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

  1. Fernández-Novales, J. 1
  2. Tardaguila, J. 12
  3. Gutiérrez, S. 1
  4. Marañón, M. 1
  5. Diago, M.P. 1
  1. 1 Instituto de Ciencias de la Vid y del Vino
    info

    Instituto de Ciencias de la Vid y del Vino

    Logroño, España

    ROR https://ror.org/01rm2sw78

  2. 2 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Aldizkaria:
Biosystems Engineering

ISSN: 1537-5110

Argitalpen urtea: 2018

Alea: 165

Orrialdeak: 47-58

Mota: Artikulua

DOI: 10.1016/J.BIOSYSTEMSENG.2017.08.018 SCOPUS: 2-s2.0-85030318061 WoS: WOS:000424178100006 GOOGLE SCHOLAR

Beste argitalpen batzuk: Biosystems Engineering

Lotura duten proiektuak

Laburpena

Precise and rapid methods to assess plant water status are needed in agriculture. The goal of this work was to evaluate the capability of a new plant-based method based on proximal near-infrared (NIR) spectroscopy acquired on-the-go from a moving vehicle to quantify and discriminate different water regimes in a commercial vineyard. Proximal on-the-go NIR spectroscopy (1100–2100 nm) was acquired at solar noon on five days from veraison (onset of ripening) to harvest 2015 in a commercial Tempranillo vineyard. Spectral measurements were taken at ∼0.30 m from the canopy, on both canopy sides, from a vehicle moving at 5 km h−1. Measurements of midday stem water potential (Ψs) and leaf stomatal conductance (gs) were simultaneously acquired to be used as reference indicators of plant water status. Partial least squares (PLS) was used to build calibration, cross validation and predictive models for Ψs and gs. The determination coefficients of prediction (R2 p) were above 0.86 for Ψs and above 0.66 for gs while the root mean square errors of prediction (RMSEP) were less than 0.18 MPa and 93.7 mmol [H2O] m−2 s−1, respectively. PLS-Discriminant Analysis (PLS-DA) was applied to classify the data into three different water regimes, according to Ψs or gs. The average correctly classified percentage was greater than 72% for Ψs and gs. This discriminant capability, together with the large number of measurements that the on-the-go NIR spectroscopy can provide, enables the quantification and mapping of the variability of a vineyard water status and may help to define precise irrigation strategies in viticulture. © 2017 IAgrE