J. Lorenzen

Trait variation and genetic diversity in a banana genomic selection training population

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31–35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.

Genomic Prediction in a Multiploid Crop: Genotype by Environment Interaction and Allele Dosage Effects on Predictive Ability in Banana

First empirical evidence of genomic prediction in a multi‐ploidy banana population is presented. The effect of allele dosage single nucleotide polymorphism on prediction accuracy depends on the trait. Use of averaged environmental data improves prediction accuracy. BayesB model can be used across all traits during genomic prediction in banana breeding. The high predictive values show the potential of genomic prediction in banana breeding.

Agronomic evaluation of common and improved dessert banana cultivars at different altitudes across Burundi

Banana is an important crop for food and income in Burundi. However, average annual yields are low (5 t/ha) because of low and declining soil fertility, and pest and disease pressure. To help overcome the challenges to banana production in the Great Lakes region of Central Africa, the Consortium for the Improvement of Agriculture-based Livelihoods in Central Africa (CIALCA) has been promoting and facilitating access to new high-yielding, pest- and disease-resistant improved hybrid banana cultivars with good consumer acceptability. The agronomic performance of the improved hybrid ‘FHIA-17’ and six commonly grown dessert banana cultivars was evaluated at six sites with contrasting altitudes across Burundi from 2008 to 2012. The data were analysed using linear mixed-effects modelling. ‘FHIA-17’ significantly outperformed the other cultivars as it had the heaviest bunch weight, was in the group of cultivars with the most hands and fruits, and the fruits were long and thick. The cultivars ‘ITC0680’, ‘Gros Michel’, ‘Prata’ and ‘Yangambi Km5’ had the next best agronomic performance, while the cultivars ‘Ikigurube’ and ‘Kamaramasenge’ had the poorest performance. The high agronomic performance of ‘FHIA-17’ shown in this research demonstrates how its increased cultivation may help to ensure the continued production of dessert types of bananas in Burundi and the food and income security of the population.