Instituto de Ciencias de la Vid y del Vino -ko ikertzaileekin lankidetzan egindako argitalpenak (67)

2023

  1. Application of near-infrared spectroscopy for the estimation of volatile compounds in Tempranillo Blanco grape berries during ripening

    Journal of the Science of Food and Agriculture, Vol. 103, Núm. 13, pp. 6317-6329

  2. Early yield prediction in different grapevine varieties using computer vision and machine learning

    Precision Agriculture, Vol. 24, Núm. 2, pp. 407-435

  3. Editorial: Resilience of grapevine to climate change: from plant physiology to adaptation strategies, volume II

    Frontiers in Plant Science

  4. NIR attribute selection for the development of vineyard water status predictive models

    Biosystems Engineering, Vol. 229, pp. 167-178

2022

  1. Deep learning and computer vision for assessing the number of actual berries in commercial vineyards

    Biosystems Engineering, Vol. 218, pp. 175-188

  2. Editorial: Resilience of grapevine to climate change: From plant physiology to adaptation strategies

    Frontiers in Plant Science

2021

  1. Assessing and mapping vineyard water status using a ground mobile thermal imaging platform

    Irrigation Science, Vol. 39, Núm. 4, pp. 457-468

  2. Smart applications and digital technologies in viticulture: A review

    Smart Agricultural Technology, Vol. 1

2020

  1. 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

  1. 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

  2. Vineyard pruning weight assessment by machine vision: Towards an on-the-go measurement system

    Oeno One

2018

  1. Automated early yield prediction in vineyards from on-the-go image acquisition

    Computers and Electronics in Agriculture, Vol. 144, pp. 26-36

  2. 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

  3. 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

  4. In field quantification and discrimination of different vineyard water regimes by on-the-go NIR spectroscopy

    Biosystems Engineering, Vol. 165, pp. 47-58

  5. Mapping and managing vineyard homogeneous zones through proximal geoelectrical sensing

    Archives of Agronomy and Soil Science, Vol. 64, Núm. 3, pp. 409-418

  6. On-the-go hyperspectral imaging under field conditions and machine learning for the classification of grapevine varieties

    Frontiers in Plant Science, Vol. 9

  7. Towards the definition of optimal grape harvest time in Grenache grapevines: Nitrogenous maturity

    Scientia Horticulturae, Vol. 239, pp. 9-16

  8. Use of non-invasive RGB imaging to assess the canopy status in organic viticulture

    EQA - International Journal of Environmental Quality, Vol. 30, pp. 23-30

  9. Vineyard water status assessment using on-the-go thermal imaging and machine learning

    PLoS ONE, Vol. 13, Núm. 2