Assessment of morphological traits of coffee used in determining the performance of Arabusta hybrids generated from crosses between the tetraploid Robusta and Arabica coffee

Abstract: 
Coffee is one of the most important commodities in the world being traded second after oil. One of the objectives of coffee breeding programs is to select for good quality coffee with high yields. The aim of this study was to determine variations within the Arabusta hybrids, its backcrosses to Arabica coffee and to estimate the relationships between the different growth traits. The study was carried out in two different locations (Siaya and Busia counties) and data were collected in 2017. The experimental design used was a Randomized Complete Block Design (RCBD) with three replications. Experimental plots were comprised of five trees. Data were collected on various growth and yield traits during the second year. These included height (cm), nodes on main stem, internode length on main stem (cm), primaries, bearing primaries, % bearing primaries, longest primary (cm), nodes on longest primary, internode length on longest primary (cm), bearing nodes on longest primary, % bearing nodes, laterals, berries, berries per node and node with highest berry number. There was a highly significant difference (P<0.001) within all traits except number of nodes on main stem and % berries on primaries. The correlation results showed statistically significant associations between different traits. The correlation of number of berries with number of berries on primaries and the nodes with number of berries was significant. Further data need to be collected for the third year to be able to take advantage of production for all trees since by the second year not all trees within the plots had berries.
Date of publication: 
2018
Country: 
Region Focus: 
East Africa
Volume: 
17
Number: 
2
Pagination: 
487-493
Collection: 
RUFORUM Working document series
Agris Subject Categories: 
Licence conditions: 
Open Access
Access restriction: 
Form: 
Web resource
ISSN: 
1607-9345