Textural and physicochemical predictors of sensory texture and sweetness of boiled plantain

Kouassi Hermann Antonin, Assemand Emma Fernande, Gibert Olivier, Maraval Isabelle, Ricci Julien, Thiemele Deless Edmond Fulgence, Bugaud Christophe. 2021. Textural and physicochemical predictors of sensory texture and sweetness of boiled plantain. International Journal of Food Science and Technology, 56 (3), n.spéc. Consumers have their say: Assessing preferred quality traits of roots, tubers and cooking bananas, and implications for breeding : 1160-1170.

Url - autre : https://rtbfoods.cirad.fr/news/textural-physicochemical-predictors-boiled-plantain-ijfst / Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/DQA1ZV / Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/NZZHDZ

Quartile : Q2, Sujet : FOOD SCIENCE & TECHNOLOGY

Résumé : Boiled pulp is a major form of consumption for plantain. We assessed instrumental (puncture test and texture profile analysis) and sensory texture attributes of 13 plantain cultivars, two cooking hybrids, and one dessert banana at different stages of ripeness after cooking in boiling water. Firmness, chewiness, stickiness, mealiness, sweetness and moistness described sensory variability, which was greater between stages of ripeness than between types of cultivars. Firmness and chewiness were well‐predicted by instrumental force and hardness (r2 > 0.72), and by soluble solid and dry matter content (r2 > 0.85). Complementary sensitivity analysis revealed that a pulp puncture force or a hardness of at least 2.1 N or of 0.3 N/mm2, was needed before a difference in firmness or chewiness could be perceived; and a Brix of 3.7 was required to ensure a detectable difference in sweetness. Rheological and biochemical predictors can be useful for breeders for high throughput phenotyping.

Mots-clés Agrovoc : banane plantain, aliment préparé, propriété physicochimique, propriété organoleptique, douceur, indicateur biologique, analyse de régression

Mots-clés libres : Musa, Cultivar, Sensory profile analysis, Penetrometry, Texture profile analysis, Multilinear regression

Classification Agris : Q04 - Composition des produits alimentaires

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

Auteurs et affiliations

• Kouassi Hermann Antonin, CIRAD-PERSYST-UMR Qualisud (FRA)
• Assemand Emma Fernande, UNA [Université Nangui Abrogoua] (CIV)
• Gibert Olivier, CIRAD-PERSYST-UMR Qualisud (FRA) ORCID: 0000-0002-1447-9003
• Maraval Isabelle, CIRAD-PERSYST-UMR Qualisud (FRA)
• Ricci Julien, CIRAD-PERSYST-UMR Qualisud (FRA) ORCID: 0000-0002-8883-7352
• Thiemele Deless Edmond Fulgence, UPGC (CIV)
• Bugaud Christophe, CIRAD-PERSYST-UMR Qualisud (FRA) ORCID: 0000-0001-9096-090X - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/596337/)

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