Skip to main content Skip to main navigation menu Skip to site footer
Scientific Electronic Archives
Agricultural Science
DOI: 10.36560/13820201015
Submitted: 2019-11-17
Published: 2020-07-31

Approaching of GOPRO camera embedded on UAV to calculate NDVI for corn’s crop

Universidade Federal de Sergipe/Departamento de Engenharia Agrícola
Embrapa Tabuleiros Costeiros - Embrapa Coastal Tablelands
Universidade Federal de Sergipe/Departamento de Engenharia Agrícola
Universidade Federal de Sergipe/Departamento de Engenharia Agrícola
Aerial imaging GreenSeeker sensor Remote Sensing

Abstract

Nitrogen (N) is a macronutrient used in large quantities in modern agriculture, due to a quantity required by plants. In the corn crop, it mainly acts on grain filling and affects protein content. One of the causes of the inefficiency of the use of nitrogen fertilizers in the corn crop is the difficulty in estimating in a timely manner the need of nitrogen fertilization through soil and / or plant analyzes. Looking for feasibility of the recommendation process of nitrogen fertilization in real time, researches has been developed aiming to detect nitrogen deficiency using remote sensing. In this paper the objective was to evaluate the feasibility of the use of the Normalized Difference Vegetation Index (NDVI), calculated by means of multispectral image processing obtained with the GOPRO’s camera and the Micasense’s Seqouia camera, embedded in UAV’s, to recommend the application of nitrogen fertilizers to the corn crop. According to results obtained with this paper, it was possible to conclude that the determination of NDVI by means of aerial images is compatible with the determination of the index using active optical sensor (GreenSeeker).

References

  1. AMADO, T. J. C., VILLALBA, E. O. H., BORTOLOTTO, R. P., NORA, D. D., BRAGAGNOLO, J., & LEÓN, E. A. B. Yield and nutritional efficiency of corn in response to rates and splits of nitrogen fertilization. Revista Ceres, 64(4), 351-359, 2017. https://dx.doi.org/10.1590/0034-737x201764040003
  3. BASYOUNI, R., DUNN, B. L., GOAD, C. The use of nondestructive sensors to assess nitrogen status in potted dianthus (Dianthus chinensis L.) production. Canadian Journal of Plant Science, 2017, 97:44-52, https://doi.org/10.1139/cjps-2016-0059
  4. DAVID, M. Use of normalized difference vegetation index (NDVI) for estimating genotypic differences in wheat seedlings response to water stress induced by gradual drying of the substrate, Romanian agricultural research, Romenia, 2019.
  5. FRANZEN, D.W., E.C. SCHULTZ, T.M. DESUTTER, L.K. SHARMA, R. ASHLEY, AND H. BU. Sunflower Type Influences Yield Prediction using Active Optical Sensors. Agron. J. 2019. 111:881-888. doi: https://doi.org/10.2134/agronj2018.07.0440
  6. GROHS, D. S., BREDEMEIER, C., MUNDSTOCK, C. M., & POLETTO, N. Modelo para estimativa do potencial produtivo em trigo e cevada por meio do sensor GreenSeeker. Engenharia Agrícola, 29(1), 101-112, 2009. https://dx.doi.org/10.1590/S0100-69162009000100011
  7. WALSH, O. S. Nitrogen Management in Field Crops with Reference Strips and Crop Sensor. University of Idaho, BUL 896, 2015.
  8. LONGCHAMPS, L. & KHOSLA R. Early detection of Nitrogen variability in maize using fluorescence. Agronomy Journal, 106:511-518, 2014. doi: https://doi.org/10.2134/agronj2013.0218
  9. MACHADO, M. L., PINTO, F. A. C., QUEIROZ, D. M., PAULA JÚNIOR, T. J., & VIEIRA, R. F. Estimativa de severidade do mofo-branco em lavouras de feijão utilizando-se sensores hiper e multiespectral. Revista Brasileira de Engenharia Agrícola e Ambiental, 19(5), 426-432, 2015. https://dx.doi.org/10.1590/1807-1929/agriambi.v19n5p426-432
  10. MOTOMIYA, A. V. A.; MOLIN, J. P.; CHIAVEGATO, E. J. Utilização de sensor óptico ativo para detectar deficiência foliar de nitrogênio em algodoeiro. Revista Brasileira de Engenharia Agrícola e Ambiental, 13(2), 137-145, (2009). https://dx.doi.org/10.1590/S1415-43662009000200005
  11. RAUN, W. R., SOLIE, J. B., STONE, M. L., MARTIN, K. L., FREEMAN, K. W., MULLEN, R. W. ZHANG, H. SCHEPERS, J. S. & JHONSON, G. V. Optical sensorâ€based algorithm for crop nitrogen fertilization. Communications in Soil Science and Plant Analysis, v. 36, n. 19-20, p. 2759-2781, 2005. doi: https://doi.org/10.1080/00103620500303988

How to Cite

Santos, A. M., Pacheco, E. P., Vale, W. G., & Chaves, M. V. S. (2020). Approaching of GOPRO camera embedded on UAV to calculate NDVI for corn’s crop. Scientific Electronic Archives, 13(8), 18–23. https://doi.org/10.36560/13820201015