Near infrared spectroscopy models to predict sensory and texture traits of sweetpotato roots

Nantongo Judith Ssali, Serunkuma Edwin, Davrieux Fabrice, Nakitto Mariam, Burgos Gabriela, Thomas Zum Felde, Eduardo Porras, Carey Ted, Swankaert Jolien, Mwanga Robert O. M., Alamu Emmanuel Oladeji, Ssali Reuben. 2024. Near infrared spectroscopy models to predict sensory and texture traits of sweetpotato roots. Journal of Near Infrared Spectroscopy, 32 (3) : 93-104.

Résumé : High-throughput phenotyping technologies successfully employed in plant breeding and precision agriculture could facilitate the screening process for developing consumer-preferred traits. The current study evaluated the potential of near infrared (NIR) spectroscopy to predict visual, aromatic, flavor, taste and texture traits of sweetpotatoes. The focus was to develop predicting models that would be cost-effective, efficient and high throughput. The roots of 207 sweetpotato genotypes from six agroecological zones of Uganda were collected from breeding trials. The spectra were collected in the wavelengths of 400 – 2500 nm at 2 nm intervals. Using the plsR package, the calibrations were carried out using external validation models. The best calibration equation between the sensory and texture reference values (10-point scales) and spectral data was identified based on the highest coefficient of determination (R2) and smallest RMSE in calibration and validation. Of the visual traits, orange color intensity was well calibrated using NIR spectroscopy (r2val = 0.92, SEP = 0.92), and the model is sufficient for field application. Pumpkin aroma (r2val = 0.67, SEP = 0.33) was the highest predicted among the aromas. The pumpkin flavour model exhibited the highest coefficient of determination in the calibration (r2val = 0.52, SEP = 0.45) for the traits considered under flavor and taste. Different models for textural traits exhibited moderate calibration coefficients: mealiness (chalky/floury) by hand (r2val = 0.75; SEP = 1.31), crumbliness (r2val = 0.73, SEP = 1.21), moisture in mass (r2val = 0.73, SEP = 1.26), fracturability (r2val = 0.60, SEP = 1.52), hardness by hand (r2val = 0.61, SEP = 1.27) and dry matter (r2val = 0.70, SEP = 3.10). The range error ratio (RER) values were mostly >6.0. These models could be used for preliminary screening. The predictability of the traits varied among different modes of samples. Models could be improved with an increased range of reference values and/or exploiting the correlations between chemical compounds and sensory traits.

Mots-clés Agrovoc : spectroscopie infrarouge, amélioration des plantes, phénotype, spectroscopie, patate douce, flaveur, agroécologie, agriculture de précision, rhizosphère

Mots-clés géographiques Agrovoc : Ouganda

Mots-clés libres : High throughput, Breeding efficiency, Consumer preferences, Food Security, Sweetpotatoes

Agences de financement hors UE : Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Bill and Melinda Gates Foundation, International Potato Center, Sweet potato Genetic Advances and Innovative Seed Systems

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

Auteurs et affiliations

• Nantongo Judith Ssali, CIP (UGA)
• Serunkuma Edwin, CIP (UGA)
• Davrieux Fabrice, CIRAD-PERSYST-UMR Qualisud (REU)
• Nakitto Mariam, CIP (UGA)
• Burgos Gabriela, CIP (PER)
• Thomas Zum Felde, CIP (PER)
• Eduardo Porras, CIP (PER)
• Carey Ted
• Swankaert Jolien
• Mwanga Robert O. M., CIP (UGA)
• Alamu Emmanuel Oladeji, IITA (ZMB)
• Ssali Reuben, CIP (UGA) - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/612982/)

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