Filtros : "Molin, José Paulo" Limpar

Filtros



Refine with date range


  • Source: Scientia Agricola. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, AMOSTRAGEM, CANA-DE-AÇÚCAR, MAPEAMENTO DO SOLO, MILHO, SENSOR, VARIABILIDADE ESPACIAL

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • 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
  • Source: Sensors. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, AMOSTRAGEM, CANA-DE-AÇÚCAR, ESPECTROSCOPIA INFRAVERMELHA, QUIMIOMETRIA, SENSOR

    Acesso à fonteDOIHow to cite
    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
  • Source: Sensors. Unidades: ESALQ, CENA

    Subjects: AGRICULTURA DE PRECISÃO, ESPECTROSCOPIA INFRAVERMELHA, FERTILIDADE DO SOLO, FLUORESCÊNCIA, RAIOS X, SENSOR, SOLO TROPICAL

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      TAVARES, Tiago Rodrigues; MOLIN, José Paulo; JAVADI, S. Hamed; CARVALHO, Hudson Wallace Pereira de; MOUAZEN, Abdul Mounem. 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., Molin, J. P., Javadi, S. H., Carvalho, H. W. P. de, & Mouazen, A. M. (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, Molin JP, Javadi SH, Carvalho HWP de, Mouazen AM. 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, Molin JP, Javadi SH, Carvalho HWP de, Mouazen AM. 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
  • Source: Remote Sensing. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, IMAGEAMENTO DE SATÉLITE, SENSORIAMENTO REMOTO, CANA-DE-AÇÚCAR

    Acesso à fonteDOIHow to cite
    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
  • Source: Scientia Agricola. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, GEOESTATÍSTICA, SATÉLITES ARTIFICIAIS, SISTEMA DE POSICIONAMENTO GLOBAL

    Versão PublicadaAcesso à fonteDOIHow to cite
    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
  • Source: Computers and Electronics in Agriculture. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, CAFÉ, COLHEITA, MATURAÇÃO VEGETAL, REDES NEURAIS, VISÃO COMPUTACIONAL

    Versão PublicadaAcesso à fonteDOIHow to cite
    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
  • Source: Agriculture. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, MODELOS MATEMÁTICOS, REGRESSÃO LINEAR, SOJA

    Versão PublicadaAcesso à fonteDOIHow to cite
    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
  • Source: Brazilian Journal of Development. Unidade: ESALQ

    Subjects: ACIDEZ DO SOLO, CALCÁRIO, CALAGEM, EQUIPAMENTOS AGRÍCOLAS

    Versão PublicadaAcesso à fonteDOIHow to cite
    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
  • Source: AI. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, CENOURA, IMAGEAMENTO DE SATÉLITE, MAPAS, SENSORIAMENTO REMOTO

    Versão PublicadaAcesso à fonteDOIHow to cite
    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
  • Source: Sugar Tech. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, CANA-DE-AÇÚCAR, COLHEDORAS, SENSOR, VARIABILIDADE ESPACIAL

    Acesso à fonteDOIHow to cite
    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
  • Source: Engenharia Agrícola. Unidade: ESALQ

    Subjects: CANA-DE-AÇÚCAR, MAPEAMENTO DO SOLO, SACAROSE, VARIABILIDADE ESPACIAL

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      FERRAZ, Marcos N; CORRÊDO, Lucas de Paula; WEI, Marcelo Chan Fu; MOLIN, José Paulo. Spatial variability mapping of sugarcane qualitative attributes. Engenharia Agrícola, Jaboticabal, v. 39, p. 109-117, 2019. Disponível em: < https://doi.org/10.1590/1809-4430-Eng.Agric.v39nep109-117/2019 > DOI: 10.1590/1809-4430-Eng.Agric.v39nep109-117/2019.
    • APA

      Ferraz, M. N., Corrêdo, L. de P., Wei, M. C. F., & Molin, J. P. (2019). Spatial variability mapping of sugarcane qualitative attributes. Engenharia Agrícola, 39, 109-117. doi:10.1590/1809-4430-Eng.Agric.v39nep109-117/2019
    • NLM

      Ferraz MN, Corrêdo L de P, Wei MCF, Molin JP. Spatial variability mapping of sugarcane qualitative attributes [Internet]. Engenharia Agrícola. 2019 ; 39 109-117.Available from: https://doi.org/10.1590/1809-4430-Eng.Agric.v39nep109-117/2019
    • Vancouver

      Ferraz MN, Corrêdo L de P, Wei MCF, Molin JP. Spatial variability mapping of sugarcane qualitative attributes [Internet]. Engenharia Agrícola. 2019 ; 39 109-117.Available from: https://doi.org/10.1590/1809-4430-Eng.Agric.v39nep109-117/2019
  • Source: Sensors. Unidades: CENA, ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, ESPECTROSCOPIA DE RAIO X, FERTILIDADE DO SOLO, NUTRIENTES MINERAIS DO SOLO

    Versão PublicadaAcesso à fonteDOIHow to cite
    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. Simplifying sample preparation for soil fertility analysis by x-ray fluorescence spectrometry. Sensors, Basel, v. 19, n. 23, p. 1-14, 2019. Disponível em: < https://doi.org/10.3390/s19235066 > DOI: 10.3390/s19235066.
    • APA

      Tavares, T. R., Molin, J. P., Nunes, L. C., Alves, E. E. N., Almeida, E. de, Maldaner, L. F., et al. (2019). Simplifying sample preparation for soil fertility analysis by x-ray fluorescence spectrometry. Sensors, 19( 23), 1-14. doi:10.3390/s19235066
    • NLM

      Tavares TR, Molin JP, Nunes LC, Alves EEN, Almeida E de, Maldaner LF, Krug FJ, Carvalho HWP de. Simplifying sample preparation for soil fertility analysis by x-ray fluorescence spectrometry [Internet]. Sensors. 2019 ; 19( 23): 1-14.Available from: https://doi.org/10.3390/s19235066
    • Vancouver

      Tavares TR, Molin JP, Nunes LC, Alves EEN, Almeida E de, Maldaner LF, Krug FJ, Carvalho HWP de. Simplifying sample preparation for soil fertility analysis by x-ray fluorescence spectrometry [Internet]. Sensors. 2019 ; 19( 23): 1-14.Available from: https://doi.org/10.3390/s19235066
  • Source: Engenharia Agrícola. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, ESPECTROSCOPIA, FERTILIDADE DO SOLO, MAPEAMENTO DO SOLO, SENSOR, SOLO TROPICAL, VARIABILIDADE ESPACIAL

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      MOLIN, José Paulo; TAVARES, Tiago Rodrigues. Sensor systems for mapping soil fertility attributes: challenges, advances, and perspectives in brazilian tropical soils. Engenharia Agrícola, Jaboticabal, v. 39, p. 126-147, 2019. Disponível em: < https://doi.org/10.1590/1809-4430-Eng.Agric.v39nep126-147/2019 > DOI: 10.1590/1809-4430-Eng.Agric.v39nep126-147/2019.
    • APA

      Molin, J. P., & Tavares, T. R. (2019). Sensor systems for mapping soil fertility attributes: challenges, advances, and perspectives in brazilian tropical soils. Engenharia Agrícola, 39, 126-147. doi:10.1590/1809-4430-Eng.Agric.v39nep126-147/2019
    • NLM

      Molin JP, Tavares TR. Sensor systems for mapping soil fertility attributes: challenges, advances, and perspectives in brazilian tropical soils [Internet]. Engenharia Agrícola. 2019 ; 39 126-147.Available from: https://doi.org/10.1590/1809-4430-Eng.Agric.v39nep126-147/2019
    • Vancouver

      Molin JP, Tavares TR. Sensor systems for mapping soil fertility attributes: challenges, advances, and perspectives in brazilian tropical soils [Internet]. Engenharia Agrícola. 2019 ; 39 126-147.Available from: https://doi.org/10.1590/1809-4430-Eng.Agric.v39nep126-147/2019
  • Source: Pesquisa Agropecuária Brasileira. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, PH DO SOLO, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO, ELETRODO

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      SILVA, Fernanda Cristina de Souza; MOLIN, José Paulo. On-the-go tropical soil sensing for pH determination using ion-selective electrodes. Pesquisa Agropecuária Brasileira, Brasília, v. 53, n. 11, p. 1189-1202, 2018. Disponível em: < http://dx.doi.org/10.1590/s0100-204x2018001100001 > DOI: 10.1590/s0100-204x2018001100001.
    • APA

      Silva, F. C. de S., & Molin, J. P. (2018). On-the-go tropical soil sensing for pH determination using ion-selective electrodes. Pesquisa Agropecuária Brasileira, 53( 11), 1189-1202. doi:10.1590/s0100-204x2018001100001
    • NLM

      Silva FC de S, Molin JP. On-the-go tropical soil sensing for pH determination using ion-selective electrodes [Internet]. Pesquisa Agropecuária Brasileira. 2018 ; 53( 11): 1189-1202.Available from: http://dx.doi.org/10.1590/s0100-204x2018001100001
    • Vancouver

      Silva FC de S, Molin JP. On-the-go tropical soil sensing for pH determination using ion-selective electrodes [Internet]. Pesquisa Agropecuária Brasileira. 2018 ; 53( 11): 1189-1202.Available from: http://dx.doi.org/10.1590/s0100-204x2018001100001
  • Source: Acta Scientiarum. Agronomy. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, COMPACTAÇÃO DOS SOLOS, MAPEAMENTO DO SOLO

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      PIAS, Osmar Henrique de Castro; CHERUBIN, Maurício Roberto; BASSO, Claudir José; et al. Soil penetration resistance mapping quality: effect of the number of subsamples. Acta Scientiarum. Agronomy, Maringá, v. 40, n. 1, p. 1-11, 2018. Disponível em: < http://dx.doi.org/10.4025/actasciagron.v40i1.34989 > DOI: 10.4025/actasciagron.v40i1.34989.
    • APA

      Pias, O. H. de C., Cherubin, M. R., Basso, C. J., Santi, A. L., Molin, J. P., & Bayer, C. (2018). Soil penetration resistance mapping quality: effect of the number of subsamples. Acta Scientiarum. Agronomy, 40( 1), 1-11. doi:10.4025/actasciagron.v40i1.34989
    • NLM

      Pias OH de C, Cherubin MR, Basso CJ, Santi AL, Molin JP, Bayer C. Soil penetration resistance mapping quality: effect of the number of subsamples [Internet]. Acta Scientiarum. Agronomy. 2018 ; 40( 1): 1-11.Available from: http://dx.doi.org/10.4025/actasciagron.v40i1.34989
    • Vancouver

      Pias OH de C, Cherubin MR, Basso CJ, Santi AL, Molin JP, Bayer C. Soil penetration resistance mapping quality: effect of the number of subsamples [Internet]. Acta Scientiarum. Agronomy. 2018 ; 40( 1): 1-11.Available from: http://dx.doi.org/10.4025/actasciagron.v40i1.34989
  • Source: Precision Agriculture. Unidade: ESALQ

    Subjects: SENSORES ÓPTICOS, FERTILIZANTES NITROGENADOS, CANA-DE-AÇÚCAR

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      AMARAL, Lucas R; TREVISAN, Rodrigo G; MOLIN, José Paulo. Canopy sensor placement for variable-rate nitrogen application in sugarcane fields. Precision Agriculture, New York, v. 19, p. 147–160, 2018. Disponível em: < http://dx.doi.org/10.1007/s11119-017-9505-x > DOI: 10.1007/s11119-017-9505-x.
    • APA

      Amaral, L. R., Trevisan, R. G., & Molin, J. P. (2018). Canopy sensor placement for variable-rate nitrogen application in sugarcane fields. Precision Agriculture, 19, 147–160. doi:10.1007/s11119-017-9505-x
    • NLM

      Amaral LR, Trevisan RG, Molin JP. Canopy sensor placement for variable-rate nitrogen application in sugarcane fields [Internet]. Precision Agriculture. 2018 ; 19 147–160.Available from: http://dx.doi.org/10.1007/s11119-017-9505-x
    • Vancouver

      Amaral LR, Trevisan RG, Molin JP. Canopy sensor placement for variable-rate nitrogen application in sugarcane fields [Internet]. Precision Agriculture. 2018 ; 19 147–160.Available from: http://dx.doi.org/10.1007/s11119-017-9505-x
  • Source: Precision Agriculture. Unidade: ESALQ

    Subjects: ADUBAÇÃO, FRUTAS CÍTRICAS, INSUMOS AGRÍCOLAS

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      COLAÇO, A. F; MOLIN, José Paulo. Variable rate fertilization in citrus: a long term study. Precision Agriculture, Dordrecht, v. 18, n. 2, p. 169–191, 2017. Disponível em: < http://link.springer.com/article/10.1007%2Fs11119-016-9454-9 > DOI: 10.1007/s11119-016-9454-9.
    • APA

      Colaço, A. F., & Molin, J. P. (2017). Variable rate fertilization in citrus: a long term study. Precision Agriculture, 18( 2), 169–191. doi:10.1007/s11119-016-9454-9
    • NLM

      Colaço AF, Molin JP. Variable rate fertilization in citrus: a long term study [Internet]. Precision Agriculture. 2017 ;18( 2): 169–191.Available from: http://link.springer.com/article/10.1007%2Fs11119-016-9454-9
    • Vancouver

      Colaço AF, Molin JP. Variable rate fertilization in citrus: a long term study [Internet]. Precision Agriculture. 2017 ;18( 2): 169–191.Available from: http://link.springer.com/article/10.1007%2Fs11119-016-9454-9
  • Source: Acta Scientiarum. Agronomy. Unidade: ESALQ

    Subjects: AGRICULTURA DE PRECISÃO, AMOSTRAGEM, CANA-DE-AÇÚCAR, DISTRIBUIÇÃO ESPACIAL

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      PAVLÚ, Franz Arthur; MOLIN, José Paulo. A sampling plan and spatial distribution for site-specific control of Sphenophorus levis in sugarcane. Acta Scientiarum. Agronomy, Maringá, v. 38, n. 3, p. 279-287, 2016. Disponível em: < http://dx.doi.org/10.4025/actasciagron.v38i3.28599 > DOI: 10.4025/actasciagron.v38i3.28599.
    • APA

      Pavlú, F. A., & Molin, J. P. (2016). A sampling plan and spatial distribution for site-specific control of Sphenophorus levis in sugarcane. Acta Scientiarum. Agronomy, 38( 3), 279-287. doi:10.4025/actasciagron.v38i3.28599
    • NLM

      Pavlú FA, Molin JP. A sampling plan and spatial distribution for site-specific control of Sphenophorus levis in sugarcane [Internet]. Acta Scientiarum. Agronomy. 2016 ; 38( 3): 279-287.Available from: http://dx.doi.org/10.4025/actasciagron.v38i3.28599
    • Vancouver

      Pavlú FA, Molin JP. A sampling plan and spatial distribution for site-specific control of Sphenophorus levis in sugarcane [Internet]. Acta Scientiarum. Agronomy. 2016 ; 38( 3): 279-287.Available from: http://dx.doi.org/10.4025/actasciagron.v38i3.28599
  • Source: Computers and Electronics in Agriculture. Unidade: ESALQ

    Subjects: SISTEMA DE INFORMAÇÃO GEOGRÁFICA, ESCOAMENTO, EROSÃO, CULTIVO EM FAIXA, MÁQUINAS AGRÍCOLAS

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      SPEKKEN, Mark; BRUIN, Sytze de; MOLIN, José Paulo; SPAROVEK, Gerd. Planning machine paths and row crop patterns on steep surfaces to minimize soil erosion. Computers and Electronics in Agriculture, Oxford, v. 124, p. 194–210, 2016. Disponível em: < http://www.sciencedirect.com/science/article/pii/S0168169916300825 > DOI: 10.1016/j.compag.2016.03.013.
    • APA

      Spekken, M., Bruin, S. de, Molin, J. P., & Sparovek, G. (2016). Planning machine paths and row crop patterns on steep surfaces to minimize soil erosion. Computers and Electronics in Agriculture, 124, 194–210. doi:10.1016/j.compag.2016.03.013
    • NLM

      Spekken M, Bruin S de, Molin JP, Sparovek G. Planning machine paths and row crop patterns on steep surfaces to minimize soil erosion [Internet]. Computers and Electronics in Agriculture. 2016 ; 124 194–210.Available from: http://www.sciencedirect.com/science/article/pii/S0168169916300825
    • Vancouver

      Spekken M, Bruin S de, Molin JP, Sparovek G. Planning machine paths and row crop patterns on steep surfaces to minimize soil erosion [Internet]. Computers and Electronics in Agriculture. 2016 ; 124 194–210.Available from: http://www.sciencedirect.com/science/article/pii/S0168169916300825
  • Source: Ciência Rural. Unidade: ESALQ

    Subjects: SOJA, BALANÇO DE ENERGIA, SOLO DE VÁRZEA

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      ANDREA, Maria Carolina da Silva; ROMANELLI, Thiago Libório; MOLIN, José Paulo. Energy flows in lowland soybean production system in Brazil. Ciência Rural, Santa Maria, v. 46, n. 8, p. 1395-1400, 2016. Disponível em: < http://www.scielo.br/pdf/cr/v46n8/1678-4596-cr-0103_8478cr20151298.pdf > DOI: 10.1590/0103-8478cr20151298.
    • APA

      Andrea, M. C. da S., Romanelli, T. L., & Molin, J. P. (2016). Energy flows in lowland soybean production system in Brazil. Ciência Rural, 46( 8), 1395-1400. doi:10.1590/0103-8478cr20151298
    • NLM

      Andrea MC da S, Romanelli TL, Molin JP. Energy flows in lowland soybean production system in Brazil [Internet]. Ciência Rural. 2016 ; 46( 8): 1395-1400.Available from: http://www.scielo.br/pdf/cr/v46n8/1678-4596-cr-0103_8478cr20151298.pdf
    • Vancouver

      Andrea MC da S, Romanelli TL, Molin JP. Energy flows in lowland soybean production system in Brazil [Internet]. Ciência Rural. 2016 ; 46( 8): 1395-1400.Available from: http://www.scielo.br/pdf/cr/v46n8/1678-4596-cr-0103_8478cr20151298.pdf

Digital Library of Intellectual Production of Universidade de São Paulo     2012 - 2021