Characterization of root hair curling and nodule development in soybean-rhizobia symbioses

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Since roots and nodules are blocked by soil and are hard to be perceived, little knowledge is available on the process of soybean root hair deformation and nodule development over time. Methods In this study, adaptive microrhizotrons and root hair processing method were used to observe root hairs and to investigate detailed root hair deformation and nodule formation. Results It was found that root hairs were not always straight even in uninfected group with relatively small angle (<30°), but root hair curling angle in infected group were large ranging from 32° to 80° since S2 to S6. Nodule was an organ developed late than root hair curling. It initiated from root axis and began to swell in S3, with color changing from light to dark brown in S5. In order to eliminate the observing error, diameter over 1 mm was converted to real diameter with relative formulation. And after conversion, diameter of nodule reached 5 mm in S6. Relationship between root hair curling number/angle and nodule number/diameter indicated that curling angle was strongly related to log nodule diameter (R 2 0.84), and curling number was strongly linear to nodule number (R 2 0.91). Conclusions Thus, nodule number could be calculated through the derived formulation and nodule diameter could be observed and converted to real diameter nondestructively. Soybean-rhizobia symbioses microrhizotron root hair deformation nodule development in situ Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Soybeans provide abundant protein and oil for human and animal diets. During soybean growth, nitrogen plays a critical role and is demanded in a great amount (Freitas et al., 2022 ; Mayhood et al., 2021). Fortunately, soybeans can form symbiotic associations with rhizobia as nodules to fix atmospheric N 2 into ammonia (Cbl et al., 2019 ; Mariana et al., 2023). Successful rhizobia–legume symbioses are the most important nitrogen (N) source in agroecosystem, depending on efficient plant root nodulation and subsequent N 2 fixation (Ferguson et al., 2018 ). Currently, the amount of symbiotically fixed N 2 totals roughly 50%-60% of that demanded in soybean lifetime (Roy et al., 2019). This natural process in rhizobia–legume symbioses is of vital importance in reducing the application of chemical fertilizers and providing more clear nitrogen source for soybean development. Root hair is the initial infection site for symbiotic (rhizobia) in soybean as well as other legume plants (Levine et al., 2007; Cervantes-Pérez et al., 2022 ; Chao et al., 2023). During nodule formation, rhizobia bacteria always attach to root hairs, induce root hair deformation, and form infection thread (Gage et al., 2000; María et al., 2022). Subsequently, the infection thread induces the bacteria to the root cortex and ultimately forms nodule organs with the ability to fix N 2 (Nishida et al., 2018; Wang et al., 2019). The inoculation of rhizobia was closely related to some changes in root morphology and structure (Li et al., 2015 ; Yang et al., 2017; Soyano et al., 2019; Schiessl et al., 2019). Li (Li et al., 2015 ) found that soybean rhizobia increased the size and number of cortical cells in root meristem and elongation areas, which expanded root hair density and root hair area and enable more nodulation. The deformed root hairs always serve as entrapping attached bacteria in the rhizobia–legume symbioses, and have been widely reported to be many shapes such as curling, wiggling, branching, and shepherd (Esseling, et al., 2003; Hwang et al., 2014 ; Ke et al., 2016 ; Velandia et al., 2022). Soybean root hair deformation responded in increase to rhizobia (nod factor) concentration (Duzan et al., 2004 ), but whether more deformed root hairs lead to more nodulation is not clear by literature. In addition, little knowledge is available on the process of soybean root hair deformation, nodule initial, and nodule development over time in situ. Therefore, it is very important to study on root hair deformation progress in soybean-rhizobia symbioses, which will help to understand the process in root hair deformation mechanism. Root hairs are very tiny and sensitive part in rhizobia–legume symbiosis (Fournier J et al., 2008 ; et al., 2021). The length of root hairs ranges from tens of microns to hundreds of microns, but only dozens of microns in width. Owing to the difficulty in observing roots into soil, most researches were carried with destructive method or in agar/solution environment observed using light microscopy (Zhaoming et al., 2017; Schiessl et al., 2019; Xue et al., 2023). It either had the limitation of losing root hairs during sampling, or could not represent real growth under soil environment. In addition, these methods didn’t support successive studies on the same roots over time. X-ray computed tomography (X-CT) (Scotson et al., 2021), nuclear magnetic resonance (NMR) (Metzner et al., 2015) and electrical impedance tomography (EIT) (Peruzzo et al., 2021) were not intended for such tiny root hair traits. To make it applicable to focus on detailed roots such as root hairs, rhizotrons and minirhizotrons were improved and adapted to a smaller scale by amplifying local area (Cai et al., 2016 ; Amato et al., 2012 ; Lu et al., 2019 ; Lu et al., 2022 ). In this study, we intended (1) to observe root hair traits and root nodulation development in rhizobia–legume symbiosis over time with previous designed microrhizotron (1.5 cm 3 in volume) in situ, (2) to clarify detailed root hair deformation from the aspect of shapes and curling angle (deforming extent), (3) to analyze relationship between root hair deformation and nodulation (number/volume), thus to comprehend mechanism in the process of root hair deformation and nodulation, and provide a method for the screening of soybean-rhizobia genotypes with higher nitrogen fixing ability Material and method Plant materials and root hairs in situ observation Soybean (Glycine max cv. Williams82) seeds were surface sterilized by treating with 7% NaClO for 5 min followed by 70% ethanol for 4 min. The seeds were then rinsed three times with sterile deionized water. After sterilization, the seeds were planted in two experimental zones filled with soil taken from local crop growing area. The soil used was filtered 3 times with 1 cm opening filter, and then was sterilized at 80°C for defaunation. One-week-old seedlings were installed with microrhizotrons (1.1 cm × 1.1 cm × 1.2 cm), designed for nondestructive root observation, around soybean root system architecture. Effective installation to intercept with more roots were carried according to the soybean lateral root initial regulations: roots of soybean belong to tetrarch, where lateral roots initiate from pole pericycle cell opposite protoxylem, and generally lateral roots are spaced along the longitudinal axis in four lines. Details see also in (Lu et al., 2019 ; Lu et al., 2020 ). So, four microrhizotrons were preset around each plant roots in depth 50 mm and 100 mm, and in each depth two microrhizotrons were along the direction of cotyledons. Soil compaction was tamped to 0.80–0.83 kg/cm2 after installation (Fig. 1 ). Two-week-old seedlings were flood-inoculated with 15 ml/plant B. japonicum suspension (Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences) for the experimental group. And for the control group, seedlings were irrigated with 15 ml/plant water. The captured images each day (16:00–17:00) were transmitted wireless to the terminal device for further processing. Root hair image was segmented based on deep learning and prior knowledge (Fig. 1 ) (Additional file 1 and Additional file 2). See also in (Lu et al., 2022 ). The proposed model was implemented in Python 3.6, where Keras 2.2.4 and TensorFlow-GPU 1.15.0 are used. The hardware platform is the Intel(R)Core(TM)i7-7700 [email protected] GHz, 8.00 GB memory. GPU is NVIDIA RTX3060, 12 GB memory. Root image processing (root hair and nodule) and root hair separation After segmentation, root hairs were thinning to single pixel used Zhang-Suen thinning algorithm (Zhang et al.,1984). There were some small gaps in root hair, and they were connected by approximating the nearest neighbor root hair with similar slope (Barnes et al., 2009 ; Chen et al., 2019 ). In order to calculate root curling angle, root hairs should be separated from one to another. For the crossing and overlapping root hairs, they were separated based on rules: root hair connectivity and continuity; plant roots and curling grow continuously with angle difference of roots change slowly (Lu et al., 2019 ) (pattern A). As is shown in Fig. 2 , in pattern A, no crossing or overlapping occurs, and there is only one path for the searching to the end. In pattern B, C, and D, there are more than one path for the searching, while only path 2 is the correct one. Path 3 is certainly wrong because the angle difference changes dramatically, and it return to the start area (axis in blue). In pattern B and C, it is also easy to figure out path 1, because these crossing and overlapping are at the end with large angle difference (threshold 80°). But in pattern D, it is a little hard to distinguish path 1 from the correct one, since it has a moderate slope, and might be mixed with real root hair curling. It is found during experiment that root hair curling always occur at root hair end, thus if the crossing point is within 1/2 root, threshold should be set smaller (30°). In detail, the root hair separation algorithm is presented as following steps: Step 1: Root hairs thinning Root hairs were thinning and separated from root axes used Zhang-Suen thinning algorithm and our proposed pruning method (Lu et al., 2022 ). Boundary coordinate of an axis was stored for further root hair connecting with root axis. Step 2: Root hair connecting with root axis After thinning, root hairs were shortened and root axis was thinned. Given the rule that root hair could only be connected to one axis, gaps between root hairs and root axis were connected by approximating the nearest neighbor, considering continuously growing features of root hairs. Boundary coordinate of an axis was compared with end point of root hair (single pixel) to ensure they were neighboring. Step 3: Searching and separating The search started from the root axis (boundary coordinate) along the single-pixel root hair (black arrows). When there was more than one path for the searching forward, angle difference was calculated and compared. If the crossing point is within 1/2 root, angle difference threshold was set as 30°. If it is at the end, where curling appears occasionally, the threshold was set as 80°. Root hairs were separated from one to another for further calculation of root hair curling angle (Additional file 3). Root hair curling angle calculation When the root hair had a small or moderate curvature (Fig. 3 a), the changed direction angle (β) was relatively small or moderate. When the root hair had a large curvature (Fig. 3 b), the changed direction angle (β) could reach more than 180° (Additional file 2). Root hair curling angle represent the changed angle from vector \({\varvec{P}}_{\varvec{i}}{\varvec{P}}_{\varvec{j}}\) and \({\varvec{P}}_{\varvec{k}}{\varvec{P}}_{\varvec{l}}\) (Fig. 3 ). It is defined as: \(\beta\) = arccos \({\varvec{P}}_{\varvec{i}}{\varvec{P}}_{\varvec{j}}\) · \({\varvec{P}}_{\varvec{k}}{\varvec{P}}_{\varvec{l}}\) / (| \({\varvec{P}}_{\varvec{i}}{\varvec{P}}_{\varvec{j}}|\) *| \({\varvec{P}}_{\varvec{k}}{\varvec{P}}_{\varvec{l}}\) |) (1) Where β is the angle between vector \({\varvec{P}}_{\varvec{i}}{\varvec{P}}_{\varvec{j}}\) and \({\varvec{P}}_{\varvec{k}}{\varvec{P}}_{\varvec{l}}\) , · is inner product, and d L is root hair length from point \({P}_{i}\) to \({P}_{k}\) . \({P}_{i}\) is selected as the 1/2 root hair here, since root hair curling always occurs at the root hair end in soybean-rhizobia symbioses. \({P}_{j}\) is the point 5 pixel forward, \({P}_{l}\) is the end point, and \({P}_{k}\) is the point 5 pixel backward. Observed nodule and real nodule conversion When the radius of root nodule is greater than visually soil depth (L), the diameter perceived by researchers(d) will be less than the true size of the nodule (D), as is shown in Fig. 4 . Accurately, the minirhizotron and microrhizotron could only see into soil about 1 mm (Taylor et al., 2014), while the diameter of root nodules could reach more than 4 mm, so the real of root nodules is calculated as: $$D=\frac{{(4L}^{2}+{d}^{2})}{4L}$$ 2 Where D is the real diameter of nodulation, d is the diameter perceived by the camera or human eye, and L is visible depth of soil. In each growing stage (emergence stage, seedling stage, flower bud differentiation stage, flowering pod stage, grain stage, and mature stage), six soybean roots were dug and measured with microcalliper to determine nodule number and diameter. Result Root hair deformation Visually from Fig. 5 , root hairs were almost straight in uninfected group, but in infected group root hairs were complex and not straight. There were several types of root hair deformation in the soybean-rhizobia symbioses, such as wiggling, waving, and branching root hairs (Fig. 5 ), and the largest root hair curling angle was 70° in infected group. Both in infected and uninfected groups, root hairs in depth 50 mm were longer than that in depth 100 mm. This was mainly caused by different developing stages, where roots in shallow soil layer initiated early and roots in deep soil layer initiated late. It could be observed from the images that the later initiating roots were very tender containing much water which made the root seem semitransparent. Root hair curling angle and proportion In infected group, both curling angle and curling proportion increased as plant grew. S4 stage provoked the highest response of root hair deformation proportion (85%), and root hair curling angle reached highest in S5 stage (79 °). Curling angle and curling proportion in infected group was larger than that in uninfected group since S2 stage. In uninfected group, curling angle and curling proportion didn’t change much over a range of growing stage. But it is worth noting that even in uninfected group, some small deformations occurred, which indicated that root hairs were not always straight. It was also obvious in Fig. 6 that there was a proportion of curling root hairs in control group. This was because not all the root hairs were straight, and deformation with small curling angle was also included. So, in further analysis, only curling angle over 32 ° was taken into consideration as real curling root hairs. Nodule development over time Soybean root hair deformation responded in time series (Fig. 7 ). At early inoculation S2 (20 days), root hairs were almost straight. Then it turned curling after a period of inoculation S3 (40 days), and later it showed more types root hair deformation in S4 (60 days). Nodule was an organ developed later than root hair curling. Swelling was observed after root hair deformation in S3 (40 days) and it initiated from root axis with light color similar to root hair and root axis. The swelling part grew bigger and then the nodule formed in dark brown in S5 (80 days). It was noted that when the nodule formed in S5, root hairs were rare and the color of root axis was a little darker containing less water. Nodule volume developed fast at the first four stages, and reached 3 mm in diameter in S4. And in S6, nodule was about 4 mm. It is worth noting that there was an inner circle (observed value) and an outer circle (calculated value) from S2 to S6. This was because, in this case, root nodule was greater than visually soil depth (1 mm), where the diameter perceived was less than the true size of the nodule. There was intersection between inner circle of S6 and outer circle of S5. As nodule volume became large, the difference between observed value and calculated value became large. Compared with digging and measuring experiment (Table 1 ), relative error was 3.94%, 4.84%, 2.08%, 6.16%, and 9.45% in S2, S3, S4, S5, and S6 with the proposed conversion formulation, much smaller than observed error 10.24%, 6.05%, 13.51%, 12.79%, and14.58%. Thus, errors could be reduced by converting formulation to real diameter when the diameter of root nodule reached more than 1 mm. Table 1 Relative error of observed diameter and calculated diameter with measured diameter S1 S2 S3 S4 S5 S6 Observed diameter(mm) 0.71 ± 0.03 1.14 ± 0.06 2.33 ± 0.11 3.33 ± 0.07 3.82 ± 0.12 4.16 ± 0.15 Calculated diameter(mm) ⁄ 1.32 ± 0.09 2.36 ± 0.06 3.77 ± 0.09 4.65 ± 0.7 5.33 ± 0.13 Measured diameter(mm) 0.68 ± 0.02 1.20 ± 0.03 2.61 ± 0.08 3.85 ± 0.08 4.08 ± 0.13 4.37 ± 0.13 Relative error vs. observed ⁄ 10.24% 6.05% 13.51% 12.79% 14.58% Relative error vs. calculated ⁄ 3.94% 4.84% 2.08% 6.16% 9.45% Relationship between root hair curling number/angle and nodule number/volume Although some regressions had poor coefficients of determination (R 2 0.48 for curling angle versus nodule number and R 2 0.39 for curling number versus nodule diameter.), some regressions had a relatively reasonable coefficient of determination (curling angle versus nodule diameter R 2 0.84 and for curling number versus nodule number R 2 0.90), suggesting that curling angle was strongly related to log nodule diameter, and curling number was strongly linear to nodule number. Thus, experimentally derived equation quantitatively described nodule number and nodule diameter as a function of curling number and curling angle of soybean root hairs. For non-destructive and long period experiment, nodule number could be calculated through the linear relationship and nodule diameter could be observed and converted to real diameter. Discussion Principal findings and comparison with other studies This study focused on root development progress in soybean-rhizobia symbioses in situ. As far as we are concerned, this is the first literature about in situ root nodule forming in soybean-rhizobia symbioses accessible. From the experiment result, it was clearly evident that rhizobia affected soybean root hair deformation and nodule formation. In consistent with many researches (Gage et al., 2000; María et al., 2022), root hair was observed induction of root hair deformation. There were several types of root hair deformation in the soybean-rhizobia symbioses including swelling, wiggling, bulging, curling, and branching root hairs in other studies (Duzan et al., 2004 ; Ke et al., 2016 ). Compared with these studies, this study was carried out in soil and monitored nondestructively instead of digging or planting in non-soil environment. In addition to qualitative description as most studies did, this study quantitatively elucidated root hair curling angles. It was interesting that even root hairs in uninfected group were not straight, with a relatively small curling angle(within 32°), while in infected group root hair curling angle was large, ranging from 32° to 80°. Our result was similar to Roy ‘s (Roy et al., 2021) opinion that not every root hair was straight with genetic mutants and root hair stress phenotypes evidence. However, due to technological bottleneck that inhibit the discovery of root hair, no more further proving studies have been carried out. To some extent, our findings about non-straight root hairs in uninfected group gave some evidence to these hypotheses. It was worth noting that when the nodule finally formed in late stage (S5), root hairs were rare and root hair angle turned small. These symptoms proved that root hair curling was a prior event than root nodule formation, and root hairs had strong plasticity in response to environment of rhizosphere. Nodule was the ultimately formed organ in soybean-rhizobia symbioses with the ability to fix N 2 . Over a period of observation in this research, nodule began to swell in S2 and reached 5 mm in diameter in S5 with color changing from light to dark brown. Field of view into soil has been a problem for large diameter in all the minirhizotrons. Usually, it was regarded as 2–3 mm in depth, but some research reported that for accurate data, the depth of view into soil should be much smaller (Taylor et al., 2014). Considering the difference from visually soil depth and perceived diameter, nodule diameter bigger than 1 mm was converted to real diameter with the formulation. Deviation was reduced and more accurate nodule diameter was acquired by the conversion formulation. After conversion, the largest nodule could reach 5 mm in diameter. Furtherly, relationship between root hair curling number/angle and nodule number/diameter indicated that curling angle was strongly related to log nodule diameter, and curling number was strongly linear to nodule number. For long period experiment that concerns nodule number could be calculated through the linear relationship instead of digging up and destroying the plant. And nodule diameter could be observed and converted to real diameter. Strengths and limitation This study aimed at characterizing root hair curling and nodule development in soybean-rhizobia symbioses. One of the strengths was that it enabled local and dynamic change of root hair deformation during soybean-rhizobia symbioses nodule process. Nodule development including diameter and color could be observed from swelling to noduling for a long period. Compared with digging or plant growing in liquid and observing with microscopy (Duzan et al., 2004 ; Schiessl et al., 2019; Minglong et al., 2022), plant grew in soil condition could represent real response to rhizobia. Furthermore, this study not only paid attention to shapes of root hairs, but also quantitatively described each root hair curling angle throughout growing stages. At last, solution to acquire nodule number nondestructively was provided through linear relationship, and nodule diameter was made more accurate with the conversion formulation. This study has some limitation. Seedlings were inoculated with the same concentration of B. japonicum suspension. More gradients should be set up to test and verify the promotion and reduction of nodulation as well as nitrogen fixation ability in the future study. Implications and potential application Nodule is the most important soybean-rhizobia symbioses outcome. This study enabled nodule development observation and identified curling number strongly linear to nodule number, which could be applied to the evaluation of nodule ability in soybean-rhizobia symbioses. Compared with digging and root hair deformations observed using light microscopy, this method is time saving and easy to carry out when high throughout is needed during soybean-rhizobia symbioses breeding and screening. The proposed method could be used to multi-purpose where local detailed root hair deformation is expected. Conclusion This study depicted root hair and nodule development progress in soybean-rhizobia symbioses in soil-based environment over a long period. Induced rhizobia caused root hair curling angle ranging from 32 °to 80° since S2 to S6, while uninfected group had relatively small curling angle within 32°. Nodule began to swell in S3 and reached 4 mm in diameter in S6 with color changing from light to dark brown. Observed diameter over 1 mm was converted to real diameter with relative formulation. And after conversion, the largest nodule could reach 5 mm in diameter. Curling angle was strongly related to log nodule diameter, and curling number was strongly linear to nodule number. With this relationship, it is time saving and easy to acquire nodule diameter and to estimate nodule number without destroying the plant, especially when high throughout and successive experiment is needed during soybean-rhizobia symbioses breeding. Abbreviations S1 emergence stage S2 seedling stage S3 flower bud differentiation stage S4 flowering pod stage S5 grain stage S6 mature stage X-CT X-ray computed tomography MRI Magnetic resonance imaging NMR nuclear magnetic resonance Declarations Ethics approval and consent to participate Not applicable Consent for publication All authors have given consent for the publication Availability of data and material Original procedure and dataset for transfer learning is available on request Financial interests The authors have no relevant financial or non-financial interests to disclose. Funding The work was funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD-2018-87), and Project of Faculty of Agricultural Equipment of Jiangsu University (Grant No. NZXB20210101). Author’s contributions The method was conceived by Xiaochan Wang and Wei Lu. Wei Lu developed the devices and designed the experiments. All scripts necessary for image processing were written by Wei Lu. Weidong Jia and Mingxiong Ou reviewed and edited the draft. All authors read and approve the final manuscript Acknowledgements We would like to express our sincere thanks to Professor Lei Shu who gave us important suggestion to improve writing method and language. References Amato M, Lupo F, Bitella G, et al., 2012. A high quality low-cost digital microscope minirhizotron system. Computers and Electronics in Agriculture, 80:50-53. Barnes C, Shechtman E, Finkelstein A, et al., 2009. PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing. ACM Trans. Graph, 28(3). Cai G., Vanderborght J., Klotzsche A., et al., 2016. Construction of minirhizotron facilities for investigating root zone processes. Vadose Zone J. 15(9). Cbl A, Msjt A, Ev B, et al., 2019. 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Right time, right place: The dynamic role of hormones in rhizobial infection and nodulation of legumes. Plant Communications, 2022, 3(5):14. Wang Youning,Yang WeiZuo, Yanyan Zhu, et al., 2019. GmYUC2a mediates auxin biosynthesis during root development and nodulation in soybean. Journal of experimental botany, 70(12):3165-3176. Xue H, Jialin W, Yu Z, et al., 2023. Changes in the m6A RNA methylome accompany the promotion of soybean root growth by rhizobia under cadmium stress. Journal of Hazardous Materials, 441:129843. Yang Y, Zhao Q, Li X, et al., 2017. Characterization of Genetic Basis on Synergistic Interactions between Root Architecture and Biological Nitrogen Fixation in Soybean. Frontiers in Plant Science, 8:1466. Zhaoming C, Youning, W, Lin Z, et al., 2017. GmTIR1/GmAFB3-based auxin perception regulated by miR393 modulates soybean nodulation. The New phytologist. doi: 10.1111/nph.14632. Zhang T Y, Suen C Y. A fast parallel algorithm for thinning digital patterns, 1984. Comm Acm, 27(3):236-239. Supplementary Files Additionalfile1.docx Additional file 1: Codes for image segmentation model based on prior knowledge and deep learning Additionalfile2.rar Additional file 2: Source image and annotation image for fine root hair segmentation model establishment Additionalfile3.docx Additional file 3: Codes for root hair thinning, root hair and root axis connecting, root hair separation and root hair curling angle calculation Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3218858","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":223355047,"identity":"1cf1845d-a99c-4e98-a52c-f5569c70cf6a","order_by":0,"name":"Wei Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApklEQVRIiWNgGAWjYBACPjDJZsPDz95ApBY2CJkmI9lzgDQth20MbjgQq0Ui9+GDD2XneRhuMDB++JhDlJZ0Y8MZ527zMM5uYJacuY0YLdJpbNK8bbd5mGUOsDHzEqmF/ffftnM8bBIJxGthY2ZsO8DDQ7wW+WfMkj3nknkkeA42E+cXfp5jjB9+lNnZ2x9vPvjhIzFakABjA2nqR8EoGAWjYBTgBgCowy24aE4t5AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-7925-5940","institution":"Jiangsu University School of Agricultural Engineering","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Lu","suffix":""},{"id":223355048,"identity":"fa63f608-1d5a-4fe0-824b-ef4bd546af3f","order_by":1,"name":"Xiaochan Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaochan","middleName":"","lastName":"Wang","suffix":""},{"id":223355049,"identity":"bfbe128e-ba7d-40c6-aa76-941032b2d4fc","order_by":2,"name":"Weidong Jia","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weidong","middleName":"","lastName":"Jia","suffix":""},{"id":223355050,"identity":"87883724-9971-444f-8712-a0a0ebadeb6b","order_by":3,"name":"Mingxiong Ou","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mingxiong","middleName":"","lastName":"Ou","suffix":""}],"badges":[],"createdAt":"2023-07-31 01:31:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3218858/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3218858/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":41196877,"identity":"e8c79d46-dc33-4d3c-b413-ec591654a85c","added_by":"auto","created_at":"2023-08-07 16:17:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":197997,"visible":true,"origin":"","legend":"\u003cp\u003eRoot image capture and image processing with proposed deep learning model based on prior knowledge and region of interest\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/87eff3925460497a526a175e.png"},{"id":41196873,"identity":"0d91760c-da78-43dc-901c-2b958fb5e30f","added_by":"auto","created_at":"2023-08-07 16:17:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35685,"visible":true,"origin":"","legend":"\u003cp\u003eCrossing and overlapping root hair separation\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/ac4164c08981adb638986b6d.png"},{"id":41196874,"identity":"99288383-a922-469c-b053-761c2c00dca4","added_by":"auto","created_at":"2023-08-07 16:17:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":15507,"visible":true,"origin":"","legend":"\u003cp\u003eRoot hair curling angle calculation\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/72bd3734f0c2ba235a8ef03c.png"},{"id":41196872,"identity":"492ba6ee-84e2-41f2-a400-cf7cc6798e1e","added_by":"auto","created_at":"2023-08-07 16:17:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":11652,"visible":true,"origin":"","legend":"\u003cp\u003eObserved nodule and real nodule. D is the true diameter of nodulation, d is the diameter perceived by the camera or human eye, and L is visible depth of soil\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/f9264958c0a413d1b7b79f8d.png"},{"id":41196880,"identity":"a98fd94b-4846-4c61-aee9-97f7270c5bf5","added_by":"auto","created_at":"2023-08-07 16:17:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":338633,"visible":true,"origin":"","legend":"\u003cp\u003eDifferent types of root hair deformation. a and c are wiggling root hairs, b and f are waving root hairs, and d and e are branching root hairs.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/87bbdd1e0d1ed2446ef1c9bf.png"},{"id":41196876,"identity":"8cd1ddd8-0285-4c45-a0b3-6da949db2a83","added_by":"auto","created_at":"2023-08-07 16:17:53","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":86400,"visible":true,"origin":"","legend":"\u003cp\u003eRoot hair curling in infected and non-infected groups. S1 to S6 represent six growing stage of soybean plants including emergence stage, seedling stage, flower bud differentiation stage, flowering pod stage, grain stage, and mature stage.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/32a403f1509d5aefa2e8aab2.png"},{"id":41196879,"identity":"48f4616f-43a7-4fd5-9e10-1bc540548ca3","added_by":"auto","created_at":"2023-08-07 16:17:53","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":253532,"visible":true,"origin":"","legend":"\u003cp\u003eRoot hair deformation in soybean-rhizobia symbioses over time\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/b04f3374e89c7e5aa1760f1f.png"},{"id":41198260,"identity":"5c4c97f2-871d-4166-9103-43a3e9b22806","added_by":"auto","created_at":"2023-08-07 16:33:53","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":29089,"visible":true,"origin":"","legend":"\u003cp\u003eNodule development and root hair curling angle in different growing stages. S1 to S6 represent six growing stage of soybean plants including emergence stage, seedling stage, flower bud differentiation stage, flowering pod stage, grain stage, mature stage. Circles represent nodule radius (inner circle is observed value and outer circle is calculated value), and colors represent root hair curling angle.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/fb60a720c786cb8aa98e9214.png"},{"id":41197727,"identity":"b205985c-6c01-4bc5-9aa0-3c8e49d9910e","added_by":"auto","created_at":"2023-08-07 16:25:53","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":41057,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between root hair curling number/angle and nodule number/volume\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/d114dbd37cef94469ac636b4.png"},{"id":41198261,"identity":"9e18d285-8466-47a3-8d46-6f319a2bc276","added_by":"auto","created_at":"2023-08-07 16:33:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1521771,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/748fb962-f22e-486b-b086-5c57040ee34d.pdf"},{"id":41196875,"identity":"997c86f5-666e-44ee-87f4-7b9c0f3a1b05","added_by":"auto","created_at":"2023-08-07 16:17:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20538,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 1: \u003c/strong\u003eCodes for image segmentation model based on prior knowledge and deep learning\u003c/p\u003e","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/778371a35ce36717e43af997.docx"},{"id":41196904,"identity":"9d780fe8-8176-4122-b4e8-9f3d7f5993ff","added_by":"auto","created_at":"2023-08-07 16:17:55","extension":"rar","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":33284887,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 2: \u003c/strong\u003eSource image and annotation image for fine root hair segmentation model establishment\u003c/p\u003e","description":"","filename":"Additionalfile2.rar","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/31f6859440aded42a6b9542c.rar"},{"id":41197726,"identity":"82351de2-ab36-43e2-b7b7-48bbbe394b5c","added_by":"auto","created_at":"2023-08-07 16:25:53","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":24551,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 3: \u003c/strong\u003eCodes for root hair thinning, root hair and root axis connecting, root hair separation and root hair curling angle calculation\u003c/p\u003e","description":"","filename":"Additionalfile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-3218858/v1/f3b896afb617b10aac8cdd1a.docx"}],"financialInterests":"","formattedTitle":"Characterization of root hair curling and nodule development in soybean-rhizobia symbioses","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSoybeans provide abundant protein and oil for human and animal diets. During soybean growth, nitrogen plays a critical role and is demanded in a great amount (Freitas et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mayhood et al., 2021). Fortunately, soybeans can form symbiotic associations with rhizobia as nodules to fix atmospheric N\u003csub\u003e2\u003c/sub\u003e into ammonia (Cbl et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mariana et al., 2023). Successful rhizobia\u0026ndash;legume symbioses are the most important nitrogen (N) source in agroecosystem, depending on efficient plant root nodulation and subsequent N\u003csub\u003e2\u003c/sub\u003e fixation (Ferguson et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Currently, the amount of symbiotically fixed N\u003csub\u003e2\u003c/sub\u003e totals roughly 50%-60% of that demanded in soybean lifetime (Roy et al., 2019). This natural process in rhizobia\u0026ndash;legume symbioses is of vital importance in reducing the application of chemical fertilizers and providing more clear nitrogen source for soybean development.\u003c/p\u003e \u003cp\u003eRoot hair is the initial infection site for symbiotic (rhizobia) in soybean as well as other legume plants (Levine et al., 2007; Cervantes-P\u0026eacute;rez et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Chao et al., 2023). During nodule formation, rhizobia bacteria always attach to root hairs, induce root hair deformation, and form infection thread (Gage et al., 2000; Mar\u0026iacute;a et al., 2022). Subsequently, the infection thread induces the bacteria to the root cortex and ultimately forms nodule organs with the ability to fix N\u003csub\u003e2\u003c/sub\u003e (Nishida et al., 2018; Wang et al., 2019). The inoculation of rhizobia was closely related to some changes in root morphology and structure (Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yang et al., 2017; Soyano et al., 2019; Schiessl et al., 2019). Li (Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found that soybean rhizobia increased the size and number of cortical cells in root meristem and elongation areas, which expanded root hair density and root hair area and enable more nodulation. The deformed root hairs always serve as entrapping attached bacteria in the rhizobia\u0026ndash;legume symbioses, and have been widely reported to be many shapes such as curling, wiggling, branching, and shepherd (Esseling, et al., 2003; Hwang et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ke et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Velandia et al., 2022). Soybean root hair deformation responded in increase to rhizobia (nod factor) concentration (Duzan et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), but whether more deformed root hairs lead to more nodulation is not clear by literature. In addition, little knowledge is available on the process of soybean root hair deformation, nodule initial, and nodule development over time in situ.\u003c/p\u003e \u003cp\u003eTherefore, it is very important to study on root hair deformation progress in soybean-rhizobia symbioses, which will help to understand the process in root hair deformation mechanism. Root hairs are very tiny and sensitive part in rhizobia\u0026ndash;legume symbiosis (Fournier J et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; et al., 2021). The length of root hairs ranges from tens of microns to hundreds of microns, but only dozens of microns in width. Owing to the difficulty in observing roots into soil, most researches were carried with destructive method or in agar/solution environment observed using light microscopy (Zhaoming et al., 2017; Schiessl et al., 2019; Xue et al., 2023). It either had the limitation of losing root hairs during sampling, or could not represent real growth under soil environment. In addition, these methods didn\u0026rsquo;t support successive studies on the same roots over time. X-ray computed tomography (X-CT) (Scotson et al., 2021), nuclear magnetic resonance (NMR) (Metzner et al., 2015) and electrical impedance tomography (EIT) (Peruzzo et al., 2021) were not intended for such tiny root hair traits. To make it applicable to focus on detailed roots such as root hairs, rhizotrons and minirhizotrons were improved and adapted to a smaller scale by amplifying local area (Cai et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Amato et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we intended (1) to observe root hair traits and root nodulation development in rhizobia\u0026ndash;legume symbiosis over time with previous designed microrhizotron (1.5 cm\u003csup\u003e3\u003c/sup\u003e in volume) in situ, (2) to clarify detailed root hair deformation from the aspect of shapes and curling angle (deforming extent), (3) to analyze relationship between root hair deformation and nodulation (number/volume), thus to comprehend mechanism in the process of root hair deformation and nodulation, and provide a method for the screening of soybean-rhizobia genotypes with higher nitrogen fixing ability\u003c/p\u003e"},{"header":"Material and method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials and root hairs in situ observation\u003c/h2\u003e \u003cp\u003eSoybean (Glycine max cv. Williams82) seeds were surface sterilized by treating with 7% NaClO for 5 min followed by 70% ethanol for 4 min. The seeds were then rinsed three times with sterile deionized water. After sterilization, the seeds were planted in two experimental zones filled with soil taken from local crop growing area. The soil used was filtered 3 times with 1 cm opening filter, and then was sterilized at 80\u0026deg;C for defaunation. One-week-old seedlings were installed with microrhizotrons (1.1 cm \u0026times; 1.1 cm \u0026times; 1.2 cm), designed for nondestructive root observation, around soybean root system architecture. Effective installation to intercept with more roots were carried according to the soybean lateral root initial regulations: roots of soybean belong to tetrarch, where lateral roots initiate from pole pericycle cell opposite protoxylem, and generally lateral roots are spaced along the longitudinal axis in four lines. Details see also in (Lu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). So, four microrhizotrons were preset around each plant roots in depth 50 mm and 100 mm, and in each depth two microrhizotrons were along the direction of cotyledons. Soil compaction was tamped to 0.80\u0026ndash;0.83 kg/cm2 after installation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTwo-week-old seedlings were flood-inoculated with 15 ml/plant B. japonicum suspension (Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences) for the experimental group. And for the control group, seedlings were irrigated with 15 ml/plant water. The captured images each day (16:00\u0026ndash;17:00) were transmitted wireless to the terminal device for further processing. Root hair image was segmented based on deep learning and prior knowledge (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Additional file 1 and Additional file 2). See also in (Lu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The proposed model was implemented in Python 3.6, where Keras 2.2.4 and TensorFlow-GPU 1.15.0 are used. The hardware platform is the Intel(R)Core(TM)i7-7700 [email protected] GHz, 8.00 GB memory. GPU is NVIDIA RTX3060, 12 GB memory.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eRoot image processing (root hair and nodule) and root hair separation\u003c/h2\u003e \u003cp\u003eAfter segmentation, root hairs were thinning to single pixel used Zhang-Suen thinning algorithm (Zhang et al.,1984). There were some small gaps in root hair, and they were connected by approximating the nearest neighbor root hair with similar slope (Barnes et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In order to calculate root curling angle, root hairs should be separated from one to another. For the crossing and overlapping root hairs, they were separated based on rules: root hair connectivity and continuity; plant roots and curling grow continuously with angle difference of roots change slowly (Lu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) (pattern A).\u003c/p\u003e \u003cp\u003eAs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, in pattern A, no crossing or overlapping occurs, and there is only one path for the searching to the end. In pattern B, C, and D, there are more than one path for the searching, while only path 2 is the correct one. Path 3 is certainly wrong because the angle difference changes dramatically, and it return to the start area (axis in blue). In pattern B and C, it is also easy to figure out path 1, because these crossing and overlapping are at the end with large angle difference (threshold 80\u0026deg;). But in pattern D, it is a little hard to distinguish path 1 from the correct one, since it has a moderate slope, and might be mixed with real root hair curling. It is found during experiment that root hair curling always occur at root hair end, thus if the crossing point is within 1/2 root, threshold should be set smaller (30\u0026deg;). In detail, the root hair separation algorithm is presented as following steps:\u003c/p\u003e \u003cp\u003eStep 1: Root hairs thinning\u003c/p\u003e \u003cp\u003eRoot hairs were thinning and separated from root axes used Zhang-Suen thinning algorithm and our proposed pruning method (Lu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Boundary coordinate of an axis was stored for further root hair connecting with root axis.\u003c/p\u003e \u003cp\u003eStep 2: Root hair connecting with root axis\u003c/p\u003e \u003cp\u003eAfter thinning, root hairs were shortened and root axis was thinned. Given the rule that root hair could only be connected to one axis, gaps between root hairs and root axis were connected by approximating the nearest neighbor, considering continuously growing features of root hairs. Boundary coordinate of an axis was compared with end point of root hair (single pixel) to ensure they were neighboring.\u003c/p\u003e \u003cp\u003eStep 3: Searching and separating\u003c/p\u003e \u003cp\u003eThe search started from the root axis (boundary coordinate) along the single-pixel root hair (black arrows). When there was more than one path for the searching forward, angle difference was calculated and compared. If the crossing point is within 1/2 root, angle difference threshold was set as 30\u0026deg;. If it is at the end, where curling appears occasionally, the threshold was set as 80\u0026deg;. Root hairs were separated from one to another for further calculation of root hair curling angle (Additional file 3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eRoot hair curling angle calculation\u003c/h2\u003e \u003cp\u003eWhen the root hair had a small or moderate curvature (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), the changed direction angle (β) was relatively small or moderate. When the root hair had a large curvature (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), the changed direction angle (β) could reach more than 180\u0026deg; (Additional file 2). Root hair curling angle represent the changed angle from vector \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{i}}{\\varvec{P}}_{\\varvec{j}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{k}}{\\varvec{P}}_{\\varvec{l}}\\)\u003c/span\u003e\u003c/span\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It is defined as:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\beta\\)\u003c/span\u003e \u003c/span\u003e= arccos\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{i}}{\\varvec{P}}_{\\varvec{j}}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e\u0026middot;\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{k}}{\\varvec{P}}_{\\varvec{l}}\\)\u003c/span\u003e\u003c/span\u003e / (|\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{i}}{\\varvec{P}}_{\\varvec{j}}|\\)\u003c/span\u003e\u003c/span\u003e*|\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{k}}{\\varvec{P}}_{\\varvec{l}}\\)\u003c/span\u003e\u003c/span\u003e|) (1)\u003c/p\u003e \u003cp\u003eWhere β is the angle between vector \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{i}}{\\varvec{P}}_{\\varvec{j}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{P}}_{\\varvec{k}}{\\varvec{P}}_{\\varvec{l}}\\)\u003c/span\u003e\u003c/span\u003e, \u003cb\u003e\u0026middot;\u003c/b\u003e is inner product, and \u003cem\u003ed\u003c/em\u003eL is root hair length from point \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({P}_{i}\\)\u003c/span\u003e\u003c/span\u003e to \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({P}_{k}\\)\u003c/span\u003e\u003c/span\u003e.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({P}_{i}\\)\u003c/span\u003e\u003c/span\u003eis selected as the 1/2 root hair here, since root hair curling always occurs at the root hair end in soybean-rhizobia symbioses. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({P}_{j}\\)\u003c/span\u003e\u003c/span\u003e is the point 5 pixel forward, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({P}_{l}\\)\u003c/span\u003e\u003c/span\u003e is the end point, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({P}_{k}\\)\u003c/span\u003e\u003c/span\u003e is the point 5 pixel backward.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eObserved nodule and real nodule conversion\u003c/h2\u003e \u003cp\u003eWhen the radius of root nodule is greater than visually soil depth (L), the diameter perceived by researchers(d) will be less than the true size of the nodule (D), as is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Accurately, the minirhizotron and microrhizotron could only see into soil about 1 mm (Taylor et al., 2014), while the diameter of root nodules could reach more than 4 mm, so the real of root nodules is calculated as:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$D=\\frac{{(4L}^{2}+{d}^{2})}{4L}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere D is the real diameter of nodulation, d is the diameter perceived by the camera or human eye, and L is visible depth of soil.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn each growing stage (emergence stage, seedling stage, flower bud differentiation stage, flowering pod stage, grain stage, and mature stage), six soybean roots were dug and measured with microcalliper to determine nodule number and diameter.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRoot hair deformation\u003c/h2\u003e \u003cp\u003eVisually from Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, root hairs were almost straight in uninfected group, but in infected group root hairs were complex and not straight. There were several types of root hair deformation in the soybean-rhizobia symbioses, such as wiggling, waving, and branching root hairs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), and the largest root hair curling angle was 70\u0026deg; in infected group. Both in infected and uninfected groups, root hairs in depth 50 mm were longer than that in depth 100 mm. This was mainly caused by different developing stages, where roots in shallow soil layer initiated early and roots in deep soil layer initiated late. It could be observed from the images that the later initiating roots were very tender containing much water which made the root seem semitransparent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eRoot hair curling angle and proportion\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn infected group, both curling angle and curling proportion increased as plant grew. S4 stage provoked the highest response of root hair deformation proportion (85%), and root hair curling angle reached highest in S5 stage (79 \u0026deg;). Curling angle and curling proportion in infected group was larger than that in uninfected group since S2 stage. In uninfected group, curling angle and curling proportion didn\u0026rsquo;t change much over a range of growing stage. But it is worth noting that even in uninfected group, some small deformations occurred, which indicated that root hairs were not always straight. It was also obvious in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e that there was a proportion of curling root hairs in control group. This was because not all the root hairs were straight, and deformation with small curling angle was also included. So, in further analysis, only curling angle over 32 \u0026deg; was taken into consideration as real curling root hairs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eNodule development over time\u003c/h2\u003e \u003cp\u003eSoybean root hair deformation responded in time series (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). At early inoculation S2 (20 days), root hairs were almost straight. Then it turned curling after a period of inoculation S3 (40 days), and later it showed more types root hair deformation in S4 (60 days). Nodule was an organ developed later than root hair curling. Swelling was observed after root hair deformation in S3 (40 days) and it initiated from root axis with light color similar to root hair and root axis. The swelling part grew bigger and then the nodule formed in dark brown in S5 (80 days). It was noted that when the nodule formed in S5, root hairs were rare and the color of root axis was a little darker containing less water.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNodule volume developed fast at the first four stages, and reached 3 mm in diameter in S4. And in S6, nodule was about 4 mm. It is worth noting that there was an inner circle (observed value) and an outer circle (calculated value) from S2 to S6. This was because, in this case, root nodule was greater than visually soil depth (1 mm), where the diameter perceived was less than the true size of the nodule. There was intersection between inner circle of S6 and outer circle of S5. As nodule volume became large, the difference between observed value and calculated value became large. Compared with digging and measuring experiment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), relative error was 3.94%, 4.84%, 2.08%, 6.16%, and 9.45% in S2, S3, S4, S5, and S6 with the proposed conversion formulation, much smaller than observed error 10.24%, 6.05%, 13.51%, 12.79%, and14.58%. Thus, errors could be reduced by converting formulation to real diameter when the diameter of root nodule reached more than 1 mm.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelative error of observed diameter and calculated diameter with measured diameter\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eS6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObserved diameter(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalculated diameter(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026frasl;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasured diameter(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelative error vs. observed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026frasl;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.51%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.58%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelative error vs. calculated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026frasl;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.94%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.08%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.45%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between root hair curling number/angle and nodule number/volume\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlthough some regressions had poor coefficients of determination (R\u003csup\u003e2\u003c/sup\u003e 0.48 for curling angle versus nodule number and R\u003csup\u003e2\u003c/sup\u003e 0.39 for curling number versus nodule diameter.), some regressions had a relatively reasonable coefficient of determination (curling angle versus nodule diameter R\u003csup\u003e2\u003c/sup\u003e 0.84 and for curling number versus nodule number R\u003csup\u003e2\u003c/sup\u003e 0.90), suggesting that curling angle was strongly related to log nodule diameter, and curling number was strongly linear to nodule number. Thus, experimentally derived equation quantitatively described nodule number and nodule diameter as a function of curling number and curling angle of soybean root hairs. For non-destructive and long period experiment, nodule number could be calculated through the linear relationship and nodule diameter could be observed and converted to real diameter.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal findings and comparison with other studies\u003c/h2\u003e \u003cp\u003eThis study focused on root development progress in soybean-rhizobia symbioses in situ. As far as we are concerned, this is the first literature about in situ root nodule forming in soybean-rhizobia symbioses accessible. From the experiment result, it was clearly evident that rhizobia affected soybean root hair deformation and nodule formation. In consistent with many researches (Gage et al., 2000; Mar\u0026iacute;a et al., 2022), root hair was observed induction of root hair deformation. There were several types of root hair deformation in the soybean-rhizobia symbioses including swelling, wiggling, bulging, curling, and branching root hairs in other studies (Duzan et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Ke et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Compared with these studies, this study was carried out in soil and monitored nondestructively instead of digging or planting in non-soil environment. In addition to qualitative description as most studies did, this study quantitatively elucidated root hair curling angles.\u003c/p\u003e \u003cp\u003eIt was interesting that even root hairs in uninfected group were not straight, with a relatively small curling angle(within 32\u0026deg;), while in infected group root hair curling angle was large, ranging from 32\u0026deg; to 80\u0026deg;. Our result was similar to Roy \u0026lsquo;s (Roy et al., 2021) opinion that not every root hair was straight with genetic mutants and root hair stress phenotypes evidence. However, due to technological bottleneck that inhibit the discovery of root hair, no more further proving studies have been carried out. To some extent, our findings about non-straight root hairs in uninfected group gave some evidence to these hypotheses. It was worth noting that when the nodule finally formed in late stage (S5), root hairs were rare and root hair angle turned small. These symptoms proved that root hair curling was a prior event than root nodule formation, and root hairs had strong plasticity in response to environment of rhizosphere.\u003c/p\u003e \u003cp\u003eNodule was the ultimately formed organ in soybean-rhizobia symbioses with the ability to fix N\u003csub\u003e2\u003c/sub\u003e. Over a period of observation in this research, nodule began to swell in S2 and reached 5 mm in diameter in S5 with color changing from light to dark brown. Field of view into soil has been a problem for large diameter in all the minirhizotrons. Usually, it was regarded as 2\u0026ndash;3 mm in depth, but some research reported that for accurate data, the depth of view into soil should be much smaller (Taylor et al., 2014). Considering the difference from visually soil depth and perceived diameter, nodule diameter bigger than 1 mm was converted to real diameter with the formulation. Deviation was reduced and more accurate nodule diameter was acquired by the conversion formulation. After conversion, the largest nodule could reach 5 mm in diameter. Furtherly, relationship between root hair curling number/angle and nodule number/diameter indicated that curling angle was strongly related to log nodule diameter, and curling number was strongly linear to nodule number. For long period experiment that concerns nodule number could be calculated through the linear relationship instead of digging up and destroying the plant. And nodule diameter could be observed and converted to real diameter.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitation\u003c/h2\u003e \u003cp\u003eThis study aimed at characterizing root hair curling and nodule development in soybean-rhizobia symbioses. One of the strengths was that it enabled local and dynamic change of root hair deformation during soybean-rhizobia symbioses nodule process. Nodule development including diameter and color could be observed from swelling to noduling for a long period. Compared with digging or plant growing in liquid and observing with microscopy (Duzan et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Schiessl et al., 2019; Minglong et al., 2022), plant grew in soil condition could represent real response to rhizobia. Furthermore, this study not only paid attention to shapes of root hairs, but also quantitatively described each root hair curling angle throughout growing stages. At last, solution to acquire nodule number nondestructively was provided through linear relationship, and nodule diameter was made more accurate with the conversion formulation.\u003c/p\u003e \u003cp\u003eThis study has some limitation. Seedlings were inoculated with the same concentration of B. japonicum suspension. More gradients should be set up to test and verify the promotion and reduction of nodulation as well as nitrogen fixation ability in the future study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImplications and potential application\u003c/h2\u003e \u003cp\u003eNodule is the most important soybean-rhizobia symbioses outcome. This study enabled nodule development observation and identified curling number strongly linear to nodule number, which could be applied to the evaluation of nodule ability in soybean-rhizobia symbioses. Compared with digging and root hair deformations observed using light microscopy, this method is time saving and easy to carry out when high throughout is needed during soybean-rhizobia symbioses breeding and screening. The proposed method could be used to multi-purpose where local detailed root hair deformation is expected.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study depicted root hair and nodule development progress in soybean-rhizobia symbioses in soil-based environment over a long period. Induced rhizobia caused root hair curling angle ranging from 32 \u0026deg;to 80\u0026deg; since S2 to S6, while uninfected group had relatively small curling angle within 32\u0026deg;. Nodule began to swell in S3 and reached 4 mm in diameter in S6 with color changing from light to dark brown. Observed diameter over 1 mm was converted to real diameter with relative formulation. And after conversion, the largest nodule could reach 5 mm in diameter. Curling angle was strongly related to log nodule diameter, and curling number was strongly linear to nodule number. With this relationship, it is time saving and easy to acquire nodule diameter and to estimate nodule number without destroying the plant, especially when high throughout and successive experiment is needed during soybean-rhizobia symbioses breeding.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eemergence stage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eseedling stage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eflower bud differentiation stage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eflowering pod stage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS5\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egrain stage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS6\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emature stage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eX-CT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eX-ray computed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMagnetic resonance imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enuclear magnetic resonance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have given consent for the publication\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOriginal procedure and dataset for transfer learning is available on request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial interests\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD-2018-87), and Project of Faculty of Agricultural Equipment of Jiangsu University (Grant No. NZXB20210101).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe method was conceived by Xiaochan Wang and Wei Lu. Wei Lu developed the devices and designed the experiments. All scripts necessary for image processing were written by Wei Lu. Weidong Jia and Mingxiong Ou reviewed and edited the draft. All authors read and approve the final manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere thanks to Professor Lei Shu who gave us important suggestion to improve writing method and language.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmato M, Lupo F, Bitella G, et al., 2012. A high quality low-cost digital microscope minirhizotron system. Computers and Electronics in Agriculture, 80:50-53.\u003c/li\u003e\n\u003cli\u003eBarnes C, Shechtman E, Finkelstein A, et al., 2009. PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing. ACM Trans. Graph, 28(3).\u003c/li\u003e\n\u003cli\u003eCai G., Vanderborght J., Klotzsche A., et al., 2016. Construction of minirhizotron facilities for investigating root zone processes. Vadose Zone J. 15(9).\u003c/li\u003e\n\u003cli\u003eCbl A, Msjt A, Ev B, et al., 2019. Development of low-cost formulations of plant growth-promoting bacteria to be used as inoculants in beneficial agricultural technologies - ScienceDirect. Microbiological Research, 219:12-25.\u003c/li\u003e\n\u003cli\u003eCervantes-P\u0026eacute;rez SA, Thibivilliers S, Laffont C, et al., 2022. Cell-specific pathways recruited for symbiotic nodulation in the Medicago truncatula legume. Molecular Plant, 15(12):21.\u003c/li\u003e\n\u003cli\u003eChao Su, Guofeng Zhang, Marta Rodriguez-Franco, et al., 2023. Transcellular progression of infection threads in Medicago truncatula roots is associated with locally confined cell wall modifications. 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Root hair curling and Rhizobium infection in Medicago truncatula are mediated by phosphatidylinositide-regulated endocytosis and reactive oxygen species. Journal of Experimental Botany, 58(7):1637.\u003c/li\u003e\n\u003cli\u003eLi X, Zhao J, Tan Z, et al., 2015. GmEXPB2, a Cell Wall b-Expansin, Affects Soybean Nodulation through Modifying Root Architecture and Promoting Nodule Formation and Development. Plant Physiol. 169:2640-2653.\u003c/li\u003e\n\u003cli\u003eLiang P, Schmitz C, Lace B, et al., 2021. Formin-mediated bridging of cell wall, plasma membrane, and cytoskeleton in symbiotic infections of Medicago truncatula - ScienceDirect. Current Biology 31, 2712\u0026ndash;2719. \u003c/li\u003e\n\u003cli\u003eLu W, Li Y, Deng Y., 2019. Root phenotypic detection of different vigorous maize seeds based on Progressive Corrosion Joining algorithm of image. Plant Methods, 15.\u003c/li\u003e\n\u003cli\u003eLu W, Wang X., Wang F., 2019. 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Field Crops Research, 295: 108893.\u003c/li\u003e\n\u003cli\u003eMar\u0026iacute;a Soledad Figueredo, Mar\u0026iacute;a Laura Tonelli, Vanina Mu\u0026ntilde;oz, et al., 2022. Role of phytohormones in legumes infected intercellularly by rhizobia without infection threads formation. Rhizosphere, 24: 100622.\u003c/li\u003e\n\u003cli\u003eMayhood P, Mirza B S, 2021. Soybean Root Nodule and Rhizosphere Microbiome: Distribution of Rhizobial and Non-rhizobial Endophytes. Applied and Environmental Microbiology, 87(10).\u003c/li\u003e\n\u003cli\u003eMetzner, R., Eggert, A., Dusschoten, D.V., et al., 2015. Direct comparison of MRI and X-ray CT technologies for 3D imaging of root systems in soil: potential and challenges for root trait quantification. Plant Methods 11 (1), 17.\u003c/li\u003e\n\u003cli\u003eMinglong Liu, Xianlin Ke, Stephen Joseph, et al., 2022. Interaction of rhizobia with native AM fungi shaped biochar effect on soybean growth. Industrial Crops and Products, 187:115508.\u003c/li\u003e\n\u003cli\u003eNishida H, Suzaki T, 2018. Nitrate-mediated control of root nodule symbiosis. Current Opinion in Plant Biology, 44:129-136. \u003c/li\u003e\n\u003cli\u003ePeruzzo L, Liu X, Chou C, et al., 2021. Three hannel electrical impedance spectroscopy for field﹕cale root phenotyping. The Plant Phenome Journal, 4(1).\u003c/li\u003e\n\u003cli\u003eRoy A, Bucksch A, 2021. Root hairs vs. trichomes: Not everyone is straight.Current Opinion in Plant Biology, 64:102151.\u003c/li\u003e\n\u003cli\u003eRoy S, Liu W, Nandety R, et al., 2019. Celebrating 20 Years of Genetic Discoveries in Legume Nodulation and Symbiotic Nitrogen Fixation. The Plant Cell, 32(1).\u003c/li\u003e\n\u003cli\u003eSchiessl K, Lilley J, Lee T, et al., 2019. NODULE INCEPTION Recruits the Lateral Root Developmental Program for Symbiotic Nodule Organogenesis in Medicago truncatula. Current Biology, 29(21).\u003c/li\u003e\n\u003cli\u003eScotson, Callum P.van Veelen, ArjenWilliams, et al., 2021. Developing a system for in vivo imaging of maize roots containing iodinated contrast media in soil using synchrotron XCT and XRF, Plant and soil, 460(1-2):647-665.\u003c/li\u003e\n\u003cli\u003eSoyano T, Shimoda Y, Kawaguchi M, et al., 2019. A shared gene drives lateral root development and root nodule symbiosis pathways in Lotus. Science, 366: 1021\u0026ndash;1023.\u003c/li\u003e\n\u003cli\u003eTaylor B N, Beidler K V, Strand A E, 2014. Improved scaling of minirhizotron data using an empirically-derived depth of field and correcting for the underestimation of root diameters.Plant and Soil, 374(1-2):941-948.\u003c/li\u003e\n\u003cli\u003eVelandia K, Reid J B, Foo E. Right time, right place: The dynamic role of hormones in rhizobial infection and nodulation of legumes. Plant Communications, 2022, 3(5):14.\u003c/li\u003e\n\u003cli\u003eWang Youning,Yang WeiZuo, Yanyan Zhu, et al., 2019. GmYUC2a mediates auxin biosynthesis during root development and nodulation in soybean. Journal of experimental botany, 70(12):3165-3176.\u003c/li\u003e\n\u003cli\u003eXue H, Jialin W, Yu Z, et al., 2023. Changes in the m6A RNA methylome accompany the promotion of soybean root growth by rhizobia under cadmium stress. Journal of Hazardous Materials, 441:129843.\u003c/li\u003e\n\u003cli\u003eYang Y, Zhao Q, Li X, et al., 2017. Characterization of Genetic Basis on Synergistic Interactions between Root Architecture and Biological Nitrogen Fixation in Soybean. Frontiers in Plant Science, 8:1466.\u003c/li\u003e\n\u003cli\u003eZhaoming C, Youning, W, Lin Z, et al., 2017. GmTIR1/GmAFB3-based auxin perception regulated by miR393 modulates soybean nodulation. The New phytologist. doi: 10.1111/nph.14632.\u003c/li\u003e\n\u003cli\u003eZhang T Y, Suen C Y. A fast parallel algorithm for thinning digital patterns, 1984. Comm Acm, 27(3):236-239.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Soybean-rhizobia symbioses, microrhizotron, root hair deformation, nodule development, in situ","lastPublishedDoi":"10.21203/rs.3.rs-3218858/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3218858/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRoot hair is the initial infection site for symbiotic (rhizobia) process including rhizobia attaching, root hair deforming, and nodule organ forming. Since roots and nodules are blocked by soil and are hard to be perceived, little knowledge is available on the process of soybean root hair deformation and nodule development over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, adaptive microrhizotrons and root hair processing method were used to observe root hairs and to investigate detailed root hair deformation and nodule formation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt was found that root hairs were not always straight even in uninfected group with relatively small angle (\u0026lt;30°), but root hair curling angle in infected group were large ranging from 32° to 80° since S2 to S6. Nodule was an organ developed late than root hair curling. It initiated from root axis and began to swell in S3, with color changing from light to dark brown in S5. In order to eliminate the observing error, diameter over 1 mm was converted to real diameter with relative formulation. And after conversion, diameter of nodule reached 5 mm in S6. Relationship between root hair curling number/angle and nodule number/diameter indicated that curling angle was strongly related to log nodule diameter (R\u003csup\u003e2\u003c/sup\u003e 0.84), and curling number was strongly linear to nodule number (R\u003csup\u003e2\u003c/sup\u003e 0.91).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThus, nodule number could be calculated through the derived formulation and nodule diameter could be observed and converted to real diameter nondestructively.\u003c/p\u003e","manuscriptTitle":"Characterization of root hair curling and nodule development in soybean-rhizobia symbioses","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-08-07 16:17:48","doi":"10.21203/rs.3.rs-3218858/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"79d99b10-4197-49ee-ac22-43a1ed58ee2a","owner":[],"postedDate":"August 7th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-08-07T16:17:50+00:00","versionOfRecord":[],"versionCreatedAt":"2023-08-07 16:17:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3218858","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3218858","identity":"rs-3218858","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}