In field quantification and discrimination of different vineyard water regimes by on-the-go NIR spectroscopy. (January 2018)

• Record Type: Journal Article
• Authors: Fernández-Novales, Juan; Tardaguila, Javier; Gutiérrez, Salvador; Marañón, Miguel; Diago, Maria P.
• Is Part Of: Biosystems engineering. Volume 165(2018)
• Page Start: 47
• Page End: 58
• Publication Date: 2018-01
• Subjects: grapevine -- plant water status -- proximal sensing -- leaf stomatal conductance -- stem water potential -- irrigation; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2017.08.018
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : 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 (R 2 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 [H2 O] 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. Graphical abstract: Highlights: Proximal on-the-go NIRS could be a powerful tool to assess the plant water status. Robust and reliable prediction models for Ψs and gs have been developed. Models from east and west sides exhibited differential performances in Ψs and gs . The discrimination models showed a clear separation between the extreme water regimes. Mapping of vineyard water status variation can be done and used in precision irrigation.