Frontiers in Plant Science最新文献

{"title":"Herbicide resistance in <i>Leptochloa chinensis</i> (L.) Nees populations from different regions of Jiangsu Province, China: sensitivity differences and underlying mechanisms.","authors":"Peng Xu, Ke Wang, Yawen Ju, Yousheng Fu, Axiu Zhu, Kaige Cao, Hongchun Wang","doi":"10.3389/fpls.2025.1535877","DOIUrl":"10.3389/fpls.2025.1535877","url":null,"abstract":"<p><p><i>Leptochloa chinensis</i> (L.) Nees, a noxious weed species commonly found in rice fields, has become a significant challenge in Jiangsu Province, China, as it has developed resistance to multiple herbicides due to extensive and continuous herbicide use in recent years. Therefore, this study was conducted to elucidate sensitivity differences and the mechanisms underlying the resistance of <i>L. chinensis</i> (L.) Nees populations to commonly used herbicides across different regions of Jiangsu Province, China. A whole-plant bioassay was used to assess the sensitivity of 46 <i>L. chinensis</i> populations collected from various areas within Jiangsu to several herbicides frequently applied in paddy fields, including: cyhalofop-butyl, fenoxaprop-P-ethyl, pyraclonil, benzobicyclon, anilofos, and oxaziclomefone. After treatment with cyhalofop-butyl, 38 out of 46 populations showed relative resistance-index values that were over four times that of the controls, indicating significant resistance to cyhalofop-butyl. All 41 cyhalofop-butyl-resistant populations showed cross-resistance to fenoxaprop-P-ethyl but remained susceptible to pyraclonil, benzobicyclon, anilofos, and oxaziclomefone. The proportion of populations resistant to acetyl-CoA carboxylase (ACCase)-inhibiting herbicides increased progressively from the south to the north of Jiangsu. Cross-resistance was evident between cyhalofop-butyl and fenoxaprop-P-ethyl; however, all resistant populations were susceptible to pyraclonil, benzobicyclon, anilofos, and oxaziclomefone. Furthermore, mutations in the <i>ACCase</i> gene were identified as a crucial mechanism for cyhalofop-butyl resistance. Specifically, we found <i>ACCase</i> mutations I1781L, W1999C, W2027C/L/S, I2041N, and D2078G in cyhalofop-butyl-resistant <i>L. chinensis</i> populations, among which, W1999C and W2027C accounted for a relatively high proportion, while I1781L, W2027L/S, I2041N, and D2078G were found in one population each. <i>ACCase</i> gene mutations are seemingly a key mechanism for the development of resistance to cyhalofop-butyl, thus, our study provides useful information for developing effective weed-management strategies for controlling this noxious weed species, while ensuring sustainable agricultural practices.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1535877"},"PeriodicalIF":4.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11832499/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143447627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Water and nitrogen regulation strategy for wolfberry farmland based on nitrogen balance in the Yellow River irrigation districts of Gansu Province, China.","authors":"Minhua Yin, Rongrong Tian, Yi Ling, Yuqing Yang, Yanlin Ma, Yanxia Kang, Guangping Qi, Jinghai Wang","doi":"10.3389/fpls.2024.1498332","DOIUrl":"10.3389/fpls.2024.1498332","url":null,"abstract":"<p><p>Agricultural production frequently encounters challenges, including soil nitrogen pollution and imbalances resulting from improper irrigation and fertilization practices. This study focuses on wolfberry farmland, analyzing the effects of four irrigation levels [full irrigation (W0, 75%-85% θ_f), mild water deficit (W1, 65%-75% θ_f), moderate water deficit (W2, 55%-65% θ_f), and severe water deficit (W3, 45%-55% θ_f)] and four nitrogen application levels [no nitrogen application (N0, 0 kg·ha^-1), low nitrogen application (N1, 150 kg·ha^-1), medium nitrogen application (N2, 300 kg·ha^-1), and high nitrogen application (N3, 450 kg·ha^-1)] on nitrogen uptake by wolfberry plants, soil nitrogen loss, plant-soil nitrogen balance, and nitrogen use efficiency. The results indicate that: (1) Plant dry matter yield (1338.90-2893.52 kg·ha^-1), fruit yield (1368.19-2623.09 kg·ha^-1), plant nitrogen uptake (28.32-96.89 kg·ha^-1) and fruit nitrogen uptake (23.53-63.56 kg·ha^-1) all increased with higher irrigation and nitrogen application levels, following the trend W1 > W0 > W2 > W3 and N2 > N3 > N1 > N0. Compared with the other treatments, W1N2 treatment increased by 4.37%-116.11%, 6.36%-91.72%, 15.23%-242.16% and 10.86%-170.13%, respectively. (2) Soil NO₃ ^--N content initially decreased, then increased, and ultimately decreased again with increasing soil depth, demonstrating inconsistent trends in response to changes in irrigation and nitrogen application. The highest residual soil NO₃ ^--N at the end of the wolfberry growth period was recorded in the W0N3 treatment, measuring 186.17 kg·ha^-1. In contrast, the lowest level was observed under the W3N0 treatment at 90.13 kg·ha^-1, which was reduced by 12.25%-51.59% compared with other treatments. (3) The soil N₂O flux (28.50-433.41 ug·m^-2·h^-1) and total emissions (0.40-1.67 kg·ha^-1) increased with increased irrigation and nitrogen application. (4) The W1N1 treatment showed the highest nitrogen productivity (14.29 kg·kg^-1), absorption efficiency (0.85 kg·kg^-1), and recovery efficiency (27.14%), outperformed other treatments by 0.64-10.94 kg·kg^-1, 0.10-0.65 kg·kg^-1, and 2.52-18.80%, respectively. Overall, a combination of 392.40 mm of irrigation and 150 kg·ha^-1 of nitrogen represented the optimal strategy for efficient and sustainable wolfberry production in the Yellow River irrigation districts of Gansu and similar regions.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1498332"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830609/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating sowing uniformity in hybrid rice using image processing and the OEW-YOLOv8n network.","authors":"Zehua Li, Yihui Pan, Xu Ma, Yongjun Lin, Xicheng Wang, Hongwei Li","doi":"10.3389/fpls.2025.1473153","DOIUrl":"10.3389/fpls.2025.1473153","url":null,"abstract":"<p><p>Sowing uniformity is an important evaluation indicator of mechanical sowing quality. In order to achieve accurate evaluation of sowing uniformity in hybrid rice mechanical sowing, this study takes the seeds in a seedling tray of hybrid rice blanket-seedling nursing as the research object and proposes a method for evaluating sowing uniformity by combining image processing methods and the ODConv_C2f-ECA-WIoU-YOLOv8n (OEW-YOLOv8n) network. Firstly, image processing methods are used to segment seed image and obtain seed grids. Next, an improved model named OEW-YOLOv8n based on YOLOv8n is proposed to identify the number of seeds in a unit seed grid. The improved strategies include the following: (1) Replacing the Conv module in the Bottleneck of C2f modules with the Omni-Dimensional Dynamic Convolution (ODConv) module, where C2f modules are located at the connection between the Backbone and Neck. This improvement can enhance the feature extraction ability of the Backbone network, as the new modules can fully utilize the information of all dimensions of the convolutional kernel. (2) An Efficient Channel Attention (ECA) module is added to the Neck for improving the network's capability to extract deep semantic feature information of the detection target. (3) In the Bbox module of the prediction head, the Complete Intersection over Union (CIoU) loss function is replaced by the Weighted Intersection over Union version 3 (WIoUv3) loss function to improve the convergence speed of the bounding box loss function and reduce the convergence value of the loss function. The results show that the mean average precision (mAP) of the OEW-YOLOv8n network reaches 98.6%. Compared to the original model, the mAP improved by 2.5%. Compared to the advanced object detection algorithms such as Faster-RCNN, SSD, YOLOv4, YOLOv5s YOLOv7-tiny, and YOLOv10s, the mAP of the new network increased by 5.2%, 7.8%, 4.9%, 2.8% 2.9%, and 3.3%, respectively. Finally, the actual evaluation experiment showed that the test error is from -2.43% to 2.92%, indicating that the improved network demonstrates excellent estimation accuracy. The research results can provide support for the mechanized sowing quality detection of hybrid rice and the intelligent research of rice seeder.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1473153"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine vision-based detection of key traits in shiitake mushroom caps.","authors":"Jiuxiao Zhao, Wengang Zheng, Yibo Wei, Qian Zhao, Jing Dong, Xin Zhang, Mingfei Wang","doi":"10.3389/fpls.2025.1495305","DOIUrl":"10.3389/fpls.2025.1495305","url":null,"abstract":"<p><p>This study puts forward a machine vision-based prediction method to solve the problem regarding the measurement of traits in shiitake mushroom caps during the shiitake mushroom breeding process. It enables precise phenotyping through accurate image acquisition and analysis. In practical applications, this method improves the breeding process by rapidly and non-invasively assessing key traits such as the size and color of shiitake mushroom caps, which helps in efficiently screening strains and reducing human errors. Firstly, an edge detection model was established. This model is called KL-Dexined. It achieved an per-image best threshold (OIS) rate of 93.5%. Also, it reached an Optimal Dynamic Stabilization (ODS) rate of 96.3%. Moreover, its Average Precision (AP) was 97.1%. Secondly, the edge information detected by KL-Dexined was mapped onto the original image of shiitake mushroom caps, and using the OpenCV model,11 phenotypic key features including shiitake mushroom caps area, perimeter, and external rectangular length were obtained. Experimental results demonstrated that the R² between predicted values and true values was 0.97 with an RMSE as low as 0.049. After conducting correlation analysis between phenotypic features and shiitake mushroom caps weight, four most correlated phenotypic features were identified: Area, Perimeter, External rectangular width, and Long axis; they were divided into four groups based on their correlation rankings. Finally,M3 group using GWO_SVM algorithm achieved optimal performance among six mainstream machine learning models tested with an R²value of 0.97 and RMSE only at 0.038 when comparing predicted values with true values. Hence, this study provided guidance for predicting key traits in shiitake mushroom caps.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1495305"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830683/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>BvBZR1</i> improves parenchyma cell development and sucrose accumulation in sugar beet (<i>Beta vulgaris</i> L.) taproot.","authors":"Ningning Li, Wei Wang, Xiaotong Guo, Yaqing Sun, Guolong Li, Shaoying Zhang","doi":"10.3389/fpls.2025.1495161","DOIUrl":"10.3389/fpls.2025.1495161","url":null,"abstract":"<p><p>BRASSINAZOLE-RESISTANT (BZR) transcription factors, key elements of brassinolide (BR) signal transduction, play an important role in regulating plant growth and development. However, little is known about the molecular regulatory mechanism of BZR in sugar beet taproot growth. In this study, <i>BvBZR1</i> expression was significantly induced by exogenous BR treatment. Transgenic sugar beet overexpressing <i>BvBZR1</i> exhibited a higher taproot diameter compared with the wild type, mainly due to a significant enhancement in the spacing between cambial rings by increasing the size and layers of parenchyma cells. <i>BvBZR1</i> regulated the expression of <i>BvCESA6</i>, <i>BvXTH33</i>, <i>BvFAD3</i>, and <i>BvCEL1</i> and enhanced cell wall metabolism to promote sugar beet taproot growth in parenchyma cells and the development of each cambium ring. In addition, <i>BvBZR1</i> overexpression significantly increased the accumulation of sucrose and soluble sugars in the taproot, which was attributed to its ability to regulate the expression of <i>BvSPS</i> and <i>BvINV</i> and improve the activity of BvSPS, BvSS-S, BvSS-C, and BvINV enzymes in each cambium ring and parenchyma cell in the sugar beet taproot. These results suggest that <i>BvBZR1</i> can regulate the expression of genes related to cell wall and sucrose metabolism, improve corresponding enzyme activity, and promote the development of each cambium ring and parenchyma cell, thereby promoting the growth and development of sugar beet taproots.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1495161"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated physiological and transcriptomic data revealed the cold-resistant mechanisms in reproductive organs of the 'Jinguang' pear cultivar.","authors":"Mengying Sun, Shun Lin, Zezhao Zhao, Weizhen Guo, Min Jiang, Ying Li, Jun Zhang, Jingxian Zhao, Minsheng Yang","doi":"10.3389/fpls.2024.1501774","DOIUrl":"10.3389/fpls.2024.1501774","url":null,"abstract":"<p><p>The <i>Pyrus</i> spp. (pears) are crucial for the fruit industry; however, low spring temperatures can cause frost damage to their reproductive organs, which poses challenges to the final yields. In this study, we evaluated the response of the flowers and young fruits of the 'Jinguang' pear cultivar to low temperatures from integrated phenotypic, physiological, and molecular approaches. We found that the flowers were less sensitive to low temperatures than the young fruits, of which their over-cooling points were -5.6°C and -5.0°C, respectively. Transcriptomic data showed that the differentially expressed genes from flowers and young fruits compared to the control conditions were primarily involved in the biosynthesis of flavonoids, phenylalanine, and tyrosine. Further weighted gene co-expression network analysis uncovered the core transcription factors that may be potentially involved in the pear cold resistance, including <i>MYB20</i>, <i>WRKY53</i>, and <i>WRKY30</i>. Our findings provide valuable insights and candidate gene resources for further exploration of the molecular mechanisms underlying cold resistance in pear trees.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1501774"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830666/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative analysis of metabolite and transcriptome reveals the biosynthetic pathway and candidate genes for iridoid glycoside biosynthesis in <i>Neopicrorhiza scrophulariiflora</i> (Pennell) D.Y.Hong.","authors":"Ke Rao, Siyu Liu, Xiaohui Tang, Guofu Jia, Shaohua Yang, Chaoxiang Ren, Jin Pei","doi":"10.3389/fpls.2025.1527477","DOIUrl":"10.3389/fpls.2025.1527477","url":null,"abstract":"<p><p><i>Neopicrorhiza scrophulariiflora</i> (Pennell) D.Y.Hong (<i>N. scrophulariiflora</i>) is an important wild medicinal plant that belongs to the Plantaginaceae family. Its main active ingredients, picroside I (P-I) and picroside II (P-II), possess anti-inflammatory, anticancer, and antibacterial properties. Due to overharvesting, <i>N. scrophulariiflora</i> resources are facing the risk of depletion, urgently requiring resource protection and rational utilization. However, the biosynthetic pathways and related genes of active compounds in <i>N. scrophulariiflora</i> have not been fully investigated. In this study, widely targeted metabolomics and RNA-seq technology were employed to perform a joint analysis of the metabolome and transcriptome in different tissues of <i>N. scrophulariiflora</i>, including the roots, stems, and leaves. A total of 196 flavonoids and 63 terpenoids were identified. Among the 158,254 annotated genes, 74 were annotated as related to iridoid synthesis. Using bioinformatics methods such as clustering analysis, phylogenetic tree construction, and weighted gene co-expression network analysis (WGCNA), 43 candidate genes were identified that may be involved in the biosynthesis of picroside-I and picroside-II, of which 26 genes were significantly correlated with the synthesis of picrosides and their intermediates. Transcriptome analysis revealed the expression patterns of differentially expressed genes, and metabolomic analysis revealed the distribution characteristics of metabolites in different tissues of <i>N. scrophulariiflora</i>. Through qRT-PCR validation, we found that three <i>NsF3H/NsF3D</i> genes, four <i>NsUGD/NsUPD</i> genes, one <i>Ns2HFD</i> gene, and three <i>NsSQM</i> genes may participate in the iridoid biosynthesis pathway. These findings provide important genetic and metabolomic information for an in-depth understanding of the biosynthetic mechanisms of iridoids and lay the foundation for the protection and sustainable utilization of <i>N. scrophulariiflora</i>.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1527477"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nano-selenium strengthens potato resistance to potato scab induced by <i>Streptomyces</i> spp., increases yield, and elevates tuber quality by influencing rhizosphere microbiomes.","authors":"Haixu Liu, Yan Zhang, Lili Zhang, Yingjie Liu, Yufei Chen, Ying Shi","doi":"10.3389/fpls.2025.1523174","DOIUrl":"10.3389/fpls.2025.1523174","url":null,"abstract":"<p><strong>Introduction: </strong>The application of selenium could directly or indirectly modulate the activity of antioxidant enzymes in crops, thereby mitigating the detrimental effects of abiotic and biotic stresses on crop health. However, there are few studies on the effects of nano-selenium fertilizer on potato scab caused by <i>Streptomyces</i> spp., potato yield and tuber quality.</p><p><strong>Methods: </strong>We aimed to elucidate the impact of nano-selenium fertilizer on potato disease resistance, yield, tuber quality, antioxidant enzyme activity and rhizosphere soil bacterial communities, and to determine the optimal frequency and growth stages of nano-selenium fertilizer spraying.</p><p><strong>Results and discussion: </strong>The application of nano-selenium fertilizer twice during the seedling stage significantly reduced the disease index of potato scab, enhanced potato yield, tuber quality (dry matter, Vitamin C, crude protein, and selenium content), and antioxidant enzyme activity (glutathione peroxidase, peroxidase, polyphenol oxidase, superoxide dismutase, and phenylalanine ammonia lyase). The diversity of the rhizosphere bacterial community of potatoes subjected to selenium fertilizer spraying at the seedling stage increased significantly, and concurrently, the symbiotic network of rhizosphere bacterial microbiome grew more complex. Beneficial microorganisms such as bacteria of the genus <i>Bacillus</i> were enriched in the rhizosphere soil. The current study provided theoretical support for the exploration of a potato selenium-enriched technology system and supplies scientific guidance for the utilization of nano-selenium.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1523174"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830815/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Highlights of iMMM2023 - International Molecular Mycorrhiza Meeting.","authors":"Marcel Bucher, Andrea Genre, Hiromu Kameoka, Luisa Lanfranco, Uta Paszkowski, Li Xue","doi":"10.3389/fpls.2025.1559814","DOIUrl":"10.3389/fpls.2025.1559814","url":null,"abstract":"","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1559814"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830810/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep phenotyping platform for microscopic plant-pathogen interactions.","authors":"Stefanie Lück, Salim Bourras, Dimitar Douchkov","doi":"10.3389/fpls.2025.1462694","DOIUrl":"10.3389/fpls.2025.1462694","url":null,"abstract":"<p><p>The increasing availability of genetic and genomic resources has underscored the need for automated microscopic phenotyping in plant-pathogen interactions to identify genes involved in disease resistance. Building on accumulated experience and leveraging automated microscopy and software, we developed <i>BluVision Micro</i>, a modular, machine learning-aided system designed for high-throughput microscopic phenotyping. This system is adaptable to various image data types and extendable with modules for additional phenotypes and pathogens. <i>BluVision Micro</i> was applied to screen 196 genetically diverse barley genotypes for interactions with powdery mildew fungi, delivering accurate, sensitive, and reproducible results. This enabled the identification of novel genetic loci and marker-trait associations in the barley genome. The system also facilitated high-throughput studies of labor-intensive phenotypes, such as precise colony area measurement. Additionally, <i>BluVision</i>'s open-source software supports the development of specific modules for various microscopic phenotypes, including high-throughput transfection assays for disease resistance-related genes.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"16 ","pages":"1462694"},"PeriodicalIF":4.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11832026/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}