Assessing Phytosanitary Application Efficiency of a Boom Sprayer Machine Using RGB Sensor in Grassy Fields

Khaoula Abrougui, Nour El Houda Boughattas, Meriem Belhaj, Maria Luisa Buchaillot, Joel Segarra, Stéphane Dorbolo, Roua Amami, Sayed Chehaibi, Neji Tarchoun and Shawn C. Kefauver
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Khaoula Abrougui: Higher Institute of Agricultural Sciences, University of Sousse, 4042 Chott Meriem, Tunisia
Nour El Houda Boughattas: Higher Institute of Agricultural Sciences, University of Sousse, 4042 Chott Meriem, Tunisia
Meriem Belhaj: Higher Institute of Agricultural Sciences, University of Sousse, 4042 Chott Meriem, Tunisia
Maria Luisa Buchaillot: Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, 08028 Barcelona, Spain
Joel Segarra: Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, 08028 Barcelona, Spain
Stéphane Dorbolo: CESAM—GRASP, Institute of Physics, University of Liege, Tilman, 4000 Liege, Belgium
Roua Amami: Higher Institute of Agricultural Sciences, University of Sousse, 4042 Chott Meriem, Tunisia
Sayed Chehaibi: Higher Institute of Agricultural Sciences, University of Sousse, 4042 Chott Meriem, Tunisia
Neji Tarchoun: Higher Institute of Agricultural Sciences, University of Sousse, 4042 Chott Meriem, Tunisia
Shawn C. Kefauver: Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, 08028 Barcelona, Spain

Sustainability, 2022, vol. 14, issue 6, 1-15

Abstract: The systematic use of plant protection products is now being called into question with the growing awareness of the risks they can represent for the environment and human health. The application of precision agriculture technologies helps to improve agricultural production but also to rationalize input costs and improve ecological footprints. Here we present a study on fungicide application efficiency and its impact on the grass quality of a golf course green using the free open-source image analysis software FIJI (Image J) to analyze ground RGB (high-resolution digital cameras) and multispectral aerial imagery in combination with experimental data of spray pressure and hydraulic slot nozzle size of a boom sprayer machine. The multivariate regression model best explained variance in the normalized green-red difference index (NGRDI) as a relevant indicator of healthy turfgrass fields from the aerial, ground, and machine data set.

Keywords: RGB sensor; imagery; precision agriculture; boom sprayer; pressure; nozzle size; application efficiency; vegetation indices; grass quality; environment risk (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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