SALVADOR
GUTIERREZ SALCEDO
Investigador en el periodo 2019-2021
![Foto de SALVADOR](/img/uploaded/413B5E3C68BF083F846B74C63F17626E.jpg)
![Foto de Instituto de Ciencias de la Vid y del Vino](/img/noimage_org.png)
Instituto de Ciencias de la Vid y del Vino
Logroño, EspañaPublicaciones en colaboración con investigadores/as de Instituto de Ciencias de la Vid y del Vino (16)
2023
-
NIR attribute selection for the development of vineyard water status predictive models
Biosystems Engineering, Vol. 229, pp. 167-178
2021
-
Assessing and mapping vineyard water status using a ground mobile thermal imaging platform
Irrigation Science, Vol. 39, Núm. 4, pp. 457-468
-
Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions
Computers and Electronics in Agriculture, Vol. 182
-
Smart applications and digital technologies in viticulture: A review
Smart Agricultural Technology, Vol. 1
2019
-
Ground based hyperspectral imaging for extensive mango yield estimation
Computers and Electronics in Agriculture, Vol. 157, pp. 126-135
-
Spectral filter design based on in-field hyperspectral imaging and machine learning for mango ripeness estimation
Computers and Electronics in Agriculture, Vol. 164
2018
-
Development and validation of a new methodology to assess the vineyard water status by on-the-go near infrared spectroscopy
Frontiers in Plant Science, Vol. 9
-
In field quantification and discrimination of different vineyard water regimes by on-the-go NIR spectroscopy
Biosystems Engineering, Vol. 165, pp. 47-58
-
On-the-go hyperspectral imaging under field conditions and machine learning for the classification of grapevine varieties
Frontiers in Plant Science, Vol. 9
-
Vineyard water status assessment using on-the-go thermal imaging and machine learning
PLoS ONE, Vol. 13, Núm. 2
2017
-
In-field assessment of grapevine water status using a portable NIR spectrophotometer
Acta Horticulturae, Vol. 1150, pp. 167-172
-
Non-destructive assessment of grapevine water status in the field using a portable NIR spectrophotometer
Journal of the Science of Food and Agriculture, Vol. 97, Núm. 11, pp. 3772-3780
2016
2015
-
Grapevine flower estimation by applying artificial vision techniques on images with uncontrolled scene and multi-model analysis
Computers and Electronics in Agriculture, Vol. 119, pp. 92-104
-
Landmark-based music recognition system optimisation using genetic algorithms
Multimedia Tools and Applications, Vol. 75, Núm. 24, pp. 16905
-
Support vector machine and artificial neural network models for the classification of grapevine varieties using a portable NIR spectrophotometer
PLoS ONE, Vol. 10, Núm. 11