Application of Hyperspectral Imaging and Deep Learning for Robust Prediction of Sugar and pH Levels in Wine Grape Berries
Remote sensing technology, such as hyperspectral imaging, in combination with machine learning algorithms, has emerged as a viable tool for rapid and nondestructive assessment of wine grape ripeness. However, the differences in terroir, together with the climatic variations and the variability exhib...
Main Authors: | Véronique Gomes, Ana Mendes-Ferreira, Pedro Melo-Pinto |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-05-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/10/3459 |
Similar Items
-
Determination of Sugar, pH, and Anthocyanin Contents in Port Wine Grape Berries through Hyperspectral Imaging: An Extensive Comparison of Linear and Non-Linear Predictive Methods
by: Véronique Gomes, et al.
Published: (2021-11-01) -
Using Support Vector Regression and Hyperspectral Imaging for the Prediction of Oenological Parameters on Different Vintages and Varieties of Wine Grape Berries
by: Rui Silva, et al.
Published: (2018-02-01) -
Dataset containing spectral data from hyperspectral imaging and sugar content measurements of grapes berries in various maturity stage
by: Maxime Ryckewaert, et al.
Published: (2023-02-01) -
Boosting the performance of SOTA convolution-based networks with dimensionality reduction: An application on hyperspectral images of wine grape berries
by: Rui Silva, et al.
Published: (2023-09-01) -
Microbiota of different wine grape berries
by: Miroslava Kačániová, et al.
Published: (2019-03-01)