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Artigo de periodico
Methodology to filter out outliers in high spatial density data to improve maps reliability (2022)
Maldaner, Leonardo Felipe ; Molin, José Paulo ; Spekken, Mark
Source: Scientia Agricola. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, AMOSTRAGEM, CANA-DE-AÇÚCAR, MAPEAMENTO DO SOLO, MILHO, SENSOR, VARIABILIDADE ESPACIAL
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ABNT
MALDANER, Leonardo Felipe; MOLIN, José Paulo; SPEKKEN, Mark. Methodology to filter out outliers in high spatial density data to improve maps reliability. Scientia Agricola, Piracicaba, v. 79, n. 1, p. 1-7, 2022. Disponível em: < http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000100102&tlng=en > DOI: dx.doi.org/10.1590/1678-992x-2020-0178.
APA
Maldaner, L. F., Molin, J. P., & Spekken, M. (2022). Methodology to filter out outliers in high spatial density data to improve maps reliability. Scientia Agricola, 79( 1), 1-7. doi:dx.doi.org/10.1590/1678-992x-2020-0178
NLM
Maldaner LF, Molin JP, Spekken M. Methodology to filter out outliers in high spatial density data to improve maps reliability [Internet]. Scientia Agricola. 2022 ; 79( 1): 1-7.Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000100102&tlng=en
Vancouver
Maldaner LF, Molin JP, Spekken M. Methodology to filter out outliers in high spatial density data to improve maps reliability [Internet]. Scientia Agricola. 2022 ; 79( 1): 1-7.Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000100102&tlng=en
Artigo de periodico
Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies (2021)
Tavares, Tiago Rodrigues ; Molin, José Paulo ; Nunes, Lidiane Cristina ; Wei, Marcelo Chan Fu ; Krug, Francisco José ; Carvalho, Hudson Wallace Pereira de ; Mouazen, Abdul Mounem
Source: Agronomy. Unidades: ESALQ, CENA
Subjects: FERTILIDADE DO SOLO, SENSOR, ESPECTROSCOPIA, QUÍMICA VERDE, LABORATÓRIOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAVARES, Tiago Rodrigues; MOLIN, José Paulo; NUNES, Lidiane Cristina; et al. Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies. Agronomy, Basel, v. 11, 2021. DOI: 10.3390/agronomy11061028.
APA
Tavares, T. R., Molin, J. P., Nunes, L. C., Wei, M. C. F., Krug, F. J., Carvalho, H. W. P. de, & Mouazen, A. M. (2021). Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies. Agronomy, 11. doi:10.3390/agronomy11061028
NLM
Tavares TR, Molin JP, Nunes LC, Wei MCF, Krug FJ, Carvalho HWP de, Mouazen AM. Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies. Agronomy. 2021 ; 11
Vancouver
Tavares TR, Molin JP, Nunes LC, Wei MCF, Krug FJ, Carvalho HWP de, Mouazen AM. Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies. Agronomy. 2021 ; 11
Artigo de periodico
Spatial distribution of sorption and desorption process of 14C- radiolabelled hexazinone and tebuthiuron in tropical soil (2021)
Mendes, Kassio Ferreira ; Wei, Marcelo Chan Fu ; Furtado, Ivan Ferreira ; Takeshita, Vanessa ; Pissolito, João Pedro ; Molin, Jose Paulo ; Tornisielo, Valdemar Luiz
Source: Chemosphere. Unidades: ESALQ, CENA
Subjects: AGRICULTURA DE PRECISÃO, CARBONO 14, DISTRIBUIÇÃO ESPACIAL, HERBICIDAS, PLANTAS DANINHAS, SOLO TROPICAL
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ABNT
MENDES, Kassio Ferreira; WEI, Marcelo Chan Fu; FURTADO, Ivan Ferreira; et al. Spatial distribution of sorption and desorption process of 14C- radiolabelled hexazinone and tebuthiuron in tropical soil. Chemosphere, Amsterdam, v. 264, p. 1-11, 2021. Disponível em: < https://doi.org/10.1016/j.chemosphere.2020.128494 > DOI: 10.1016/j.chemosphere.2020.128494.
APA
Mendes, K. F., Wei, M. C. F., Furtado, I. F., Takeshita, V., Pissolito, J. P., Molin, J. P., & Tornisielo, V. L. (2021). Spatial distribution of sorption and desorption process of 14C- radiolabelled hexazinone and tebuthiuron in tropical soil. Chemosphere, 264, 1-11. doi:10.1016/j.chemosphere.2020.128494
NLM
Mendes KF, Wei MCF, Furtado IF, Takeshita V, Pissolito JP, Molin JP, Tornisielo VL. Spatial distribution of sorption and desorption process of 14C- radiolabelled hexazinone and tebuthiuron in tropical soil [Internet]. Chemosphere. 2021 ; 264 1-11.Available from: https://doi.org/10.1016/j.chemosphere.2020.128494
Vancouver
Mendes KF, Wei MCF, Furtado IF, Takeshita V, Pissolito JP, Molin JP, Tornisielo VL. Spatial distribution of sorption and desorption process of 14C- radiolabelled hexazinone and tebuthiuron in tropical soil [Internet]. Chemosphere. 2021 ; 264 1-11.Available from: https://doi.org/10.1016/j.chemosphere.2020.128494
Artigo de periodico
Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy (2021)
Corrêdo, Lucas de Paula ; Maldaner, Leonardo Felipe ; Bazame, Helizani Couto ; Molin, José Paulo
Source: Sensors. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, AMOSTRAGEM, CANA-DE-AÇÚCAR, ESPECTROSCOPIA INFRAVERMELHA, QUIMIOMETRIA, SENSOR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CORRÊDO, Lucas de Paula; MALDANER, Leonardo Felipe; BAZAME, Helizani Couto; MOLIN, José Paulo. Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy. Sensors, Basel, v. 21, p. 1-23, 2021. Disponível em: < https://doi.org/10.3390/s21062195 > DOI: 10.3390/s21062195.
APA
Corrêdo, L. de P., Maldaner, L. F., Bazame, H. C., & Molin, J. P. (2021). Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy. Sensors, 21, 1-23. doi:10.3390/s21062195
NLM
Corrêdo L de P, Maldaner LF, Bazame HC, Molin JP. Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy [Internet]. Sensors. 2021 ; 21 1-23.Available from: https://doi.org/10.3390/s21062195
Vancouver
Corrêdo L de P, Maldaner LF, Bazame HC, Molin JP. Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy [Internet]. Sensors. 2021 ; 21 1-23.Available from: https://doi.org/10.3390/s21062195
Artigo de periodico
Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies (2021)
Tavares, Tiago Rodrigues ; Molin, José Paulo ; Nunes, Lidiane Cristina ; Wei, Marcelo Chan Fu ; Krug, Francisco José ; Carvalho, Hudson Wallace Pereira de ; Mouazen, Abdul Mounem
Source: Agronomy. Unidades: ESALQ, CENA
Subjects: FERTILIDADE DO SOLO, SOLO TROPICAL, SENSOR, ESPECTROSCOPIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAVARES, Tiago Rodrigues; MOLIN, José Paulo; NUNES, Lidiane Cristina; et al. Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies. Agronomy, Basel, v. 11, p. 1-18, 2021. Disponível em: < https://doi.org/10.3390/agronomy11061028 > DOI: 10.3390/agronomy11061028.
APA
Tavares, T. R., Molin, J. P., Nunes, L. C., Wei, M. C. F., Krug, F. J., Carvalho, H. W. P. de, & Mouazen, A. M. (2021). Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies. Agronomy, 11, 1-18. doi:10.3390/agronomy11061028
NLM
Tavares TR, Molin JP, Nunes LC, Wei MCF, Krug FJ, Carvalho HWP de, Mouazen AM. Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies [Internet]. Agronomy. 2021 ; 11 1-18.Available from: https://doi.org/10.3390/agronomy11061028
Vancouver
Tavares TR, Molin JP, Nunes LC, Wei MCF, Krug FJ, Carvalho HWP de, Mouazen AM. Multi-sensor approach for tropical soil fertility analysis: comparison of individual and combined performance of VNIR, XRF, and LIBS spectroscopies [Internet]. Agronomy. 2021 ; 11 1-18.Available from: https://doi.org/10.3390/agronomy11061028
Artigo de periodico
Combined use of Vis-NIR and XRF sensors for tropical soil fertility analysis: assessing different data fusion approaches (2021)
Tavares, Tiago Rodrigues ; Javadi, S. Hamed ; Carvalho, Hudson Wallace Pereira de ; Mouazen, Abdul Mounem ; Molin, José Paulo
Source: Sensors. Unidades: ESALQ, CENA
Subjects: AGRICULTURA DE PRECISÃO, ESPECTROSCOPIA INFRAVERMELHA, FERTILIDADE DO SOLO, FLUORESCÊNCIA, RAIOS X, SENSOR, SOLO TROPICAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAVARES, Tiago Rodrigues; JAVADI, S. Hamed; CARVALHO, Hudson Wallace Pereira de; MOUAZEN, Abdul Mounem; MOLIN, José Paulo. Combined use of Vis-NIR and XRF sensors for tropical soil fertility analysis: assessing different data fusion approaches. Sensors, Basel, v. 21, p. 493-501, 2021. Disponível em: < https://doi.org/10.3390/s21010148 > DOI: 10.3390/s21010148.
APA
Tavares, T. R., Javadi, S. H., Carvalho, H. W. P. de, Mouazen, A. M., & Molin, J. P. (2021). Combined use of Vis-NIR and XRF sensors for tropical soil fertility analysis: assessing different data fusion approaches. Sensors, 21, 493-501. doi:10.3390/s21010148
NLM
Tavares TR, Javadi SH, Carvalho HWP de, Mouazen AM, Molin JP. Combined use of Vis-NIR and XRF sensors for tropical soil fertility analysis: assessing different data fusion approaches [Internet]. Sensors. 2021 ; 21 493-501.Available from: https://doi.org/10.3390/s21010148
Vancouver
Tavares TR, Javadi SH, Carvalho HWP de, Mouazen AM, Molin JP. Combined use of Vis-NIR and XRF sensors for tropical soil fertility analysis: assessing different data fusion approaches [Internet]. Sensors. 2021 ; 21 493-501.Available from: https://doi.org/10.3390/s21010148
Artigo de periodico
Sensor fusion with NARX neural network to predict the mass flow in a sugarcane harvester (2021)
Lima, Jeovano de Jesus Alves de; Maldaner, Leonardo Felipe ; Molin, José Paulo
Source: Sensors. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, CANA-DE-AÇÚCAR, COLHEDORAS, REDES NEURAIS, SENSOR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIMA, Jeovano de Jesus Alves de; MALDANER, Leonardo Felipe; MOLIN, José Paulo. Sensor fusion with NARX neural network to predict the mass flow in a sugarcane harvester. Sensors, Basel, v. 21, p. 1-14, 2021. Disponível em: < https://www.mdpi.com/1424-8220/21/13/4530 >.
APA
Lima, J. de J. A. de, Maldaner, L. F., & Molin, J. P. (2021). Sensor fusion with NARX neural network to predict the mass flow in a sugarcane harvester. Sensors, 21, 1-14. Recuperado de https://www.mdpi.com/1424-8220/21/13/4530
NLM
Lima J de JA de, Maldaner LF, Molin JP. Sensor fusion with NARX neural network to predict the mass flow in a sugarcane harvester [Internet]. Sensors. 2021 ; 21 1-14.Available from: https://www.mdpi.com/1424-8220/21/13/4530
Vancouver
Lima J de JA de, Maldaner LF, Molin JP. Sensor fusion with NARX neural network to predict the mass flow in a sugarcane harvester [Internet]. Sensors. 2021 ; 21 1-14.Available from: https://www.mdpi.com/1424-8220/21/13/4530
Artigo de periodico
Identification and measurement of gaps within sugarcane rows for site-specific management: Comparing different sensor-based approaches (2021)
Maldaner, Leonardo Felipe ; Molin, Jose Paulo ; Martello, Maurício ; Tavares, Tiago Rodrigues ; Dias, F.L.F
Source: Biosystems Engineering. Unidade: ESALQ
Subjects: AERONAVES NÃO TRIPULADAS, AGRICULTURA DE PRECISÃO, CANA-DE-AÇÚCAR, COLHEITA, MAPEAMENTO DO SOLO, SENSOR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALDANER, Leonardo Felipe; MOLIN, Jose Paulo; MARTELLO, Maurício; TAVARES, Tiago Rodrigues; DIAS, F.L.F. Identification and measurement of gaps within sugarcane rows for site-specific management: Comparing different sensor-based approaches. Biosystems Engineering, Amsterdam, v. 209, p. 64-73, 2021. Disponível em: < https://doi.org/10.1016/j.biosystemseng.2021.06.016 > DOI: 10.1016/j.biosystemseng.2021.06.016.
APA
Maldaner, L. F., Molin, J. P., Martello, M., Tavares, T. R., & Dias, F. L. F. (2021). Identification and measurement of gaps within sugarcane rows for site-specific management: Comparing different sensor-based approaches. Biosystems Engineering, 209, 64-73. doi:10.1016/j.biosystemseng.2021.06.016
NLM
Maldaner LF, Molin JP, Martello M, Tavares TR, Dias FLF. Identification and measurement of gaps within sugarcane rows for site-specific management: Comparing different sensor-based approaches [Internet]. Biosystems Engineering. 2021 ; 209 64-73.Available from: https://doi.org/10.1016/j.biosystemseng.2021.06.016
Vancouver
Maldaner LF, Molin JP, Martello M, Tavares TR, Dias FLF. Identification and measurement of gaps within sugarcane rows for site-specific management: Comparing different sensor-based approaches [Internet]. Biosystems Engineering. 2021 ; 209 64-73.Available from: https://doi.org/10.1016/j.biosystemseng.2021.06.016
Artigo de periodico
Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique (2021)
Canata, Tatiana Fernanda ; Wei, Marcelo Chan Fu ; Maldaner, Leonardo Felipe ; Molin, José Paulo
Source: Remote Sensing. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, IMAGEAMENTO DE SATÉLITE, SENSORIAMENTO REMOTO, CANA-DE-AÇÚCAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CANATA, Tatiana Fernanda; WEI, Marcelo Chan Fu; MALDANER, Leonardo Felipe; MOLIN, José Paulo. Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique. Remote Sensing, Basel, v. 13, p. 1-14, 2021. Disponível em: < https://doi.org/10.3390/rs13020232 > DOI: 10.3390/rs13020232.
APA
Canata, T. F., Wei, M. C. F., Maldaner, L. F., & Molin, J. P. (2021). Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique. Remote Sensing, 13, 1-14. doi:10.3390/rs13020232
NLM
Canata TF, Wei MCF, Maldaner LF, Molin JP. Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique [Internet]. Remote Sensing. 2021 ; 13 1-14.Available from: https://doi.org/10.3390/rs13020232
Vancouver
Canata TF, Wei MCF, Maldaner LF, Molin JP. Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique [Internet]. Remote Sensing. 2021 ; 13 1-14.Available from: https://doi.org/10.3390/rs13020232
Artigo de periodico
Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches (2021)
Maldaner, Leonardo Felipe ; Corrêdo, Lucas de Paula ; Canata, Tatiana Fernanda ; Molin, José Paulo
Source: Computers and Electronics in Agriculture. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, COMPUTACIONAL, CANA-DE-AÇÚCAR, COLHEDORAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALDANER, Leonardo Felipe; CORRÊDO, Lucas de Paula; CANATA, Tatiana Fernanda; MOLIN, José Paulo. Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches. Computers and Electronics in Agriculture, Amsterdam, v. 181, p. 1-9, 2021. Disponível em: < https://www.sciencedirect.com/science/article/pii/S0168169920331501?via%3Dihub > DOI: doi.org/10.1016/j.compag.2020.105945.
APA
Maldaner, L. F., Corrêdo, L. de P., Canata, T. F., & Molin, J. P. (2021). Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches. Computers and Electronics in Agriculture, 181, 1-9. doi:doi.org/10.1016/j.compag.2020.105945
NLM
Maldaner LF, Corrêdo L de P, Canata TF, Molin JP. Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches [Internet]. Computers and Electronics in Agriculture. 2021 ; 181 1-9.Available from: https://www.sciencedirect.com/science/article/pii/S0168169920331501?via%3Dihub
Vancouver
Maldaner LF, Corrêdo L de P, Canata TF, Molin JP. Predicting the sugarcane yield in real-time by harvester engine parameters and machine learning approaches [Internet]. Computers and Electronics in Agriculture. 2021 ; 181 1-9.Available from: https://www.sciencedirect.com/science/article/pii/S0168169920331501?via%3Dihub
Artigo de periodico
Near-infrared spectroscopy as a tool for monitoring the spatial variability of sugarcane quality in the fields (2021)
Corrêdo, Lucas de Paula ; Wei,Marcelo Chan Fu ; Ferraz, Marcos N; Molin, José Paulo
Source: Biosystems Engineering. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, CANA-DE-AÇÚCAR, ESPECTROSCOPIA INFRAVERMELHA, QUIMIOMETRIA, VARIABILIDADE ESPACIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CORRÊDO, Lucas de Paula; WEI, Marcelo Chan Fu; FERRAZ, Marcos N; MOLIN, José Paulo. Near-infrared spectroscopy as a tool for monitoring the spatial variability of sugarcane quality in the fields. Biosystems Engineering, Amsterdam, v. 206, p. 150-161, 2021. Disponível em: < https://www.sciencedirect.com/science/article/pii/S1537511021000854?via%3Dihub > DOI: doi.org/10.1016/j.biosystemseng.2021.04.001.
APA
Corrêdo, L. de P., Wei, M. C. F., Ferraz, M. N., & Molin, J. P. (2021). Near-infrared spectroscopy as a tool for monitoring the spatial variability of sugarcane quality in the fields. Biosystems Engineering, 206, 150-161. doi:doi.org/10.1016/j.biosystemseng.2021.04.001
NLM
Corrêdo L de P, Wei MCF, Ferraz MN, Molin JP. Near-infrared spectroscopy as a tool for monitoring the spatial variability of sugarcane quality in the fields [Internet]. Biosystems Engineering. 2021 ; 206 150-161.Available from: https://www.sciencedirect.com/science/article/pii/S1537511021000854?via%3Dihub
Vancouver
Corrêdo L de P, Wei MCF, Ferraz MN, Molin JP. Near-infrared spectroscopy as a tool for monitoring the spatial variability of sugarcane quality in the fields [Internet]. Biosystems Engineering. 2021 ; 206 150-161.Available from: https://www.sciencedirect.com/science/article/pii/S1537511021000854?via%3Dihub
Artigo de periodico
A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations (2021)
Maldaner, Leonardo Felipe ; Canata, Tatiana Fernanda ; Dias, Carlos Tadeu dos Santos ; Molin, José Paulo
Source: Scientia Agricola. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, GEOESTATÍSTICA, SATÉLITES ARTIFICIAIS, SISTEMA DE POSICIONAMENTO GLOBAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALDANER, Leonardo Felipe; CANATA, Tatiana Fernanda; DIAS, Carlos Tadeu dos Santos; MOLIN, José Paulo. A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations. Scientia Agricola, Piracicaba, v. 78, n. 5, p. 1-9, 2021. Disponível em: < https://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000500101&tlng=en > DOI: dx.doi.org/10.1590/1678-992x-2019-0252.
APA
Maldaner, L. F., Canata, T. F., Dias, C. T. dos S., & Molin, J. P. (2021). A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations. Scientia Agricola, 78( 5), 1-9. doi:dx.doi.org/10.1590/1678-992x-2019-0252
NLM
Maldaner LF, Canata TF, Dias CT dos S, Molin JP. A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations [Internet]. Scientia Agricola. 2021 ; 78( 5): 1-9.Available from: https://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000500101&tlng=en
Vancouver
Maldaner LF, Canata TF, Dias CT dos S, Molin JP. A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations [Internet]. Scientia Agricola. 2021 ; 78( 5): 1-9.Available from: https://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000500101&tlng=en
Artigo de periodico
Detection, classification, and mapping of coffee fruits during harvest with computer vision (2021)
Bazame, Helizani Couto ; Molin, José Paulo ; Althoff, Daniel; Martello, Maurício
Source: Computers and Electronics in Agriculture. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, CAFÉ, COLHEITA, MATURAÇÃO VEGETAL, REDES NEURAIS, VISÃO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BAZAME, Helizani Couto; MOLIN, José Paulo; ALTHOFF, Daniel; MARTELLO, Maurício. Detection, classification, and mapping of coffee fruits during harvest with computer vision. Computers and Electronics in Agriculture, Amsterdam, v. 183, p. 1-11, 2021. Disponível em: < https://doi.org/10.1016/j.compag.2021.106066 > DOI: 10.1016/j.compag.2021.106066.
APA
Bazame, H. C., Molin, J. P., Althoff, D., & Martello, M. (2021). Detection, classification, and mapping of coffee fruits during harvest with computer vision. Computers and Electronics in Agriculture, 183, 1-11. doi:10.1016/j.compag.2021.106066
NLM
Bazame HC, Molin JP, Althoff D, Martello M. Detection, classification, and mapping of coffee fruits during harvest with computer vision [Internet]. Computers and Electronics in Agriculture. 2021 ; 183 1-11.Available from: https://doi.org/10.1016/j.compag.2021.106066
Vancouver
Bazame HC, Molin JP, Althoff D, Martello M. Detection, classification, and mapping of coffee fruits during harvest with computer vision [Internet]. Computers and Electronics in Agriculture. 2021 ; 183 1-11.Available from: https://doi.org/10.1016/j.compag.2021.106066
Artigo de periodico
Soybean Yield Estimation and Its Components: A Linear Regression Approach (2020)
Wei, Marcelo Chan Fu ; Molin, José Paulo
Source: Agriculture. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, MODELOS MATEMÁTICOS, REGRESSÃO LINEAR, SOJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
WEI, Marcelo Chan Fu; MOLIN, José Paulo. Soybean Yield Estimation and Its Components: A Linear Regression Approach. Agriculture, Basel, v. 10, p. 1-13, 2020. Disponível em: < https://www.mdpi.com/2077-0472/10/8/348/htm > DOI: doi.org/10.3390/agriculture10080348.
APA
Wei, M. C. F., & Molin, J. P. (2020). Soybean Yield Estimation and Its Components: A Linear Regression Approach. Agriculture, 10, 1-13. doi:doi.org/10.3390/agriculture10080348
NLM
Wei MCF, Molin JP. Soybean Yield Estimation and Its Components: A Linear Regression Approach [Internet]. Agriculture. 2020 ; 10 1-13.Available from: https://www.mdpi.com/2077-0472/10/8/348/htm
Vancouver
Wei MCF, Molin JP. Soybean Yield Estimation and Its Components: A Linear Regression Approach [Internet]. Agriculture. 2020 ; 10 1-13.Available from: https://www.mdpi.com/2077-0472/10/8/348/htm
Artigo de periodico
Yield mapping methods for manually harvested crops (2020)
Colaço, A.F; Trevisan, R.G; Karp, F.H.S; Molin, Jose Paulo
Source: Computers and Electronics in Agriculture. Unidade: ESALQ
Subjects: COLHEITA, FRUTAS, HORTALIÇAS, MAPAS, PRODUTIVIDADE, SAFRA, VARIABILIDADE ESPACIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COLAÇO, A.F; TREVISAN, R.G; KARP, F.H.S; MOLIN, Jose Paulo. Yield mapping methods for manually harvested crops. Computers and Electronics in Agriculture, Amsterdam, v. 177, p. 1-14, 2020. Disponível em: < https://www.sciencedirect.com/science/article/pii/S0168169920315453?via%3Dihub#! > DOI: doi.org/10.1016/j.compag.2020.105693.
APA
Colaço, A. F., Trevisan, R. G., Karp, F. H. S., & Molin, J. P. (2020). Yield mapping methods for manually harvested crops. Computers and Electronics in Agriculture, 177, 1-14. doi:doi.org/10.1016/j.compag.2020.105693
NLM
Colaço AF, Trevisan RG, Karp FHS, Molin JP. Yield mapping methods for manually harvested crops [Internet]. Computers and Electronics in Agriculture. 2020 ; 177 1-14.Available from: https://www.sciencedirect.com/science/article/pii/S0168169920315453?via%3Dihub#!
Vancouver
Colaço AF, Trevisan RG, Karp FHS, Molin JP. Yield mapping methods for manually harvested crops [Internet]. Computers and Electronics in Agriculture. 2020 ; 177 1-14.Available from: https://www.sciencedirect.com/science/article/pii/S0168169920315453?via%3Dihub#!
Artigo de periodico
Pendulum-action spreader for lime application (2020)
Duarte, Cassio da Costa; Molin, José Paulo ; Wei, Marcelo Chan Fu ; Santos, Pedro Henrique
Source: Brazilian Journal of Development. Unidade: ESALQ
Subjects: ACIDEZ DO SOLO, CALCÁRIO, CALAGEM, EQUIPAMENTOS AGRÍCOLAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DUARTE, Cassio da Costa; MOLIN, José Paulo; WEI, Marcelo Chan Fu; SANTOS, Pedro Henrique. Pendulum-action spreader for lime application. Brazilian Journal of Development, Curitiba, PR, v. 6, n. Ju 2020, p. 41211-42222, 2020. Disponível em: < https://doi.org/10.34117/bjdv6n6-601 > DOI: 10.34117/bjdv6n6-601.
APA
Duarte, C. da C., Molin, J. P., Wei, M. C. F., & Santos, P. H. (2020). Pendulum-action spreader for lime application. Brazilian Journal of Development, 6( Ju 2020), 41211-42222. doi:10.34117/bjdv6n6-601
NLM
Duarte C da C, Molin JP, Wei MCF, Santos PH. Pendulum-action spreader for lime application [Internet]. Brazilian Journal of Development. 2020 ; 6( Ju 2020): 41211-42222.Available from: https://doi.org/10.34117/bjdv6n6-601
Vancouver
Duarte C da C, Molin JP, Wei MCF, Santos PH. Pendulum-action spreader for lime application [Internet]. Brazilian Journal of Development. 2020 ; 6( Ju 2020): 41211-42222.Available from: https://doi.org/10.34117/bjdv6n6-601
Artigo de periodico
Carrot yield mapping: a precision agriculture approach based on machine learning (2020)
Wei, Marcelo Chan Fu ; Maldaner, Leonardo Felipe ; Ottoni, Pedro Medeiros Netto; Molin, José Paulo
Source: AI. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, CENOURA, IMAGEAMENTO DE SATÉLITE, MAPAS, SENSORIAMENTO REMOTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
WEI, Marcelo Chan Fu; MALDANER, Leonardo Felipe; OTTONI, Pedro Medeiros Netto; MOLIN, José Paulo. Carrot yield mapping: a precision agriculture approach based on machine learning. AI, Basel, v. 1, n. 2, p. 229-241, 2020. Disponível em: < https://www.mdpi.com/2673-2688/1/2/15 > DOI: doi.org/10.3390/ai1020015.
APA
Wei, M. C. F., Maldaner, L. F., Ottoni, P. M. N., & Molin, J. P. (2020). Carrot yield mapping: a precision agriculture approach based on machine learning. AI, 1( 2), 229-241. doi:doi.org/10.3390/ai1020015
NLM
Wei MCF, Maldaner LF, Ottoni PMN, Molin JP. Carrot yield mapping: a precision agriculture approach based on machine learning [Internet]. AI. 2020 ; 1( 2): 229-241.Available from: https://www.mdpi.com/2673-2688/1/2/15
Vancouver
Wei MCF, Maldaner LF, Ottoni PMN, Molin JP. Carrot yield mapping: a precision agriculture approach based on machine learning [Internet]. AI. 2020 ; 1( 2): 229-241.Available from: https://www.mdpi.com/2673-2688/1/2/15
Artigo de periodico
Effect of X-Ray Tube Configuration on Measurement of Key Soil Fertility Attributes with XRF (2020)
Tavares, Tiago Rodrigues ; Molin, Jose Paulo ; Nunes, Lidiane Cristina ; Alves, Elton Eduardo Novais ; Melquiades, Fabio L; Carvalho, Hudson Wallace Pereira de ; Mouazen, Abdul Mounem
Source: Remote Sensing. Unidades: ESALQ, CENA
Subjects: AGRICULTURA DE PRECISÃO, ANÁLISE DO SOLO, FERTILIDADE DO SOLO, FLUORESCÊNCIA, RAIOS X, SENSOR, SOLO TROPICAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAVARES, Tiago Rodrigues; MOLIN, Jose Paulo; NUNES, Lidiane Cristina; et al. Effect of X-Ray Tube Configuration on Measurement of Key Soil Fertility Attributes with XRF. Remote Sensing, Basel, v. 12, p. 1-21, 2020. Disponível em: < https://doi.org/10.3390/rs12060963 > DOI: 10.3390/rs12060963.
APA
Tavares, T. R., Molin, J. P., Nunes, L. C., Alves, E. E. N., Melquiades, F. L., Carvalho, H. W. P. de, & Mouazen, A. M. (2020). Effect of X-Ray Tube Configuration on Measurement of Key Soil Fertility Attributes with XRF. Remote Sensing, 12, 1-21. doi:10.3390/rs12060963
NLM
Tavares TR, Molin JP, Nunes LC, Alves EEN, Melquiades FL, Carvalho HWP de, Mouazen AM. Effect of X-Ray Tube Configuration on Measurement of Key Soil Fertility Attributes with XRF [Internet]. Remote Sensing. 2020 ; 12 1-21.Available from: https://doi.org/10.3390/rs12060963
Vancouver
Tavares TR, Molin JP, Nunes LC, Alves EEN, Melquiades FL, Carvalho HWP de, Mouazen AM. Effect of X-Ray Tube Configuration on Measurement of Key Soil Fertility Attributes with XRF [Internet]. Remote Sensing. 2020 ; 12 1-21.Available from: https://doi.org/10.3390/rs12060963
Artigo de periodico
Economic viability, energy and nutrient balances of site-specific fertilisation for citrus (2020)
Colaço, André Freitas ; Pagliuca, Larissa G; Romanelli, Thiago Liborio ; Molin, Jose Paulo
Source: Biosystems Engineering. Unidade: ESALQ
Subjects: ADUBAÇÃO, AGRICULTURA DE PRECISÃO, BALANÇO DE ENERGIA, FRUTAS CÍTRICAS, LARANJA, NUTRIENTES MINERAIS DO SOLO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COLAÇO, André Freitas; PAGLIUCA, Larissa G; ROMANELLI, Thiago Liborio; MOLIN, Jose Paulo. Economic viability, energy and nutrient balances of site-specific fertilisation for citrus. Biosystems Engineering, Amsterdam, v. 200, p. 138-156, 2020. Disponível em: < https://doi.org/10.1016/j.biosystemseng.2020.09.007 > DOI: 10.1016/j.biosystemseng.2020.09.007.
APA
Colaço, A. F., Pagliuca, L. G., Romanelli, T. L., & Molin, J. P. (2020). Economic viability, energy and nutrient balances of site-specific fertilisation for citrus. Biosystems Engineering, 200, 138-156. doi:10.1016/j.biosystemseng.2020.09.007
NLM
Colaço AF, Pagliuca LG, Romanelli TL, Molin JP. Economic viability, energy and nutrient balances of site-specific fertilisation for citrus [Internet]. Biosystems Engineering. 2020 ; 200 138-156.Available from: https://doi.org/10.1016/j.biosystemseng.2020.09.007
Vancouver
Colaço AF, Pagliuca LG, Romanelli TL, Molin JP. Economic viability, energy and nutrient balances of site-specific fertilisation for citrus [Internet]. Biosystems Engineering. 2020 ; 200 138-156.Available from: https://doi.org/10.1016/j.biosystemseng.2020.09.007
Artigo de periodico
Sugarcane Harvester for In-field Data Collection:: State of the Art, Its Applicability and Future Perspectives (2020)
Corrêdo, Lucas de Paula ; Canata, Tatiana Fernanda ; Maldaner, Leonardo Felipe ; Lima, Jeovano de Jesus Alves de; Molin, José Paulo
Source: Sugar Tech. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, CANA-DE-AÇÚCAR, COLHEDORAS, SENSOR, VARIABILIDADE ESPACIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CORRÊDO, Lucas de Paula; CANATA, Tatiana Fernanda; MALDANER, Leonardo Felipe; LIMA, Jeovano de Jesus Alves de; MOLIN, José Paulo. Sugarcane Harvester for In-field Data Collection:: State of the Art, Its Applicability and Future Perspectives. Sugar Tech, Heidelberg, p. 1-14, 2020. Disponível em: < https://link.springer.com/article/10.1007%2Fs12355-020-00874-3 > DOI: doi.org/10.1007/s12355-020-00874-3.
APA
Corrêdo, L. de P., Canata, T. F., Maldaner, L. F., Lima, J. de J. A. de, & Molin, J. P. (2020). Sugarcane Harvester for In-field Data Collection:: State of the Art, Its Applicability and Future Perspectives. Sugar Tech, 1-14. doi:doi.org/10.1007/s12355-020-00874-3
NLM
Corrêdo L de P, Canata TF, Maldaner LF, Lima J de JA de, Molin JP. Sugarcane Harvester for In-field Data Collection:: State of the Art, Its Applicability and Future Perspectives [Internet]. Sugar Tech. 2020 ; 1-14.Available from: https://link.springer.com/article/10.1007%2Fs12355-020-00874-3
Vancouver
Corrêdo L de P, Canata TF, Maldaner LF, Lima J de JA de, Molin JP. Sugarcane Harvester for In-field Data Collection:: State of the Art, Its Applicability and Future Perspectives [Internet]. Sugar Tech. 2020 ; 1-14.Available from: https://link.springer.com/article/10.1007%2Fs12355-020-00874-3

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