# Clean and Calibrate Yield Data

In this use case, we work with yield datasets to understand the distribution and quality of harvested data across the field. Using the connected GeoPard MCP, an LLM retrieves statistical summaries for the original yield dataset, detects irregularities or sensor noise, and identifies where cleaning or calibration is required.

Once the quality checks are complete, the LLM triggers the GeoPard MCP cleaning and calibration workflow with the optimal parameters.

{% hint style="success" %}
Ensure GeoPard MCP is connected before running this workflow. Setup details are provided [here](/geopard-tutorials/product-tour-web-app/geopard-mcp/connect-geopard-mcp.md).
{% endhint %}

## Single Yield Dataset

{% @arcade/embed url="<https://app.arcade.software/share/Zjf8Hpwf0Ykij1Dl5r4L>" flowId="Zjf8Hpwf0Ykij1Dl5r4L" %}

### Before

<figure><img src="/files/xBQY8GrlcE9NIwOLYPtF" alt=""><figcaption></figcaption></figure>

### After

<figure><img src="/files/LOEFn74OaoSypTgoDIBi" alt=""><figcaption></figcaption></figure>

## Batch Yield Dataset Calibration

{% @arcade/embed url="<https://app.arcade.software/share/bibREyFI1hqQvPk7rBFq>" flowId="bibREyFI1hqQvPk7rBFq" %}

### Before

<figure><img src="/files/CD3qLDII1sJJxsHXdr8V" alt=""><figcaption></figcaption></figure>

### After

<figure><img src="/files/kA1oAsmsZFX6qbnsT6MW" alt=""><figcaption></figcaption></figure>


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