Predictive Analysis and Wine-Grapes Disease Risk Assessment Based on Atmospheric Parameters and Precision Agriculture Platform

Ioana Marcu, Ana-Maria Drăgulinescu (), Cristina Oprea, George Suciu and Cristina Bălăceanu
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Ioana Marcu: Telecommunications Department, University Politehnica of Bucharest, 61071 Bucharest, Romania
Ana-Maria Drăgulinescu: Telecommunications Department, University Politehnica of Bucharest, 61071 Bucharest, Romania
Cristina Oprea: Telecommunications Department, University Politehnica of Bucharest, 61071 Bucharest, Romania
George Suciu: R&D Department, Beia Consult International, 41386 Bucharest, Romania
Cristina Bălăceanu: R&D Department, Beia Consult International, 41386 Bucharest, Romania

Sustainability, 2022, vol. 14, issue 18, 1-18

Abstract: In the precision viticulture domain, data recorded by monitoring devices are large-scale processed to improve solutions for grapes’ quality and global production and to offer various recommendations to achieve these goals. Soil-related parameters (soil moisture, structure, etc.) and atmospheric parameters (precipitation, cumulative amount of heat) may facilitate crop diseases occurrence; thus, following predictive analysis, their estimation in vineyards can offer an early-stage warning for farmers and, therefore, suggestions for their prevention and treatment are of particular importance. Using remote sensing devices (e.g., satellites, unmanned vehicles) and proximal sensing methods (e.g., wireless sensor networks (WSNs)), we developed an efficient precision agriculture telemetry platform to provide reliable assessments of atmospheric phenomena periodicity and crop diseases estimation in a vineyard near Bucharest, Romania. The novelty of the materials and methods of this work relies on providing comprehensive preliminary references about monitored parameters to enable efficient, sustainable agriculture. Comparative analyses for two consecutive years illustrate an excellent correlation between cumulative and daily heat, precipitation quantity, and daily evapotranspiration (ET). In addition, the platform proved viable for wine-grapes disease estimation (powdery mildew, grape bunch rot, and grape downy mildew) and treatment recommendations based on the elaborated phenological calendar. Our results, together with continuous monitoring for the upcoming years, may be used as a reference to perform productive, sustainable smart agriculture in terms of yield and crop quality in Romania. In the Conclusion section, we show that farmers and personnel from cooperatives can use this information to make assessments based on the correlation of the available data to avoid critical damage to the wine-grape.

Keywords: IoT-WSN; precision sustainable agriculture; parameter prediction; disease estimation (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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