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A strategy to instigate SSCM in Australian potato production

Published online by Cambridge University Press:  01 June 2017

B. M. Whelan*
Affiliation:
Precision Agriculture Laboratory, Sydney Institute of Agriculture, University of Sydney, NSW Australia
F. Mulcahy
Affiliation:
Simplot Australia Pty Ltd, Wesley Vale, Tasmania, Australia
*
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Abstract

To explore the potential for site-specific crop management in Australian potato production, soil apparent electrical conductivity (ECa) and high resolution elevation data were used to first define the variation in soil and landscape resources in two regions in Tasmania. Variation in crop production was estimated using in-season aerial multispectral VIS-NIR reflectance measurements and then measured using a first generation on-harvester yield monitoring system. During the season, soil and crop physical, chemical and pathogen properties were measured to groundtruth the sensor-derived data. Substantial within-field and between field variation was found in soil physical, chemical and pathogen properties, elevation and crop yield. The average potato yield for the study fields was 64 t/ha, with over three-fold within-field variation recorded. The in-season aerial crop reflectance significantly correlated with soil physical variability and pathogen load when gathered early in the season and to variation in plant physical and chemical properties, as well as important soil nutrient properties and crop yield when gathered from week 14 onwards. A set of general rules for instigating Site-specific crop management (SSCM) in potato production has been devised based initially on nutrient and pathogen management with irrigation management as an option.

Type
PA in practice
Copyright
© The Animal Consortium 2017 

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References

Bramley, RGV 2001. Progress in the development of precision viticulture - Variation in yield, quality and soil properties in contrasting Australian vineyards. In: Precision tools for improving land management, edited by LD Currie and P Loganathan, Occasional Report 14. Fertilizer and Lime Research Centre, Massey University, Palmerston North, pp. 25–43.Google Scholar
Cambouris, AN, Zebath, BJ, Ziadi, N and Perron, I 2014. Precision agriculture in potato production. Potato Research 57, 249262.CrossRefGoogle Scholar
Cotching, WE, Sparrow, LA, Hawkins, K, McCorkell, BE and Rowley, W 2005. Linking Tasmanian potato and poppy yields to selected soil physical and chemical properties. Australian Journal of Experimental Agriculture 44, 12411249.CrossRefGoogle Scholar
Hartigan, JA and Wong, MA 1979. Algorithm AS136: A k-means clustering algorithm. Applied Statistics 28, 100108.CrossRefGoogle Scholar
Jaynes, DB 1996. Improved soil mapping using electromagnetic induction surveys. In Precision Agriculture: Proceedings of the 3rd International Conference on Precision Agriculture, edited by PC Robert, RH Rust and WE Larson, ASA, Madison. pp. 169180.Google Scholar
Khosla, R, Inman, D, Westfall, DG, Reich, RM, Frasier, M, Mzuku, M, Koch, B and Hornung, A 2008. A synthesis of multi-disciplinary research in precision agriculture: Site-specific management zones in the semi-arid western Great Plains of the USA. Precision Agriculture 9, 85100.CrossRefGoogle Scholar
Moore, ID, Gessler, PE, Nielsen, GA and Peterson, GA 1993. Terrain analysis for soil specific crop management. In Soil-Specific Crop Management: Proceedings of a Workshop on Research and Development Issues, edited by PC Robert, RH Rust and WE Larson, ASA, Madison. pp. 2755.Google Scholar
Robertson, MJ, Llewellyn, RS, Mandel, R, Lawes, R, Bramley, RGV, Swift, L, Metz, L and O’Callaghan, C 2012. Adoption of variable-rate fertiliser application in the Australian grains industry: status, issues and prospects. Precision Agriculture 12, 181199.CrossRefGoogle Scholar
Rud, R, Cohen, Y, Alchanatis, V, Dar, Z, Levi, A, Brikman, R, Shenderey, C, Heuer, B, Markovits, T and Mulla Dand Rosen, C 2013. The potential of CWSI based on thermal imagery for in-season irrigation management in potato fields. In Precision Agriculture ‘13, Proceedings of the 9th European Conference on Precision Agriculture, Uppsala, Sweden, edited by JV Stafford, Wageningen Academic Publishers, The Netherlands. pp. 721726.Google Scholar
Simard, RR, Nolin, MC and Cambouris, AN 1998. Application of precision farming to potato production in Quebec. Better Crops 82, 2224.Google Scholar
Sudduth, KA, Drummond, ST, Birrell, SJ and Kitchen, NR 1996. Analysis of spatial factors influencing crop yield. In Precision Agriculture: Proceedings of the 3rd International Conference on Precision Agriculture, edited by PC Robert, RH Rust and WE Larson, ASA, Madison. pp. 129140.Google Scholar
Taylor, JA, McBratney, AB and Whelan, BM 2007. Establishing management classes for broadacre agriculture production. Agronomy Journal 99, 13661376.CrossRefGoogle Scholar
Whelan, BM and McBratney, AB 2003. Definition and interpretation of potential management zones in Australia.Proceedings of the 11th Australian Agronomy Conference. Geelong, Australia. 11p.Google Scholar
Wijkmark, L, Lindholm, Rand and Nissen, K 2005. Uniform potato quality with site-specific potassium application. In Precision Agriculture ‘05, Proceedings of the 5th European Conference on Precision Agriculture, Uppsala, Sweden, edited by JV Stafford, Wageningen Academic Publishers, The Netherlands. pp. 393400.Google Scholar