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Hyperspectral calibration database on fresh cassava to predict optimal cooking time (OCT) and water absorption at 30'

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Title Hyperspectral calibration database on fresh cassava to predict optimal cooking time (OCT) and water absorption at 30'
 
Creator Meghar, Karima
Tran, Thierry
Ospina Portilla, Maria Alejandra
Davrieux, Fabrice
 
Subject food analysis
texture
 
Description This database contains 109 NIR average spectra of HSI images of fresh cassava root acquired in CIAT (Colombia), by using hyper spectral camera Specim FX17. Cassava roots were harvested from 07/03/2022 to 11/03/2022 in CIAT (Colombia) and analysed immediately after harverst. Twelve roots were used and each root is divided into six semicylinders . The semicylinders number 03,43,103 and 114 are used for HSI, WAB30%, OCT, and texture. Data was acquired using MEGHAR, K., DAVRIEUX, F., & ALAMU, E. (2020). SOP for Hyperspectral Imaging Analysis of Fresh RTB Crops. High-Throughput Phenotyping Protocols (HTPP), WP3. Montpellier, France: RTBfoods Project Report, 12 p. (2022-10-19)
 
Date 2023-02-06
2023-10-25T15:02:52Z
2023-10-25T15:02:52Z
 
Type Dataset
 
Identifier Meghar, K..; Tran, T.; Ospina Portilla, M.A.; Davrieux, F. (2023) Hyperspectral calibration database on fresh cassava to predict optimal cooking time (OCT) and water absorption at 30'. https://doi.org/10.18167/DVN1/VHJ0NX
https://hdl.handle.net/10568/132447
https://doi.org/10.18167/DVN1/VHJ0NX
 
Language en
 
Rights CC-BY-4.0
Limited Access