Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing

This study evaluated the performance of the SAFER and METRIC algorithms to estimate the actual evapotranspiration (ETa) of irrigated tomato crops for industrial processing in the south-central region of Goiás, Brazil. The research was conducted in eight tomato-producing areas using center-pivot irri...

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Main Authors: Carolina Carvalho Rocha Sena, José Alves Júnior, João Mauricio Fernandes Souza, Adão Wagner Pego Evangelista, Rafael Battisti, Derblai Casaroli, Elson de Jesus Antunes Junior
Format: Article
Language:English
Published: Universidade Federal de Uberlândia 2025-02-01
Series:Bioscience Journal
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Online Access:https://seer.ufu.br/index.php/biosciencejournal/article/view/70757
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author Carolina Carvalho Rocha Sena
José Alves Júnior
João Mauricio Fernandes Souza
Adão Wagner Pego Evangelista
Rafael Battisti
Derblai Casaroli
Elson de Jesus Antunes Junior
author_facet Carolina Carvalho Rocha Sena
José Alves Júnior
João Mauricio Fernandes Souza
Adão Wagner Pego Evangelista
Rafael Battisti
Derblai Casaroli
Elson de Jesus Antunes Junior
author_sort Carolina Carvalho Rocha Sena
collection DOAJ
description This study evaluated the performance of the SAFER and METRIC algorithms to estimate the actual evapotranspiration (ETa) of irrigated tomato crops for industrial processing in the south-central region of Goiás, Brazil. The research was conducted in eight tomato-producing areas using center-pivot irrigation during the 2018 and 2019 harvests. Landsat 8 OLI/TIRS satellite images (temporal resolution of 16 days) helped estimate ETa through the SAFER e METRIC models compared with FAO methods, using the single crop coefficient (Kc) of the FAO-56/Embrapa and the soil water balance (BHS) method based on statistical indices. The analyzed algorithms presented spatiotemporal variations for ETa during the tomato crop cycle for industrial processing. The maximum evapotranspiration estimated by SAFER was 5.20 mm d-1, and by METRIC was 5.00 mm d-1. The algorithms were accurate compared with the standard methods, mainly the FAO using Embrapa’s Kc. The mean squared error was lower than 0.59 mm d-1 for SAFER and lower than 0.73 mm d-1 for METRIC. The ETa estimated by both models in the vegetative and fructification phases was lower than the mean absolute error of 0.24 mm d-1 compared with the standard methods. The SAFER model showed higher agreement with standard practices than the METRIC model, with an index between 0.64 and 0.99. This study demonstrated that algorithms may effectively estimate ETa in tomato crops for industrial processing in the analyzed region.
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spelling doaj-art-d92d40df89444d438a7a2cf8352d14312025-08-20T03:12:51ZengUniversidade Federal de UberlândiaBioscience Journal1981-31632025-02-0141e41002e4100210.14393/BJ-v41n0a2025-7075772473Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processingCarolina Carvalho Rocha Sena0https://orcid.org/0000-0002-7818-8010José Alves Júnior1https://orcid.org/0000-0001-5972-6306João Mauricio Fernandes Souza2https://orcid.org/0000-0002-1945-6695Adão Wagner Pego Evangelista3Rafael Battisti4https://orcid.org/0000-0001-5768-4501Derblai Casaroli5https://orcid.org/0000-0001-8041-0066Elson de Jesus Antunes Junior6Universidade Federal de GoiásUniversidade Federal de GoiásUniEvangélicaUniversidade Federal de GoiásUniversidade Federal de GoiásUniversidade Federal de GoiásUniEvangélicaThis study evaluated the performance of the SAFER and METRIC algorithms to estimate the actual evapotranspiration (ETa) of irrigated tomato crops for industrial processing in the south-central region of Goiás, Brazil. The research was conducted in eight tomato-producing areas using center-pivot irrigation during the 2018 and 2019 harvests. Landsat 8 OLI/TIRS satellite images (temporal resolution of 16 days) helped estimate ETa through the SAFER e METRIC models compared with FAO methods, using the single crop coefficient (Kc) of the FAO-56/Embrapa and the soil water balance (BHS) method based on statistical indices. The analyzed algorithms presented spatiotemporal variations for ETa during the tomato crop cycle for industrial processing. The maximum evapotranspiration estimated by SAFER was 5.20 mm d-1, and by METRIC was 5.00 mm d-1. The algorithms were accurate compared with the standard methods, mainly the FAO using Embrapa’s Kc. The mean squared error was lower than 0.59 mm d-1 for SAFER and lower than 0.73 mm d-1 for METRIC. The ETa estimated by both models in the vegetative and fructification phases was lower than the mean absolute error of 0.24 mm d-1 compared with the standard methods. The SAFER model showed higher agreement with standard practices than the METRIC model, with an index between 0.64 and 0.99. This study demonstrated that algorithms may effectively estimate ETa in tomato crops for industrial processing in the analyzed region.https://seer.ufu.br/index.php/biosciencejournal/article/view/70757center pivotgeoprocessingsolanum lycopersicum l. water management.
spellingShingle Carolina Carvalho Rocha Sena
José Alves Júnior
João Mauricio Fernandes Souza
Adão Wagner Pego Evangelista
Rafael Battisti
Derblai Casaroli
Elson de Jesus Antunes Junior
Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing
Bioscience Journal
center pivot
geoprocessing
solanum lycopersicum l.
water management.
title Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing
title_full Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing
title_fullStr Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing
title_full_unstemmed Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing
title_short Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing
title_sort remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing
topic center pivot
geoprocessing
solanum lycopersicum l.
water management.
url https://seer.ufu.br/index.php/biosciencejournal/article/view/70757
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