Wheat Yield Response to Management and Soil Properties in South Africa's Western Cape

Field trial data from six on-farm experiments conducted in 2023 and 2024 as part of the Data-Intensive Farm Management project. The dataset, authored by Karen J Truter, was last updated on 2026-06-02 and is licensed under CC-BY-4.0. It was used to model profit-maximizing seeding and fertilizer rates and assess the influence of soil physical properties on yield variability.

Use Cases

• Training Random Forest models to predict wheat yield based on seeding rate, fertilizer rate, and soil properties.
• Analyzing the site-specific influence of soil depth, structure, and water capacity on yield response to inputs.
• Determining profit-maximizing variable-rate application strategies for seeding and fertilizer under dryland conditions.
• Delineating management zones within fields based on observed yield responses to varying input rates.

Strengths

• Data originates from six field-scale on-farm trials conducted over two seasons (2023 and 2024).
• Analysis includes real-time economic factors like seed, fertilizer, and grain prices to determine profit-maximizing rates.
• The study explicitly evaluates non-linear interactions between management inputs and soil properties.

Limitations

• The dataset is small (648.3 KB) and the row count is unknown, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect geographic bias inherent to the Western Cape province of South Africa.

Provenance

Source

Karen J Truter via figshare.

Collection Method

Data collected from six field-scale on-farm trials as part of the Data-Intensive Farm Management project.

Time Range

2023 to 2024 seasons.

Freshness

Last updated 2026-06-02 08:55:13; freshness should be verified.

Geography

Western Cape province, South Africa.