# Cucumber Downy Mildew Disease Prediction Using a CNN-LSTM Approach

*PRI Rank #9 · Topics and Trends in Most Cited Plant Pathogens and Fungal Diseases Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/plant-pathogens-and-fungal-diseases/2026/rank-9*

| Field | Value |
| --- | --- |
| Rank | #9 |
| 18m citations | 36 |
| Journal | Agriculture |
| Year | 2024 |
| DOI | 10.3390/agriculture14071155 |
| Corresponding authors | Hanping Mao |
| Institution | Jiangsu Changdian Technology Co., Ltd., China |

**Ranking page:** [Topics and Trends in Most Cited Plant Pathogens and Fungal Diseases Papers, Class of 2026](https://pri.pepkio.com/top-papers/plant-pathogens-and-fungal-diseases/2026)

**Paper link:** [10.3390/agriculture14071155](https://doi.org/10.3390/agriculture14071155)

## Topics

cucumber downy mildew · CNN-LSTM · Convolutional neural network · LSTM · spore counting · portable spore catcher · disease incidence prediction · greenhouse environment monitoring · Pearson correlation analysis · leaf area proportion · environmental data fusion · Mean Absolute Error · Mean Square Error · root mean square error · Bland-Altman analysis · airborne plant disease · early warning model · time series prediction

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Plant Pathogens and Fungal Diseases Papers, Class of 2026. https://pri.pepkio.com/top-papers/plant-pathogens-and-fungal-diseases/2026. Accessed 2026-07-14.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```