ArticleFrontiers in plant science2023
Effect of varying UAV height on the precise estimation of potato crop growth.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Methodology for Selecting Stable UAV-Based Vegetation Indices for Prediction of Agronomic Variables in Maize Using a Multispectral Sensor.Plants (Basel, Switzerland) · 2026Article
- Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits.The Plant journal : for cell and molecular biology · 2024Article
- Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning.Sensors (Basel, Switzerland) · 2024Article
- Enhancing Winter Wheat Soil-Plant Analysis Development Value Prediction through Evaluating Unmanned Aerial Vehicle Flight Altitudes, Predictor Variable Combinations, and Machine Learning Algorithms.Plants (Basel, Switzerland) · 2024Article
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Authors and funding
6 authors.
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Abstract
A phenotyping pipeline utilising DeepLab was developed for precisely estimating the height, volume, coverage and vegetation indices of European and Japanese varieties. Using this pipeline, the effect of varying UAV height on the precise estimation of potato crop growth properties was evaluated. A UAV fitted with a multispectral camera was flown at a height of 15 m and 30 m in an experimental field where various varieties of potatoes were grown. The properties of plant height, volume and NDVI were evaluated and compared with the manually obtained parameters. Strong linear correlations with R
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