Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability

While precision agriculture (PA) technologies are widely used in cropping systems, these technologies have received less attention in mixed farming systems. Little is known about the nature, extent, and temporal stability of spatial variability of pastures in mixed farming systems and the feasibilit...

Full description

Bibliographic Details
Main Authors: McEntee, P.J., Bennett, Sarita, Belford, R.K.
Format: Journal Article
Published: 2019
Online Access:http://hdl.handle.net/20.500.11937/75972
_version_ 1848763591908392960
author McEntee, P.J.
Bennett, Sarita
Belford, R.K.
author_facet McEntee, P.J.
Bennett, Sarita
Belford, R.K.
author_sort McEntee, P.J.
building Curtin Institutional Repository
collection Online Access
description While precision agriculture (PA) technologies are widely used in cropping systems, these technologies have received less attention in mixed farming systems. Little is known about the nature, extent, and temporal stability of spatial variability of pastures in mixed farming systems and the feasibility of managing this variability. This paper describes a technique to create a Stability Index based on both crop grain yield and pasture total green dry matter (TGDM) production over time, using high resolution spatial data in two climatic zones of Australia. Four productivity zones were used to characterise the Stability Index: high and stable, high and unstable, low and stable, and low and unstable. Mapping the indices shows the location and size of the spatial and temporal features of each paddock. The features of the stability zones generally corresponded with soil texture classes. Testing the Stability Indices with a Kruskal–Wallis one-way ANOVA showed significantly different medians for high and low production categories for both grain yield and pasture TGDM (p < 0.01). Crop grain yield stability showed significant differences between medians. In pasture TGDM, the differences between stability medians were not significant, but the technique still separated medians into stable and unstable groupings. This production Stability Index has the potential to be used by farmers to manage spatial variability in mixed farming systems by identifying homogenous areas within a paddock for investigation/amelioration and can also separate out areas of either spatial and/or temporal instability for specific management strategies.
first_indexed 2025-11-14T11:05:54Z
format Journal Article
id curtin-20.500.11937-75972
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T11:05:54Z
publishDate 2019
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-759722020-04-24T07:29:03Z Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability McEntee, P.J. Bennett, Sarita Belford, R.K. While precision agriculture (PA) technologies are widely used in cropping systems, these technologies have received less attention in mixed farming systems. Little is known about the nature, extent, and temporal stability of spatial variability of pastures in mixed farming systems and the feasibility of managing this variability. This paper describes a technique to create a Stability Index based on both crop grain yield and pasture total green dry matter (TGDM) production over time, using high resolution spatial data in two climatic zones of Australia. Four productivity zones were used to characterise the Stability Index: high and stable, high and unstable, low and stable, and low and unstable. Mapping the indices shows the location and size of the spatial and temporal features of each paddock. The features of the stability zones generally corresponded with soil texture classes. Testing the Stability Indices with a Kruskal–Wallis one-way ANOVA showed significantly different medians for high and low production categories for both grain yield and pasture TGDM (p < 0.01). Crop grain yield stability showed significant differences between medians. In pasture TGDM, the differences between stability medians were not significant, but the technique still separated medians into stable and unstable groupings. This production Stability Index has the potential to be used by farmers to manage spatial variability in mixed farming systems by identifying homogenous areas within a paddock for investigation/amelioration and can also separate out areas of either spatial and/or temporal instability for specific management strategies. 2019 Journal Article http://hdl.handle.net/20.500.11937/75972 10.1007/s11119-019-09658-6 fulltext
spellingShingle McEntee, P.J.
Bennett, Sarita
Belford, R.K.
Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability
title Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability
title_full Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability
title_fullStr Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability
title_full_unstemmed Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability
title_short Mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability
title_sort mapping the spatial and temporal stability of production in mixed farming systems: an index that integrates crop and pasture productivity to assist in the management of variability
url http://hdl.handle.net/20.500.11937/75972