Nowadays, a more robust and cheaper sensors are still needed, especially plant sensors, which involve several practical difficulties but which information is key regarding the health and the status of the plant crops during the precise irrigation process .
Contactless ultrasonic sensors have been proven as a powerful tool to estimate non-destructively and non-invasively the water status of plant leaves in more than 50 species [2,3]. More recently, it was shown that the combination of these contactless ultrasonic sensors with deep learning algorithms constitute a robust tool for the instantaneous, accurate and non-destructive determination of Relative Water Content in plant leaves .
In this study, we would like to present our latest experimental data comparing in field measurements over Clemenules x carrizo leaves with the traditional pressure chamber and the contactless ultrasonic sensors. The plants are in three different watering states: fully hydrated - control, 50% below the control irrigation and 75% below the control irrigation.
This project was presented during the Scientific Seminar organised by Robagri in the 2019 FIRA.
Find out more in the video below:
Lola Fariñas, Departamento de Tecnología de Alimentos, Universitat Politècnica de València (UPV), España.
Amparo Martínez, Eduardo Badal, Luis Bonet: Servicio de Tecnología de Riego, Instituto Valenciano de Investigaciones Agrarias (STR-IVIA), Moncada, Valencia, España
Juan Manzano,Departamento de Ingeniería Hidráulica y Medio Ambiente, Universitat Politècnica de València (UPV), Valencia, España
1. Vera J, Abrisqueta I, Conejero W, Ruiz-Sánchez MC. Precise sustainable irrigation: a review of soil-plant- atmosphere monitoring. Acta Hortic [Internet]. International Society for Horticultural Science; 2017 [cited 2019 Oct 22];1150:195–202. Available from: https://www.actahort.org/books/1150/1150_28.htm
2. Gómez Álvarez-Arenas TE, Gil-Pelegrin E, Ealo Cuello J, Fariñas MD, Sancho-Knapik D, Collazos Burbano D, et al. Ultrasonic Sensing of Plant Water Needs for Agriculture. Sensors [Internet]. 2016;16:1089. Available from: http://www.mdpi.com/1424-8220/16/7/1089
3. Fariñas MD, Sancho Knapik D, Peguero Pina JJ, Gil Pelegrin E, Álvarez-Arenas TEG. Monitoring Plant Response toEnvironmental Stimuli by Ultrasonic Sensing of the Leaves. Ultrasound Med Biol [Internet]. 2014 [cited 2014 Jul 30];c:1–12. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25023117
4. Fariñas MD, Jimenez-Carretero D, Sancho-Knapik D, Peguero-Pina JJ, Gil-Pelegrín E, Gómez Álvarez-Arenas T. Instantaneous and non-destructive relative water content estimation from deep learning applied to resonant ultrasonic spectra of plant leaves. Plant Methods [Internet]. BioMed Central; 2019;15:128. Available from: https://doi.org/10.1186/s13007-019-0511-z