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178 results on '"Coelho, Rubens Duarte"'

4. Irrigation Developments in Brazil

Author

da Silva Barros, Timóteo Herculino, primary, Abreu-Junior, Cassio Hamilton, additional, Coelho, Rubens Duarte, additional, Barros da Silva, Flávia Rosana, additional, and Lizcano, Jonathan Vasquez, additional

Published
2023
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5. Smart Coffee: Machine Learning Techniques for Estimating Arabica Coffee Yield.

Author

Freitas, Cleverson Henrique de, Coelho, Rubens Duarte, Costa, Jéfferson de Oliveira, and Sentelhas, Paulo Cesar

Subjects
*SUPPORT vector machines, *COMPUTERS, *ESTIMATION theory, *AGRICULTURE, *COFFEE
Abstract

Coffee is a global commodity, with Brazil being a major producer, particularly in the Minas Gerais state. This study applied machine learning to predict the Arabica coffee yield in the region, analyzing two groups of cultivars (G1 and G2) using data from 1993 to 2020. The Factor Analysis of Mixed Data (FAMD) was employed to explore the relationships between climatic factors, management practices, and the coffee yield. Four machine learning models, such as Multiple Linear Regression (MLR), Random Forest (RF), XGBoost (XGB), and Support Vector Machines (SVM) were calibrated and evaluated for yield prediction. The FAMD revealed complex interactions among variables, requiring four principal components to explain approximately 64.6% of the total variance. Management practices, such as the planting density and pruning, had a stronger influence on G1 cultivars, while G2 cultivars were more sensitive to climatic conditions, particularly the air temperature. Among the machine learning models, RF and XGB performed best in the yield estimation, whereas MLR and SVM were less effective, particularly for values above 60 bags ha−1 (1 bag = 60 kg). These findings underscore the variability in the yield across cultivars and demonstrate the potential of machine learning to guide tailored management strategies for different coffee cultivars. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Production and Harvest Quality of Tomato Fruit Cultivated Under Different Water Replacement Levels and Photoprotector Strategies.

Author

Stein, Bruno Baptista, Duarte, Sergio Nascimento, Freire, Martiliana Mayani, Nascimento, Luiz Fernando da Silva, Jacomino, Angelo Pedro, Costa, Jéfferson de Oliveira, and Coelho, Rubens Duarte

Subjects
DEFICIT irrigation, WATER levels, CROPS, IRRIGATION water, SOIL temperature, TOMATOES
Abstract

The tomato (Solanum lycopersicum) is the second most produced vegetable globally, playing a significant role in national and international economies. This crop is highly sensitive to water deficit and thermal stress, which directly affect yield and fruit quality. Foliar application of calcium carbonate (CaCO3) may be a possible strategy to minimize the effects of these abiotic stresses. This research aimed to determine: (a) the effects of different water replacement levels (WRLs) and photoprotector strategies (Ps) applied to the canopy on production and harvest quality of tomato fruit, (b) thermal responses—Crop Water Stress Index (CWSI) and soil temperature and (c) crop water productivity (WPc). The research was conducted at the University of São Paulo (USP/ESALQ), Piracicaba, State of São Paulo, Brazil. The experimental design adopted was randomized blocks, with four blocks and nine treatments, totaling 36 plots. The treatments were arranged in a 3 × 3 factorial scheme, with three WRLs (70, 100 and 130% of the required irrigation depth) and three photoprotector strategies (without photoprotector, with photoprotector and with photoprotector + adjuvant). Biometric and thermal responses, productivity, harvest quality and WPc were determined. The highest plant height and stalk diameter values were found in the treatment with photoprotector and adjuvant, with an average of 0.98 m and 0.0130 m, respectively. For the variables soil temperature, CWSI and tomato productivity, no significant differences were observed. The general average productivity obtained was 77.9 Mg ha−1. The highest WPc values were found in the WRL 70 treatments, with an average of 23.6 kg m−3. No significant differences were observed for pulp firmness. The highest average value of soluble solids was observed in the treatments with photoprotector (4.8 °Brix) and the highest average value of titratable acidity was observed in the WRL 130 treatments (0.36%). Therefore, deficit irrigation resulted in water savings without compromising tomato productivity and the application of photoprotector and adjuvant increased tomato quality. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Sugarcane Water Productivity for Bioethanol, Sugar and Biomass under Deficit Irrigation

Author

Barbosa, Fernando da Silva, primary, Coelho, Rubens Duarte, additional, Barros, Timóteo Herculino da Silva, additional, Lizcano, Jonathan Vásquez, additional, Fraga Júnior, Eusímio Felisbino, additional, Santos, Lucas da Costa, additional, Leal, Daniel Philipe Veloso, additional, Ribeiro, Nathália Lopes, additional, and Costa, Jéfferson de Oliveira, additional

Published
2024
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19. Precision irrigation trends and perspectives: a review

Author

Gundim, Alice da Silva, primary, Melo, Verônica Gaspar Martins Leite de, additional, Coelho, Rubens Duarte, additional, Silva, Janderson Pedro da, additional, Rocha, Marcos Paulo Alves da, additional, França, Ana Carolina Ferreira, additional, and Conceição, Ana Michele Pereira da, additional

Published
2023
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28. Ballistic model to estimate microsprinkler droplet distribution

Author

Conceição Marco Antônio Fonseca and Coelho Rubens Duarte

Subjects
irrigation, modeling, simulation, Agriculture (General), S1-972
Abstract

Experimental determination of microsprinkler droplets is difficult and time-consuming. This determination, however, could be achieved using ballistic models. The present study aimed to compare simulated and measured values of microsprinkler droplet diameters. Experimental measurements were made using the flour method, and simulations using a ballistic model adopted by the SIRIAS computational software. Drop diameters quantified in the experiment varied between 0.30 mm and 1.30 mm, while the simulated between 0.28 mm and 1.06 mm. The greatest differences between simulated and measured values were registered at the highest radial distance from the emitter. The model presented a performance classified as excellent for simulating microsprinkler drop distribution.

Published
2003

37. Spatial variability quantification of maize water consumption based on Google EEflux tool

Author

de Oliveira Costa, Jéfferson, primary, José, Jefferson Vieira, additional, Wolff, Wagner, additional, de Oliveira, Niclene Ponce Rodrigues, additional, Oliveira, Rafaella Conceição, additional, Ribeiro, Nathália Lopes, additional, Coelho, Rubens Duarte, additional, da Silva, Tonny José Araújo, additional, Bonfim-Silva, Edna Maria, additional, and Schlichting, Alessana Franciele, additional

Published
2020
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42. Quantification of cotton water consumption by remote sensing

Author

José, Jefferson Vieira, primary, Oliveira, Niclene Ponce Rodrigues de, additional, Silva, Tonny José de Araújo da, additional, Bonfim-Silva, Edna Maria, additional, Costa, Jéfferson de Oliveira, additional, Fenner, Willian, additional, and Coelho, Rubens Duarte, additional

Published
2019
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44. Quantification of cotton water consumption by remote sensing.

Author

José, Jefferson Vieira, Oliveira, Niclene Ponce Rodrigues de, Silva, Tonny José de Araújo da, Bonfim-Silva, Edna Maria, Costa, Jéfferson de Oliveira, Fenner, Willian, and Coelho, Rubens Duarte

Subjects
WATER consumption, REMOTE sensing, WATER supply, WATER management, EVAPOTRANSPIRATION, ALGORITHMS, COTTON
Abstract

Quantifying crop water consumption is essential for water resource management. The objective was to estimate the current evapotranspiration (ETa) of the cotton crop (Gossypium hirsutum L.) in the rainfed system, as well as the components of the radiation and energy balance in the Cerrado biome conditions using orbital images and the SEBAL algorithm and validate the estimates of evapotranspiration (ET) using FAO guidelines for crop coefficient (Kc) of the cotton crop. Research was carried out in the State of Mato Grosso, Brazil, in areas with three cotton cultivars. Images of the Operational Land Imager and Thermal Infrared Sensor sensors were used and ET estimation was made based on the SEBAL algorithm. Mean ETa in the cotton cycle was 3.5 mm dia−1 and the Kc values ranged from 0.22 and 1.12, on average, in the smaller and larger leaf area, respectively. [ABSTRACT FROM AUTHOR]

Published
2020
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