Phytophthora is a long-established, well-known, and globally important genus of plant pathogens. Phylogenetic evidence has shown that the biologically distinct, obligate biotrophic downy mildews evolved from Phytophthora at least twice. Because, cladistically, this renders Phytophthora “paraphyletic,” it has been proposed that Phytophthora evolutionary clades be split into multiple genera ( Crous et al. 2021 ; Runge et al. 2011 ; Thines 2023 , 2024 ). In this letter, we review arguments for the retention of the generic name Phytophthora with a broad circumscription made by Brasier et al. (2022) and by many delegates at an open workshop organized by The American Phytopathological Society. We present our well-considered responses to the genus splitting proposals, both in general terms and in terms of the specific proposals for new genera, alongside new information regarding the biological properties and mode of origin of the Phytophthora clades. We consider that the proposals are mostly non-rigorous and not supported by the scientific evidence. Further, given (i) the apparent lack of any distinguishing biological characteristics (synapomorphies) between the Phytophthora clades; (ii) the fundamental monophyly of Phytophthora in the original Haeckelian sense ( Haeckel 1877 ); (iii) the fact that paraphyly is not a justification for taxonomic splitting; and (iv) the considerable likely damage to effective scientific communication and disease management from an unnecessary breakup of the genus, we report that workshop delegates voted unanimously in favor of preserving the current generic concept and for seeking endorsement of this view by a working group of the International Commission on the Taxonomy of Fungi. [ ] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Pepper production is a critical component of the global agricultural economy, with exports reaching a remarkable $6.9B in 2023. This underscores the crop’s importance as a major economic driver of export revenue for producing nations. Botrytis cinerea, the causative agent of gray mold, significantly impacts crops like fruits and vegetables, including peppers. Early detection of this pathogen is crucial for a reduction in fungicide reliance and economic loss prevention. Traditionally, visual inspection has been a primary method for detection. However, symptoms often appear after the pathogen has begun to spread. This study employs the Deep Learning algorithm YOLO for single-class segmentation on plant images to extract spatial details of pepper leaves. The dataset included hyperspectral images at discrete wavelengths (460 nm, 540 nm, 640 nm, 775 nm, and 875 nm) from derived vegetation indices (CVI, GNDVI, NDVI, NPCI, and PSRI) and from RGB. At an Intersection over Union with a 0.5 threshold, the Mean Average Precision (mAP50) achieved by the leaf-segmentation solution YOLOv11-Small was 86.4%. The extracted leaf segments were processed by multiple Transformer models, each yielding a descriptor. These descriptors were combined in ensemble and classified into three distinct classes using a K-nearest neighbor, a Long Short-Term Memory (LSTM), and a ResNet solution. The Transformer models that comprised the best ensemble classifier were as follows: the Swin-L (P:4 × 4–W:12 × 12), the ViT-L (P:16 × 16), the VOLO (D:5), and the XCIT-L (L:24–P:16 × 16), with the LSTM-based classification solution on the RGB, CVI, GNDVI, NDVI, and PSRI image sets. The classifier achieved an overall accuracy of 87.42% with an F1-Score of 81.13%. The per-class F1-Scores for the three classes were 85.25%, 66.67%, and 78.26%, respectively. Moreover, for B. cinerea detection during the initial as well as quiescent stages of infection prior to symptom development, qPCR-based methods (RT-qPCR) were used for quantification of in planta fungal biomass and integrated with the findings from the AI approach to offer a comprehensive strategy. The study demonstrates early and accurate detection of B. cinerea on pepper plants by combining segmentation techniques with Transformer model descriptors, ensembled for classification. This approach marks a significant step forward in the detection and management of crop diseases, highlighting the potential to integrate such methods into in situ systems like mobile apps or robots.

The wilt-inducing strains of Fusarium oxysporum are responsible for severe damage to many economically important plant species. The most cost-effective and environmentally safe method for the management of Fusarium wilt is the use of resistant cultivars when they are available. In the present study, the Arabidopsis genotype with disruptions in the β-amylase 3 (BAM3) gene, which encodes the major hydrolytic enzyme that degrades starch to maltose, had significantly lower susceptibility to Fusarium oxysporum f. sp. raphani (For) compared to wild-type (wt) plants. It showed the lowest disease severity and contained reduced quantities of fungal DNA in the plant vascular tissues when analyzed with real-time PCR. Through metabolomic analysis using gas chromatography (GC)–mass spectrometry (MS) and gene-expression analysis by reverse-transcription quantitative PCR (RT-qPCR), we observed that defense responses of Arabidopsis bam3 mutants are associated with starch-degradation enzymes, the corresponding modification of the carbohydrate balance, and alterations in sugar (glucose, sucrose, trehalose, and myo-inositol) and auxin metabolism.

Halophytic microbiomes represent an untapped reservoir of stress-adapted microbial functions, yet whether these functions can be transferred across ecological boundaries to enhance crop immune resilience remains unknown. Here we show that Kushneria , a halophyte-associated genus with broad environmental resilience, confers robust disease protection in tomato and cucumber plants against fungal and oomycete pathogens despite lacking direct antagonistic activity. Comparative genomics across 26 genomes revealed extensive biosynthetic novelty and conserved catabolic clusters associated with rhizosphere competence, providing a genomic framework for persistence of Kushneria in saline environments. Multi-omics profiling associated protection with a distinct host immune regulatory response, characterized by strong induction of core NLR receptors, including a ZAR1 paralogue. This response was further linked to a previously uncharacterized long noncoding RNA, Solyc10r048010.1, connected to the induced NLR network. Our findings establish halophytic endophytes as field-validated and transferable modulators of crop immunity and identify a candidate regulatory RNA–NLR axis associated with Kushneria -induced disease resistance.