Instituto Internacional de Agricultura Tropical (IITA)
URI permanente para esta colecciónhttp://hdl.handle.net/123456789/114560
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8 resultados
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Ítem Food quality profile of pounded yam and implications for yam breeding(Wiley) Otegbayo, B.; Oluyinka, O.; Tanimola, A.; Fawehinmi, B.; Alamu, A.; Bolaji, T.; Madu, Tessy; Okoye, B.; Chijioke, Alamu Ugo; Ofoeze, M.; Alamu, E.O.; Adesokan, M.; Ayetigbo, O.; Bouniol, A.; DJibril-Mousa, I.; Adinsi, L.; Akissoe, N.H.; Cornet, D.; Agre, A.P.; Amele, A.; Obidiegwu, J.; Maziya-Dixon, B.Ítem Rapid analysis of starch, sugar, and amylose in fresh yam tubers and boiled yam texture using near-infrared hyperspectral imaging and chemometrics(Elsevier) Adesokan, M.; Alamu, E.O.; Otegbayo, B.; Asfaw, A.; Afolabi, M.O.; Fawole, S.; Meghar, K.; Dufour, D.; Ayetigbo, O.; Davrieux, F.; Maziya-Dixon, B.Ítem Elite Genotypes of Water Yam (Dioscorea alata) Yield Food Product Quality Comparable to White Yam (Dioscorea rotundata)(MDPI) Adesokan, M.; Alamu, E.O.; Fawole, S.; Asfaw, A.; Maziya-Dixon, B.Ítem Genome-wide dissection of the genetic factors underlying food quality in boiled and pounded white Guinea yam(Wiley) Asfaw, A.; Agre, A.P.; Matsumoto, R.; Olatunji, A.A.; Edemodu, A.; Olusola, T.; Odom-Kolombia, O.L.; Adesokan, M.; Alamu, E.O.; Adebola, P.O.; Asiedu, R.; Maziya-Dixon, B.Ítem Convolutional neural network allows amylose content prediction in yam (Dioscorea alata L.) flour using near infrared spectroscopy(Wiley) Houngbo, M.E.; Desfontaines, L.; Diman, J.L.; Arnau, G.; Mestres, C.; Davrieux, F.; Rouan, L.; Beurier, G.; Marie-Magdeleine, C.; Meghar, K.; Alamu, E.O.; Otegbayo, B.; Cornet, D.Ítem Breeding and end‑use quality traits of roots, tubers, and bananas (RTB) crops for authentic African cuisines—a review(Springer) Alamu, E.O.; Adesokan, M.; Awoyale, W.; Maziya-Dixon, B.Ítem Evaluating the dry matter content of raw yams using hyperspectral imaging spectroscopy and machine learning(Elsevier) Adesokan, M.; Otegbayo, B.; Alamu, E.O.; Olutoyin, M.A.; Maziya-Dixon, B.Ítem A review of the use of Near-Infrared Hyperspectral Imaging (NIR-HSI) techniques for the non-destructive quality assessment of root and tuber crops(MDPI) Adesokan, M.; Alamu, E.O.; Otegbayo, B.; Maziya-Dixon, B.