Food quality profile of pounded yam and implications for yam breeding

Otegbayo Bolanle Omolara, Oluyinka Oroniran, Tanimola Abiola, Bisi Fawehinmi, Ayomide Alamu, Tomilola Bolaji, Madu Tessy, Okoye Benjamin, Chijioke Ugo, Ofoeze Miriam, Alamu Emmanuel Oladeji, Adesokan Michael, Ayetigbo Oluwatoyin, Bouniol Alexandre, DJibril-Mousa Imayath, Adinsi Laurent, Akissoé Noël, Cornet Denis, Agre Paterne Angelot, Asfaw Asrat, Obidiegwu Jude, Maziya‐Dixon Busie. 2024. Food quality profile of pounded yam and implications for yam breeding. Journal of the Science of Food and Agriculture, 104 (8), n.spéc. Tropical roots, tubers and bananas: New breeding tools and methods to meet consumer preferences : 4635-4651.

Résumé : BACKGROUND: Assessment of the key preferred quality traits in pounded yam, a popularly consumed yam food product in West Africa, is often done through sensory evaluation. Such assessment is time-consuming and results may be biased. Therefore, there is a need to develop objective, high-throughput methods to predict the quality of consumer-preferred traits in pounded yam. This study focused on how key quality traits in pounded yam proposed to yam breeders were determined, measured by biophysical and biochemical methods, in order to shorten the breeding selection cycle through adoption of these methods by breeders. RESULTS: Consumer tests and sensory quantitative descriptive analysis (QDA) validated that preferred priority quality traits in pounded yam were related to textural quality (smooth, stretchable, moldable, slightly sticky and moderately hard) and color (white, cream or light yellow). There were significant correlations between sensory textural quality attributes cohesiveness/moldability, hardness, and adhesiveness/stickiness, with textural quality measurements from instrumental texture profile analysis (TPA). Color measurement parameters (L*, a*, and b*) with chromameter agreed with that of sensory evaluation and can replace the sensory panel approach. The smoothness (R2 = 1.00), stickiness (R2 = 1.00), stretchability (R2 = 1.00), hardness (R2 = 0.99), and moldability (R2 = 0.53) of pounded yam samples can be predicted by the starch, amylose, and protein contents of yam tubers estimated by near-infrared spectroscopy. CONCLUSION: TPA and Hunter colorimeter can be used as medium-high throughput methods to evaluate the textural quality and color of pounded yam in place of the sensory panelists.

Mots-clés Agrovoc : qualité des aliments, analyse organoleptique, préférence alimentaire, Dioscorea rotundata, igname, comportement du consommateur, propriété organoleptique, amélioration génétique, Dioscorea, Dioscorea alata

Mots-clés géographiques Agrovoc : Bénin, Nigéria, Afrique occidentale

Mots-clés libres : Pounded yam, Color, Textural quality, Texture Profile Analysis, Chromameter, Consumer preferences

Classification Agris : Q04 - Composition des produits alimentaires
F30 - Génétique et amélioration des plantes

Champ stratégique Cirad : CTS 3 (2019-) - Systèmes alimentaires

Agences de financement hors UE : Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Bill and Melinda Gates Foundation

Projets sur financement : (FRA) Breeding RTB Products for End User Preferences

Auteurs et affiliations

• Otegbayo Bolanle Omolara, Bowen university (NGA) - auteur correspondant
• Oluyinka Oroniran, Bowen university (NGA)
• Tanimola Abiola, Bowen university (NGA)
• Bisi Fawehinmi, Bowen university (NGA)
• Ayomide Alamu, Bowen university (NGA)
• Tomilola Bolaji, Bowen university (NGA)
• Madu Tessy, NRCRI (NGA)
• Okoye Benjamin, NRCRI (NGA)
• Chijioke Ugo, NRCRI (NGA)
• Ofoeze Miriam, NRCRI (NGA)
• Alamu Emmanuel Oladeji, IITA (NGA)
• Adesokan Michael, IITA (NGA)
• Ayetigbo Oluwatoyin, CIRAD-PERSYST-UMR Qualisud (FRA) ORCID: 0000-0001-5757-6674
• Bouniol Alexandre, CIRAD-PERSYST-UMR Qualisud (BEN) ORCID: 0000-0002-6140-424X
• DJibril-Mousa Imayath, UAC (BEN)
• Adinsi Laurent, UAC (BEN)
• Akissoé Noël, UAC (BEN)
• Cornet Denis, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0001-9297-2680 - auteur correspondant
• Agre Paterne Angelot, IITA (NGA)
• Asfaw Asrat, International Livestock Research Institute (ETH)
• Obidiegwu Jude, NRCRI (NGA)
• Maziya‐Dixon Busie, IITA (NGA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/605863/)

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