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Participatory processing diagnosis of boiled yam in Benin. Understanding the drivers of trait preferences and the development of multi-user RTB product profiles, WP1

Bouniol A., Adinsi L., Honfozo F.L., Hounhouigan J.D., Fliedel G., Akissoé N.. 2021. Cotonou : RTBfoods Project; CIRAD, 27 p..

DOI: 10.18167/DVN1/HQQ2VQ

DOI: 10.18167/agritrop/00627

This study is part of the RTBfoods project WP1 outputs, essentially the step 3 of the developed methodology which deals with the quality traits of boiled yam, collected through a participatory processing diagnosis. Six local varieties with contrasting characteristics identified within the WP1 step 2 survey were processed into boiled yam by 6 qualified processors. Completes sets of quantitative data (raw material characteristics, yield, productivity, applied conditions for each unit operation) and qualitative data (raw material and end products evaluation) were collected in one small urban center, Bohicon - Benin. The varieties have been classified according their phenotypic characteristics according 3 groups having significant differences according their lengths and weights. Processors indicated that a variety could not be evaluated or selected only according its appearance. Significant differences were also identified on their dry matter content which ranged between 25.8 and 43.2 %. With regard to the peeling unit operation it is important that the peeled yam do not change colour. Regarding the cooking step, the control of the [Qwater/Qyam] ratio is important in the quality of the boiled yam, and in particular its textural friable homogeneity and the level of the stickiness. No significant varietal difference was observed as far as cooking time is concerned. The texture of the boiled yam pieces and the behaviour of the tubers during cooking appear to be related to the initial dry matter content. In our conditions, a minimum threshold for the dry matter content of the raw material seems to be around 30%. The processor's end products evaluation allowed to generate a complete set of good and bad descriptors on colour, textural, taste and flavor properties, with 16 good and 19 bad descriptors that have been useful for the step 4 of the WP1's methodology.

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