Estimation of grapevine predawn leaf water potential based on hyperspectral reflectance data in Douro wine region

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Tosin, R (Author) FCUP; Pocas, I (Author) Other; Goncalves, I (Author) Other; Mario Cunha (Author) FCUP

Journal

The Journal is awaiting validation by the Administrative Services.

Title: VITIS

Vol. 59

Pages: 9-18

ISSN: 0042-7500

Indexing

ISI Web of Knowledge - 9 Citations

Scopus - 10 Citations

Other information

Authenticus ID: P-00R-SM5

DOI: 10.5073/vitis.2020.59.9-18

Abstract (EN): Hyperspectral data collected through a handheld spectroradiometer (400-1010 nm) were tested for assessing the grapevine predawn leaf water potential (psi(pd)) measured by a Scholander chamber in two test sites of Douro wine region. The study was implemented in 2017, being a year with very hot and dry summer, conditions prone to severe water shortage. Three grapevine cultivars, 'Touriga Nacional', 'Touriga Franca' and 'Tinta Barroca' were sampled both in rainfed and irrigated vineyards, with a total of 325 plants assessed in four post-flowering dates. A large set of vegetation indices computed with the hyperspectral data and optimized for the psi(pd) values, as well as structural variables, were used as predictors in the model. From a total of 631 possible predictors, four variables were selected based on a stepwise forward procedure and the Wald statistics: irrigation treatment, test site, Anthocyanin Reflectance Index Optimized (ARI(opt_656,647)) and Normalized Ratio Index (NRI711,700). An ordinal logistic regression model was calibrated using 70 % of the dataset randomly selected and the 30 of the remaining observations where used in model validation. The overall model accuracy obtained with the validation dataset was 73.2 %, with the class of psi(pd) corresponding to the high-water deficit presenting a positive prediction value of 79.3 %. The accuracy and operability of this predictive model indicates good perspectives for its use in the monitoring of grapevine water status, and to support the irrigation tasks.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10