Measurement of Rice Tillers Based on Magnetic Resonance Imaging

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Measurement of Rice Tillers Based on Magnetic Resonance Imaging Measurement of Rice Tillers Based on Magnetic Resonance Imaging Measurement of Rice Tillers Based on Magnetic Resonance Imaging Huang Zhifeng*. Gong Liang**. Liu Chengliang***. Huang Yixiang****. Niu Qingliang***** Huang Zhifeng*. Gong Liang**. Liu Chengliang***. Huang Yixiang****. Niu Qingliang*****  Huang Zhifeng*. Gong Liang**. Liu Chengliang***. Huang Yixiang****. Niu Qingliang***** 

 * School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, CO 200240 * School of Mechanical Shanghai Jiao Tong University, Shanghai, CO 200240 CHINA Engineering, (Tel: 021-34206075; e-mail: zhifeng@ sjtu.edu.cn). CHINA (Tel: 021-34206075; e-mail: zhifeng@ sjtu.edu.cn). ***School of Mechanical Engineering, Shanghai Jiao Tong University, School of Mechanical Engineering, Shanghai Jiao Tong University,Shanghai, Shanghai,CO CO200240 200240 ** School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, CO 200240 CHINA CHINA (Tel: 021-34206075; e-mail: zhifeng@ sjtu.edu.cn). (e-mail: [email protected]) (e-mail:Shanghai [email protected]) ** School Engineering, Jiao *** School of of Mechanical MechanicalCHINA Engineering, Shanghai Jiao Tong Tong University, University, Shanghai, Shanghai, CO CO 200240 200240 *** School of MechanicalCHINA Engineering, Shanghai Jiao Tong University, Shanghai, CO 200240 (e-mail: [email protected]) CHINA (e-mail: [email protected]) CHINA (e-mail: [email protected]) *** School Shanghai Jiao **** School of ofMechanical MechanicalEngineering, Engineering, Shanghai JiaoTong TongUniversity, University,Shanghai, Shanghai,CO CO200240 200240 **** School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, CO 200240 CHINA (e-mail: [email protected]) CHINA (e-mail: [email protected]) CHINA (e-mail:Shanghai [email protected]) **** School of Engineering, Jiao *****School ofMechanical Agriculture and Biology, Shanghai Jiao Tong Tong University, University, Shanghai, Shanghai, CO CO 200240 200240 *****School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, CO 200240 CHINA (e-mail: [email protected]) CHINA (e-mail: [email protected]) CHINA (e-mail: [email protected]) *****School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, CO 200240 CHINA (e-mail: [email protected]) Abstract: Tiller, as an important agronomy trait, determines panicle number contributing to grain yield. Abstract: Tiller, as an important trait, determines number contributing to grain yield. For replacing traditional inefficientagronomy methods of counting tillers,panicle rapid and accurate measurement of phenoFor replacing traditional inefficient methods of counting tillers, rapid and accurate measurement of phenoAbstract: Tiller, as an important agronomy trait, determines panicle number contributing to grain yield. type in modern breeding has become urgent recently. Therefore, to automate its process and improve its type in modern breeding has become urgent recently. Therefore, to automate its process and improve its For replacing traditional inefficient methods of counting tillers, rapid and accurate measurement of phenoaccuracy and efficiency, many high-throughput facilities were developed, some of which base on convenaccuracy and computed efficiency, many high-throughput facilities were CT developed, some which base ona conventype modern breedingtomography has become urgent recently. Therefore, to automate itsofprocess andinimprove its tionalinX-ray (CT) system. However, system should be placed security tional X-ray computed tomography (CT) system. However, CT system should be placed in a security accuracy and efficiency, many high-throughput facilities were developed, some of which base on convenapartment, in case of exposing operators into radiation and causing experiment objects gene mutation. In apartment, in computed case ofmagnetic exposing operators into radiation and causing experiment gene inmutation. In tional X-ray tomography (CT)imaging system. However, CTnon-destructive system shouldobjects be placed a security this study, initially, resonance which features and non-radiation is apthis study, initially, magnetic resonance imaging which features non-destructive and non-radiation is apapartment, in case of exposing operators into radiation and causing experiment objects gene mutation. In plied to obtain transversal section images of rice culms. After that, these MRI images were processed by plied to obtain transversal section images of rice culms. After that, these MRI images were processed by this study, initially, magnetic resonance imaging which features non-destructive and non-radiation is apseparating algorithm which can extract tillers’ section and acquire its number based on morphological paseparating algorithm can extract tillers’ section and acquire number based on were morphological paplied to obtain transversal section of rice culms. After that,its these images processedcan by rameters. Finally, by which comparing theimages processed image of MRI with CT’s, itMRI proves that this algorithm rameters. Finally, by comparing the processed image of MRI with CT’s, it proves that this algorithm can separating algorithm which can extract tillers’ section and acquire its number based on morphological pacapture clear segmented image as CT does. Meaningfully, it turns out that this method can be recommendcapture segmented image asthe CTprocessed does. Meaningfully, it turns method recommendrameters. Finally, by comparing image of MRI without CT’s, itthis proves thatcan thisbealgorithm can ed as anclear efficient replaceable way for studying rice tiller’s agronomy inthat breeding work. ed as anclear efficient replaceable way rice tiller’s agronomy breeding work. can be recommendcapture segmented image as for CT studying does. Meaningfully, it turns outinthat this method Keywords: MRI, Rice tiller, Federation Phenotype, Agronomic trait © 2016, (International ofCT, Automatic Control) Hosting by All rights reserved. ed as an IFAC efficient replaceable way for studying rice tiller’s agronomy in Elsevier breedingLtd. work. Keywords: MRI, Rice tiller, Phenotype, CT, Agronomic trait Keywords: MRI, Rice tiller, Phenotype, CT, Agronomic trait

1. INTRODUCTION 1. INTRODUCTION Tiller which is produced by the outgrowth of axillary buds to 1. INTRODUCTION Tiller whichbranches, is produced of axillary buds to form shoot onebyofthe theoutgrowth rice’s agronomic trait, is an form shoot branches, one of the rice’s agronomic trait, is an Tiller which is produced by the outgrowth of axillary buds to important factor that contributes to panicle number per unit important factor that contributes to panicle number per unit form shoot branches, one of the rice’s agronomic trait, is an land area (K.A.K. Moldenhauer, et al.2003). In accordance land area (K.A.K. Moldenhauer, et panicle al.2003).number In accordance important factor that contributes to per have unit with different growth stage and architecture, rice tiller with different growth stage and architecture, rice tiller have land area (K.A.K. Moldenhauer, et al.2003). In accordance three patterns: primary, secondary, and tertiary tillers. And three patterns: growth primary, secondary, and tertiary And withpanicle-bearing different stage architecture, ricetillers. tiller the tiller rateand which mostly depends onhave prithe panicle-bearing tiller rate which mostly depends on prithree patterns: primary, secondary, and tertiary tillers. And mary tillers directly influences grain production (M.A. Badmary tillers directly influences grain production (M.A. Badthe panicle-bearing tiller rate which mostly depends on prishah, et al. 2014 and Tomasz Głąb, et al. 2015). To increase shah, et al. 2014 andinfluences Tomasz etproduction al. 2015).between To increase mary tillers directly grain (M.A. Badgrain yield, the research aboutGłąb, the relationship engrain yield, the research about(Wanneng the relationship enshah, et al. 2014 and Tomasz Głąb, et al.Yang, 2015).etbetween To vironmental influence factors al. increase 2011a), vironmental influence factors (Wanneng Yang, et al. 2011a), grain yield, the research about the relationship between enand specific modes of gene action provide a way to underand specific modes of gene action provide a way to undervironmental influence factors (Wanneng Yang, et al. 2011a), standing genes via environmental interactions. In these studstanding genes via of environmental interactions. In that these studand the specific modes oftiller geneisaction provide a way to can underies, phenotype feasible parameter be ies, the phenotype of tiller is feasible parameter that can be standing genes via environmental interactions. In these studmeasured directly. Hopefully, it may provide a reliable measured directly. Hopefully, it may provide a reliable ies, the phenotype of tiller is feasible parameter that can be method based on this idea, eventually, to modify crop archimethod based on this idea, eventually, to modify crop archimeasured directly. Hopefully, it may provide a reliable tecture and achieve greater yields( Yang, W, et al. 2013b). tecture achieve greater Yang,toW, et al. 2013b). methodand based on this idea, yields( eventually, modify crop architecture and achieve greater yields( Yang, W, et al. 2013b).

In relative research, recognizing the phenome of tillering is In relative research, recognizing the phenome of tillering is core mission, however, high-through measurement that feacore mission, however, high-through measurement that feaIn relative research, recognizing the phenome of tillering is tures high measurement efficiency should be introduced into tures high measurement efficiency should be introduced into core mission, however, high-through measurement that fearesearch or breeding work in consideration of demands in research breeding work of demands in turesapplication. highormeasurement efficiency shouldreported, be introduced real As Wang etinalconsideration (2013b) due tointo the real application. As Wang et al (2013b) reported, due to the research or breeding work in consideration of demands in rapid development of functional genomic and gene technolorapid development of functional genomic and gene technoloreal application. As Wang et al (2013b) reported, due to the gies over the past decade, particularly sequencing technologies over the pastrice decade, particularly sequencing rapid development of genome functional genomic and gene gy, the complete is now available, and technolothe funcgy, the complete rice genome is now available, the funcgies over the past decade, particularly sequencing technolotional analysis of the rice genome has and entered the tional analysis of the rice genome has entered the gy, the complete rice genome is now available, and funchigh-throughput stage. Therefore, it is possible andthe imperahigh-throughput stage. Therefore, it is possible and imperational analysis of the rice genome has entered the tive to utilize modern efficient techniques for screening cantive to utilize modern efficient techniques for screening canhigh-throughput stage. Therefore, it is possible and imperadidate plant’s agronomic traits, from breeding perspective. didate agronomic traits, frominfrared breeding perspective. tive to plant’s utilize efficient techniques for and screening canRanging from modern visible light imaging, hyperspecRanging from visible light imaging, infrared and hyperspecdidate plant’s agronomic traits, from breeding perspective. tral imaging to 3D structural tomography and functional imtral imaging 3D structural tomography andare functional imRanging fromto light imaging, and hyperspecaging (Saito, K,visible et al. 1996), actually,infrared there many develaging (Saito, K, et al. 1996), actually, there are many develtral imaging to 3D structural tomography and functional imopmental and advanced applications spring up in agriculture, opmental and advanced applications spring up in agriculture, aging (Saito, K, et al. 1996), actually, there are many develespecially, computed tomography, magnetic resonance imagespecially, computed tomography, magnetic resonance imagopmental and advanced applications spring technology. up in agriculture, ing and other non-destructive measurement ing and other non-destructive measurement especially, computed tomography, magnetictechnology. resonance imaging and other non-destructive measurement technology.

2405-8963 © IFAC (International Federation of Automatic Control) Copyright © 2016, 2016 IFAC 259Hosting by Elsevier Ltd. All rights reserved. Copyright 2016 responsibility IFAC 259Control. Peer review©under of International Federation of Automatic 10.1016/j.ifacol.2016.10.047 Copyright © 2016 IFAC 259

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Scanning position

(a) Rice plant

(b) Tillers’ NMR Pseudo-Color Map

Fig 1. MesoMR60 X-ray computed tomography technology which bases on differences in mass density and absorption of the material (Lammertyn, J, et al. 2003) is an appropriate way to achieve the goal of high-through and non-destructive measurement in agriculture field. Because of the high moisture content in most agricultural products, like fruit, vegetable, water dominates X-ray absorption. This truth reminds us that the application of CT in agronomic traits detection should be feasible way. Therefore, in consideration of relative low cost but actual high efficiency, X-ray CT has been explored to study the interior of horticultural produce. Internal disorders like filled or unfilled rice spikelets (Herremans, E, et al. 2015), fruit parenchyma tissue (Duan, L, et al. 2011), and soil like void distribution and construct (Elliot, T, et al), are detectable by means of X-ray measurements. Besides, assisted by three-dimensional morphological filter algorithm which can reconstruct 3D models from 2D information, CT scans can trace connected macropores (Pierret, A, et al. 2002). Quantitative knowledge of 3D root traits would help to acquire better acquaintance about root architecture and growth mechanism as it develops in a soil environment and researchers can study its physical (Tracy, S. R, et al. 2015) and physiological processes (Pfeifer, J, et al. 2015). Other similar way can also provide visualization information like tiller. (Jiang, N, et al. 2012 and Stijn Dhondt, et al. 2010). Even though the advantages of CT’s application in agronomic research, it is inevitable to consider the effects of X-ray radiation.

Scanning position

(c) Single culm

(d) Culm’s NMR Pseudo-Color Map

Fig 2. Rice plant sample (Scalar bar of signal resonance strength ranging from 0 to 250) different resistances to apple scab attacks. These similar research illuminate a new way to recognize and distinguish non-visual phenotypes. Furthermore, by comparing CT and MRI (Metzner, R, et al. 2015, and Van As, H., & van Duynhoven, J. 2013), Both techniques perform well for small pots which are suited to monitor root development of seedlings. Besides, for larger pot diameters, MRI delivered higher fractions than CT. These truths inspire authors. Therefore, this paper argues that MRI is applied to recognize culm’s transversal section and count rice tillers. By creating quantitative T2 maps images the distribution of water in study objects. Then NMR spectra revealed the relative concentrations of water (or organism with high hydrogen) in tiller’s tissue. After relative image processing depending on certain algorithm, these results can be used to achieve our target.

Magnetic resonance (MR) imaging, as another non-destructive and non-invasive technique that allows detecting and monitoring the development of internal defects and storage disorders over time, has been used to determine moisture distribution and mobility, and to visualize internal structures (Saito, K, et al. 1996, and Glidewell, S. M. ,et al, 2006).

2.

Phenotypes of research objects that are non-visual or hard to measure, generally, are breeders and researchers’ hot spots and hard nuts. Moreda, G. P., et al. review different methods about non-destructive horticultural produce size determination, focusing on electronic technologies capable of measuring fruit volume. Based on MRI’s characters, Musse, M, et al (2009) monitored the postharvest ripening of tomato fruit. And Sciubba, F, et al. (2015) studied two apple varieties with

MATERIALS AND METHODS

2.1. Material The material of this study, rice plants (SANHUANGZHAN NO 2), grow up in a greenhouse which locates in School of Agriculture and Biology, Shanghai Jiao Tong university, China. Tillers at the appropriate development stage, mostly sprout stage, after screening, were removed to laboratory. Then those representative plants whose culms’ section diameter is large enough to be recognized by NMR scanner.

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Start MRI section image Median filter Binaryzation Filling holes

a

Removing small particle

b

Fig 4. Processed CT image

Touching tillers? Non-touching culms

Touching culms Erosion Watershed segmentation

The number of culms:N1

The number of culms:N2 The number of tillers: N=N1+N2

a

End

b

Fig 5. CT histograms

Fig 3 Flowchart of tiller identification 2.2. Apparatus As it shows in Fig. 1, it is photograph of the superconducting magnet scanner (Suzhou Niumag analytical instrument corporation, Su Zhou, China) that carried out tillers’ MRI measurement. This facilite which is assisted with corresponding software kit can implement dynamic observation of moisture change of living plants in different periods of plant under the different state. Its probe coil is 60 mm diameter which limit the size of test objects.

a

b

Fig 6. NMR segmented image

Generally, the working temperature is set at 32 ℃, and the proton MR imaging experiments were performed with 21.3 MHz 1H NMR spectrometer. In addition, the magnetic field intensity is limited in 0.5±0.08 T.

and 3D spin echo datasets were acquired with an echo time (TE) of 5.56 ms and a repeat time (TR) of 300 ms. For whole plant test, to hold tillers closely, the sample up to 20 culms were placed in a 1.5 cm NMR tube and held parallel by a capillary containing 1mM Gd-DTPA which was used as an intensity scale object. Then, rice plant sample is placed flatly on detect room, and its transversal section (between primary tiller and secondary one) were captured as a pixel size of 0.278×0.278mm2 NMR image with the similar setting of single culm , except 3 mm slice thickness and a repetition time of 1s and an echo time of 10.20 ms.

2.3. Methods NMR Imaging As an integrate system, the functions of MesoMR60 computer workstation includes image acquisition and processing, and result display and storage.

The test result is showed in Fig 2, which includes two images: single culm and tillers sample’s image, and their corresponding NMR test result. The scanning position is seted on 2~3 mm distant from root pot.

For single culm test, before achieving NMR image, the experiment’s magnetic field intensity is settled on 0.51 T. Then culm NMR image is acquired with a microimaging probe, 261

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have validation method and corresponding results, so the validation index of sample tests, including RMSE and MAPE et al, should be taken into consideration in future sampling test. Hopefully, as a feasible method, this separating algorithm based on MRI can obtain acceptable result. It can be applied into breeding work or some else similar works, and implement the purpose of high-through measurement.

Tiller identification After MesoMR60 capture tillers’ transversal MRI image that is reconstructed by MesoMR60 inner algorithm, the tiller identification procedure is followed like Fig 3. The details of image processing procedure can be summed up as these steps:

However, this method is just a lab test, and the key equipment, MesoMR60, just provides a closed operation environment which disables to simulate real tillage condition and phenomenon. So there are many works should be done if it was applied to real breeding works. For example, real paddy land where unstable environment elements which will disturb NMR sensor, cause image regression are complex, like light intensity, wind speed, and plant density. So it is a question how to cope with those unstable elements and get clear images.

1) Turn image into monochrome image with weighted parameters; 2) Divide the gray image into the background and foreground with optimized threshold by filter which is appropriate gray value is 30-35 percent of maxim gray level, then target is segmented and becomes a binary image. 3) The filling-holes operation helps to maintain a consistent size and shape for all objects. Next, too small objects that are not tillers must be removed. Due to the presence of hollow medullary cavities in the rice stems, some objects in the binary image may appear holey. Hence,

ACKNOWLEDGE All authors deeply appreciate our collaborators, at School of Agriculture and Biology, Shanghai Jiao Tong University, with obtaining the rice plant samples. This research is supported by the National Key Technology R&D Program (2014BAD08B01), and Shanghai Science Project 1411104600.

4) Acquire clear tillers, then note them and count its number, through more filtering operation and morphological processing, It is worthy to mention that, after we got clear image, two outcomes, touching culms and non-touching culms, should be recognized by different way. As flowchart of tiller identification (Figure 3) showed, touching block should be denoted, then erosion and watershed segmentation is applied precisely to detach those objects. 3.

REFERENCE Moldenhauer, K. A., & Gibbons, J. H. (2003). Rice morphology and development (pp. 103-127). Rice: Origin, History, Technology, and Production. Hoboken, NJ. John Wiley and Sons.

RESULTS AND DISCUSSION

Badshah, M. A., Naimei, T., Zou, Y., Ibrahim, M., & Wang, K. (2014). Yield and tillering response of super hybrid rice Liangyoupeijiu to tillage and establishment methods. The Crop Journal, 2(1), 79-86.

To evaluate tiller segment algorithm, computed tomography images are used to compare with magnetic resonance images, as Figure 4 shows. Identification of the transversal features was made, principally, with reference to Bi Kun 2009. Figure 4a has been preprocessed, and its processed outcomes filtered by OSTU presented by figure 4b. Figure 4b reveal CT’s resolution in capturing images of tillers’ cross section is distinguishable, but this bases on reliable preprocessing. Figure 5 is corresponding histogram which just show the changes of gray level distribution. Figure 4 and 6, respectively, owed to CT and MRI image. Both of them shows clear segmented objects which stand for culms section. Contrast to culms’ gray image origining from NMR image (Figure 2), Figure 4a shows more distinct texture image. Figure 6a and 6b shows the pseudo-color image is operated and changed into some seperated blocks in different gray level. 4.

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CONCLUSION AND FUTURE

This algorithm is able to obtain agronomic traits and identify tillers’ section, providing major advantages over manual method: avoiding human disturbance, automation, and high throughput. In addition, contrast experiment between MRI and CT demonstrates that MRI also can obtain clear image as CT dose. Moreover, MRI as a non-destructive and non-touch method can avoid radiation effect because its working principle totally differs from CT.

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For confirming the accuracy of this method, there should 262

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