Evaluating two high-throughput phenotyping platforms at early stages of the post-harvest pipeline of sweetpotatoes-Reference-Cited by-同舟云学术

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Evaluating two high-throughput phenotyping platforms at early stages of the post-harvest pipeline of sweetpotatoes

Published:2024-08 Issue: Volume:8 Page:100469
ISSN:2772-3755
Container-title:Smart Agricultural Technology
language:en
Short-container-title:Smart Agricultural Technology

Author:

Pena Martinez Enrique E.^ORCID,Kudenov Michael,Nguyen Hoang,Jones Daniela S.,Williams Cranos

Publisher

Elsevier BV

Reference25 articles.

1. A comprehensive review of high throughput phenotyping and machine learning for plant stress phenotyping;Gill;Phenomics,2022

2. A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice;Duan;Plant Methods,2011

3. Potato quality grading based on machine vision and 3D shape analysis;Su;Comput. Electron. Agric.,2018

4. Non-destructive, high-content analysis of wheat grain traits using X-ray micro computed tomography;Hughes;Plant Methods,2017

5. Pheno seeder - a robot system for automated handling and phenotyping of individual seeds;Jahnke;Plant Physiol.,2016

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting sweetpotato traits using machine learning: Impact of environmental and agronomic factors on shape and size;Computers and Electronics in Agriculture;2024-10

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