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Rice production has faced numerous challenges in recent years, and traditional methods are still being used to detect rice diseases. This research project developed an automated rice blast disease diagnosis technique based on deep learning, image processing, and transfer learning with pre-trained models such as Inception V3, VGG16, VGG19, and ResNet50. The public dataset consists of 2000 images; about 1200 images belong to the leaf blast class, and 800 to the healthy leaf class. The modified connection-skipping ResNet 50 had the highest accuracy of 99.75% with a loss rate of 0.33, while the other models achieved 98.16%, 98.47%, and 98.56%, respectively. Furthermore, ResNet 50 achieved a validation accuracy of 99.69%, precision of 99.50%, F1-score of 99.70, and AUC of 99.83%. In conclusion, the study demonstrated a superior performance and disease prediction using the Gradio web application.

OsWRKY76 encodes a group IIa WRKY transcription factor of rice. The expression of OsWRKY76 was induced within 48h after inoculation with rice blast fungus (Magnaporthe oryzae), and by wounding, low temperature, benzothiadiazole, and abscisic acid. Green fluorescent protein-fused OsWRKY76 localized to the nuclei in rice epidermal cells. OsWRKY76 showed sequence-specific DNA binding to the W-box element in vitro and exhibited W-box-mediated transcriptional repressor activity in cultured rice cells. Overexpression of OsWRKY76 in rice plants resulted in drastically increased susceptibility to M. oryzae, but improved tolerance to cold stress. Microarray analysis revealed that overexpression of OsWRKY76 suppresses the induction of a specific set of PR genes and of genes involved in phytoalexin synthesis after inoculation with blast fungus, consistent with the observation that the levels of phytoalexins in the transgenic rice plants remained significantly lower than those in non-transformed control plants. Furthermore, overexpression of OsWRKY76 led to the increased expression of abiotic stress-associated genes such as peroxidase and lipid metabolism genes. These results strongly suggest that OsWRKY76 plays dual and opposing roles in blast disease resistance and cold tolerance.

Rice is one of the staple foods for the majority of the global population that depends directly or indirectly on it. The yield of this important crop is constantly challenged by various biotic stresses. Rice blast, caused by Magnaporthe oryzae (M. oryzae), is a devastating rice disease causing severe yield losses annually and threatening rice production globally. The development of a resistant variety is one of the most effective and economical approaches to control rice blast. Researchers in the past few decades have witnessed the characterization of several qualitative resistance (R) and quantitative resistance (qR) genes to blast disease as well as several avirulence (Avr) genes from the pathogen. These provide great help for either breeders to develop a resistant variety or pathologists to monitor the dynamics of pathogenic isolates, and ultimately to control the disease. Here, we summarize the current status of the isolation of R, qR and Avr genes in the rice–M. oryzae interaction system, and review the progresses and problems of these genes utilized in practice for reducing rice blast disease. Research perspectives towards better managing blast disease by developing a broad-spectrum and durable blast resistance variety and new fungicides are also discussed.

One of the biotic constraints in rice production worldwide is blast disease which can control by planting resistant varieties. To find out effective resistance, blast resistance quantitative trait loci (QTL) were mapped against 20 and 3 virulent isolates for leaf blast and neck blast, respectively, using 111 doubled haploid lines from the cross of IR64 and Azucena. QTLs associated with leaf blast were found on chromosomes 1, 2, 4, 7, 8, 10, 11, and 12 (%R2 = 3.6 – 64.3), while neck blast linked QTLs were identified on chromosomes 1, 6, 10, and 12 (%R2 = 6.4 – 22.6). The new QTLs were identified on chromosome 1; however, most QTLs were mapped in the vicinity of resistance genes in previous references. The genetic relationship of leaf and neck blast was explained by the coincidence of detected QTLs and positive value of pathogenicity correlation (r = 4.5 – 4.7). This study provides reliable QTLs locations that will benefit rice breeding programs to develop new cultivars containing durable and broad-spectrum resistance to leaf and neck blast disease.

Immune activation usually trades off growth, leading to yield loss. Genes that coordinate resistance and yield are urgently required for crop improvement. MicroRNAs (miRNAs) provide rich candidates for coordinating resistance with yield. Here, we demonstrated that mutation of MIR1863a enhances blast disease resistance without yield loss accompanying increased panicle number. However, overexpression and mutation of MIR1863a both lead to compromised yield traits such as seed setting rate. The expression of MIR1863a was antagonistically regulated by two transcription factors, MADS51 and ESR1. MADS51 activates, whereas ESR1 suppresses MIR1863a in leaves and panicles during the growth period and upon pathogen invasion, thus avoiding a penalty in yield caused by excessive resistance. Consistent with the phenotype of mir1863a lines, mutation of MADS51 boosts blast disease resistance without yield loss. Moreover, the haplotypes of MADS51 and ESR1, which exhibit differential activity on the MIR1863a promoter, correlate with disease phenotypes in diverse Japonica and Indica rice accessions, implying a subspecies‐specific evolution of these ‘transcriptional factor‐MIR1863a’ models. Taken together, our results revealed a fine‐tuning mechanism controlling an miRNA amounts to balance disease resistance and yield, advancing our understanding of the regulation of the resistance‐yield trade‐off.

Rice blast is the primary disease affecting rice yield and quality, and its effective detection is essential to ensure rice yield and promote sustainable agricultural production. To address traditional disease detection methods’ time-consuming and inefficient nature, we proposed a method called Pyramid-YOLOv8 for rapid and accurate rice leaf blast disease detection in this study. The algorithm is built on the YOLOv8x network framework and features a multi-attention feature fusion network structure. This structure enhances the original feature pyramid structure and works with an additional detection head for improved performance. Additionally, this study designs a lightweight C2F-Pyramid module to enhance the model’s computational efficiency. In the comparison experiments, Pyramid-YOLOv8 shows excellent performance with a mean Average Precision (mAP) of 84.3%, which is an improvement of 9.9%, 4.3%, 7.4%, 6.1%, 1.5%, 3.7%, and 8.2% compared to the models Faster-RCNN, RT-DETR, YOLOv3-SPP, YOLOv5x, YOLOv9e, and YOLOv10x, respectively. Additionally, it reaches a detection speed of 62.5 FPS; the model comprises only 42.0 M parameters. Meanwhile, the model size and Floating Point Operations (FLOPs) are reduced by 41.7% and 23.8%, respectively. These results demonstrate the high efficiency of Pyramid-YOLOv8 in detecting rice leaf blast. In summary, the Pyramid-YOLOv8 algorithm developed in this study offers a robust theoretical foundation for rice disease detection and introduces a new perspective on disease management and prevention strategies in agricultural production.

Key messagePi65, a leucine-rich repeat receptor-like kinase (LRR-RLK) domain cloned from Oryza sativa japonica, is a novel rice blast disease resistance gene.Rice blast seriously threatens rice production worldwide. Utilizing the rice blast resistance gene to breed rice blast-resistant varieties is one of the best ways to control rice blast disease. Using a map-based cloning strategy, we cloned a novel rice blast resistance gene, Pi65, from the resistant variety GangYu129 (abbreviated GY129, Oryza sativa japonica). Overexpression of Pi65 in the susceptible variety LiaoXing1 (abbreviated LX1, Oryza sativa japonica) enhanced rice blast resistance, while knockout of Pi65 in GY129 resulted in susceptibility to rice blast disease. Pi65 encodes two transmembrane domains, with 15 LRR domains and one serine/threonine protein kinase catalytic domain, conferring resistance to isolates of Magnaporthe oryzae (abbreviated M. oryzae) collected from Northeast China. There were sixteen amino acid differences between the Pi65 resistance and susceptible alleles. Compared with the Pi65-resistant allele, the susceptible allele exhibited one LRR domain deletion. Pi65 was constitutively expressed in whole plants, and it could be induced in the early stage of M. oryzae infection. Transcriptome analysis revealed that numerous genes associated with disease resistance were specifically upregulated in GY129 24 h post inoculation (HPI); in contrast, photosynthesis and carbohydrate metabolism-related genes were particularly downregulated at 24 HPI, demonstrating that disease resistance-associated genes were activated in GY129 (carrying Pi65) after rice blast fungal infection and that cellular basal metabolism and energy metabolism were inhibited simultaneously. Our study provides genetic resources for improving rice blast resistance and enriches the study of rice blast resistance mechanisms.

MicroRNAs (miRNAs) play essential roles in rice immunity against Magnaporthe oryzae, the causative agent of rice blast disease. Here we demonstrate that Osa-miR162a fine-tunes rice immunity against M. oryzae and yield traits. Overexpression of Osa-miR162a enhances rice resistance to M. oryzae accompanying enhanced induction of defense-related genes and accumulation of hydrogen peroxide (H2O2). In contrast, blocking Osa-miR162 by overexpressing a target mimic of Osa-miR162a enhances susceptibility to blast fungus associating with compromised induction of defense-related gene expression and H2O2 accumulation. Moreover, the transgenic lines overexpressing Osa-miR162a display decreased seed setting rate resulting in slight reduced yield per plant, whereas the transgenic lines blocking Osa-miR162 show an increased number of grains per panicle, resulting in increased yield per plant. Altered accumulation of Osa-miR162 had a limited impact on the expression of rice Dicer-like 1 (OsDCL1) in these transgenic lines showing normal gross morphology, and silencing of OsDCL1 led to enhanced resistance to blast fungus similar to that caused by overexpression of Osa-miR162a, suggesting the involvement of OsDCL1 in Osa-miR162a-regulated resistance. Together, our results indicate that Osa-miR162a is involved in rice immunity against M. oryzae and fine-tunes resistance and yield.

Rice production needs to be sustained in the coming decades, as the changeable climatic conditions are becoming more conducive to disease outbreaks. The majority of rice diseases cause enormous economic damage and yield instability. Among them, rice blast caused by Magnaportheoryzae is a serious fungal disease and is considered one of the major threats to world rice production. This pathogen can infect the above-ground tissues of rice plants at any growth stage and causes complete crop failure under favorable conditions. Therefore, management of blast disease is essentially required to sustain global food production. When looking at the drawback of chemical management strategy, the development of durable, resistant varieties is one of the most sustainable, economic, and environment-friendly approaches to counter the outbreaks of rice blasts. Interestingly, several blast-resistant rice cultivars have been developed with the help of breeding and biotechnological methods. In addition, 146 R genes have been identified, and 37 among them have been molecularly characterized to date. Further, more than 500 loci have been identified for blast resistance which enhances the resources for developing blast resistance through marker-assisted selection (MAS), marker-assisted backcross breeding (MABB), and genome editing tools. Apart from these, a better understanding of rice blast pathogens, the infection process of the pathogen, and the genetics of the immune response of the host plant are very important for the effective management of the blast disease. Further, high throughput phenotyping and disease screening protocols have played significant roles in easy comprehension of the mechanism of disease spread. The present review critically emphasizes the pathogenesis, pathogenomics, screening techniques, traditional and molecular breeding approaches, and transgenic and genome editing tools to develop a broad spectrum and durable resistance against blast disease in rice. The updated and comprehensive information presented in this review would be definitely helpful for the researchers, breeders, and students in the planning and execution of a resistance breeding program in rice against this pathogen.

Biotrophic invasive hyphae (IH) of the blast fungus Magnaporthe oryzae secrete effectors to alter host defenses and cellular processes as they successively invade living rice (Oryza sativa) cells. However, few blast effectors have been identified. Indeed, understanding fungal and rice genes contributing to biotrophic invasion has been difficult because so few plant cells have encountered IH at the earliest infection stages. We developed a robust procedure for isolating infected-rice sheath RNAs in which ~20% of the RNA originated from IH in first-invaded cells. We analyzed these IH RNAs relative to control mycelial RNAs using M. oryzae oligoarrays. With a 10-fold differential expression threshold, we identified known effector PWL2 and 58 candidate effectors. Four of these candidates were confirmed to be fungal biotrophy-associated secreted (BAS) proteins. Fluorescently labeled BAS proteins were secreted into rice cells in distinct patterns in compatible, but not in incompatible, interactions. BAS1 and BAS2 proteins preferentially accumulated in biotrophic interfacial complexes along with known avirulence effectors, BAS3 showed additional localization near cell wall crossing points, and BAS4 uniformly outlined growing IH. Analysis of the same infected-tissue RNAs with rice oligoarrays identified putative effector-induced rice susceptibility genes, which are highly enriched for sensor-transduction components rather than typically identified defense response genes.