In vivo human-like robotic phenotyping of leaf traits in maize and sorghum in greenhouse

Author:

Atefi Abbas,Ge Yufeng,Pitla Santosh,Schnable James

Funder

National Institute of Food and Agriculture

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference29 articles.

1. Autonomous leaf picking using deep learning and visual-servoing;Ahlin;IFAC-PapersOnLine,2016

2. Alenyà Ribas, G., Dellen, B., Foix Salmerón, S., Torras, C., 2012. Robotic leaf probing via segmentation of range data into surface patches. In: Proceedings of the 2012 IROS Workshop on Agricultural Robotics: Enabling Safe, Efficient, Affordable Robots for Food Production. pp. 1–6.

3. Development and evaluation of a field-based high-throughput phenotyping platform;Andrade-Sanchez;Funct. Plant Biol.,2014

4. A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding;Bai;Comput. Electron. Agric.,2016

5. NU-Spidercam: a large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research;Bai;Comput. Electron. Agric.,2019

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