E-LIB Suche - Ergebnisse für: Davrieux, Fabrice

1

Machine learning methods in near infrared spectroscopy for ..:

Ssali Nantongo, Judith ; Serunkuma, Edwin ; Burgos, Gabriela...
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 318 (2024) - p. 124406 , 2024

Link: https://doi.org/10.1016/..

2

Near infrared spectroscopy models to predict sensory and te..:

Nantongo, Judith Ssali ; Serunkuma, Edwin ; Davrieux, Fabrice...
Journal of Near Infrared Spectroscopy. , 2024

Link: https://doi.org/10.1177/..

3

Application of near-infrared spectroscopy for fast germplas..:

Kassie, Fentanesh Chekole ; Chaix, Gilles ; Ngalle, Hermine Bille...
Oil Crop Science. 9 (2024) 2 - p. 132-141 , 2024

Link: https://doi.org/10.1016/..

4

Quantification of Dry Matter Content in Hass Avocado by Nea..:

Rodríguez, Pablo ; Villamizar, Jairo ; Londoño, Luis..
Plants. 12 (2023) 17 - p. 3135 , 2023

Link: https://doi.org/10.3390/..

5

Hyperspectral imaging for the determination of relevant coo..:

Meghar, Karima ; Tran, Thierry ; Delgado, Luis Fernando...
Journal of the Science of Food and Agriculture. 104 (2023) 8 - p. 4782-4792 , 2023

Link: https://doi.org/10.1002/..

6

Development and validation of near‐infrared spectroscopy pr..:

Nuwamanya, Ephraim ; Wembabazi, Enoch ; Kanaabi, Michael...
Journal of the Science of Food and Agriculture. 104 (2023) 8 - p. 4793-4800 , 2023

Link: https://doi.org/10.1002/..

7

Convolutional neural network allows amylose content predict..:

Houngbo, Mahugnon Ezékiel ; Desfontaines, Lucienne ; Diman, Jean‐Louis...
Journal of the Science of Food and Agriculture. 104 (2023) 8 - p. 4915-4921 , 2023

Link: https://doi.org/10.1002/..

8

NIRS analyses of sensory and biochemical traits in potato b..:

Nantongo, Judith S ; Serunkuma, Edwin ; Davrieux, Fabrice..
http://agritrop.cirad.fr/603872/. , 2023

Link: http://agritrop.cirad.fr..

9

NIRS calibration database on fresh cassava puree to predict..:

Tran, Thierry ; Davrieux, Fabrice ; Belalcazar Martinez, John Eiver
Tran, T.; Davrieux, F.; Belalcazar Martinez, J.E. (2023) NIRS calibration database on fresh cassava puree to predict cooking time. https://doi.org/10.18167/DVN1/XVJVB8. , 2023

Link: https://hdl.handle.net/1..

10

Hyperspectral calibration database on fresh cassava to pred..:

Meghar, Karima ; Tran, Thierry ; Ospina Portilla, Maria Alejandra.
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. , 2023

Link: https://hdl.handle.net/1..

11

Hyperspectral imaging for the determination of relevant coo..:

Meghar, Karima ; Tran, Thierry ; Delgado, Luis Fernando...
Meghar, K.; Tran, T.; Delgado, L.F.; Ospina, M.A.; Moreno, J.L.; Luna, J.; Londoño, L.; Dufour, D.; Davrieux, F. (2023) Hyperspectral imaging for the determination of relevant cooking quality traits of boiled cassava. Journal of the Science of Food and Agriculture, Online first paper (22 April 2023). ISSN: 0022-5142. , 2023

Link: https://hdl.handle.net/1..

12

Development and validation of near‐infrared spectroscopy pr..:

Nuwamanya, Ephraim ; Wembabazi, Enoch ; Kanaabi, Michael...
http://agritrop.cirad.fr/607435/. , 2023

Link: http://agritrop.cirad.fr..

13

Convolutional neural network allows amylose content predict..:

Houngbo, Mahugnon, Ezékiel ; Desfontaines, Lucienne ; Diman, Jean‐louis...
info:eu-repo/semantics/altIdentifier/doi/10.1002/jsfa.12825. , 2023

Link: https://hal.inrae.fr/hal..

14

Convolutional neural network allows amylose content predict..:

Houngbo, Mahugnon, Ezékiel ; Desfontaines, Lucienne ; Diman, Jean‐louis...
info:eu-repo/semantics/altIdentifier/doi/10.1002/jsfa.12825. , 2023

Link: https://hal.inrae.fr/hal..

15

Quantification of Dry Matter Content in Hass Avocado by Nea..:

Pablo Rodríguez ; Jairo Villamizar ; Luis Londoño..
Phytochemistry. , 2023

Link: https://doi.org/10.3390/..