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Pepper-4D: Spatiotemporal 3D Pepper Crop Dataset for Phenotyping.

Foysal Ahmed1, Dawei Li1,2,3, Boyuan Zhao4,5

  • 1School of Information and Intelligent Science (SIIS), Donghua University, Shanghai 201620, China.

Plants (Basel, Switzerland)
|February 27, 2026
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Summary

Researchers developed Pepper-4D, a high-precision 4D point cloud dataset for detailed 3D analysis of pepper (Capsicum annuum) plants. This dataset supports advanced phenotyping and breeding for sustainable crop production.

Keywords:
4D datagenerative 3D plantsgrowth event detectionneural radiance field (NeRF)organ segmentationorgan trackingpepperplant phenotypingpoint clouds

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Area of Science:

  • Agricultural Science
  • Computer Vision
  • Plant Biology

Background:

  • Pepper (Capsicum annuum) is a vital global crop facing unsustainable production increases through traditional methods.
  • Advancements in AI and 3D computer vision offer new avenues for crop phenotyping and breeding.
  • A significant gap exists in detailed 3D datasets for organ-level analysis of pepper plants.

Purpose of the Study:

  • To introduce Pepper-4D, a novel 4D point cloud dataset for high-precision spatial and temporal analysis of pepper plants.
  • To provide a comprehensive dataset supporting organ-level phenotyping and advanced breeding strategies.
  • To address the lack of detailed 3D data for Capsicum annuum research.

Main Methods:

  • Creation of a new 4D point cloud dataset (Pepper-4D) capturing pepper plant development.
  • Inclusion of 916 individual point clouds from 29 indoor-cultivated pepper plant samples across various growth stages.
  • Manual annotation of data at both plant-level and organ-level for detailed analysis.

Main Results:

  • The Pepper-4D dataset offers high-precision 3D spatial and temporal data for pepper plants.
  • Annotations enable diverse phenotyping tasks, including growth classification and organ segmentation.
  • The dataset supports organ growth tracking, new organ detection, and synthetic data generation.

Conclusions:

  • Pepper-4D provides crucial data for advancing pepper breeding and cultivation through AI and computer vision.
  • The dataset facilitates detailed organ-level analysis, supporting sustainable agricultural intensification.
  • This resource enables new research directions in plant phenotyping and synthetic data generation for Capsicum annuum.