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Development of methods for remotely sensing grass growth to enable precision application of nitrogen fertilizer

Published online by Cambridge University Press:  01 June 2017

P.M. Berry ,
H.F. Holmes  and
C. Blacker
P.M. Berry*
Affiliation:
ADAS High Mowthorpe, Duggleby, Malton, N Yorkshire YO178BP, UK
H.F. Holmes
Affiliation:
ADAS Boxworth, Boxworth, Cambridge CB234NN, UK
C. Blacker
Affiliation:
Precision Decisions, Shipton by Beningbrough, York, North Yorkshire, YO301BS, UK
*
† E-mail: pete.berry@adas.co.uk
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Abstract

A ‘chessboard’ field experiment set up to investigate how the yield response to nitrogen (N) fertiliser varied spatially within a field in the UK indicated that the optimum N rate varied substantially by up to 100 kg N/ha within the three hectare experimental area. Variation in N optima was negatively related to the soil N supply. However, soil N supply, yield potential and apparent fertiliser recovery rate were inter-related which meant that the influence of each element on N optima was complex. Spectral reflectance indices related well to crop N uptake and could be used to help estimate soil N supply.

Keywords

grassnitrogen fertiliseroptimum fertiliser ratevariable rate technology

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References

Alberda, T 1977. Possibilities of dry matter production from forage plants under different climatic conditions. In Proceedings of the 13th International Grassland Congress E, WOjahn and H Thons (eds), 18–27. MayLeipzig, Germany, pp. 61–69.Google Scholar
Defra 2010. Fertiliser Manual (RB209), 8th Edition. The Stationery Office, Norwich, UK.Google Scholar
Kindred, DR, Hatley, D, Ginsburg, D, Catalayud, A, Storer, K, Wilson, L, Hockridge, B, Milne, A, Marchant, B, Miller, P and Sylvester-Bradley, R 2016. Automating nitrogen fertiliser management for cereals (Auto-N). AHDB Project Report No. 561, UK. 196 pp.Google Scholar
Pullanagari, RR, Yule, IJ, Tuohy, MP, Hedley, MJ, Dynes, RA and King, WM 2013. Proximal sensing of the seasonal variability of pasture nutritive value using multispectral radiometry. Grass Forage Science 68, 110–119.Google Scholar
Sylvester-Bradley, R, Berry, PM, Wiseman, J and Cottrill, B 2005. Yields of UK crops and livestock: physiological and technological constraints, and expectations of progress to 2050’. DEFRA Project No. IS0210. Final Report, 21 pp, UK.Google Scholar