0.01). By using a centroid dispersion method, we could identify four clones of low, eight of specific (to favorable or unfavorable environments), and seven of broad adaptability to the environments. The clones BRS 2314, 11, and 17 had average quality scores above 80 in all environments, with potential for specialty coffee production. The clones BRS 1216, BRS 3220, and BRS 3193 presented unstable behavior, with beans of higher quality in some of the evaluated environments. Such inconsistency in clone behavior is caused by unpredictable changes in plant performance in different environments. Our results indicate that both genotypic (clones) and G x E interaction effects are important for the expression of coffee beverage quality. However, the clones BRS 3213, BRS 3210, and BRS 2299 had less prominent nuances, with lower potential for specialty coffee production.

Abstract Amazonian Robustas are ten new clones of high yield potential with characteristics typical of the botanical varieties conilon and robusta. With individual registration, the new cultivars were developed to be grown together with other clones, with flexibility of composition of the crops according to the preference of the producer.

Este trabalho foi realizado para determinar, entre seis índices de vegetação baseados em dados de refletância espectral, aquele que melhor discrimina doses de nitrogênio e que possui maior correlação com leituras de clorofila e massa seca do capim-tanzânia (Panicum maximum Jacq.). Os índices testados foram o NDVI (índice de vegetação por diferença normalizada, calculado utilizando a banda do vermelho e a banda do infravermelho próximo), VARI (índice resistente à atmosfera na região do visível, calculado utilizando a banda de transição do vermelho ao infravermelho e a banda do verde) e WDRVI (índice de vegetação de amplo alcance, calculado utilizando três coeficientes de ponderação, 0,05; 0,1 e 0,2). Foram avaliadas quatro doses de nitrogênio (0, 80, 160 e 320 kg/ha) em delineamento de blocos ao acaso com subamostras, com três repetições e três subamostras por bloco. Os índices VARI utilizando a banda de transição do vermelho ao infravermelho e o WDRVI utilizando os coeficientes 0,05 e 0,1 foram os melhores para discriminar as doses de nitrogênio aplicadas em todos os períodos de avaliação estudados. O índice que apresentou maior correlação com as leituras de clorofila e massa seca foi o VARI com banda de transição do vermelho ao infravermelho.

The objective of this study was to determine, among five vegetation indices, calculated based on spectral reflectance data, the one that best discriminated nitrogen rates, and presented highest correlation with chlorophyll readings and tanzania grass (Panicum maximum Jacq.) dry matter. The tested vegetation indices were NDVI (normalized difference vegetation index), VARI (visible atmospherically resistant index using red edge and green bands), WDRVI (wide dynamic range vegetation index using three weighted coefficients, 0.05, 0.1 and 0.2). Four nitrogen levels (0, 80, 160 and 320 kg/ha) were evaluated in a randomized complete block design with three replications and three subsamplings per block. The indices VARI, using red edge band, and WDRVI, using weighted coefficients 0.05 and 0.1, were the best indices to discriminate nitrogen rates. The index that presented the highest correlation with chlorophyll readings and dry matter was the VARI using red edge band.