Plant Methods最新文献

{"title":"DSCONV-GAN: a UAV-BASED model for Verticillium Wilt disease detection in Chinese cabbage in complex growing environments.","authors":"Jun Zhang, Dongfang Zhang, Jingyan Liu, Yuhong Zhou, Xiaoshuo Cui, Xiaofei Fan","doi":"10.1186/s13007-024-01303-2","DOIUrl":"https://doi.org/10.1186/s13007-024-01303-2","url":null,"abstract":"<p><p>Verticillium wilt greatly hampers Chinese cabbage growth, causing significant yield limitations. Rapid and accurate detection of Verticillium wilt in the Chinese cabbage (Brassica rapa L. ssp. pekinensis) can provide significant agronomic benefits. Here, we propose a detection model, DSConv-GAN, which is based on images acquired by an unmanned aerial vehicle (UAV). Based on YOLOv8, with the addition of the dynamic snake convolution (DSConv) module and the improved loss function maximum possible distance intersection-over-union (MPDIoU), we acquired enhanced complex structures and global characteristics in Chinese cabbage images under different growth conditions. To reduce the difficulty of acquiring diseased Chinese cabbage data, a cycle-consistent generative adversarial network (CycleGAN) was used to simulate and generate images of the Verticillium wilt characteristics for multiple fields. The detection of lightly infected plants achieved precision, recall, mean average precision (mAP), and F1-score of 81.3, 86.6, 87.7, and 83.9%, respectively. DSConv-GAN outperforms other models in terms of precision, detection speed, robustness, and generalization. The model is combined with software to improve the practicability of the proposed method. Our results demonstrate DSConv-GAN to be an effective intelligent farming tool that provides early, rapid, and accurate detection of Chinese cabbage Verticillium wilt in complex growing environments.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"186"},"PeriodicalIF":4.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal resolution trumps spectral resolution in UAV-based monitoring of cereal senescence dynamics.","authors":"Flavian Tschurr, Lukas Roth, Nicola Storni, Olivia Zumsteg, Achim Walter, Jonas Anderegg","doi":"10.1186/s13007-024-01308-x","DOIUrl":"https://doi.org/10.1186/s13007-024-01308-x","url":null,"abstract":"<p><strong>Background: </strong>Senescence is a complex developmental process that is regulated by a multitude of environmental, genetic, and physiological factors. Optimizing the timing and dynamics of this process has the potential to significantly impact crop adaptation to future climates and for maintaining grain yield and quality, particularly under terminal stress. Accurately capturing the dynamics of senescence and isolating the genetic variance component requires frequent assessment as well as intense field testing. Here, we evaluated and compared the potential of temporally dense drone-based RGB- and multispectral image sequences for this purpose. Regular measurements were made throughout the grain filling phase for more than 600 winter wheat genotypes across three experiments in a high-yielding environment of temperate Europe. At the plot level, multispectral and RGB indices were extracted, and time series were modelled using different parametric and semi-parametric models. The capability of these approaches to track senescence was evaluated based on estimated model parameters, with corresponding parameters derived from repeated visual scorings as a reference. This approach represents the need for remote-sensing based proxies that capture the entire process, from the onset to the conclusion of senescence, as well as the rate of the progression.</p><p><strong>Results: </strong>Our results indicated the efficacy of both RGB and multispectral reflectance indices in monitoring senescence dynamics and accurately identifying key temporal parameters characterizing this phase, comparable to more sophisticated proximal sensing techniques that offer limited throughput. Correlation coefficients of up to 0.8 were observed between multispectral (NDVIred668-index) and visual scoring, respectively 0.9 between RGB (ExGR-index) and visual scoring. Sub-sampling of measurement events demonstrated that the timing and frequency of measurements were highly influential, arguably even more than the choice of sensor.</p><p><strong>Conclusions: </strong>Remote-sensing based proxies derived from both RGB and multispectral sensors can capture the senescence process accurately. The sub-sampling emphasized the importance of timely and frequent assessments, but also highlighted the need for robust methods that enable such frequent assessments to be made under variable environmental conditions. The proposed measurement and data processing strategies can improve the measurement and understanding of senescence dynamics, facilitating adaptive crop breeding strategies in the context of climate change.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"188"},"PeriodicalIF":4.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quality assurance of hyperspectral imaging systems for neural network supported plant phenotyping.","authors":"Justus Detring, Abel Barreto, Anne-Katrin Mahlein, Stefan Paulus","doi":"10.1186/s13007-024-01315-y","DOIUrl":"https://doi.org/10.1186/s13007-024-01315-y","url":null,"abstract":"<p><strong>Background: </strong>This research proposes an easy to apply quality assurance pipeline for hyperspectral imaging (HSI) systems used for plant phenotyping. Furthermore, a concept for the analysis of quality assured hyperspectral images to investigate plant disease progress is proposed. The quality assurance was applied to a handheld line scanning HSI-system consisting of evaluating spatial and spectral quality parameters as well as the integrated illumination. To test the spatial accuracy at different working distances, the sine-wave-based spatial frequency response (s-SFR) was analysed. The spectral accuracy was assessed by calculating the correlation of calibration-material measurements between the HSI-system and a non-imaging spectrometer. Additionally, different illumination systems were evaluated by analysing the spectral response of sugar beet canopies. As a use case, time series HSI measurements of sugar beet plants infested with Cercospora leaf spot (CLS) were performed to estimate the disease severity using convolutional neural network (CNN) supported data analysis.</p><p><strong>Results: </strong>The measurements of the calibration material were highly correlated with those of the non-imaging spectrometer (r>0.99). The resolution limit was narrowly missed at each of the tested working distances. Slight sharpness differences within individual images could be detected. The use of the integrated LED illumination for HSI can cause a distortion of the spectral response at 677nm and 752nm. The performance for CLS diseased pixel detection of the established CNN was sufficient to estimate a reliable disease severity progression from quality assured hyperspectral measurements with external illumination.</p><p><strong>Conclusion: </strong>The quality assurance pipeline was successfully applied to evaluate a handheld HSI-system. The s-SFR analysis is a valuable method for assessing the spatial accuracy of HSI-systems. Comparing measurements between HSI-systems and a non-imaging spectrometer can provide reliable results on the spectral accuracy of the tested system. This research emphasizes the importance of evenly distributed diffuse illumination for HSI. Although the tested system showed shortcomings in image resolution, sharpness, and illumination, the high spectral accuracy of the tested HSI-system, supported by external illumination, enabled the establishment of a neural network-based concept to determine the severity and progression of CLS. The data driven quality assurance pipeline can be easily applied to any other HSI-system to ensure high quality HSI.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"189"},"PeriodicalIF":4.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an infiltration-based RNA preservation method for cryogen-free storage of leaves for gene expression analyses in field-grown plants.","authors":"Yoshiaki Ueda","doi":"10.1186/s13007-024-01311-2","DOIUrl":"https://doi.org/10.1186/s13007-024-01311-2","url":null,"abstract":"<p><strong>Background: </strong>Gene expression is a fundamental process for plants to express their phenotype, and its analysis is the basis of molecular studies. However, the instability of RNA often poses an obstacle to analyzing plants grown in fields or remote locations where the availability of liquid nitrogen or dry ice is limited. To deepen our understanding of plant phenotypes and tolerance to field-specific stresses, it is crucial to develop methodologies to maintain plant RNA intact and safely transfer it for downstream analyses such as qPCR and RNA-seq.</p><p><strong>Results: </strong>In this study, the author developed a novel tissue preservation method that involved the infiltration of RNA preservation solution into the leaf apoplast using a syringe and subsequent storage at 4 °C. RNA-seq using samples stored for 5 d and principal component analyses showed that rice leaves treated with the infiltration method maintained the original transcriptome pattern better than those treated with the traditional method when the leaves were simply immersed in the solution. Additionally, it was also found that extracted RNA can be transported with minimum risk of degradation when it is bound to the membrane of RNA extraction kits. The developed infiltration method was applied to rice plants grown in a local farmer's field in northern Madagascar to analyze the expression of nutrient-responsive genes, suggesting nutrient imbalances in some of the fields examined.</p><p><strong>Conclusions: </strong>This study showed that the developed infiltration method was effective in preserving the transcriptome status of rice and sorghum leaves when liquid nitrogen or a deep freezer is not available. The developed method was useful for diagnosing plants in the field based on the expression of nutrient-responsive marker genes. Moreover, the method used to protect RNA samples from degradation during transportation offers the possibility to use them for RNA-seq. This novel technique could pave the way for revealing the molecular basis of plant phenotypes by accelerating gene expression analyses using plant samples that are unique in the field.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"187"},"PeriodicalIF":4.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic investigation and validation of peanut genetic transformation via the pollen tube injection method.","authors":"Chen Huang, Chen Yang, Huifang Yang, Yadi Gong, Xiaomeng Li, Lexin Li, Ling Li, Xu Liu, Xiaoyun Li","doi":"10.1186/s13007-024-01314-z","DOIUrl":"https://doi.org/10.1186/s13007-024-01314-z","url":null,"abstract":"<p><p>Genetic transformation is a pivotal approach in plant genetic engineering. Peanut (Arachis hypogaea L.) is an important oil and cash crop, but the stable genetic transformation of peanut is still difficult and inefficient. Recently, the pollen tube injection pathway has been shown to be effective for the genetic transformation of peanut. However, the poor reproducibility of this pathway is still controversial. In this study, the appropriate time and location of injection, along with transgenic screening, were systematically investigated in the pollen tube mediated peanut genetic transformation. Our findings revealed that Agrobacterium injections could be conducted within a time window of two to three hours preceding and succeeding the blooming process. Among the various selective markers evaluated, the Basta screening emerged as the most expedient, followed closely by the DsRed visual screening. According to resistance screening and molecular identification, the average transformation efficiency was 2.6% in the heritable transgenic progenies, which was more likely affected by individual operation by style cavity injection. Furthermore, the use of synergistic FT artificially regulated the blooming of peanuts under indoor conditions, facilitating operations involving keel petal injection and ultimately enhancing the genetic transformation efficiency. Thus, our study systematically validated the feasibility of peanut genetic transformation through an optimized pollen-tube injection technique without tissue culture, potentially guiding future advancements in peanut engineering and molecular breeding programs.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"190"},"PeriodicalIF":4.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction and mapping of leaf water content in Populus alba var. pyramidalis using hyperspectral imagery.","authors":"Zhao-Kui Li, Hong-Li Li, Xue-Wei Gong, Heng-Fang Wang, Guang-You Hao","doi":"10.1186/s13007-024-01312-1","DOIUrl":"https://doi.org/10.1186/s13007-024-01312-1","url":null,"abstract":"<p><p>Leaf water content (LWC) encapsulates critical aspects of tree physiology and is considered a proxy for assessing tree drought stress and the risk of forest decline; however, its measurement relies on destructive sampling and is thus less efficient. Advancements in hyperspectral imaging technology present new prospects for noninvasively evaluating LWC and mapping drought severity across forested regions. In this study, leaf samples were obtained from Populus alba var. pyramidalis, a species widely employed for constructing farmland shelterbelts in water-limited regions of northern China but notably susceptible to drought. These samples were dehydrated to varying degrees to generate concurrent LWC measurements and hyperspectral images, enabling the development of narrow-band and multivariate spectral prediction models for LWC estimation. Two visible-spectrum narrow-band indices identified, the single-band index (R₆₂₇) and the band subtraction index (R₄₃₇ - R₄₄₄), demonstrated a strong correlation with LWC. Despite certain influences of variable preprocessing and selection on multivariate model performance, most models exhibited robust predictive accuracy for LWC. The FDRL-UVE-PLSR combination emerged as the optimal multivariate model, with R² values reaching 0.9925 and 0.9853 and RMSE values below 0.0124 and 0.0264 for the calibration and validation datasets, respectively. Using this optimal model, along with localized spectral smoothing, moisture distribution across leaf surfaces was visualized, revealing lower water retention at the leaf margins compared to central regions. These methodologies provide critical insights into subtle water-associated physiological processes at the leaf scale and facilitate high-frequency, large-scale assessments and monitoring of drought stress levels and the risk of drought-induced tree mortality and forest degradation in drylands.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"184"},"PeriodicalIF":4.7,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-vivo Raman microspectroscopy reveals differential nitrate concentration in different developmental zones in Arabidopsis roots.","authors":"Alma Fernández González, Ze Tian Fang, Dipankar Sen, Brian Henrich, Yukihiro Nagashima, Alexei V Sokolov, Sakiko Okumoto, Aart J Verhoef","doi":"10.1186/s13007-024-01302-3","DOIUrl":"https://doi.org/10.1186/s13007-024-01302-3","url":null,"abstract":"<p><strong>Background: </strong>Nitrate (NO₃^-) is one of the two major forms of inorganic nitrogen absorbed by plant roots, and the tissue nitrate concentration in roots is considered important for optimizing developmental programs. Technologies to quantify the expression levels of nitrate transporters and assimilating enzymes at the cellular level have improved drastically in the past decade. However, a technological gap remains for detecting nitrate at a high spatial resolution. Using extraction-based methods, it is challenging to reliably estimate nitrate concentration from a small volume of cells (i.e., with high spatial resolution), since targeting a small or specific group of cells is physically difficult. Alternatively, nitrate detection with microelectrodes offers subcellular resolution with high cell specificity, but this method has some limitations on cell accessibility and detection speed. Finally, optical nitrate biosensors have very good (in-vivo) sensitivity (below 1 mM) and cellular-level spatial resolution, but require plant transformation, limiting their applicability. In this work, we apply Raman microspectroscopy for high-dynamic range in-vivo mapping of nitrate in different developmental zones of Arabidopsis thaliana roots in-situ.</p><p><strong>Results: </strong>As a proof of concept, we have used Raman microspectroscopy for in-vivo mapping of nitrate content in roots of Arabidopsis seedlings grown on agar media with different nitrate concentrations. Our results revealed that the root nitrate concentration increases gradually from the meristematic zone (~ 250 µm from the root cap) to the maturation zone (~ 3 mm from the root cap) in roots grown under typical growth conditions used for Arabidopsis, a trend that has not been previously reported. This trend was observed for plants grown in agar media with different nitrate concentrations (0.5-10 mM). These results were validated through destructive measurement of nitrate concentration.</p><p><strong>Conclusions: </strong>We present a methodology based on Raman microspectroscopy for in-vivo label-free mapping of nitrate within small root tissue volumes in Arabidopsis. Measurements are done in-situ without additional sample preparation. Our measurements revealed nitrate concentration changes from lower to higher concentration from tip to mature root tissue. Accumulation of nitrate in the maturation zone tissue shows a saturation behavior. The presented Raman-based approach allows for in-situ non-destructive measurements of Raman-active compounds.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"185"},"PeriodicalIF":4.7,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minirhizotron measurements can supplement deep soil coring to evaluate root growth of winter wheat when certain pitfalls are avoided.","authors":"Jessica Arnhold, Facundo R Ispizua Yamati, Henning Kage, Anne-Katrin Mahlein, Heinz-Josef Koch, Dennis Grunwald","doi":"10.1186/s13007-024-01313-0","DOIUrl":"https://doi.org/10.1186/s13007-024-01313-0","url":null,"abstract":"<p><strong>Background: </strong>Root growth is most commonly determined with the destructive soil core method, which is very labor-intensive and destroys the plants at the sampling spots. The alternative minirhizotron technique allows for root growth observation throughout the growing season at the same spot but necessitates a high-throughput image analysis for being labor- and cost-efficient. In this study, wheat root development in agronomically varied situations was monitored with minirhizotrons over the growing period in two years, paralleled by destructive samplings at two dates. The aims of this study were to (i) adapt an existing CNN-based segmentation method for wheat minirhizotron images, (ii) verify the results of minirhizotron measurements with root growth data obtained by the destructive soil core method, and (iii) investigate the effect of the presence of the minirhizotron tubes on root growth.</p><p><strong>Results: </strong>The previously existing CNN could successfully be adapted for wheat root images. The minirhizotron technique seems to be more suitable for root growth observation in the subsoil, where a good agreement with destructively gathered data was found, while root length results in the topsoil were dissatisfactory in comparison to the soil core method in both years. The tube presence was found to affect root growth only if not installed with a good soil-tube contact which can be achieved by slurrying, i.e. filling gaps with a soil/water suspension.</p><p><strong>Conclusions: </strong>Overall, the minirhizotron technique in combination with high-throughput image analysis seems to be an alternative and valuable technique for suitable research questions in root research targeting the subsoil.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"183"},"PeriodicalIF":4.7,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142838570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights into lncRNA-mediated regulatory networks in Hevea brasiliensis under anthracnose stress.","authors":"Yanluo Zeng, Tianbin Guo, Liping Feng, Zhuoda Yin, Hongli Luo, Hongyan Yin","doi":"10.1186/s13007-024-01301-4","DOIUrl":"10.1186/s13007-024-01301-4","url":null,"abstract":"<p><p>In recent years, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have emerged as critical regulators in plant biology, governing complex gene regulatory networks. In the context of disease resistance in Hevea brasiliensis, the rubber tree, significant progress has been made in understanding its response to anthracnose disease, a serious threat posed by fungal pathogens impacting global rubber tree cultivation and latex quality. While advances have been achieved in unraveling the genetic and molecular foundations underlying anthracnose resistance, gaps persist in comprehending the regulatory roles of lncRNAs and miRNAs under such stress conditions. The specific contributions of these non-coding RNAs in orchestrating molecular responses against anthracnose in H. brasiliensis remain unclear, necessitating further exploration to uncover strategies that increase disease resistance. Here, we integrate lncRNA sequencing, miRNA sequencing, and degradome sequencing to decipher the regulatory landscape of lncRNAs and miRNAs in H. brasiliensis under anthracnose stress. We investigated the genomic and regulatory profiles of differentially expressed lncRNAs (DE-lncRNAs) and constructed a competitive endogenous RNA (ceRNA) regulatory network in response to pathogenic infection. Additionally, we elucidated the functional roles of HblncRNA29219 and its antisense hbr-miR482a, as well as the miR390-TAS3-ARF pathway, in enhancing anthracnose resistance. These findings provide valuable insights into plant-microbe interactions and hold promising implications for advancing agricultural crop protection strategies. This comprehensive analysis sheds light on non-coding RNA-mediated regulatory mechanisms in H. brasiliensis under pathogen stress, establishing a foundation for innovative approaches aimed at enhancing crop resilience and sustainability in agriculture.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"182"},"PeriodicalIF":4.7,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11619270/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780527","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":"The rGO@AuNPs modified label-free electrochemical immunosensor to sensitive detection of CP-BNYVV protein of Rhizomania disease agent in sugar beet.","authors":"Marziye Karimzade, Hashem Kazemzadeh-Beneh, Negar Heidari, Mehrasa Rahimi Boroumand, Parviz Norouzi, Mohammad Reza Safarnejad, Masoud Shams-Bakhsh","doi":"10.1186/s13007-024-01307-y","DOIUrl":"https://doi.org/10.1186/s13007-024-01307-y","url":null,"abstract":"<p><p>For the first time, a novel simple label-free electrochemical immunosensor was fabricated for sensitive detection of the coat protein of beet necrotic yellow vein virus (CP-BNYVV) as the causal agent of Rhizomania disease in sugar beet. To boost the amplification of the electrochemical signal, gold nanoparticles-reduced graphene oxide (AuNPs-rGO) nanocomposite was employed to modify the glassy carbon electrode. Anti-BNYVV polyclonal was immobilized onto a modified electrode by applying a thiol linker via a self-assembly monolayer (SAM) and activating the functionalized surface using (3-aminopropyl triethoxysilane) and glutaraldehyde. The determination step relied on the forming of an immunocomplex between the antigen and oriented antibody, resulting in a decrease in current in the [Fe (CN)₆]^3-/4- redox reaction. The response value exhibited direct proportionality to the concentrations of CP-BNYVV. Scanning electron microscopy, energy dispersive x-ray, cyclic voltammetry, and electrochemical impedance spectroscopy techniques collectively provided a comprehensive understanding of the structural, morphological, and electrochemical features during the modification steps. Under optimized experimental conditions, the fast Fourier transform square wave voltammetry responds to the logarithm of CP-BNYVV concentrations in a wide linear range from 0.5 to 50000 pg/mL and the limit of detection is calculated to be 150 fg/mL, implying the admirable sensitivity. Selectivity assay exhibited no cross-reactivity with other proteins from interfering virus samples. Satisfactory reproducibility and stability were achieved with a relative standard deviation of 3.1% and a stable value of 90% after 25 days, respectively. More importantly, the high performance of the immunosensor resulted in the direct detection of CP-BNYVV in spiked and infected plant samples, which affords a sensing platform with huge potential application for the early detection of BNYVV virus in field conditions.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"181"},"PeriodicalIF":4.7,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11608474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142771368","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}