UAV remote sensing phenotyping of wheat collection for response to water stress and yield prediction using machine learning-Reference-Cited by-同舟云学术

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UAV remote sensing phenotyping of wheat collection for response to water stress and yield prediction using machine learning

Published:2024-06 Issue: Volume:12 Page:100464
ISSN:2667-064X
Container-title:Plant Stress
language:en
Short-container-title:Plant Stress

Author:

Sharma Vikas,Honkavaara Eija,Hayden Matthew,Kant Surya^ORCID

Publisher

Elsevier BV

Reference57 articles.

1. Quantitative remote sensing at ultra-high resolution with uav spectroscopy: a review of sensor technology, measurement procedures, and data correction workflows;Aasen;Remote. Sens.,2018

2. A GBS-based GWAS analysis of adaptability and yield traits in bread wheat (Triticum aestivum L.);Akram;J. Appl. Genet.,2021

3. Appropriate application methods for salicylic acid and plant nutrients combinations to promote morpho-physiological traits, production, and water use efficiency of wheat under normal and deficit irrigation in an arid climate;Alotaibi;Plants,2023

4. Machine learning regression analysis for estimation of crop emergence using multispectral UAV imagery;Banerjee;Remote Sens. (Basel),2021

Cited by 2 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. Advances in Sustainable Crop Management: Integrating Precision Agriculture and Proximal Sensing;AgriEngineering;2024-09-02

2. Functional phenomics and genomics: Unravelling heat stress responses in wheat;Plant Stress;2024-09

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