Meghar Karima, Davrieux Fabrice. 2022. Proof of Concept of visualisation of dry matter content in yam tuber during storage, using Hyperspectral Imaging. High-Throughput Phenotyping Protocols (HTPP), WP3. Montpellier : RTBfoods Project-CIRAD, 16 p.
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Résumé : Fast screening methods are needed for plant breeding. The objective of this research was to evaluate the potential of hypespectral imaging coupled with Near infrared spectroscopy (HSI-NIR) for the analysis of dry matter (DM) in intact discs of fresh yam tubers during storage process (0, 15, 30, 45, 60 and 75 days) at 16 °C and 70 % of relative humidity. Partial least square regression (PLS) was applied to establish calibration. The coefficient of determination for calibration (R²) was equal to 0.89 and the root mean square of error of cross validation (RMSECV) was 2.85 % with a ratio performance to deviation(RPD) of 3.05. Finally, distribution maps were displayed to visualize DM repartition within tubersat different storage days.These results suggested that HSI-NIRS can be used to determine dry matter in fresh tuber samples of yam with acceptable accuracy. Further research will have to determine if additional traits can be incorporated into this scheme.
Mots-clés libres : Hyperspectral imaging, Yam tuber, Dry matter, PLS regression
Agences de financement hors UE : Bill and Melinda Gates Foundation, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Centro Internacional de Agricultura Tropical, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, James Hutton Institute
Projets sur financement : (FRA) Breeding RTB Products for End User Preferences
Auteurs et affiliations
- Meghar Karima, CIRAD-PERSYST-UMR Qualisud (FRA)
Contributeurs et affiliations
- Davrieux Fabrice, CIRAD-PERSYST-UMR Qualisud (REU) - collaborateur
Source : Cirad-Agritrop (https://agritrop.cirad.fr/603475/)
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