Dissertation/Thesis Abstract

Calibrating capacitance sensors to estimate water content, matric potential, and electrical conductivity in soilless substrates
by Arguedas Rodriguez, Felix Ruben, M.S., University of Maryland, College Park, 2009, 137; 1478116
Abstract (Summary)

The nursery and greenhouse industry requires precise methods to schedule irrigations, since current practices are subjective and contribute to water and nutrient runoff. Capacitance sensors were calibrated to precisely estimate substrate water content, matric potential, and pore water electrical conductivity (EC) in five soilless substrates. Regression coefficients (R2) ranged from 0.29–0.88 and 0.16–0.79 for water content in 5-cm and 20-cm column heights; matric potential R2 ranged from 0.10–0.98 and 0.79–0.98, respectively. Pore water EC calibrations were investigated, contrasting two sensor types and two prediction models. Results were applied to an empirical greenhouse dataset. Better precision and accuracy were achieved with ECH2O-TE sensor and Rhoades model. Capacitance sensors provide precise estimates of plant-available water in most soilless substrates, while pore water EC accuracy and precision depends on the sensor-model combination. These results will enable growers to precisely schedule irrigations based on water content and pore water EC.

Indexing (document details)
Advisor: Lea-Cox, John D.
Commitee: Ristvey, Andrew G., Ross, David S.
School: University of Maryland, College Park
Department: Natural Resource Sciences
School Location: United States -- Maryland
Source: MAI 48/06M, Masters Abstracts International
Subjects: Horticulture, Plant sciences, Soil sciences
Keywords: Capacitance, Electrical-conductivity, Irrigation, Real-time, Sensor, Substrate
Publication Number: 1478116
ISBN: 978-1-124-07546-4
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