# Datasets and growing recipes

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Required files, metadata and evidence levels for raw datasets, processed data and reusable cultivation recipes.

In brief

Required files, metadata and evidence levels for raw datasets, processed data and reusable cultivation recipes.

## Dataset release

Each dataset contains raw sensor records, actuator events, calibration identifiers, plant-material metadata, treatment allocation, deviations, harvest records and analysis code or processing instructions.

## Recipe release

A growing recipe includes crop, cultivar, seed lot, developmental timeline, physical light targets, elemental nutrient formulation, pH and EC policy, root-zone conditions, rotation schedule, harvest protocol and validation scope.

## Release package

 |
 Object | Minimum contents

 | Raw data | unaltered sensor, event, image and laboratory records
 | Metadata | system, biological material, environment, units, calibration and provenance
 | Processing | versioned scripts, parameters and generated outputs
 | Recipe | time-indexed physical targets, tolerances, safety limits and supported system
 | Result summary | tested crop, cultivar, cycles, effect size, uncertainty and replication status

Datasets are designed around MIAPPE-compatible plant metadata and FAIR principles. A recipe is released only with a bounded statement of where it was tested. [R23] [R24]

## References

- [R23] Papoutsoglou, E. A. et al. (2020). Enabling reusability of plant phenomic datasets with MIAPPE 1.1. *New Phytologist*. https://doi.org/10.1111/nph.16544
- [R24] Wilkinson, Mark D. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. *Scientific Data*. https://doi.org/10.1038/sdata.2016.18