Elucidation of microstructural changes in leaves during senescence using spectral domain optical coherence tomography View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Tulsi Anna, Sandeep Chakraborty, Chia-Yi Cheng, Vishal Srivastava, Arthur Chiou, Wen-Chuan Kuo

ABSTRACT

Leaf senescence provides a unique window to explore the age-dependent programmed degradation at organ label in plants. Here, spectral domain optical coherence tomography (SD-OCT) has been used to study in vivo senescing leaf microstructural changes in the deciduous plant Acer serrulatum Hayata. Hayata leaves show autumn phenology and change color from green to yellow and finally red. SD-OCT image analysis shows distinctive features among different layers of the leaves; merging of upper epidermis and palisade layers form thicker layers in red leaves compared to green leaves. Moreover, A-scan analysis showed a significant (p < 0.001) decrease in the attenuation coefficient (for wavelength range: 1100-1550 nm) from green to red leaves. In addition, the B-scan analysis also showed significant changes in 14 texture parameters extracted from second-order spatial gray level dependence matrix (SGLDM). Among these parameters, a set of three features (energy, skewness, and sum variance), capable of quantitatively distinguishing difference in the microstructures of three different colored leaves, has been identified. Furthermore, classification based on k-nearest neighbors algorithm (k-NN) was found to yield 98% sensitivity, 99% specificity, and 95.5% accuracy. Following the proposed technique, a portable noninvasive tool for quality control in crop management can be anticipated. More... »

PAGES

1167

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-018-38165-3

DOI

http://dx.doi.org/10.1038/s41598-018-38165-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111917775

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30718740


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0607", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Plant Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National Yang Ming University", 
          "id": "https://www.grid.ac/institutes/grid.260770.4", 
          "name": [
            "National Yang-Ming University, Biophotonics and Molecular Imaging Research Center, 11221, Taipei, R.O.C., Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Anna", 
        "givenName": "Tulsi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Taiwan University", 
          "id": "https://www.grid.ac/institutes/grid.19188.39", 
          "name": [
            "National Yang-Ming University, Biophotonics and Molecular Imaging Research Center, 11221, Taipei, R.O.C., Taiwan", 
            "National Taiwan University, Graduate Institute of Photonics and Optoelectronics, 10617, Taipei, R.O.C., Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chakraborty", 
        "givenName": "Sandeep", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Yang Ming University", 
          "id": "https://www.grid.ac/institutes/grid.260770.4", 
          "name": [
            "National Yang-Ming University, Biophotonics and Molecular Imaging Research Center, 11221, Taipei, R.O.C., Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cheng", 
        "givenName": "Chia-Yi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Thapar University", 
          "id": "https://www.grid.ac/institutes/grid.412436.6", 
          "name": [
            "Thapar University, Electrical and Instrumentation Engineering Department, 147004, Patiala, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Srivastava", 
        "givenName": "Vishal", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Yang Ming University", 
          "id": "https://www.grid.ac/institutes/grid.260770.4", 
          "name": [
            "National Yang-Ming University, Biophotonics and Molecular Imaging Research Center, 11221, Taipei, R.O.C., Taiwan", 
            "National Yang-Ming University, Institute of Biophotonics, 11221, Taipei, R.O.C., Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chiou", 
        "givenName": "Arthur", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Yang Ming University", 
          "id": "https://www.grid.ac/institutes/grid.260770.4", 
          "name": [
            "National Yang-Ming University, Biophotonics and Molecular Imaging Research Center, 11221, Taipei, R.O.C., Taiwan", 
            "National Yang-Ming University, Institute of Biophotonics, 11221, Taipei, R.O.C., Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kuo", 
        "givenName": "Wen-Chuan", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.3174/ajnr.a4285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000220818"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1469-8137.1999.00423.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002153831"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01431160802036359", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002248743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/oxfordjournals.pcp.a029455", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004912831"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/02757259009532129", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007102045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tplants.2004.02.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011868968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13580-012-0071-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011871972", 
          "https://doi.org/10.1007/s13580-012-0071-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/jcs.109116", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012722140"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1104/pp.114.238899", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013182365"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2016/1093734", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017876455"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1439-0523.2004.00989.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021372162"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.arplant.57.032905.105316", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026082516"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/sca.21065", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028109965"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/lapl.200910141", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029089567"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/lapl.200910141", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029089567"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep38878", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029588399", 
          "https://doi.org/10.1038/srep38878"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1104/pp.24.1.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029730230"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3807/josk.2012.16.2.133", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030300740"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1746-4811-6-17", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031228015", 
          "https://doi.org/10.1186/1746-4811-6-17"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1746-4811-9-40", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033899795", 
          "https://doi.org/10.1186/1746-4811-9-40"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jbio.201400153", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035756347"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep02190", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035955828", 
          "https://doi.org/10.1038/srep02190"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s2095-3119(16)61393-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037422313"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12551-011-0054-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040667081", 
          "https://doi.org/10.1007/s12551-011-0054-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c5ay00377f", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043220444"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00340-007-2743-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046593288", 
          "https://doi.org/10.1007/s00340-007-2743-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jxb/ers392", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047752379"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-313x.2005.02399.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047984774"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/treephys/tpv148", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048604619"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/bip.10297", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049320291"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1104/pp.113.2.313", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060841279"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tsmc.1973.4309314", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061792707"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.134.3492.1727", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062476686"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1957169", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062514972"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5121/ijcsit.2012.4615", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072616564"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/ao.56.00d108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083961858"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.plaphy.2017.06.025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086119981"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "Leaf senescence provides a unique window to explore the age-dependent programmed degradation at organ label in plants. Here, spectral domain optical coherence tomography (SD-OCT) has been used to study in vivo senescing leaf microstructural changes in the deciduous plant Acer serrulatum Hayata. Hayata leaves show autumn phenology and change color from green to yellow and finally red. SD-OCT image analysis shows distinctive features among different layers of the leaves; merging of upper epidermis and palisade layers form thicker layers in red leaves compared to green leaves. Moreover, A-scan analysis showed a significant (p\u2009<\u20090.001) decrease in the attenuation coefficient (for wavelength range: 1100-1550\u2009nm) from green to red leaves. In addition, the B-scan analysis also showed significant changes in 14 texture parameters extracted from second-order spatial gray level dependence matrix (SGLDM). Among these parameters, a set of three features (energy, skewness, and sum variance), capable of quantitatively distinguishing difference in the microstructures of three different colored leaves, has been identified. Furthermore, classification based on k-nearest neighbors algorithm (k-NN) was found to yield 98% sensitivity, 99% specificity, and 95.5% accuracy. Following the proposed technique, a portable noninvasive tool for quality control in crop management can be anticipated.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/s41598-018-38165-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "9"
      }
    ], 
    "name": "Elucidation of microstructural changes in leaves during senescence using spectral domain optical coherence tomography", 
    "pagination": "1167", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "e0e18eaf192faec605d6b4c091a7924ce907147af119655cc537df8b11b0b4fc"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30718740"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41598-018-38165-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111917775"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41598-018-38165-3", 
      "https://app.dimensions.ai/details/publication/pub.1111917775"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:01", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000330_0000000330/records_116376_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/s41598-018-38165-3"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-38165-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-38165-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-38165-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-38165-3'


 

This table displays all metadata directly associated to this object as RDF triples.

220 TRIPLES      21 PREDICATES      65 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41598-018-38165-3 schema:about anzsrc-for:06
2 anzsrc-for:0607
3 schema:author N5c6bb3963d7e4edda629e455b1f9a38e
4 schema:citation sg:pub.10.1007/s00340-007-2743-2
5 sg:pub.10.1007/s12551-011-0054-7
6 sg:pub.10.1007/s13580-012-0071-x
7 sg:pub.10.1038/srep02190
8 sg:pub.10.1038/srep38878
9 sg:pub.10.1186/1746-4811-6-17
10 sg:pub.10.1186/1746-4811-9-40
11 https://doi.org/10.1002/bip.10297
12 https://doi.org/10.1002/jbio.201400153
13 https://doi.org/10.1002/lapl.200910141
14 https://doi.org/10.1002/sca.21065
15 https://doi.org/10.1016/j.plaphy.2017.06.025
16 https://doi.org/10.1016/j.tplants.2004.02.008
17 https://doi.org/10.1016/s2095-3119(16)61393-x
18 https://doi.org/10.1039/c5ay00377f
19 https://doi.org/10.1046/j.1469-8137.1999.00423.x
20 https://doi.org/10.1080/01431160802036359
21 https://doi.org/10.1080/02757259009532129
22 https://doi.org/10.1093/jxb/ers392
23 https://doi.org/10.1093/oxfordjournals.pcp.a029455
24 https://doi.org/10.1093/treephys/tpv148
25 https://doi.org/10.1104/pp.113.2.313
26 https://doi.org/10.1104/pp.114.238899
27 https://doi.org/10.1104/pp.24.1.1
28 https://doi.org/10.1109/tsmc.1973.4309314
29 https://doi.org/10.1111/j.1365-313x.2005.02399.x
30 https://doi.org/10.1111/j.1439-0523.2004.00989.x
31 https://doi.org/10.1126/science.134.3492.1727
32 https://doi.org/10.1126/science.1957169
33 https://doi.org/10.1146/annurev.arplant.57.032905.105316
34 https://doi.org/10.1155/2016/1093734
35 https://doi.org/10.1242/jcs.109116
36 https://doi.org/10.1364/ao.56.00d108
37 https://doi.org/10.3174/ajnr.a4285
38 https://doi.org/10.3807/josk.2012.16.2.133
39 https://doi.org/10.5121/ijcsit.2012.4615
40 schema:datePublished 2019-12
41 schema:datePublishedReg 2019-12-01
42 schema:description Leaf senescence provides a unique window to explore the age-dependent programmed degradation at organ label in plants. Here, spectral domain optical coherence tomography (SD-OCT) has been used to study in vivo senescing leaf microstructural changes in the deciduous plant Acer serrulatum Hayata. Hayata leaves show autumn phenology and change color from green to yellow and finally red. SD-OCT image analysis shows distinctive features among different layers of the leaves; merging of upper epidermis and palisade layers form thicker layers in red leaves compared to green leaves. Moreover, A-scan analysis showed a significant (p < 0.001) decrease in the attenuation coefficient (for wavelength range: 1100-1550 nm) from green to red leaves. In addition, the B-scan analysis also showed significant changes in 14 texture parameters extracted from second-order spatial gray level dependence matrix (SGLDM). Among these parameters, a set of three features (energy, skewness, and sum variance), capable of quantitatively distinguishing difference in the microstructures of three different colored leaves, has been identified. Furthermore, classification based on k-nearest neighbors algorithm (k-NN) was found to yield 98% sensitivity, 99% specificity, and 95.5% accuracy. Following the proposed technique, a portable noninvasive tool for quality control in crop management can be anticipated.
43 schema:genre research_article
44 schema:inLanguage en
45 schema:isAccessibleForFree true
46 schema:isPartOf N0fe83fb7362b4da88ace4194f694d6c5
47 N403fc6d691a54295813956a4dffc33a5
48 sg:journal.1045337
49 schema:name Elucidation of microstructural changes in leaves during senescence using spectral domain optical coherence tomography
50 schema:pagination 1167
51 schema:productId N01a008c86abc4303bbff44cf76f9e574
52 N0840cf6bbb6b4ea49d80c543f3bec02c
53 N7c989a9cc28649b7b5bc548eda341fa2
54 N7d4de15e82df4847b6a49da4953dbe2a
55 Nbe35ab1549214baeb39541ddd05f53df
56 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111917775
57 https://doi.org/10.1038/s41598-018-38165-3
58 schema:sdDatePublished 2019-04-11T09:01
59 schema:sdLicense https://scigraph.springernature.com/explorer/license/
60 schema:sdPublisher Nd82171f009194a7e922e8fac21829821
61 schema:url https://www.nature.com/articles/s41598-018-38165-3
62 sgo:license sg:explorer/license/
63 sgo:sdDataset articles
64 rdf:type schema:ScholarlyArticle
65 N01a008c86abc4303bbff44cf76f9e574 schema:name doi
66 schema:value 10.1038/s41598-018-38165-3
67 rdf:type schema:PropertyValue
68 N0840cf6bbb6b4ea49d80c543f3bec02c schema:name readcube_id
69 schema:value e0e18eaf192faec605d6b4c091a7924ce907147af119655cc537df8b11b0b4fc
70 rdf:type schema:PropertyValue
71 N0fe83fb7362b4da88ace4194f694d6c5 schema:issueNumber 1
72 rdf:type schema:PublicationIssue
73 N305c4abe5b7a4f458b4866df41bb41e2 schema:affiliation https://www.grid.ac/institutes/grid.19188.39
74 schema:familyName Chakraborty
75 schema:givenName Sandeep
76 rdf:type schema:Person
77 N32c83d9390e740b89d60fb5763a67cf6 schema:affiliation https://www.grid.ac/institutes/grid.260770.4
78 schema:familyName Kuo
79 schema:givenName Wen-Chuan
80 rdf:type schema:Person
81 N3b3d15c440ca4fb49ee723a2908b3dae rdf:first N305c4abe5b7a4f458b4866df41bb41e2
82 rdf:rest N62b37f6cbaa34cda96cc1014e9a750b1
83 N403fc6d691a54295813956a4dffc33a5 schema:volumeNumber 9
84 rdf:type schema:PublicationVolume
85 N5982e9b3e3184aba857fe988b7276651 schema:affiliation https://www.grid.ac/institutes/grid.260770.4
86 schema:familyName Chiou
87 schema:givenName Arthur
88 rdf:type schema:Person
89 N5c6bb3963d7e4edda629e455b1f9a38e rdf:first Nd263d50311ae46ab996080a34b9ec7ce
90 rdf:rest N3b3d15c440ca4fb49ee723a2908b3dae
91 N62b37f6cbaa34cda96cc1014e9a750b1 rdf:first Nc21f4e9e3d944422ab551808f4dd8581
92 rdf:rest Nb868fbfbe4b540f595f13ce45aa6a713
93 N7c989a9cc28649b7b5bc548eda341fa2 schema:name dimensions_id
94 schema:value pub.1111917775
95 rdf:type schema:PropertyValue
96 N7d4de15e82df4847b6a49da4953dbe2a schema:name pubmed_id
97 schema:value 30718740
98 rdf:type schema:PropertyValue
99 N93484cdbb3ac41b2b845e6c2bc44fcf7 rdf:first N5982e9b3e3184aba857fe988b7276651
100 rdf:rest Nac56ad31183645a3ad18e914c7f8ce94
101 Na2d6a70887c94cfc9b69d29627f87d1d schema:affiliation https://www.grid.ac/institutes/grid.412436.6
102 schema:familyName Srivastava
103 schema:givenName Vishal
104 rdf:type schema:Person
105 Nac56ad31183645a3ad18e914c7f8ce94 rdf:first N32c83d9390e740b89d60fb5763a67cf6
106 rdf:rest rdf:nil
107 Nb868fbfbe4b540f595f13ce45aa6a713 rdf:first Na2d6a70887c94cfc9b69d29627f87d1d
108 rdf:rest N93484cdbb3ac41b2b845e6c2bc44fcf7
109 Nbe35ab1549214baeb39541ddd05f53df schema:name nlm_unique_id
110 schema:value 101563288
111 rdf:type schema:PropertyValue
112 Nc21f4e9e3d944422ab551808f4dd8581 schema:affiliation https://www.grid.ac/institutes/grid.260770.4
113 schema:familyName Cheng
114 schema:givenName Chia-Yi
115 rdf:type schema:Person
116 Nd263d50311ae46ab996080a34b9ec7ce schema:affiliation https://www.grid.ac/institutes/grid.260770.4
117 schema:familyName Anna
118 schema:givenName Tulsi
119 rdf:type schema:Person
120 Nd82171f009194a7e922e8fac21829821 schema:name Springer Nature - SN SciGraph project
121 rdf:type schema:Organization
122 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
123 schema:name Biological Sciences
124 rdf:type schema:DefinedTerm
125 anzsrc-for:0607 schema:inDefinedTermSet anzsrc-for:
126 schema:name Plant Biology
127 rdf:type schema:DefinedTerm
128 sg:journal.1045337 schema:issn 2045-2322
129 schema:name Scientific Reports
130 rdf:type schema:Periodical
131 sg:pub.10.1007/s00340-007-2743-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046593288
132 https://doi.org/10.1007/s00340-007-2743-2
133 rdf:type schema:CreativeWork
134 sg:pub.10.1007/s12551-011-0054-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040667081
135 https://doi.org/10.1007/s12551-011-0054-7
136 rdf:type schema:CreativeWork
137 sg:pub.10.1007/s13580-012-0071-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011871972
138 https://doi.org/10.1007/s13580-012-0071-x
139 rdf:type schema:CreativeWork
140 sg:pub.10.1038/srep02190 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035955828
141 https://doi.org/10.1038/srep02190
142 rdf:type schema:CreativeWork
143 sg:pub.10.1038/srep38878 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029588399
144 https://doi.org/10.1038/srep38878
145 rdf:type schema:CreativeWork
146 sg:pub.10.1186/1746-4811-6-17 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031228015
147 https://doi.org/10.1186/1746-4811-6-17
148 rdf:type schema:CreativeWork
149 sg:pub.10.1186/1746-4811-9-40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033899795
150 https://doi.org/10.1186/1746-4811-9-40
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1002/bip.10297 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049320291
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1002/jbio.201400153 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035756347
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1002/lapl.200910141 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029089567
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1002/sca.21065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028109965
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1016/j.plaphy.2017.06.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086119981
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1016/j.tplants.2004.02.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011868968
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1016/s2095-3119(16)61393-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1037422313
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1039/c5ay00377f schema:sameAs https://app.dimensions.ai/details/publication/pub.1043220444
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1046/j.1469-8137.1999.00423.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1002153831
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1080/01431160802036359 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002248743
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1080/02757259009532129 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007102045
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1093/jxb/ers392 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047752379
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1093/oxfordjournals.pcp.a029455 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004912831
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1093/treephys/tpv148 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048604619
179 rdf:type schema:CreativeWork
180 https://doi.org/10.1104/pp.113.2.313 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060841279
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1104/pp.114.238899 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013182365
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1104/pp.24.1.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029730230
185 rdf:type schema:CreativeWork
186 https://doi.org/10.1109/tsmc.1973.4309314 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061792707
187 rdf:type schema:CreativeWork
188 https://doi.org/10.1111/j.1365-313x.2005.02399.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1047984774
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1111/j.1439-0523.2004.00989.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021372162
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1126/science.134.3492.1727 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062476686
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1126/science.1957169 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062514972
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1146/annurev.arplant.57.032905.105316 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026082516
197 rdf:type schema:CreativeWork
198 https://doi.org/10.1155/2016/1093734 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017876455
199 rdf:type schema:CreativeWork
200 https://doi.org/10.1242/jcs.109116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012722140
201 rdf:type schema:CreativeWork
202 https://doi.org/10.1364/ao.56.00d108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083961858
203 rdf:type schema:CreativeWork
204 https://doi.org/10.3174/ajnr.a4285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000220818
205 rdf:type schema:CreativeWork
206 https://doi.org/10.3807/josk.2012.16.2.133 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030300740
207 rdf:type schema:CreativeWork
208 https://doi.org/10.5121/ijcsit.2012.4615 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072616564
209 rdf:type schema:CreativeWork
210 https://www.grid.ac/institutes/grid.19188.39 schema:alternateName National Taiwan University
211 schema:name National Taiwan University, Graduate Institute of Photonics and Optoelectronics, 10617, Taipei, R.O.C., Taiwan
212 National Yang-Ming University, Biophotonics and Molecular Imaging Research Center, 11221, Taipei, R.O.C., Taiwan
213 rdf:type schema:Organization
214 https://www.grid.ac/institutes/grid.260770.4 schema:alternateName National Yang Ming University
215 schema:name National Yang-Ming University, Biophotonics and Molecular Imaging Research Center, 11221, Taipei, R.O.C., Taiwan
216 National Yang-Ming University, Institute of Biophotonics, 11221, Taipei, R.O.C., Taiwan
217 rdf:type schema:Organization
218 https://www.grid.ac/institutes/grid.412436.6 schema:alternateName Thapar University
219 schema:name Thapar University, Electrical and Instrumentation Engineering Department, 147004, Patiala, India
220 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...