IoT sensors and dendrometer monitoring reveal differential irrigation requirements during arabica coffee phenological phases
DOI:
https://doi.org/10.17268/Palabras clave:
soil moisture sensors, dendrometer, drip, coffee crop, irrigationResumen
A remote irrigation management system using Internet of Things (IoT) sensors was evaluated in arabica coffee (Coffea arabica L.) under drip irrigation in the Cerrado Mineiro region of Brazil. The study compared the GBI (Growth-Based Irrigation™) system, which integrates dendrometer and soil moisture sensors readings with meteorological data, to conventional climatic-based management. The experiment was conducted from August 2017 to May 2018 in a randomized complete block design with two treatments and twelve replicates. Evaluations were made during three phenological phases (flowering, small green, and graining) between September 2017 and May 2018. Biometric parameters, leaf water potential, grain yield, and maturation were assessed. No statistically significant differences were found between treatments in any evaluated variable (Tukey, p≤0.05). However, dendrometer readings showed greater and more continuous stem diameter expansion in the GBI system, and the sensor-based approach substantially reduced field labor requirements while enabling real-time automated irrigation control.
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Derechos de autor 2026 Jefferson Vasconcelos Oliveira De Lima, André Luís Teixeira Fernandes, Eusímio Felisbino Fraga Júnior, Pedro Otávio Honorato Da Cruz, João Pedro Honorato Da Cruz, Márcio José De Santana
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
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