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

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 (R²ₚ) 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.

Plant phenotyping relevance

ブドウ樹の水分状態という植物生理形質を、移動式近接NIR分光で定量・識別する手法を開発・検証しており、手法が研究の中心である。

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