# Detecting fungi-affected multi-crop disease on heterogeneous region dataset using modified ResNeXt approach

*PRI Rank #8 · 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-8*

| Field | Value |
| --- | --- |
| Rank | #8 |
| 18m citations | 37 |
| Journal | Environmental Monitoring and Assessment |
| Year | 2024 |
| DOI | 10.1007/s10661-024-12790-0 |
| Corresponding authors | Nidhi Upadhyay |
| Institution | GLA University, India |

**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:** [10.1007/s10661-024-12790-0](https://doi.org/10.1007/s10661-024-12790-0)

## Topics

fungi-affected disease · multi-crop disease detection · heterogeneous region dataset · modified ResNeXt · ResNeXt architecture · deep learning classification · Plant disease diagnosis · fungal pathogen detection · Convolutional neural network · agricultural image analysis · transfer learning · model modification strategy

## 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
```