A thesis of the UR combines artificial intelligence and sensors in digital agriculture.

It combines artificial intelligence and non-invasive sensory technologies for the estimation of important agronomic, physiological, and quantitative characteristics in agriculture and digital viticulture. With this thesis, Salvador Gutiérrez Salcedo has obtained the degree of doctor by the UR.

A thesis of the UR combines artificial intelligence and sensors in digital agriculture.
A thesis of the UR combines artificial intelligence and sensors in digital agriculture.



Developed in the Department of Agriculture and Food - within the framework of the Enology, Viticulture and Sustainability program - this thesis has been directed by Javier Tardáguila Laso and María Paz Diago Santamaría, and qualified with outstanding 'cum laude' by unanimity and international mention to the title.

In agriculture and viticulture, a reduction of costs and environmental impact is sought through the making of better decisions. The new advances in non-invasive sensor technology and artificial intelligence allow the acquisition of large amounts of data and its transformation into information to be useful in the decision-making process.

The main objective of this doctoral thesis - one of the first in Spain to address this issue - was to achieve the combination of artificial intelligence and non-invasive sensory technologies for the estimation of important agronomic, physiological and quantitative characteristics in agriculture and digital viticulture.

In this sense, Salvador Gutiérrez developed and published different innovative methodologies. The first was the combination of artificial intelligence and portable spectroscopy algorithms for the monitoring of the vine, opening new ways in digital viticulture for the rapid study of the vine under field conditions.

The new technique developed in constant is beneficial in the wine industry to measure the water status of a vineyard and generate maps of spatial variability.

The last development of the thesis was the use of hyperspectral vision in continuous field conditions and modeled with artificial intelligence techniques. The works on this subject are pioneers in the field of hyperspectral view in agriculture.

Among the applications presented, a system of evaluation of the composition of fruits at a distance and continuously, something that did not exist until now stands out. The results suggest that hyperspectral vision can be used to estimate different aspects of the vineyard and other fruit trees, becoming a powerful and accurate tool for decision making.

The results of the research work carried out in this doctoral thesis, published in six scientific articles, show that artificial intelligence techniques can take advantage of vegetative data captured through non-invasive sensor technology for the development of new solutions and tools of decision support in the agricultural industry.

During his doctoral research, Salvador Gutiérrez Salcedo enjoyed an FPI / CAR contract funded by the University of La Rioja and the Government of La Rioja and conducted a research stay at an internationally renowned robotics research center at the University of Rioja. Sydney (Australia), for which he received the mention of the international doctor.