AI Compass
Compass

Agriculture

Crop management, plant protection and yield planning: where image analysis and forecasting hold in the field, and what hangs on subsidy law and data ownership.

·2 min read·By Redaktion KI-Kompass
DETAIL
4 sections

What this is about

TaskClassification
Detecting weeds and treating selectivelyunproblematic
Spotting disease and pests on leavesunproblematic
Estimating stand density and heightunproblematic
Forecasting yieldunproblematic
Observing animal health from behaviour and imageunproblematic
Preparing applications and documentationlimited
Generating area and subsidy figures automaticallylimited, liability stays

Why a foreign model fails on your own farm

A weed detection model trained on fields in another region meets different soil, different varieties, different light and a different camera height. Quality collapses without anything being wrong with the model. That is a distribution shift, see Overfitting, bias and variance.

  1. 01

    Collect your own images

    Over a season, at different times of day, in different weather. Two hundred good images of your own beat ten thousand foreign ones.

  2. 02

    Label cleanly

    Few classes, clear boundaries. Two people label the same fifty images and compare, see Annotation.

  3. 03

    Adapt an existing model

    Fine-tune on your own images rather than training from scratch.

  4. 04

    Measure in the field

    Not on the test set. The number that counts is input saved at equal outcome.

Data ownership

QuestionWhere it is decided
Who owns the machine data produced?Purchase contract or terms of use
Who may analyse and pass it on?The same, usually in the manufacturer's favour
Can the farm get at the raw data?Interfaces, often at a charge
What happens on changing manufacturer?Export format, rarely regulated

The code of conduct on agricultural data sharing is voluntary. A clause in the purchase contract is more effective than a reference to it.

Subsidy law and documentation

  • Statements in subsidy applications are the farm's responsibility. An automatically produced area figure does not relieve it.
  • Remote sensing is used on the authorities' side too. Differences between your own and the official analysis should be settled before filing.
  • Plant protection records are prescribed and auditable. Automatic capture must cover every required field.
  • Livestock keeping carries its own documentation duties, which behavioural analysis does not replace.

Operating in the field

  • Compute on the device rather than in the cloud, because network coverage in a field cannot be assumed, see Edge AI.
  • Match latency per image to working speed. Detection that arrives too late is worthless.
  • Freeze and document the model version per season so that analyses stay comparable across years.
  • Provide a fallback to blanket treatment when detection fails.

Entry sheet: agriculture

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Entry sheet for agriculture

This sector's tasks by risk class, the points to settle beforehand, and the metrics the benefit shows up in.

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Agriculture