Raghav Jain, Mandira Kochar, Mukul Kumar Dubey, Shayam Sundar Sharma, Wenrong Yang and David Cahill*,
{"title":"Advancing Diagnostics for Xanthomonas oryzae pv. oryzae: Challenges and Future Directions","authors":"Raghav Jain, Mandira Kochar, Mukul Kumar Dubey, Shayam Sundar Sharma, Wenrong Yang and David Cahill*, ","doi":"10.1021/acsagscitech.5c00197","DOIUrl":null,"url":null,"abstract":"<p ><i>Xanthomonas oryzae</i> pv. <i>oryzae</i> (Xoo) is a widespread bacterial pathogen in rice with worldwide implications. This pathogen causes bacterial blight in rice and is a concern for global food security, causing up to 50% yield loss. This review provides a comprehensive analysis of Xoo, including its global distribution, disease cycle, and current management strategies, while critically evaluating the limitations of existing diagnostic methods. By focusing on Xoo, the paper addresses a gap in research that mostly focuses on the wider <i>Xanthomonas</i> genus. Emphasizing the role of Xoo in maintaining rice health, the review underscores the importance of detecting Xoo for successful disease management. Conventional approaches such as visual inspection, biochemical assays, and PCR-based techniques often lack the sensitivity, specificity, and scalability required for early and accurate detection, especially in resource-limited settings. To address these challenges, the review explores both current and emerging diagnostic technologies, including molecular, serological, and innovative field-deployable methods. Particular attention is given to advanced tools like biosensors, artificial intelligence, and IoT-enabled systems, which promise to enhance precision and efficiency in pathogen detection. By identifying research gaps and proposing actionable pathways, this work underscores the need for integrating traditional and modern diagnostic methods to achieve accessible, scalable, and effective solutions. These advancements hold the potential to revolutionize Xoo management, ensuring sustainable rice production and global food security.</p>","PeriodicalId":93846,"journal":{"name":"ACS agricultural science & technology","volume":"5 8","pages":"1529–1548"},"PeriodicalIF":2.9000,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS agricultural science & technology","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsagscitech.5c00197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Xanthomonas oryzae pv. oryzae (Xoo) is a widespread bacterial pathogen in rice with worldwide implications. This pathogen causes bacterial blight in rice and is a concern for global food security, causing up to 50% yield loss. This review provides a comprehensive analysis of Xoo, including its global distribution, disease cycle, and current management strategies, while critically evaluating the limitations of existing diagnostic methods. By focusing on Xoo, the paper addresses a gap in research that mostly focuses on the wider Xanthomonas genus. Emphasizing the role of Xoo in maintaining rice health, the review underscores the importance of detecting Xoo for successful disease management. Conventional approaches such as visual inspection, biochemical assays, and PCR-based techniques often lack the sensitivity, specificity, and scalability required for early and accurate detection, especially in resource-limited settings. To address these challenges, the review explores both current and emerging diagnostic technologies, including molecular, serological, and innovative field-deployable methods. Particular attention is given to advanced tools like biosensors, artificial intelligence, and IoT-enabled systems, which promise to enhance precision and efficiency in pathogen detection. By identifying research gaps and proposing actionable pathways, this work underscores the need for integrating traditional and modern diagnostic methods to achieve accessible, scalable, and effective solutions. These advancements hold the potential to revolutionize Xoo management, ensuring sustainable rice production and global food security.