Browsing by Author "Florence Osaru"

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Breeding Cultivars for Resistance to the African Sweetpotato Weevils, Cylas puncticollis and Cylas brunneus, in Uganda: A Review of the Current Progress
(Insects, 2023-10-25) Benard Yada; Paul Musana; Doreen M. Chelangat; Florence Osaru; Milton O. Anyanga; Arnold Katungisa; Bonny M. Oloka; Reuben T. Ssali; Immaculate Mugisa
In sub-Saharan Africa, sweetpotato weevils are the major pests of cultivated sweetpotato, causing estimated losses of between 60% and 100%, primarily during dry spells. The predominantly cryptic feeding behavior of Cylas spp. within their roots makes their control difficult, thus, host plant resistance is one of the most promising lines of protection against these pests. However, limited progress has been made in cultivar breeding for weevil resistance, partly due to the complex hexaploid genome of sweetpotato, which complicates conventional breeding, in addition to the limited number of genotypes with significant levels of resistance for use as sources of resistance. Pollen sterility, cross incompatibility, and poor seed set and germination in sweetpotato are also common challenges in improving weevil resistance. The accurate phenotyping of sweetpotato weevil resistance to enhance the efficiency of selection has been equally difficult. Genomics-assisted breeding, though in its infancy stages in sweetpotato, has a potential application in overcoming some of these barriers. However, it will require the development of more genomic infrastructure, particularly single-nucleotide polymorphism markers (SNPs) and robust next-generation sequencing platforms, together with relevant statistical procedures for analyses. With the recent advances in genomics, we anticipate that genomic breeding for sweetpotato weevil resistance will be expedited in the coming years. This review sheds light on Uganda’s efforts, to date, to breed against the Cylas puncticollis (Boheman) and Cylas brunneus (Fabricius) species of African sweetpotato weevil.
Decision tree scoring system to guide selection for consumer preference in sweetpotato breeding trials.
(Journal of The Science of Food and Agriculture, 2023-08-08) Mariam Nakitto; Reuben T Ssali; Suzanne D Johanningsmeier; Mukani Moyo; Henriette de Kock; Ingunn Berget; Julius J Okello; Sarah Mayanja; Samuel Edgar Tinyiro; Thiago Mendes; Yada Benard; Doreen Chelengat; Florence Osaru; Christophe Bugaud
BACKGROUND: Previously, a lexicon and protocol for quantitative descriptive analysis (QDA) was established for the Uganda sweetpotato breeding program. The implication of QDA scores for priority sensory attributes on consumer preference should be determined to interpret results efficiently and make decisions effectively. The present study aimed to develop a gender- responsive decision tree to obtain an overall sweetpotato eating quality score to facilitate demand-led targeted breeding selection. It focused on Kamuli and Hoima districts (Uganda) and uses pre-lease advanced clones (‘NKB3’, ‘NKB105’, ‘NKB135’, ‘D11’ and ‘D20’), released varieties (‘NASPOT 8’ and ‘NAROSPOT 1’) and landraces (‘Muwulu-Aduduma’, ‘Umbrella’). RESULTS: Including boiled sweetpotato sensory characteristics, namely mealy, sweet taste, sweetpotato smell, firm and not fibrous, in breeding design would benefit end-users, especially women given their role in varietal selection, food preparation and marketing. ‘D20’, ‘NASPOT 8’ and ‘NAROSPOT 1’ were most liked in both districts. ‘NKB3’ and ‘D11’ were the least liked in Hoima, whereas ‘Muwulu-Aduduma’ was the least liked in Kamuli. There was a positive correlation between color and overall liking (r2 = 0.8) and consumers liked the color (average rating ≥ 6 on a nine-point hedonic scale) of all genotypes. Threshold values (average rating on 11-point scales) for consumer acceptability were identified (sweet taste = 6, sweetpotato aroma and flavor = 6, firmness = 3, and mealiness = 4). A regression decision tree tool was created to calculate an eating quality selection index when screening lines in breeding programs using the values. CONCLUSION: Decision trees that include consumer needs and gender considerations would facilitate demand-led breeding and make varietal selection in sweetpotato breeding programs more effective.
Identification of the key morphological sweetpotato weevil resistance predictors in Ugandan sweetpotato genotypes using correlation and path-coefficient analysis
(Crop Science, 2023-03-16) Florence Osaru; Jeninah Karungi; Roy Odama; Doreen Murenju Chelangat; Paul Musana; Milton Anyanga Otema; Bonny Oloka; Paul Gibson; Richard Edema; Reuben Tendo Ssali; George Craig Yencho; Benard Yada
Sweetpotato weevils (SPWs) can cause up to 100% yield losses in sweetpotato (Ipomoea batatas). Nevertheless, there has been limited success in breeding for SPW resistance globally. This is attributed partly to difficulty in screening for resistance because resistance to the SPW is complex and is mediated by several resistance indicators. Measuring all these resistance indicators is costly and time consuming. To enhance efficiency in selection for SPW resistance, there is need to profile and identify key resistance indicators. Potentially, this will better enable breeders to timely and precisely select for SPW resistance. The objective of this study was to identify the most efficient morphological resistance indicators against SPW. Thirty sweetpotato genotypes that varied in resistance to SPW comprising local collections, released varieties, and breeding lines were evaluated at three locations for two seasons in Uganda using an alpha lattice design. Data were collected on storage root yield, SPW root and stem damage, and weevil resistance indicators such as vine vigor (VV), ground cover (GC), vine weight (VW), storage root neck length (NL), latex content, cortex thickness (CT), and dry matter content (DM). Genotype means for all mea- sured traits varied significantly except for CT. Negative relationships were observed between SPW root damage and GC, VW, CT, VV, NL, and DM. However, path coefficient analysis showed storage root NL (direct effect of −0.43, p < 0.001) as the most important morphological resistance indicator. Therefore, NL could be the most