Browsing by Author "Reuben Tendo Ssali"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Connecting data for consumer preferences, food quality, and breeding in support of market-oriented breeding of root, tuber, and banana crops
    (Journal of The Science of Food and Agriculture, 2023-05-24) Elizabeth Arnaud; Naama Menda; Thierry Tran; Amos Asiimwe; Michael Kanaabi; Karima Meghar; Lora Forsythe; Robert Kawuki; Bryan Ellebrock; Ismail Siraj Kayondo; Afolabi Agbona; Xiaofei Zhang; Thiago Mendes; Marie-Angélique Laporte; Mariam Nakitto; Reuben Tendo Ssali; Asrat Asfaw; Brigitte Uwimana; Chukwudi E. Ogbete; Godwill Makunde; Isabelle Maraval; Lukas A. Mueller; Alexandre Bouniol; Eglantine Fauvelle; Dominique Dufour
    The 5-year project ‘Breeding roots, tubers and banana products for end user preferences’ (RTBfoods) focused on collecting consumers' preferences on 12 food products to guide breeding programmes. It involved multidisciplinary teams from Africa, Latin America, and Europe. Diverse data types were generated on preferred qualities of users (farmers, family and entrepreneurial processors, traders or retailers, and consumers). Country-based target product profiles were produced with a comprehensive market analysis, disaggregating gender's role and preferences, providing prioritised lists of traits for the development of new plant varieties. We describe the approach taken to create, in the roots, tubers, and banana breeding databases, a centra- lised and meaningful open access to sensory information on food products and genotypes. Biochemical, instrumental textural, and sensory analysis data are then directly connected to the specific plant record while user survey data, bearing personal information, were analysed, anonymised, and uploaded in a repository. Names and descriptions of food quality traits were added into the Crop Ontology for labelling data in the databases, along with the various methods of measurement used by the project. The development and application of standard operating procedures, data templates, and adapted trait ontologies improved the data quality and its format, enabling the linking of these to the plant material studied when uploaded in the breeding databases or in repositories. Some modifications to the database model were necessary to accommodate the food sensory traits and sensory panel trials.
  • Thumbnail Image
    Item
    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