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EVALUATION OF FLAT AND VARIABLE RATE NITROGEN APPLICATION EFFECT ON WINTER WHEAT YIELD ON THE BASIS OF YIELD MAPS
Abstract
The main aim of this work was to evaluate the effect of flat (UNI) and variable application (VRA) of mineral nitrogen fertilizers (NF) on the yield of winter wheat grain using yield maps. VRA NF technologies represent a wide range of procedures and processes that are a part of precision farming. The technologies are used to optimize the applied NF dose in order to fertilize high-yield crops with regard to their nutritional needs and the condition of the land where they are located. VRA NF on winter wheat fields were made based on application maps that were prepared in a SatAgro system. All application maps were prepared based on spectral analysis of satellite images (Sentinel 2, SPOT) taken maximum 5 days before the scheduled application. The selected application maps contained at least one 60 m long control strip where the UNI application of NF was implemented. VRA NF was used for production and qualitative fertilization of winter wheat. The yield principle was used for both applications, i.e. the highest doses of NF were applied to those parts of the land where the vegetation was the most abundant and vice versa. The hypothesis was that weak parts of the crop are not able to withdraw the same amount of N as the stronger ones. The variability in the NF dose between zones was 30%. The field experiment was established in Spearhead Czech Ltd., where selected VRA technologies were used for approximately 5,000 ha in 2018. The main parameters for the assessment of VRA NF effect were grain yield (GY) and grain quality (gluten and N-compounds content). GY was detected using yield maps which are based on harvester data and calibrated according to total yield weight. In all years of the experiment, a significant positive effect (LSD, at level of significance P < 0.05) of VRA NF on grain yield was found. The difference in yield when comparing UNI and VRA technology has always been minimum 6% in favor of VRA. Grain quality was at a similar level in both variants, no negative effect of VRA technology on gluten and N-compounds content was found.
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Fu Y., Yang G., Wang J., Song X., Feng H., Winter wheat biomass estimation based on spectral indices, band depth analysis and partial least squares regression using hyperspectral measurements, Computers and Electronics in Agriculture, GB, 2014, vol. 100, pp. 51-59.
Li F., Mistele B., Hu Y., Chen X., Schmidhalter U., Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression, European Journal of Agronomy, NL, 2014, vol. 52, pp. 198-209.
Hatfield J.L., Gitelson A.A., Schepers J.S., Walthall C.L., Application of spectral remote sensing for agronomic decisions, Agronomy Journal, USA, 2008, vol.100, pp. 117-131.
Corwin D.L., Plant R.E., Applications of apparent soil electrical conductivity in precision agriculture, Computers and Electronics in Agriculture, GB, 2005, vol. 46, pp. 1–10.
Rouse J.W., Haas R.H., Schell J.A., Deering D.W., 1974. Monitoring vegetation systems in the Great Plains with ERTS, In: Freden S.C., Mercanti E.P., Becker M. (eds), Third Earth Resources Technology Satellite–1 Syposium. Volume I: Technical Presentations, NASA SP-351, NASA, Washington, D.C., USA, pp. 309- 317.
Söderström M., Stadig H.., Martinsson J., Piikki K., Stenberg M., CropSAT – A public satellite-based decision support system for variable-rate nitrogen fertilization in Scandinavia, 13th International Conference on Precision Agriculture (ICPA), At St Louis, USA, 2016, pp. 1-8.
Kaivosoja J., Näsi R., Hakala T., Viljanen N., Honkavaara E., Different remote sensing data in relative biomass determination and in precision fertilization task generation for cereal crops, Communications in Computer and Information Science, USA, 2019, vol 953, pp. 164-176.
I SO 1871:2009, Food and feed products - General guidelines for the determination of nitrogen by the Kjeldahl method, International Organization for Standardization, CH, 2009, 7 p.
ISO 21415-1:2006, Wheat and wheat flour - Gluten content - Part 1: Determination of wet gluten by a manual method, International Organization for Standardization, CH, 2006, 9 p.
Charf P.C., Kitchen N. R., Sudduth K. A., Davis J. G., Hubbard V. C., Lory J. A., Field-scale variability in optimal nitrogen fertilizer rate for corn, Agronomy Journal, USA, 2005, vol. 97/issue 2, pp. 452-461.
Baso B., Dumont B., Cammarano D., Pezzuolo A., Marinello F., Sartori L., Environmental and economic benefits of variable rate nitrogen fertilization in a nitrate vulnerable zone, Science of The Total Environment, NL, 2016, vol. 545- 546, pp. 227-235.
Shanahan J.F., Kitchen N. R., Raun W. R., Schepers J. S., Responsive in-season nitrogen management for cereals, Computers and Electronics in Agriculture, GB, 2008, vol. 61, pp. 51-62.
Algerbo P.A., Thylén L., Variable nitrogen application: effects on crop yield and quality, In: Robert P.C., Rust R.H., Larson W.E. (eds), Precision Agriculture, ASA, CSSA, SSSA, Madison, USA, 1999, vol. 51, pp. 709-718.
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