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Purpose <p>Fields characterised by large within-field variation stand to potentially gain from the differential application of inputs via Site-Specific Crop Management (SSCM). Maps generated from wheat grain yield and protein sensors are revealing considerable spatiotemporal variability within and between fields, farms, and seasons. Yet one of the biggest barriers to the successful adoption of SSCM is an assessment of the magnitude and spatial distribution of variability, and whether this is sufficient to warrant a change from uniform management. This study aimed to compare opportunities for SSCM between wheat grain yield and grain protein content (GPC) using the Opportunity Index (OI), a measure of the magnitude and spatial structure of within-field variability.</p> Methods <p>This research used a database of 86 paired wheat grain yield and protein maps from 70 fields, collected over four seasons (2020–2023) across two farms in northern New South Wales (NSW) and four farms in Western Australia (WA), resulting in 86 field-years of data. The OI was calculated for every yield and protein map, and maps were then classed as having relatively low, medium, or high opportunities for SSCM. To assess which had a greater opportunity within each field, pairwise differences between the OI for yield and GPC were also calculated.</p> Results <p>Overall, results showed that there was a greater opportunity for SSCM for wheat grain yield than for GPC. While both yield and GPC had a similar spatial structure, yield had a greater magnitude of variation within fields. The OI was greater in NSW than in WA, likely due to variable-rate fertiliser applications already being employed in WA, but not in NSW.</p> Conclusion <p>In calculating the OI across a farm or region, the OI ranks fields as to their suitability for SSCM and provides growers with a simple decision-making tool to determine where SSCM practices may be best directed for the stepwise adoption of precision agriculture. However, it does not provide recommendations for management options, and further investigations by the grower/advisor are needed to make SSCM decisions. Future work should include an economic analysis of the opportunities for SSCM with respect to the premium and discount system applied for grain quality in Australia, and more work is needed to better understand the drivers of the differences in the OI between yield and GPC within and between fields, farms, and seasons.</p>

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Quantity vs. quality: does wheat grain yield or protein content have a greater opportunity for precision management?

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月15日

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  • Mikaela J. Tilse,
  • Thomas F. A. Bishop,
  • Patrick Filippi

摘要

Purpose

Fields characterised by large within-field variation stand to potentially gain from the differential application of inputs via Site-Specific Crop Management (SSCM). Maps generated from wheat grain yield and protein sensors are revealing considerable spatiotemporal variability within and between fields, farms, and seasons. Yet one of the biggest barriers to the successful adoption of SSCM is an assessment of the magnitude and spatial distribution of variability, and whether this is sufficient to warrant a change from uniform management. This study aimed to compare opportunities for SSCM between wheat grain yield and grain protein content (GPC) using the Opportunity Index (OI), a measure of the magnitude and spatial structure of within-field variability.

Methods

This research used a database of 86 paired wheat grain yield and protein maps from 70 fields, collected over four seasons (2020–2023) across two farms in northern New South Wales (NSW) and four farms in Western Australia (WA), resulting in 86 field-years of data. The OI was calculated for every yield and protein map, and maps were then classed as having relatively low, medium, or high opportunities for SSCM. To assess which had a greater opportunity within each field, pairwise differences between the OI for yield and GPC were also calculated.

Results

Overall, results showed that there was a greater opportunity for SSCM for wheat grain yield than for GPC. While both yield and GPC had a similar spatial structure, yield had a greater magnitude of variation within fields. The OI was greater in NSW than in WA, likely due to variable-rate fertiliser applications already being employed in WA, but not in NSW.

Conclusion

In calculating the OI across a farm or region, the OI ranks fields as to their suitability for SSCM and provides growers with a simple decision-making tool to determine where SSCM practices may be best directed for the stepwise adoption of precision agriculture. However, it does not provide recommendations for management options, and further investigations by the grower/advisor are needed to make SSCM decisions. Future work should include an economic analysis of the opportunities for SSCM with respect to the premium and discount system applied for grain quality in Australia, and more work is needed to better understand the drivers of the differences in the OI between yield and GPC within and between fields, farms, and seasons.