Global Kale Phenomics and Yield Data from Controlled Environments

Supplementary material from a study on global kale germplasm phenomics and vegetative yield in controlled environment agriculture. The dataset, authored by Adrian Ming Jern Lee and released in 2026, contains plant breeding and high-throughput phenotyping data under a CC BY license.

Use Cases

• Analyze Brassica Oleracea Var Acephala phenomics data to identify traits linked to vegetative yield in indoor farming
• Apply machine learning to high-throughput phenotyping data for predictive plant breeding models
• Study trait correlations within global kale germplasm to support controlled environment agriculture research

Strengths

• Data is recent, last updated in March 2026.
• Released under a permissive CC BY license for reuse.
• Focuses on a specific crop (kale) and environment (controlled agriculture) for targeted analysis.

Limitations

• The dataset is small at 1.3 MB, limiting analytical scope.
• Specific data structure, row count, and column details are unknown from the input.
• As supplementary material, it may lack standalone documentation or context.

Provenance

Source

figshare

Collection Method

High-throughput phenotyping in controlled environment agriculture, likely from experimental trials.

Time Range

null

Freshness

2026-03-26

Geography

Global germplasm collection