Javier
Tardáguila Laso
CATEDRÁTICO DE UNIVERSIDAD
![Foto de Javier](/img/uploaded/8D51BFA55A0E19355B4BC8394C595766.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 (72)
2023
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Early yield prediction in different grapevine varieties using computer vision and machine learning
Precision Agriculture, Vol. 24, Núm. 2, pp. 407-435
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Inteligencia artificial y visión por ordenador para evaluar los componentes del rendimiento de la vid en viñedos comerciales
BIO Web of Conferences: 44th World Congress of Vine and Wine
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NIR attribute selection for the development of vineyard water status predictive models
Biosystems Engineering, Vol. 229, pp. 167-178
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Using artificial intelligence (AI) for grapevine disease detection based on images
BIO Web of Conferences: 44th World Congress of Vine and Wine
2022
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Deep learning and computer vision for assessing the number of actual berries in commercial vineyards
Biosystems Engineering, Vol. 218, pp. 175-188
2021
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Assessing and mapping vineyard water status using a ground mobile thermal imaging platform
Irrigation Science, Vol. 39, Núm. 4, pp. 457-468
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Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions
Computers and Electronics in Agriculture, Vol. 182
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Smart applications and digital technologies in viticulture: A review
Smart Agricultural Technology, Vol. 1
2020
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Automated grapevine flower detection and quantification method based on computer vision and deep learning from on-the-go imaging using a mobile sensing platform under field conditions
Computers and Electronics in Agriculture, Vol. 178
2019
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On-the-go hyperspectral imaging for the in-field estimation of grape berry soluble solids and anthocyanin concentration
Australian Journal of Grape and Wine Research, Vol. 25, Núm. 1, pp. 127-133
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Vineyard pruning weight assessment by machine vision: Towards an on-the-go measurement system
Oeno One
2018
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Automated early yield prediction in vineyards from on-the-go image acquisition
Computers and Electronics in Agriculture, Vol. 144, pp. 26-36
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CAUSES OF SOIL MALFUNCTIONING IN DEGRADED AREAS OF EUROPEAN AND TURKISH VINEYARDS
EQA-INTERNATIONAL JOURNAL OF ENVIRONMENTAL QUALITY, Vol. 30, pp. 15-22
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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
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Effects of soil erosion on agro-ecosystem services and soil functions: A multidisciplinary study in nineteen organically farmed European and Turkish vineyards
Journal of Environmental Management, Vol. 223, pp. 614-624
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Geographical and cultivar features differentiate grape microbiota in Northern Italy and Spain vineyards
Frontiers in Microbiology, Vol. 9, Núm. MAY
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In field quantification and discrimination of different vineyard water regimes by on-the-go NIR spectroscopy
Biosystems Engineering, Vol. 165, pp. 47-58
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Mapping and managing vineyard homogeneous zones through proximal geoelectrical sensing
Archives of Agronomy and Soil Science, Vol. 64, Núm. 3, pp. 409-418
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On-the-go hyperspectral imaging under field conditions and machine learning for the classification of grapevine varieties
Frontiers in Plant Science, Vol. 9
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Restoring soil functionality in degraded areas within vineyards by organic treatments: The experimental layout of the RESOLVE Core-Organic+ Project
International Journal of Environmental Quality, pp. 30-38