Extraction of matooke genotypes with superior quality traits from the breeding populations, using the RTBfoods SOPs.
Year: 2025
Type: article
Abstract: Accurate selection of matooke (East African Highland banana, Musa spp.) hybrids with end-user quality traits is essential for the development of improved cultivars. This report presents results of a study whose aim was to deploy colour and texture screening SOPs developed during Phase 1 of the RTBFoods project to extract hybrids with end-user acceptable colour and texture from an existing breeding population. Thirty-six matooke genotypes were screened using SOPs. The genotypes included twenty one hybrids and 15 landrace genotypes. A combination of sensory evaluations (Quantitative descriptive analysis) and instrumental analyses (TPA and Chroma meter) were employed to screen the genotypes. Statistical tools (XLSTAT) were used to identify genotypes with consistently desirable attributes.Results of quantitative descriptive sensory analysis and texture profile analysis showed significant differences (p<0.05) among the different matooke genotypes. The instrumentally and sensorially assessed colour and texture parameters of most matooke hybrid were outside the acceptability thresholds, implying that they would not be selected for advancement. However the instrumental and sensory parameters of matooke hybrid NARITA 17 and NAROBAN 4 were not significantly different from that of most local genotypes (p>0.05). The sensory yellowness and colour homogeneity of hybrid NARITA17 and NAROBAN were close to that of Mbwazirume, one of the most preferred landrace genotype qualifying them for selection for advancement in the breeding pipeline and eventual variety release. Both NAROBAN 4 and NARITA 17 have been released to farming communities, confirming the usefulness of the SOPs to pick genotypes that satisfy consumer preference.The use of the SOPs is being mainstreamed into the selection process of matooke breeding programme in NARO as medium throughput tools.
Institution: National Agricultural Research Organisation
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W6930906808
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