Articles
Study of the suitability of a robotic platform to detect water stress in vineyards using proximal sensing technologies
Article number
1409_46
Pages
361 – 368
Language
English
Abstract
The onset of climate change has exacerbated the problem of water scarcity in the agricultural sector.
It has thus become imperative that irrigation protocols and schedules are based on water stress indicators rather than set scheduling methods.
Traditional water stress indicators used in vineyards and other crops are often time-consuming and labour intensive.
Important advances have been made in the detection of water stress, especially with the use of thermography, however, this technology presents some limitations for practical use.
Current advances in precision viticulture and digital analysis, show that robotic platforms offer a real alternative for carrying non-invasive proximal sensors in order to deliver field maps that help growers in decision making.
The use of robotic platforms is still in the research domain and several aspects need to be analysed and improved.
The main objective of this research was to study the suitability of a robotic platform to detect water stress in an experimental vineyard using proximal sensing technologies particular infrared thermometry.
A field experiment was set up at the Welgevallen experimental farm, Stellenbosch, South Africa during the growing season 2021-2022. The vineyard consists of three cultivars and two rootstock combinations namely ‘Cabernet Sauvignon’, ‘Pinotage’, and ‘Shiraz’ grafted on 110-Richter and US-87 rootstocks.
These combinations were managed with different irrigation levels.
In this experiment a robotic rover was used to navigate through the experimental vineyard.
The robotic platform contains a sensor suite that records various water stress indicators.
One of these sensors is the infrared thermometer located at 2 canopy levels.
The results show that the differential between the canopy and ambient temperature (Tc-Ta) presents a positive corelation with reference measurements (stem water potential and stomatal conductance), therefore, this method could be used for mapping water stress.
However, in order to improve the accuracy, technical pitfalls and potential improvements are discussed in the context of the results obtained in this exploratory analysis.
It has thus become imperative that irrigation protocols and schedules are based on water stress indicators rather than set scheduling methods.
Traditional water stress indicators used in vineyards and other crops are often time-consuming and labour intensive.
Important advances have been made in the detection of water stress, especially with the use of thermography, however, this technology presents some limitations for practical use.
Current advances in precision viticulture and digital analysis, show that robotic platforms offer a real alternative for carrying non-invasive proximal sensors in order to deliver field maps that help growers in decision making.
The use of robotic platforms is still in the research domain and several aspects need to be analysed and improved.
The main objective of this research was to study the suitability of a robotic platform to detect water stress in an experimental vineyard using proximal sensing technologies particular infrared thermometry.
A field experiment was set up at the Welgevallen experimental farm, Stellenbosch, South Africa during the growing season 2021-2022. The vineyard consists of three cultivars and two rootstock combinations namely ‘Cabernet Sauvignon’, ‘Pinotage’, and ‘Shiraz’ grafted on 110-Richter and US-87 rootstocks.
These combinations were managed with different irrigation levels.
In this experiment a robotic rover was used to navigate through the experimental vineyard.
The robotic platform contains a sensor suite that records various water stress indicators.
One of these sensors is the infrared thermometer located at 2 canopy levels.
The results show that the differential between the canopy and ambient temperature (Tc-Ta) presents a positive corelation with reference measurements (stem water potential and stomatal conductance), therefore, this method could be used for mapping water stress.
However, in order to improve the accuracy, technical pitfalls and potential improvements are discussed in the context of the results obtained in this exploratory analysis.
Authors
T. Chalmers, C.J. Jurgens, A. Van der Merwe, M.A. Vivier, C. Poblete-Echeverría
Keywords
proximal sensing, robotic platform, water stress, infrared sensor, climate change
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