Performance of Soil Moisture Sensors in Florida Sandy Soils
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3390/w12020358 http://hdl.handle.net/11449/196690 |
Resumo: | Soil moisture sensors can improve water management efficiency by measuring soil volumetric water content (theta nu) in real time. Soil-specific calibration equations used to calculate theta nu can increase sensor accuracy. A laboratory study was conducted to evaluate the performance of several commercial sensors and to establish soil-specific calibration equations for different soil types. We tested five Florida sandy soils used for citrus production (Pineda, Riviera, Astatula, Candler, and Immokalee) divided into two depths (0.0-0.3 and 0.3-0.6 m). Readings were taken using twelve commercial sensors (CS650, CS616, CS655 (Campbell Scientific), GS3, 10HS, 5TE, GS1 (Meter), TDT-ACC-SEN-SDI, TDR315, TDR315S, TDR135L (Acclima), and Hydra Probe (Stevens)) connected to a datalogger (CR1000X; Campbell Scientific). Known amounts of water were added incrementally to obtain a broad range of theta nu Small 450 cm(3) samples were taken to determine the gravimetric water content and calculate the theta nu used to obtain the soil-specific calibration equations. Results indicated that factory-supplied calibration equations performed well for some sensors in sandy soils, especially 5TE, TDR315L, and GS1 (R-2 = 0.92) but not for others (10HS, GS3, and Hydra Probe). Soil -specific calibrations from this study resulted in accuracy expressed as root mean square error (RMSE) ranging from 0.018 to 0.030 m(3) m(-3) for 5TE, CS616, CS650, CS655, GS1, Hydra Probe, TDR310S, TDR315, TDR315L, and TDT-ACC-SEN-SDI, while lower accuracies were found for 10HS (0.129 m(3) m(-3)) and GS3 (0.054 m(3) m(-3)). This study provided soil -specific calibration equations to increase the accuracy of commercial soil moisture sensors to facilitate irrigation scheduling and water management in Florida sandy soils used for citrus production. |
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Performance of Soil Moisture Sensors in Florida Sandy Soilsbulk densityirrigation managementwater loss reductionvolumetric water contentSoil moisture sensors can improve water management efficiency by measuring soil volumetric water content (theta nu) in real time. Soil-specific calibration equations used to calculate theta nu can increase sensor accuracy. A laboratory study was conducted to evaluate the performance of several commercial sensors and to establish soil-specific calibration equations for different soil types. We tested five Florida sandy soils used for citrus production (Pineda, Riviera, Astatula, Candler, and Immokalee) divided into two depths (0.0-0.3 and 0.3-0.6 m). Readings were taken using twelve commercial sensors (CS650, CS616, CS655 (Campbell Scientific), GS3, 10HS, 5TE, GS1 (Meter), TDT-ACC-SEN-SDI, TDR315, TDR315S, TDR135L (Acclima), and Hydra Probe (Stevens)) connected to a datalogger (CR1000X; Campbell Scientific). Known amounts of water were added incrementally to obtain a broad range of theta nu Small 450 cm(3) samples were taken to determine the gravimetric water content and calculate the theta nu used to obtain the soil-specific calibration equations. Results indicated that factory-supplied calibration equations performed well for some sensors in sandy soils, especially 5TE, TDR315L, and GS1 (R-2 = 0.92) but not for others (10HS, GS3, and Hydra Probe). Soil -specific calibrations from this study resulted in accuracy expressed as root mean square error (RMSE) ranging from 0.018 to 0.030 m(3) m(-3) for 5TE, CS616, CS650, CS655, GS1, Hydra Probe, TDR310S, TDR315, TDR315L, and TDT-ACC-SEN-SDI, while lower accuracies were found for 10HS (0.129 m(3) m(-3)) and GS3 (0.054 m(3) m(-3)). This study provided soil -specific calibration equations to increase the accuracy of commercial soil moisture sensors to facilitate irrigation scheduling and water management in Florida sandy soils used for citrus production.University of Florida's Joye Giglia Endowment for Innovative Agricultural TechnologyU.S. Department of Agriculture's Specialty Crop Research Initiative (SCRI) Citrus Disease Research and Extension Program (CDRE)U.S. Department of Agriculture's National Institute of Food and Agriculture (NIFA)Univ Florida, Inst Food & Agr Sci, Indian River Res & Educ Ctr, 2199 South Rock Rd, Ft Pierce, FL 34945 USASao Paulo State Univ, Sch Engn, Dept Plant Protect Rural Engn & Soils, Av Brasil Sul 56, BR-15385000 Ilha Solteira, SP, BrazilZamorano Pan Amer Agr Sch, POB 93,Km 30 Rd Tegucigalpa Danli, San Antonio De Oriente 11101, Francisco Moraz, HondurasSao Paulo State Univ, Sch Engn, Dept Plant Protect Rural Engn & Soils, Av Brasil Sul 56, BR-15385000 Ilha Solteira, SP, BrazilUniversity of Florida's Joye Giglia Endowment for Innovative Agricultural Technology: 2017-F0013964U.S. Department of Agriculture's Specialty Crop Research Initiative (SCRI) Citrus Disease Research and Extension Program (CDRE): 2018-70016-27387U.S. Department of Agriculture's National Institute of Food and Agriculture (NIFA): 1021596MdpiUniv FloridaUniversidade Estadual Paulista (Unesp)Zamorano Pan Amer Agr SchFerrarezi, Rhuanito SoranzRodrigues Nogueira, Thiago Assis [UNESP]Cornejo Zepeda, Sara Gabriela2020-12-10T19:53:07Z2020-12-10T19:53:07Z2020-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article20http://dx.doi.org/10.3390/w12020358Water. Basel: Mdpi, v. 12, n. 2, 20 p., 2020.http://hdl.handle.net/11449/19669010.3390/w12020358WOS:000519846500049Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengWaterinfo:eu-repo/semantics/openAccess2021-10-23T09:20:10Zoai:repositorio.unesp.br:11449/196690Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T09:20:10Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Performance of Soil Moisture Sensors in Florida Sandy Soils |
title |
Performance of Soil Moisture Sensors in Florida Sandy Soils |
spellingShingle |
Performance of Soil Moisture Sensors in Florida Sandy Soils Ferrarezi, Rhuanito Soranz bulk density irrigation management water loss reduction volumetric water content |
title_short |
Performance of Soil Moisture Sensors in Florida Sandy Soils |
title_full |
Performance of Soil Moisture Sensors in Florida Sandy Soils |
title_fullStr |
Performance of Soil Moisture Sensors in Florida Sandy Soils |
title_full_unstemmed |
Performance of Soil Moisture Sensors in Florida Sandy Soils |
title_sort |
Performance of Soil Moisture Sensors in Florida Sandy Soils |
author |
Ferrarezi, Rhuanito Soranz |
author_facet |
Ferrarezi, Rhuanito Soranz Rodrigues Nogueira, Thiago Assis [UNESP] Cornejo Zepeda, Sara Gabriela |
author_role |
author |
author2 |
Rodrigues Nogueira, Thiago Assis [UNESP] Cornejo Zepeda, Sara Gabriela |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Univ Florida Universidade Estadual Paulista (Unesp) Zamorano Pan Amer Agr Sch |
dc.contributor.author.fl_str_mv |
Ferrarezi, Rhuanito Soranz Rodrigues Nogueira, Thiago Assis [UNESP] Cornejo Zepeda, Sara Gabriela |
dc.subject.por.fl_str_mv |
bulk density irrigation management water loss reduction volumetric water content |
topic |
bulk density irrigation management water loss reduction volumetric water content |
description |
Soil moisture sensors can improve water management efficiency by measuring soil volumetric water content (theta nu) in real time. Soil-specific calibration equations used to calculate theta nu can increase sensor accuracy. A laboratory study was conducted to evaluate the performance of several commercial sensors and to establish soil-specific calibration equations for different soil types. We tested five Florida sandy soils used for citrus production (Pineda, Riviera, Astatula, Candler, and Immokalee) divided into two depths (0.0-0.3 and 0.3-0.6 m). Readings were taken using twelve commercial sensors (CS650, CS616, CS655 (Campbell Scientific), GS3, 10HS, 5TE, GS1 (Meter), TDT-ACC-SEN-SDI, TDR315, TDR315S, TDR135L (Acclima), and Hydra Probe (Stevens)) connected to a datalogger (CR1000X; Campbell Scientific). Known amounts of water were added incrementally to obtain a broad range of theta nu Small 450 cm(3) samples were taken to determine the gravimetric water content and calculate the theta nu used to obtain the soil-specific calibration equations. Results indicated that factory-supplied calibration equations performed well for some sensors in sandy soils, especially 5TE, TDR315L, and GS1 (R-2 = 0.92) but not for others (10HS, GS3, and Hydra Probe). Soil -specific calibrations from this study resulted in accuracy expressed as root mean square error (RMSE) ranging from 0.018 to 0.030 m(3) m(-3) for 5TE, CS616, CS650, CS655, GS1, Hydra Probe, TDR310S, TDR315, TDR315L, and TDT-ACC-SEN-SDI, while lower accuracies were found for 10HS (0.129 m(3) m(-3)) and GS3 (0.054 m(3) m(-3)). This study provided soil -specific calibration equations to increase the accuracy of commercial soil moisture sensors to facilitate irrigation scheduling and water management in Florida sandy soils used for citrus production. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-10T19:53:07Z 2020-12-10T19:53:07Z 2020-02-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.3390/w12020358 Water. Basel: Mdpi, v. 12, n. 2, 20 p., 2020. http://hdl.handle.net/11449/196690 10.3390/w12020358 WOS:000519846500049 |
url |
http://dx.doi.org/10.3390/w12020358 http://hdl.handle.net/11449/196690 |
identifier_str_mv |
Water. Basel: Mdpi, v. 12, n. 2, 20 p., 2020. 10.3390/w12020358 WOS:000519846500049 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Water |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
20 |
dc.publisher.none.fl_str_mv |
Mdpi |
publisher.none.fl_str_mv |
Mdpi |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1803046305720696832 |