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Multispectral Information in the Classification of Soybean Genotypes Using Algorithms Regarding Micronutrient Nutritional Contents.
- Published in:
- AgriEngineering, 2024, v. 6, n. 4, p. 4493, doi. 10.3390/agriengineering6040256
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- Article
Caffeine Content Prediction in Coffee Beans Using Hyperspectral Reflectance and Machine Learning.
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- AgriEngineering, 2024, v. 6, n. 4, p. 4480, doi. 10.3390/agriengineering6040255
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- Article
Multispectral Sensors and Machine Learning as Modern Tools for Nutrient Content Prediction in Soil.
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- AgriEngineering, 2024, v. 6, n. 4, p. 4384, doi. 10.3390/agriengineering6040248
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- Article
Can Different Cultivars of Panicum maximum Be Identified Using a VIS/NIR Sensor and Machine Learning?
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- AgriEngineering, 2024, v. 6, n. 4, p. 3739, doi. 10.3390/agriengineering6040213
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- Article
Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach.
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- Scientific Reports, 2021, v. 11, n. 1, p. 1, doi. 10.1038/s41598-021-01350-y
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- Article
Silicon mitigates nutritional stress in quinoa (Chenopodium quinoa Willd.).
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- Scientific Reports, 2021, v. 11, n. 1, p. 1, doi. 10.1038/s41598-021-94287-1
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- Article
Rainfall and Extreme Drought Detection: An Analysis for a Potential Agricultural Region in the Southern Brazilian Amazon.
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- Sustainability (2071-1050), 2024, v. 16, n. 14, p. 5959, doi. 10.3390/su16145959
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- Article
Macro- and Micronutrient Contents and Their Relationship with Growth in Six Eucalyptus Species.
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- Sustainability (2071-1050), 2023, v. 15, n. 22, p. 15771, doi. 10.3390/su152215771
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- Article
Machine Learning Methods for Woody Volume Prediction in Eucalyptus.
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- Sustainability (2071-1050), 2023, v. 15, n. 14, p. 10968, doi. 10.3390/su151410968
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- Article
Wildfire Incidence throughout the Brazilian Pantanal Is Driven by Local Climate Rather Than Bovine Stocking Density.
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- Sustainability (2071-1050), 2022, v. 14, n. 16, p. 10187, doi. 10.3390/su141610187
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- Article
Soybean Cultivars Identification Using Remotely Sensed Image and Machine Learning Models.
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- Sustainability (2071-1050), 2022, v. 14, n. 12, p. N.PAG, doi. 10.3390/su14127125
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- Article
CO 2 Flux Model Assessment and Comparison between an Airborne Hyperspectral Sensor and Orbital Multispectral Imagery in Southern Amazonia.
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- Sustainability (2071-1050), 2022, v. 14, n. 9, p. 5458, doi. 10.3390/su14095458
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- Article
The "New Transamazonian Highway": BR-319 and Its Current Environmental Degradation.
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- Sustainability (2071-1050), 2022, v. 14, n. 2, p. 823, doi. 10.3390/su14020823
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- Article
Adaptability and yield stability of cowpea genotypes in Mato Grosso do Sul.
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- Crop Breeding & Applied Biotechnology, 2023, v. 23, n. 4, p. 1, doi. 10.1590/1984-70332023v23n4a45
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- Article
Multi-volume modeling of Eucalyptus trees using regression and artificial neural networks.
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- PLoS ONE, 2020, v. 15, n. 9, p. 1, doi. 10.1371/journal.pone.0238703
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- Article
Persistent fire foci in all biomes undermine the Paris Agreement in Brazil.
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- Scientific Reports, 2020, v. 10, n. 1, p. N.PAG, doi. 10.1038/s41598-020-72571-w
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- Article
The fewer, the better fare: Can the loss of vegetation in the Cerrado drive the increase in dengue fever cases infection?
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- PLoS ONE, 2022, v. 17, n. 1, p. 1, doi. 10.1371/journal.pone.0262473
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- Article
19-year remotely sensed data in the forecast of spectral models of the environment.
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- International Journal of Digital Earth, 2021, v. 14, n. 8, p. 1040, doi. 10.1080/17538947.2021.1923841
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- Article
Detection of Irrigated and Non-Irrigated Soybeans Using Hyperspectral Data in Machine-Learning Models.
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- Algorithms, 2024, v. 17, n. 12, p. 542, doi. 10.3390/a17120542
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- Article
A New Approach to Identifying Sorghum Hybrids Using UAV Imagery Using Multispectral Signature and Machine Learning.
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- Algorithms, 2024, v. 17, n. 1, p. 23, doi. 10.3390/a17010023
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- Article
Effect of land uses and land cover on soil attributes in the southern Brazilian Amazon.
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- Environmental Monitoring & Assessment, 2022, v. 194, n. 10, p. 1, doi. 10.1007/s10661-022-10342-y
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- Article
Twenty-year impact of fire foci and its relationship with climate variables in Brazilian regions.
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- Environmental Monitoring & Assessment, 2022, v. 194, n. 2, p. 1, doi. 10.1007/s10661-021-09702-x
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- Article
Application of remote sensing in environmental impact assessment: a case study of dam rupture in Brumadinho, Minas Gerais, Brazil.
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- Environmental Monitoring & Assessment, 2021, v. 193, n. 9, p. 1, doi. 10.1007/s10661-021-09417-z
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- Article
Predicting the quality of soybean seeds stored in different environments and packaging using machine learning.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-12863-5
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- Article
Reduction of pesticide application via real-time precision spraying.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-09607-w
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- Article
Prognosis of aboveground woody biomass in a central Brazilian Cerrado monitored for 27 years after the implementation of management systems.
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- European Journal of Forest Research, 2022, v. 141, n. 1, p. 1, doi. 10.1007/s10342-021-01421-9
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- Article
Tempering time and air temperature relationships for real-scale paddy drying and their effects on the physical, physicochemical, and morphological qualities of polished rice.
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- Drying Technology, 2023, v. 41, n. 11, p. 1878, doi. 10.1080/07373937.2023.2199834
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- Article
Effect of Water Deficit on Secondary Metabolites and Nutrient Content on Forage Sorghum.
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- Agronomy, 2024, v. 14, n. 9, p. 2046, doi. 10.3390/agronomy14092046
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- Article
Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes.
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- Agronomy, 2021, v. 11, n. 11, p. 2179, doi. 10.3390/agronomy11112179
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- Article
SOIL MACROFAUNA IN GREEN MANURES PRECEDING COTTON GROWING.
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- Bioscience Journal, 2020, v. 36, n. 6, p. 2229, doi. 10.14393/BJ-v36n6a2020-48180
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- Article
RELATIONSHIP BETWEEN VEGETATION INDICES AND AGRONOMIC PERFORMANCE OF MAIZE VARIETIES UNDER DIFFERENT NITROGEN RATES.
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- Bioscience Journal, 2020, v. 36, n. 5, p. 1638, doi. 10.14393/BJ-v36n5a2020-47993
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- Article
PHENOTYPIC ADAPTABILITY OF COTTON GENOTYPES TO THE BRAZILIAN CERRADO FOR YIELD AND FIBER QUALITY.
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- Bioscience Journal, 2020, v. 36, n. 4, p. 1223, doi. 10.14393/BJ-v36n4a2020-48148
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- Article
Machine Learning in the Hyperspectral Classification of Glycaspis brimblecombei (Hemiptera Psyllidae) Attack Severity in Eucalyptus.
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- Remote Sensing, 2023, v. 15, n. 24, p. 5657, doi. 10.3390/rs15245657
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- Article
Changes in Carbon Dioxide Balance Associated with Land Use and Land Cover in Brazilian Legal Amazon Based on Remotely Sensed Imagery.
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- Remote Sensing, 2023, v. 15, n. 11, p. 2780, doi. 10.3390/rs15112780
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- Article
Machine Learning in the Classification of Soybean Genotypes for Primary Macronutrients' Content Using UAV–Multispectral Sensor.
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- Remote Sensing, 2023, v. 15, n. 5, p. 1457, doi. 10.3390/rs15051457
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- Article
Maize Yield Prediction with Machine Learning, Spectral Variables and Irrigation Management.
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- Remote Sensing, 2023, v. 15, n. 1, p. 79, doi. 10.3390/rs15010079
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- Article
Fires Drive Long-Term Environmental Degradation in the Amazon Basin.
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- Remote Sensing, 2022, v. 14, n. 2, p. 338, doi. 10.3390/rs14020338
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- Article
Predicting Days to Maturity, Plant Height, and Grain Yield in Soybean: A Machine and Deep Learning Approach Using Multispectral Data.
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- Remote Sensing, 2021, v. 13, n. 22, p. 4632, doi. 10.3390/rs13224632
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- Article
Leaf Nitrogen Concentration and Plant Height Prediction for Maize Using UAV-Based Multispectral Imagery and Machine Learning Techniques.
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- Remote Sensing, 2020, v. 12, n. 19, p. 3237, doi. 10.3390/rs12193237
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- Article
Models for optimizing selection based on adaptability and stability of cotton genotypes.
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- Ciência Rural, 2021, v. 51, n. 5, p. 1, doi. 10.1590/0103-8478cr20200530
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- Article
Real‐time equilibrium moisture content monitoring to predict grain quality of corn stored in silo and raffia bags.
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- Journal of Food Process Engineering, 2022, v. 45, n. 9, p. 1, doi. 10.1111/jfpe.14076
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- Article
Classification of Soybean Genotypes as to Calcium, Magnesium, and Sulfur Content Using Machine Learning Models and UAV–Multispectral Sensor.
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- AgriEngineering, 2024, v. 6, n. 2, p. 1581, doi. 10.3390/agriengineering6020090
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- Publication type:
- Article
Maize Crop Detection through Geo-Object-Oriented Analysis Using Orbital Multi-Sensors on the Google Earth Engine Platform.
- Published in:
- AgriEngineering, 2024, v. 6, n. 1, p. 491, doi. 10.3390/agriengineering6010030
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- Article
Hyperspectral Response of the Soybean Crop as a Function of Target Spot (Corynespora cassiicola) Using Machine Learning to Classify Severity Levels.
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- AgriEngineering, 2024, v. 6, n. 1, p. 330, doi. 10.3390/agriengineering6010020
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- Article
Characterizing and Predicting the Quality of Milled Rice Grains Using Machine Learning Models.
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- AgriEngineering, 2023, v. 5, n. 3, p. 1196, doi. 10.3390/agriengineering5030076
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- Publication type:
- Article
Assessing soil CO<sub>2</sub> emission on eucalyptus species using UAV-based reflectance and vegetation indices.
- Published in:
- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-71430-2
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- Article
Flavonoids and their relationship with the physiological quality of seeds from different soybean genotypes.
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- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-68117-z
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- Publication type:
- Article
Monitoring and predicting corn grain quality on the transport and post-harvest operations in storage units using sensors and machine learning models.
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- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-56879-5
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- Article
Understanding the combining ability for physiological traits in soybean.
- Published in:
- PLoS ONE, 2019, v. 14, n. 12, p. 1, doi. 10.1371/journal.pone.0226523
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- Article
High-throughput phenotyping as an auxiliary tool in the selection of corn hybrids for agronomic traits.
- Published in:
- Revista Ceres, 2023, v. 70, n. 1, p. 106, doi. 10.1590/0034-737X202370010012
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- Article