Search Results (765)

The health of crops is a major challenge for productivity growth in agriculture, with plant diseases playing a key role in limiting crop yield. Identifying and understanding these diseases is crucial to preventing their spread. In particular, greenhouse pepper leaves are susceptible to diseases such as mildew, mites, caterpillars, aphids, and blight, which leave distinctive marks that can be used for disease classification. The study proposes a seven-class classifier for the rapid and accurate diagnosis of pepper diseases, with a primary focus on pre-processing techniques to enhance colour differentiation between green and yellow shades, thereby facilitating easier classification among the classes. A novel algorithm is introduced to improve image vibrancy, contrast, and colour properties. The diagnosis is performed using a modified VGG16Net model, which includes three additional layers for fine-tuning. After initialising on the ImageNet dataset, some layers are frozen to prevent redundant learning. The classification is additionally accelerated by introducing flattened, dense, and dropout layers. The proposed model is tested on a private dataset collected specifically for this study. Notably, this work is the first to focus on diagnosing aphid and caterpillar diseases in peppers. The model achieves an average accuracy of 92.00%, showing promising potential for seven-class deep learning-based disease diagnostics. Misclassifications in the aphid class are primarily due to the limited number of samples available. Full article

Downy mildew caused by Plasmopara viticola is an important disease in grape production, particularly in the highly susceptible, widely cultivated Vitis vinifera L. Breeding for disease resistance is an effective solution, and V. vinifera intraspecific crosses can yield progeny with both disease resistance and high quality. To assess the potential of intraspecific recurrent selection in V. vinifera (IRSV) in improving grapevine resistance to downy mildew and to analyze the pattern of disease resistance inheritance, the disease-resistant variety Ecolly was selected as one of the parents and crossed with Cabernet Sauvignon, Marselan, and Dunkelfelder, respectively, creating three reciprocal combinations, resulting in 1657 hybrid F1 progenies. The primary results are as follows: (1) significant differences in disease resistance among grape varieties and, significant differences in disease resistance between different vintages of the same variety were found; (2) the leaf downy mildew resistance levels of F1 progeny of different hybrid combinations conformed to a skewed normal distribution and showed some maternal dominance; (3) the degree of leaf bulbous elevation was negatively correlated with the level of leaf downy mildew resistance, and the correlation coefficient with the level of field resistance was higher; (4) five progenies with higher levels of both field and in vitro disease resistance were obtained. Intraspecific hybridization can improve the disease resistance of offspring through super-parent genetic effects, and Ecolly can be used as breeding material for recurrent hybridization to obtain highly resistant varieties. Full article

Phytoalexins are antimicrobial compounds of diverse chemical classes whose production is triggered in plants in response to pathogen infection. This study demonstrated that spraying with a celery flavonoid-rich extract (CFRE) or a spinach flavonoid-rich extract (SFRE) enhanced the production of phytoalexins in cucumber leaves artificially infected with powdery mildew incited by Podosphaera fusca. High-performance liquid chromatographic (HPLC) analysis revealed a noticeable increase in the content of phenolic acids, including caffeic acid, ellagic acid, ferulic acid, gallic acid, p-coumaric acid, and syringic acid, as well as the flavonoid rutin in both non-inoculated and inoculated leaves of cucumber seedlings treated with CFRE and SFRE, compared to healthy untreated leaves used as a control. Fluorescence microscopy revealed the accumulation of phenolic acid compounds in chloroplasts and at the periphery of epidermal cells. Overall, results suggest the reduced severity of P. fusca infection following the application of CFRE and SFRE in cucumber leaves could be due, at least in part, to the production of phytoalexins of polyphenolic nature. These findings provide insights into the mechanisms of systemic resistance induced by CFRE and SFRE. Moreover, they confirm these two natural flavonoid-rich products could be promising alternatives to synthetic chemical fungicides for the safe and ecofriendly control of cucumber powdery mildew. Full article

Powdery mildew, caused by Erysiphe quercicola, is one of the primary diseases responsible for the reduction in natural rubber production in China. This disease is a typical airborne pathogen, characterized by its ability to spread via air currents and rapidly escalate into an epidemic under favorable environmental conditions. Accurate prediction and determination of the prevention and control period represent both a critical challenge and key focus area in managing rubber-tree powdery mildew. This study investigates the effects of spore concentration, environmental factors, and infection time on the progression of powdery mildew in rubber trees. By employing six distinct machine learning model construction methods, with the disease index of powdery mildew in rubber trees as the response variable and spore concentration, temperature, humidity, and infection time as predictive variables, a preliminary predictive model for the disease index of rubber-tree powdery mildew was developed. Results from indoor inoculation experiments indicate that spore concentration directly influences disease progression and severity. Higher spore concentrations lead to faster disease development and increased severity. The optimal relative humidity for powdery mildew development in rubber trees is 80% RH. At varying temperatures, the influence of humidity on the disease index differs across spore concentration, exhibiting distinct trends. Each model effectively simulates the progression of powdery mildew in rubber trees, with predicted values closely aligning with observed data. Among the models, the Kernel Ridge Regression (KRR) model demonstrates the highest accuracy, the R² values for the training set and test set were 0.978 and 0.964, respectively, while the RMSE values were 4.037 and 4.926, respectively. This research provides a robust technical foundation for reducing the labor intensity of traditional prediction methods and offers valuable insights for forecasting airborne forest diseases. Full article

Powdery mildew (PM), caused by Sphaerotheca phaseoli, severely threatens mungbean (Vigna radiata) productivity and quality, yet the molecular basis of resistance remains poorly defined. This study employed transcriptome profiling to compare defense responses in a resistant genotype, SUPER5, and a susceptible variety, CN84-1, following pathogen infection. A total of 1755 differentially expressed genes (DEGs) were identified, with SUPER5 exhibiting strong upregulation of genes encoding pathogenesis-related (PR) proteins, disease resistance proteins, and key transcription factors. Notably, genes involved in phenylpropanoid and flavonoid biosynthesis, pathways associated with antimicrobial compound and lignin production, were markedly induced in SUPER5. In contrast, CN84-1 showed limited activation of defense genes and downregulation of essential regulators such as MYB14. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses highlighted the involvement of plant–pathogen interaction pathways, MAPK signaling, and reactive oxygen species (ROS) detoxification in the resistant response. Quantitative real-time PCR validated 11 candidate genes, including PAL3, PR2, GSO1, MLO12, and P21, which function in pathogen recognition, signaling, the biosynthesis of antimicrobial metabolites, the production of defense proteins, defense regulation, and the reinforcement of the cell wall. Co-expression network analysis revealed three major gene modules linked to flavonoid metabolism, chitinase activity, and responses to both abiotic and biotic stresses. These findings offer valuable molecular insights for breeding PM-resistant mungbean varieties. Full article

Strawberries are highly perishable fruits prone to postharvest losses due to defects, diseases, and uneven ripening. This study proposes a deep learning-based approach for automated quality assessment using the YOLOv8n object detection model. A custom dataset of 5663 annotated strawberry images was compiled, covering eight quality categories, including anthracnose, gray mold, powdery mildew, uneven ripening, and physical defects. Data augmentation techniques, such as rotation and Gaussian blur, were applied to enhance model generalization and robustness. The model was trained over 100 and 200 epochs, and its performance was evaluated using standard metrics: Precision, Recall, and mean Average Precision (mAP). The 200-epoch model achieved the best results, with a mAP50 of 0.79 and an inference time of 1 ms per image, demonstrating suitability for real-time applications. Classes with distinct visual features, such as anthracnose and gray mold, were accurately classified. In contrast, visually similar categories, such as ‘Good Quality’ and ‘Unripe’ strawberries, presented classification challenges. Full article

Wheat powdery mildew is a major fungal disease threatening global wheat production. To develop an effective and environmentally friendly control strategy, this study systematically evaluated the disease-suppressive efficacy of strong oxidative free radicals across a series of treatment parameters, including radical concentrations (3.0–8.0 mg/L), spraying durations (20–60 s), solution pH levels (5–8), spraying heights (0–20 cm), and treatment timings corresponding to different infection stages (0–120 h post-inoculation). Response surface methodology (RSM) was used to optimize these variables with the objective of maximizing disease control efficacy. The results showed that control efficacy increased with radical concentration up to 5.0 mg/L, beyond which a saturation effect was observed. The most effective conditions included a spraying duration of 50 s and a height of 6.5 cm. Maximum suppression was achieved when the treatment was applied within 0–12 h post-infection. Moreover, adjusting the solution pH to a range of 5–7 further enhanced the efficacy. The RSM-based predictive model demonstrated high accuracy (R² = 0.9942), and the optimized parameters—6.65 mg/L radical concentration, 50.84 s spraying duration, and treatment at 15.67 h post-infection—yielded a predicted control efficacy of 97.64%, with a validation error below 0.5%. This study provides a quantitative basis for the precise and sustainable deployment of free radical-based treatments in wheat disease management. Full article

Grapevine breeding programs face difficulties in preserving germplasm, especially from species and interspecific hybrids, since most collections are maintained in the field and exposed to biotic and abiotic stress, which can lead to material loss. The Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF) Grapevine Breeding Program faces similar challenges, limiting studies on hybrids resistant to the nematode Pratylenchus brachyurus and downy mildew (Plasmopara viticola), which are valuable for genetic improvement. This study aimed to implement in vitro conservation under minimal growth conditions for interspecific hybrids of Vitis spp. from the UENF program. The protocol followed a completely randomized design in a 2 × 2 × 3 factorial scheme: two hybrids (CH1.2 and CH1.3), two temperatures (18 ± 1 °C and 27 ± 2 °C), and three sucrose concentrations (10, 20, and 30 g L⁻¹), over 180 days of in vitro culture. The results showed that conservation of the UENF hybrids is feasible using nodal segments as explants, at 18 ± 2 °C and 10 g L⁻¹ of sucrose, for up to four months. This protocol may also be applied to other Vitis spp., contributing to the preservation and continued study of valuable germplasm. Full article

Crop disease identification is a pivotal research area in smart agriculture, forming the foundation for disease mapping and targeted prevention strategies. Among the most prevalent global wheat diseases, powdery mildew—caused by fungal infection—poses a significant threat to crop yield and quality, making early and accurate detection crucial for effective management. In this study, we present QY-SE-MResNet34, a deep learning-based classification model that builds upon ResNet34 to perform multi-class classification of wheat leaf images and assess powdery mildew severity at the single-leaf level. The proposed methodology begins with dataset construction following the GBT 17980.22-2000 national standard for powdery mildew severity grading, resulting in a curated collection of 4248 wheat leaf images at the grain-filling stage across six severity levels. To enhance model performance, we integrated transfer learning with ResNet34, leveraging pretrained weights to improve feature extraction and accelerate convergence. Further refinements included embedding a Squeeze-and-Excitation (SE) block to strengthen feature representation while maintaining computational efficiency. The model architecture was also optimized by modifying the first convolutional layer (conv1)—replacing the original 7 × 7 kernel with a 3 × 3 kernel, adjusting the stride to 1, and setting padding to 1—to better capture fine-grained leaf textures and edge features. Subsequently, the optimal training strategy was determined through hyperparameter tuning experiments, and GrabCut-based background processing along with data augmentation were introduced to enhance model robustness. In addition, interpretability techniques such as channel masking and Grad-CAM were employed to visualize the model’s decision-making process. Experimental validation demonstrated that QY-SE-MResNet34 achieved an 89% classification accuracy, outperforming established models such as ResNet50, VGG16, and MobileNetV2 and surpassing the original ResNet34 by 11%. This study delivers a high-performance solution for single-leaf wheat powdery mildew severity assessment, offering practical value for intelligent disease monitoring and early warning systems in precision agriculture. Full article

A study was conducted to examine the effects of the spray application of nine antifungal products, including microbial-derived fungicides, plant-derived fungicides, and chemical fungicides, on the grass Achnatherum inebrians that was either host to Epichloë gansuensis (E+) or E. gansuensis-free (E−) and that was exposed to Blumeria graminis, the fungal pathogen causing powdery mildew. The Epichloë endophyte is a seed-borne mutualistic biotrophic fungus whose growth is fully synchronized with the host grass. Bl. graminis is a biotrophic pathogen that continually infects leaves and stems via conidia, the formation of appressoria, leading to the presence of haustoria in epidermal cells. Prior to fungicide application, the presence of endophytes significantly increased the resistance of A. inebrians to powdery mildew and was able to increase the chlorophyll content. However, the positive effects of the Epichloë endophyte on the plant were suppressed with the use of some fungicides and the increase in the number of sprays, but the reciprocal relationship between the Epichloë endophyte and the plant was not significantly disrupted. Full article

The RasGAP SH3 domain binding protein (G3BP) is a highly conserved family of proteins in eukaryotic organisms that coordinates signal transduction and post-transcriptional gene regulation and functions in the formation of stress granules. G3BPs have important roles in abiotic/biotic stresses in mammals, and recent research suggests that they have similar functions in higher plants. Brassica contains many important oilseeds, vegetables, and ornamental plants, but there are no reports on the G3BP family in Brassica species. In this study, we identified G3BP family genes from six species of the U’s triangle (B. rapa, B. oleracea, B. nigra, B. napus, B. juncea, and B. carinata) at the genome-wide level. We then analyzed their gene structure, protein motifs, gene duplication type, phylogeny, subcellular localization, SSR loci, and upstream miRNAs. Based on transcriptome data, we analyzed the expression patterns of B. napus G3BP (BnaG3BP) genes in various tissues/organs in response to Sclerotinia disease, blackleg disease, powdery mildew, dehydration, drought, heat, cold, and ABA treatments, and its involvement in seed traits including germination, α-linolenic acid content, oil content, and yellow seed. Several BnaG3BP DEGs might be regulated by BnaTT1. The qRT-PCR assay validated the inducibility of two cold-responsive BnaG3BP DEGs. This study will enrich the systematic understanding of Brassica G3BP family genes and lay a molecular basis for the application of BnaG3BP genes in stress tolerance, disease resistance, and quality improvement in rapeseed. Full article

Background: The short strand-related sequence (SRS) gene family is a class of plant-specific transcription factors related to a group of genes known as the short internode (SHI) or SRS/STY gene family, which plays important roles in regulating plant growth and development and stress responses. Although the SRS genes have been studied in many plants, in cucurbit crops, they have thus far only been identified in cucumber. Methods: In the Cucurbitaceae database from melon (Cucumis melo), cucumber (Cucumis sativus), watermelon (Citrullus lanatus), bottle gourd (Lagenaria siceraria), wax gourd (Benincasa hispida), moschata pumpkin (Cucurbita moschata), and pumpkin (Cucurbita maxima), a total of 60 SRS genes were identified in seven Cucurbitaceae crops, which were classified into three subfamilies. Results: The same subfamily showed conserved motifs and gene structures. The differences in the number of SRS genes in different Cucurbitaceae crops implied likely gene loss or duplication events during evolution. Analysis of promoter cis-regulatory elements indicated that these SRS genes may be involved in hormone response, growth and development, and biotic and abiotic stress responses in plants. Most of the CmSRS genes in melons were expressed in the roots, with a few expressed in the leaves and ovaries. In addition, CmSRS expression was induced by biotic (wilt and powdery mildew) and abiotic (drought and salt) stresses. Subcellular localization of CmSRS proteins showed predominant expression in the nucleus. Conclusions: A total of 60 Cucurbitaceae SRS genes are present in the genomes of seven Cucurbitaceae crops. These cucurbit SRS genes seem to have maintained similar characteristics and functions during the evolutionary process. These results lay the foundation for the study of biological functions of SRS genes in Cucurbitaceae crops. Full article

Powdery mildew caused by Sphaerotheca fusca poses a significant threat to cucumber (Cucumis sativus L.) production worldwide, underscoring the need for sustainable disease management strategies. This study investigates the potential of L-lysine, abundantly produced by Bacillus subtilis M 320 (BSM320), to prime systemic acquired resistance (SAR) pathways in cucumber plants. Liquid chromatography–mass spectrometry analysis identified L-lysine as the primary bioactive metabolite in the BSM320 culture filtrate. Foliar application of purified L-lysine significantly reduced powdery mildew symptoms, lowering disease severity by up to 92% at concentrations ≥ 2500 mg/L. However, in vitro spore germination assays indicated that L-lysine did not exhibit direct antifungal activity, indicating that its protective effect is likely mediated through the activation of plant immune responses. Quantitative reverse transcription PCR revealed marked upregulation of key defense-related genes encoding pathogenesis-related proteins 1 and 3, lipoxygenase 1 and 23, WRKY transcription factor 20, and L-type lectin receptor kinase 6.1 within 24 h of treatment. Concurrently, salicylic acid (SA) levels increased threefold in lysine-treated plants, confirming the induction of an SA-dependent SAR pathway. These findings highlight L-lysine as a sustainable, residue-free priming agent capable of enhancing broad-spectrum plant immunity, offering a promising approach for amino acid-based crop protection. Full article

Wheat leaf rust (Lr), caused by Puccinia triticina Eriks. (Pt), is one of the most important diseases affecting wheat production worldwide. Using resistant wheat cultivars is the most economic and environmentally friendly way to control leaf rust. The Chinese wheat cultivar Xinong1163-4 has shown good resistance to Lr in field trials. To identify the genetic basis of Lr resistance in Xinong1163-4, 195 recombinant inbred lines (RILs) from the Xinong1163-4/Thatcher cross were phenotyped for Lr severity in three environments: the 2017/2018, 2018/2019, and 2019/2020 growing seasons in Baoding, Hebei Province. Bulked segregant analysis and simple sequence repeat markers were then used to identify the quantitative trait loci (QTLs) for Lr adult plant resistance (APR) in the population. As a result, six QTLs were detected, designated as QLr.hbau-1BL.1, QLr.hbau-1BL.2, and QLr.hbau-1BL.3. These QTLs were predicted to be novel. QLr.hbau-4BL, QLr.hbau-4BL.1, and QLr.hbau-3A were identified at similar physical positions to previously reported QTLs. Based on chromosome positions and molecular marker testing, QLr.hbau-1BL.3 shares similar flanking markers with Lr46. Lr46 is a non-race-specific APR gene for leaf rust, stripe rust, and powdery mildew. Similarly, QLr.hebau-4BL showed resistance to multiple diseases, including leaf rust, stripe rust, Fusarium head blight, and powdery mildew. The QTLs identified in this study, as well as their closely linked markers, can potentially be used for marker-assisted selection in wheat breeding. Full article

Downy mildew, caused by Plasmopara viticola, is a major threat to grapevine (Vitis vinifera) cultivation in humid climates. Restrictions on synthetic pesticides and inconsistent efficacy of current biocontrol agents, especially under rainy conditions, complicate disease management. This study evaluated the potential of compost tea to suppress downy mildew in a two-year field experiment (2023 and 2024), combined with reduced synthetic fungicide applications. The study design compared two phytosanitary management strategies on a commercial vineyard: a conventional fungicide against a compost tea strategy supplemented with two cymoxanil applications. The experiment set up had three replicated blocks, each consisting of 100 plants for a total of 600 plants. Mechanistic insights were provided through controlled laboratory experiments involving pre- and post-infection leaf assays, vineyard bacteriome profiling, via 16S rRNA gene sequencing for bacterial communities, across vineyard compartments, i.e., bulk soil, rhizosphere, and phyllosphere, and grapevine metabolomic analysis by GC-MS analysis. Field trials demonstrated that compost tea combined with two fungicide applications effectively reduced disease severity, notably outperforming the fungicide alone in the particularly rainy year of 2023. Bacteriome analysis revealed that compost tea treatment enriched beneficial bacterial genera, including Pseudomonas, Sphingomonas, Enterobacter, Massilia, and Bacillus, known for their growth-promoting and biocontrol activity in the rhizosphere and phyllosphere. Laboratory assays on detached leaves further showed that compost tea alone could suppress both infection and sporulation of P. viticola. Metabolomic analysis highlighted the accumulation of compounds such as tartaric and shikimic acids in compost tea treated leaves, suggesting a potential role in induced resistance. The findings indicate that applying compost tea with reduced fungicide treatments represents a promising and sustainable strategy for managing grapevine downy mildew, even in challenging climates. Full article