La Organización de las Naciones Unidas para la Alimentación y la Agricultura estima que el 95% de la producción de alimentos proviene de los suelos. Cuidar este recurso es una de las mayores prioridades de la humanidad. En Bayer, la sustentabilidad es parte de todo lo que hacemos , ya que el objetivo siempre es el mismo: producir más con menos, en la misma superficie.
Ciarlo, E. A., Muschietti, M. D. P., Peralta, N., Comparín, M., Gregorini, F., Cipriotti, P. A., & Giuffre, L. (2020). Spatial variability of soil properties: Effect of land use and type. Ciencia del Suelo, 38(2), 249-261. Scopus.
Cicore, P. L., Franco, M. C., Peralta, N. R., Marques da Silva, J. R., & Costa, J. L. (2019). Relationship between soil apparent electrical conductivity and forage yield in temperate pastures according to nitrogen availability and growing season. Crop and Pasture Science, 70(10), 908. https://doi.org/10.1071/CP19224
Muschietti-Piana, M. del P., Cipriotti, P. A., Urricariet, S., Peralta, N. R., & Niborski, M. (2018). Using site-specific nitrogen management in rainfed corn to reduce the risk of nitrate leaching. Agricultural Water Management, 199, 61-70. https://doi.org/10.1016/j.agwat.2017.12.002
Peralta, N., Assefa, Y., Du, J., Barden, C., & Ciampitti, I. (2016). Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield. Remote Sensing, 8(12), 848. https://doi.org/10.3390/rs8100848
Schwalbert, R., Amado, T., Nieto, L., Corassa, G., Rice, C., Peralta, N., Schauberger, B., Gornott, C., & Ciampitti, I. (2020a). Mid-season county-level corn yield forecast for US Corn Belt integrating satellite imagery and weather variables. Crop Science, 60(2), 739-750. Scopus. https://doi.org/10/gk3t9f
Schwalbert, R., Amado, T., Nieto, L., Corassa, G., Rice, C., Peralta, N., Schauberger, B., Gornott, C., & Ciampitti, I. (2020b). Mid‐season county‐level corn yield forecast for US Corn Belt integrating satellite imagery and weather variables. Crop Science, 60(2), 739-750. https://doi.org/10.1002/csc2.20053
Varela, S., Assefa, Y., Vara Prasad, P. V., Peralta, N. R., Griffin, T. W., Sharda, A., Ferguson, A., & Ciampitti, I. A. (2017). Spatio-temporal evaluation of plant height in corn via unmanned aerial systems. Journal of Applied Remote Sensing, 11(03), 1. https://doi.org/10.1117/1.JRS.11.036013
Varela, S., Dhodda, R. P., Hsu, H. W., Prasad, V. P. V., Assefa, Y., Peralta, R. N., Griffin, T., Sharda, A., Ferguson, A., & Ciampitti, A. I. (2018). Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques. Remote Sensing, 10(2). https://doi.org/10.3390/rs10020343