RTBfoods project: Breeding RTB products for end user preferences

The RTBfoods project is implemented with five partner countries: Benin, Cameroon, Ivory Coast, Nigeria and Uganda. It analyzes three common uses of each target root, tuber and banana crops (cassava, yam, sweet potato, plantain and tropical potato). The analysis uses a reverse engineering approach, working backwards from consumers to breeders.

Projet RTBfoods : Améliorer la sélection de variétés de racines, tubercules et bananes à cuire (RTB) pour en faciliter l'adoption par les utilisateurs

Le projet RTBfoods prend place dans cinq pays partenaires : le Bénin, le Cameroun, la Côte d’Ivoire, le Nigeria et l’Ouganda. Il vise à analyser des préparations culinaires différentes (bouilli, pilé, frit,...) et les préférences variétales associées, ainsi que l’aptitude à la transformation (facilité de stockage, d’épluchage, de fermentation, défibrage ou granulation des productions de racines, tubercules et bananes (RTB) (manioc, igname, patate douce, banane à cuire, pomme de terre). L’approche employée tient de l’ingénierie réverse : il s’agit de partir du consommateur pour remonter à l’améliorateur.
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41 to 50 of 220 Results
28 juil. 2023
Bolanle, Otegbayo; Oluyinka, Oroniran; Fawehinmi, Olabisi; Abiola, Tanimola; Tolulope, Alamu, 2023, "Gendered pounded yam product profile in Nigeria (2)", https://doi.org/10.18167/DVN1/FKFPOS, CIRAD Dataverse, V3, UNF:6:npFHzMJv5BT1mvniQVTF4w== [fileUNF]
The WP1 Gendered Food Product Profile for pounded yam in Nigeria reflects the final step of an interdisciplinary five-step methodology developed to identify demand for quality characteristics among diverse user groups along the food chain (Forsythe et al., 2022). This methodology...
28 juil. 2023
Madu, Tessy; Onyemuwa, Nnaemeka; Ofoeze, Mariam; Okoye, Benjamin, 2022, "Gendered pounded yam product profile in Nigeria (1)", https://doi.org/10.18167/DVN1/F2GBV3, CIRAD Dataverse, V3, UNF:6:m/5k+/p1oqG4eNzaqWLEcg== [fileUNF]
The WP1 Gendered Food Product Profile for pounded yam in Nigeria reflects the final step of an interdisciplinary five-step methodology developed to identify demand for quality characteristics among diverse user groups along the food chain (Forsythe et al., 2022). This methodology...
28 juil. 2023
Tran, Thierry; Meghar, Karima; Belalcazar, John, 2023, "MIRS Database on cassava cell wall to predict cooking time at CIAT, Colombia", https://doi.org/10.18167/DVN1/WUOJSL, CIRAD Dataverse, V1, UNF:6:fDGG0+OlQwWFmSoVgsi6OQ== [fileUNF]
This database contains 111 MIR (mid-infrared) spectra of cassava flours acquired at 23/10/2020 in CIRAD (Montpellier), by using Nicolet IS50R Research FTIR spectrometer. The cassava roots used to produce the flour samples are harvested at CIAT (Colombia) from 2 fields : "parental...
28 juil. 2023
Alamu, Emmanuel; Adesokan, Michael, 2023, "NIRS Database on Dried Grounded Cassava Flour for Moisture, Ash, Fat, Protein, Sugar, Starch & Amylose Calibrations at IITA, Nigeria", https://doi.org/10.18167/DVN1/SH5FG7, CIRAD Dataverse, V1, UNF:6:a60OMzA9w8goRSr3Nkgy0g== [fileUNF]
The dataset contains spectral data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) for prediction of Moisture, Ash, Fat, Protein, Sugar, Starch & Amylose of dried ground cassava
28 juil. 2023
Alamu, Emmanuel; Adesokan, Michael, 2023, "NIRS Database on Fresh Grounded Cassava for Starch Calibration at IITA, Nigeria", https://doi.org/10.18167/DVN1/VJ0NTP, CIRAD Dataverse, V1, UNF:6:9adtVfNz9cajiKl4uR8w2g== [fileUNF]
The dataset contains spectral data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) for prediction of starch of fresh ground cassava
28 juil. 2023
Alamu, Emmanuel; Adesokan, Michael, 2023, "NIRS Database on Fresh Grounded Cassava for Dry Matter Calibration at IITA, Nigeria", https://doi.org/10.18167/DVN1/H83HHX, CIRAD Dataverse, V1, UNF:6:5JrETwrb9t6GJWS9OL15jQ== [fileUNF]
The dataset contains spectral data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) for prediction of dry matter of fresh ground cassava
28 juil. 2023
Alamu, Emmanuel; Adesokan, Michael, 2023, "NIRS Database on milled Gari for Water Absorption Capacity, Bulk Density, Dispersibility, Titratable Acidity Calibrations at IITA, Nigeria", https://doi.org/10.18167/DVN1/RP9EOS, CIRAD Dataverse, V1, UNF:6:vfPuJMGzuX4Ruwj9H4i/KA== [fileUNF]
The dataset contains spectra data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) used for prediction of Water Absorption Capacity, Bulk Density, Dispersibility, and Titratable Acidity of milled gari.
28 juil. 2023
Alamu, Emmanuel, 2023, "NIRS Database on cassava milled Gari at IITA, Nigeria", https://doi.org/10.18167/DVN1/0ZRLOY, CIRAD Dataverse, V1, UNF:6:aphAIvA+E2dWVmDnwYkvQg== [fileUNF]
This database consists of spectra data collected on milled gari using the benchtop FOSS Near-Infrared Spectrometer (NIRS) with serial number 3013-0857. A total of 64 spectra data were collected in a duplicate scan of 32 gari samples. The Spectra data were collected in IITA, Niger...
28 juil. 2023
Alamu, Emmanuel; Adesokan, Michael, 2023, "NIRS Database on Fresh Intact Cassava for Dry Matter Calibration at IITA, Nigeria", https://doi.org/10.18167/DVN1/6LEFW6, CIRAD Dataverse, V1, UNF:6:sDoYS5suWT6M9WQPzLgzEw== [fileUNF]
The dataset contains spectral data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) for prediction of dry matter of fresh intact cassava roots
28 juil. 2023
Alamu, Emmanuel; Adesokan, Michael, 2023, "NIRS Database on cassava un-milled Gari at IITA, Nigeria", https://doi.org/10.18167/DVN1/FLOLCC, CIRAD Dataverse, V1, UNF:6:4/DsIdhkfPD44qi3Q19fMg== [fileUNF]
This database consists of spectra data collected on un-milled gari using the benchtop FOSS Near Infrared Spectrometer (NIRS) with serial number 3013-0857. A total of 36 spectra data were collected by the duplicate scan of 16 gari samples. The Spectra data were collected in IITA,...
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