# Estimating Canopy Chlorophyll Content of Potato Using Machine Learning and Remote Sensing

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/estimating-canopy-chlorophyll-content-of-potato-using-machine-learning-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | X. F. Yang,Hao Zhou,Qiao Li,Xueliang Fu,Honghui Li |
| Citations | 13 |
| DOI | 10.3390/agriculture15040375 |
| Fields | Agricultural and Biological Sciences,Chemistry,Environmental Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.3390/agriculture15040375 |
| OpenAlex ID | https://openalex.org/W4407363783 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Xueliang Fu](https://scholariq.org/researchers/xueliang-fu/)
- [Honghui Li](https://scholariq.org/researchers/honghui-li/)

## Paper journal

- [Agriculture](https://scholariq.org/journals/agriculture/)

## Paper primary topic

- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)

## Paper topics

- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)
- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)
- [Potato Plant Research](https://scholariq.org/topics/potato-plant-research/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.