Evidence map›Paper›PMID 38202887›Full record

ArticleSensors (Basel, Switzerland)2023

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

Fernando Fuentes-Peñailillo, Samuel Ortega-Farías, Cesar Acevedo-Opazo, Marco Rivera, Miguel Araya-Alman

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Fernando Fuentes-PeñaililloInstituto de Investigación Interdisciplinaria (I3), Vicerrectoría Académica (VRA), Universidad de Talca, Talca 3460000, Chile.ORCID 0000-0001-5658-7558
Samuel Ortega-FaríasResearch 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.ORCID 0000-0001-7850-5410
Cesar Acevedo-OpazoResearch 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.
Marco RiveraPower 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.ORCID 0000-0002-4353-2088
Miguel Araya-AlmanDepartamento de Ciencias Agrarias, Campus "San Isidro", Universidad Católica del Maule, km 6 Camino Los Niches, Curicó 3340000, Chile.

Funding

ANID/FONDECYT 1160997ANID/International, and regional cooperation and exchange projects of the National, ANID/PCI NSFC190013National Agency for Research and Development (ANID)/Scholarship Program/Doctorado Nacional 2018-21181790Nodo CTCI MCS-ANID NODO220006
6 · The paper itself

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 (R

Indexed as

crop water stress indexirrigationspatial variabilityvine water consumption

Identifiers

PMID38202887
PMCPMC10780677

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.