A Smart Crop Water Stress Index-Based IoT Solution for Precision Irrigation of Wine Grape

Author:

Fuentes-Peñailillo Fernando1ORCID,Ortega-Farías Samuel2ORCID,Acevedo-Opazo Cesar2,Rivera Marco34ORCID,Araya-Alman Miguel5

Affiliation:

1. Instituto de Investigación Interdisciplinaria (I3), Vicerrectoría Académica (VRA), Universidad de Talca, Talca 3460000, Chile

2. Research and Extension Center for Irrigation and Agroclimatology (CITRA) and Research Program on Adaptation of Agriculture to Climate Change (A2C2), Faculty of Agricultural Science, University of Talca, Talca 3460000, Chile

3. Power Electronics, Machines and Control (PEMC) Research Group, Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Nottingham, 15 Triumph Rd, Lenton, Nottingham NG7 2GT, UK

4. Laboratorio de Conversión de Energías y Electrónica de Potencia (LCEEP), Faculty of Engineering, Universidad de Talca, Merced 437, Curicó 3341717, Chile

5. Departamento de Ciencias Agrarias, Campus “San Isidro”, Universidad Católica del Maule, km 6 Camino Los Niches, Curicó 3340000, Chile

Abstract

The Scholander-type pressure chamber to measure midday stem water potential (MSWP) has been widely used to schedule irrigation in commercial vineyards. However, the limited number of sites that can be evaluated using the pressure chamber makes it difficult to evaluate the spatial variability of vineyard water status. As an alternative, several authors have suggested using the crop water stress index (CWSI) based on low-cost thermal infrared (TIR) sensors to estimate the MSWP. Therefore, this study aimed to develop a low-cost wireless infrared sensor network (WISN) to monitor the spatial variability of MSWPs in a drip-irrigated Cabernet Sauvignon vineyard under two levels of water stress. For this study, the MLX90614 sensor was used to measure canopy temperature (Tc), and thus compute the CWSI. The results indicated that good performance of the MLX90614 infrared thermometers was observed under laboratory and vineyard conditions with root mean square error (RMSE) and mean absolute error (MAE) values being less than 1.0 °C. Finally, a good nonlinear correlation between the MSWP and CWSI (R2 = 0.72) was observed, allowing the development of intra-vineyard spatial variability maps of MSWP using the low-cost wireless infrared sensor network.

Funder

National Agency for Research and Development (ANID)/Scholarship Program/Doctorado Nacional

Nodo CTCI

ANID/International, and regional cooperation and exchange projects of the National, ANID/PCI

ANID/FONDECYT

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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