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Conceptual Spatial Crop Models for Potato Production

Published online by Cambridge University Press:  01 June 2017

H. Chen ,
I. Leinonen ,
B. Marshall  and
J.A. Taylor
H. Chen*
Affiliation:
School of Agriculture, Food and Rural Development, Newcastle University, NE1 7RU, UK
I. Leinonen
Affiliation:
School of Agriculture, Food and Rural Development, Newcastle University, NE1 7RU, UK
B. Marshall
Affiliation:
Consultant, 5 Muirloch Farm Cottage, Liff, Dundee, DD2 5NQ, UK
J.A. Taylor
Affiliation:
School of Agriculture, Food and Rural Development, Newcastle University, NE1 7RU, UK
*
†Email: hongyan.chen@newcastle.ac.uk
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Abstract

Advances in agricultural machinery, information and sensor technology have led to an increasing amount of data that is available spatially both pre and within season. The case is compelling for the spatialisation of existing, non-spatial (field-scale) crop models that can accommodate this ‘big data’ and lead to more precise predictions of yield and quality and an improved field management. This study explores the conceptual spatial models based on the potato crop models that simulate crop physical and physiological processes and predict yields and graded yields at a field-scale. Through exploring the possible spatial scales and model application approaches considering spatial variation an optimal and more effective solution is expected. Issues concerning model quality and uncertainty are also discussed.

Keywords

crop model spatialisationspatial autocorrelationspatial stratified heterogeneity
Type
Spatial Crop Models
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 678 - 683
Copyright
© The Animal Consortium 2017 

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