Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 1, 2025AgronomyOpen Access

Methodological Study on Maize Water Stress Diagnosis Based on UAV Multispectral Data and Multi-Model Comparison

View Full Paper
Ask AI
Bookmark
Share

Authors

JZJiaxin ZhuSLSien LiWWWenyong Wu

Discussion

Loading...

Member takes

Overview

This methodological study evaluates water stress in maize using UAV multispectral data, suggesting improved irrigation methods and model efficiency.

Key Points

  • The Random Forest model under shallow-buried drip irrigation achieved the highest accuracy with R2 = 0.88.
  • Plastic film-mulched irrigation methods showed significant impacts on leaf water content throughout the growth stages.
  • Partial Least Squares Regression and Support Vector Regression were also leveraged for estimating water stress levels.
  • Correlation analysis identified plant height as the strongest predictor of leaf water content across irrigation treatments.

Cite This Study

Zhu et al. (2025) studied this question.

synapsesocial.com/papers/68dd9537fe798ba2fc4995ddhttps://doi.org/10.3390/agronomy15102318
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Estimation of Wheat Leaf Water Content Based on UAV Hyper-Spectral Remote Sensing and Machine Learning2025 · 20 citations
  2. 2Impact of reclaimed wastewater on alfalfa production under different irrigation methods2024 · 10 citations
  3. 3Unmanned Aerial Vehicle for Remote Sensing Applications—A Review2019 · 713 citations
  4. 4Soil water dynamics and yield response of broccoli (Brassica oleracea) under drip irrigation with different irrigation frequency2022 · 4 citations
  5. 5Mapping Maize Water Stress Based on UAV Multispectral Remote Sensing2019 · 232 citations