Uni- and Multi-Variate Assessment of Drought Response Yield Indices in 10 Wheat Cultivars View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

Bardees Mickky, Heshmat Aldesuquy, Mustafa Elnajar

ABSTRACT

Wheat (Triticum aestivum L.) is a major cereal with its productivity being highly affected by drought. In the current study, 10 wheat cultivars were evaluated for their grain yield under well-watered (Yp) and drought (Ys) conditions. Various drought response indices (mean productivity (MP), geometric productivity (GMP), tolerance index (TOL), stress susceptibility index (SSI), stress tolerance index (STI), harmonic mean of yield (HARM), yield stability index (YSI), relative drought index (RDI), two drought resistance indices (DRI1 and DRI2), yield reduction ratio (YRR) and yield index (YI)) were determined to identify high-yielding and drought tolerant cultivars. Spearman’s correlation coefficient among the estimated indices, hierarchical clustering of the concerned cultivars as well as principle component analysis (PCA) of both the indices and cultivars were employed. Wheat cultivars Sids 13 and Gemmeiza 11 were superior while Sakha 94 and Shandaweel 1 were inferior depending upon their Yp, Ys and drought response indices. Also, a non-significant positive correlation was recorded between Yp and Ys of the studied cultivars with GMP, STI and HARM being significantly correlated with both Yp and Ys. Based on PCA, Yp and Ys explained 61.6 and 38.1% of the total variation; respectively. Furthermore, cluster analysis sequestered the concerned cultivars into drought susceptible cultivars (Shandaweel 1, Giza 168 and Gemmeiza 11), drought moderate ones (Misr 2, Sakha 93 and Sakha 94) and drought tolerant ones (Misr 1, Sids 13, Gemmeiza 9 and Sids 12) based on the mean values of YSI, RDI, TOL, SSI and YRR within each group. More... »

PAGES

21-29

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12892-018-0221-0

DOI

http://dx.doi.org/10.1007/s12892-018-0221-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113144324


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/2008/0703", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Crop and Pasture Production", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/07", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Agricultural and Veterinary Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Mansoura University", 
          "id": "https://www.grid.ac/institutes/grid.10251.37", 
          "name": [
            "Botany Department, Faculty of Science, Mansoura University, Mansoura, Egypt"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mickky", 
        "givenName": "Bardees", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Mansoura University", 
          "id": "https://www.grid.ac/institutes/grid.10251.37", 
          "name": [
            "Botany Department, Faculty of Science, Mansoura University, Mansoura, Egypt"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Aldesuquy", 
        "givenName": "Heshmat", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Mansoura University", 
          "id": "https://www.grid.ac/institutes/grid.10251.37", 
          "name": [
            "Botany Department, Faculty of Science, Mansoura University, Mansoura, Egypt"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Elnajar", 
        "givenName": "Mustafa", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.4067/s0718-34292015000400002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005987891"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1018307111569", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006153393", 
          "https://doi.org/10.1023/a:1018307111569"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4141/p96-130", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007179512"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/ar9780897", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010847789"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.fcr.2006.02.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031108163"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejbas.2016.10.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034556479"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1071/ar9791001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040511844"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2478/v10298-012-0053-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048204613"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.15192/pscp.aab.2015.4.1.1930", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067604970"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2135/cropsci1981.0011183x002100060033x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069019050"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2135/cropsci1984.0011183x002400050026x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069020217"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2135/cropsci1997.0011183x003700010007x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069025308"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2135/cropsci2003.8070", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069028334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5539/jas.v4n7p126", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072959869"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5539/jas.v7n3p49", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072960680"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2135/cropsci2002.1100", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090703494"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jxb/ery081", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101609140"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/ijerph15050839", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103631780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/ijerph15050839", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103631780"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-03", 
    "datePublishedReg": "2019-03-01", 
    "description": "Wheat (Triticum aestivum L.) is a major cereal with its productivity being highly affected by drought. In the current study, 10 wheat cultivars were evaluated for their grain yield under well-watered (Yp) and drought (Ys) conditions. Various drought response indices (mean productivity (MP), geometric productivity (GMP), tolerance index (TOL), stress susceptibility index (SSI), stress tolerance index (STI), harmonic mean of yield (HARM), yield stability index (YSI), relative drought index (RDI), two drought resistance indices (DRI1 and DRI2), yield reduction ratio (YRR) and yield index (YI)) were determined to identify high-yielding and drought tolerant cultivars. Spearman\u2019s correlation coefficient among the estimated indices, hierarchical clustering of the concerned cultivars as well as principle component analysis (PCA) of both the indices and cultivars were employed. Wheat cultivars Sids 13 and Gemmeiza 11 were superior while Sakha 94 and Shandaweel 1 were inferior depending upon their Yp, Ys and drought response indices. Also, a non-significant positive correlation was recorded between Yp and Ys of the studied cultivars with GMP, STI and HARM being significantly correlated with both Yp and Ys. Based on PCA, Yp and Ys explained 61.6 and 38.1% of the total variation; respectively. Furthermore, cluster analysis sequestered the concerned cultivars into drought susceptible cultivars (Shandaweel 1, Giza 168 and Gemmeiza 11), drought moderate ones (Misr 2, Sakha 93 and Sakha 94) and drought tolerant ones (Misr 1, Sids 13, Gemmeiza 9 and Sids 12) based on the mean values of YSI, RDI, TOL, SSI and YRR within each group.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12892-018-0221-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1047356", 
        "issn": [
          "1975-9479", 
          "2005-8276"
        ], 
        "name": "Journal of Crop Science and Biotechnology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "22"
      }
    ], 
    "name": "Uni- and Multi-Variate Assessment of Drought Response Yield Indices in 10 Wheat Cultivars", 
    "pagination": "21-29", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ebe2ba5f3067b5c380d36e4d8c9671db92b63b4733a48e234a95321603b012f8"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12892-018-0221-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113144324"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12892-018-0221-0", 
      "https://app.dimensions.ai/details/publication/pub.1113144324"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:29", 
    "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/v90/0000000370_0000000370/records_46747_00000003.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs12892-018-0221-0"
  }
]
 

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.10.1007/s12892-018-0221-0'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12892-018-0221-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12892-018-0221-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12892-018-0221-0'


 

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

127 TRIPLES      21 PREDICATES      45 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12892-018-0221-0 schema:about anzsrc-for:07
2 anzsrc-for:0703
3 schema:author N172f47c85402472fbc0883960b30fb17
4 schema:citation sg:pub.10.1023/a:1018307111569
5 https://doi.org/10.1016/j.ejbas.2016.10.001
6 https://doi.org/10.1016/j.fcr.2006.02.001
7 https://doi.org/10.1071/ar9780897
8 https://doi.org/10.1071/ar9791001
9 https://doi.org/10.1093/jxb/ery081
10 https://doi.org/10.15192/pscp.aab.2015.4.1.1930
11 https://doi.org/10.2135/cropsci1981.0011183x002100060033x
12 https://doi.org/10.2135/cropsci1984.0011183x002400050026x
13 https://doi.org/10.2135/cropsci1997.0011183x003700010007x
14 https://doi.org/10.2135/cropsci2002.1100
15 https://doi.org/10.2135/cropsci2003.8070
16 https://doi.org/10.2478/v10298-012-0053-2
17 https://doi.org/10.3390/ijerph15050839
18 https://doi.org/10.4067/s0718-34292015000400002
19 https://doi.org/10.4141/p96-130
20 https://doi.org/10.5539/jas.v4n7p126
21 https://doi.org/10.5539/jas.v7n3p49
22 schema:datePublished 2019-03
23 schema:datePublishedReg 2019-03-01
24 schema:description Wheat (Triticum aestivum L.) is a major cereal with its productivity being highly affected by drought. In the current study, 10 wheat cultivars were evaluated for their grain yield under well-watered (Yp) and drought (Ys) conditions. Various drought response indices (mean productivity (MP), geometric productivity (GMP), tolerance index (TOL), stress susceptibility index (SSI), stress tolerance index (STI), harmonic mean of yield (HARM), yield stability index (YSI), relative drought index (RDI), two drought resistance indices (DRI1 and DRI2), yield reduction ratio (YRR) and yield index (YI)) were determined to identify high-yielding and drought tolerant cultivars. Spearman’s correlation coefficient among the estimated indices, hierarchical clustering of the concerned cultivars as well as principle component analysis (PCA) of both the indices and cultivars were employed. Wheat cultivars Sids 13 and Gemmeiza 11 were superior while Sakha 94 and Shandaweel 1 were inferior depending upon their Yp, Ys and drought response indices. Also, a non-significant positive correlation was recorded between Yp and Ys of the studied cultivars with GMP, STI and HARM being significantly correlated with both Yp and Ys. Based on PCA, Yp and Ys explained 61.6 and 38.1% of the total variation; respectively. Furthermore, cluster analysis sequestered the concerned cultivars into drought susceptible cultivars (Shandaweel 1, Giza 168 and Gemmeiza 11), drought moderate ones (Misr 2, Sakha 93 and Sakha 94) and drought tolerant ones (Misr 1, Sids 13, Gemmeiza 9 and Sids 12) based on the mean values of YSI, RDI, TOL, SSI and YRR within each group.
25 schema:genre research_article
26 schema:inLanguage en
27 schema:isAccessibleForFree false
28 schema:isPartOf N487cd9cec83645348e457cc519e21fcb
29 Neb0a24829e7a4ad69f435d80a8a018fe
30 sg:journal.1047356
31 schema:name Uni- and Multi-Variate Assessment of Drought Response Yield Indices in 10 Wheat Cultivars
32 schema:pagination 21-29
33 schema:productId N23fbc5cd31dc4b7a868b4f7214991548
34 Nd404145bef5740eeb9ccb53a586a6980
35 Nd9d35dc9435049d9b4d2ed4f733b285e
36 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113144324
37 https://doi.org/10.1007/s12892-018-0221-0
38 schema:sdDatePublished 2019-04-11T13:29
39 schema:sdLicense https://scigraph.springernature.com/explorer/license/
40 schema:sdPublisher Nfcbe53c23cd643bb885046920c2ce3ab
41 schema:url https://link.springer.com/10.1007%2Fs12892-018-0221-0
42 sgo:license sg:explorer/license/
43 sgo:sdDataset articles
44 rdf:type schema:ScholarlyArticle
45 N172f47c85402472fbc0883960b30fb17 rdf:first Naf7d4ba20669471ebaa863d073e50d6d
46 rdf:rest Na761b3c899994f288563c2872ce2ba82
47 N23fbc5cd31dc4b7a868b4f7214991548 schema:name doi
48 schema:value 10.1007/s12892-018-0221-0
49 rdf:type schema:PropertyValue
50 N487cd9cec83645348e457cc519e21fcb schema:issueNumber 1
51 rdf:type schema:PublicationIssue
52 N868bfa645c644fadb7bc8d89b9d60121 schema:affiliation https://www.grid.ac/institutes/grid.10251.37
53 schema:familyName Aldesuquy
54 schema:givenName Heshmat
55 rdf:type schema:Person
56 N97b4f955a39b44fd9b532b87d389d982 rdf:first Nb1987bff0ecc43f5b856e7b5ebe9bf7f
57 rdf:rest rdf:nil
58 Na761b3c899994f288563c2872ce2ba82 rdf:first N868bfa645c644fadb7bc8d89b9d60121
59 rdf:rest N97b4f955a39b44fd9b532b87d389d982
60 Naf7d4ba20669471ebaa863d073e50d6d schema:affiliation https://www.grid.ac/institutes/grid.10251.37
61 schema:familyName Mickky
62 schema:givenName Bardees
63 rdf:type schema:Person
64 Nb1987bff0ecc43f5b856e7b5ebe9bf7f schema:affiliation https://www.grid.ac/institutes/grid.10251.37
65 schema:familyName Elnajar
66 schema:givenName Mustafa
67 rdf:type schema:Person
68 Nd404145bef5740eeb9ccb53a586a6980 schema:name dimensions_id
69 schema:value pub.1113144324
70 rdf:type schema:PropertyValue
71 Nd9d35dc9435049d9b4d2ed4f733b285e schema:name readcube_id
72 schema:value ebe2ba5f3067b5c380d36e4d8c9671db92b63b4733a48e234a95321603b012f8
73 rdf:type schema:PropertyValue
74 Neb0a24829e7a4ad69f435d80a8a018fe schema:volumeNumber 22
75 rdf:type schema:PublicationVolume
76 Nfcbe53c23cd643bb885046920c2ce3ab schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 anzsrc-for:07 schema:inDefinedTermSet anzsrc-for:
79 schema:name Agricultural and Veterinary Sciences
80 rdf:type schema:DefinedTerm
81 anzsrc-for:0703 schema:inDefinedTermSet anzsrc-for:
82 schema:name Crop and Pasture Production
83 rdf:type schema:DefinedTerm
84 sg:journal.1047356 schema:issn 1975-9479
85 2005-8276
86 schema:name Journal of Crop Science and Biotechnology
87 rdf:type schema:Periodical
88 sg:pub.10.1023/a:1018307111569 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006153393
89 https://doi.org/10.1023/a:1018307111569
90 rdf:type schema:CreativeWork
91 https://doi.org/10.1016/j.ejbas.2016.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034556479
92 rdf:type schema:CreativeWork
93 https://doi.org/10.1016/j.fcr.2006.02.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031108163
94 rdf:type schema:CreativeWork
95 https://doi.org/10.1071/ar9780897 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010847789
96 rdf:type schema:CreativeWork
97 https://doi.org/10.1071/ar9791001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040511844
98 rdf:type schema:CreativeWork
99 https://doi.org/10.1093/jxb/ery081 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101609140
100 rdf:type schema:CreativeWork
101 https://doi.org/10.15192/pscp.aab.2015.4.1.1930 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067604970
102 rdf:type schema:CreativeWork
103 https://doi.org/10.2135/cropsci1981.0011183x002100060033x schema:sameAs https://app.dimensions.ai/details/publication/pub.1069019050
104 rdf:type schema:CreativeWork
105 https://doi.org/10.2135/cropsci1984.0011183x002400050026x schema:sameAs https://app.dimensions.ai/details/publication/pub.1069020217
106 rdf:type schema:CreativeWork
107 https://doi.org/10.2135/cropsci1997.0011183x003700010007x schema:sameAs https://app.dimensions.ai/details/publication/pub.1069025308
108 rdf:type schema:CreativeWork
109 https://doi.org/10.2135/cropsci2002.1100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090703494
110 rdf:type schema:CreativeWork
111 https://doi.org/10.2135/cropsci2003.8070 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069028334
112 rdf:type schema:CreativeWork
113 https://doi.org/10.2478/v10298-012-0053-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048204613
114 rdf:type schema:CreativeWork
115 https://doi.org/10.3390/ijerph15050839 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103631780
116 rdf:type schema:CreativeWork
117 https://doi.org/10.4067/s0718-34292015000400002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005987891
118 rdf:type schema:CreativeWork
119 https://doi.org/10.4141/p96-130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007179512
120 rdf:type schema:CreativeWork
121 https://doi.org/10.5539/jas.v4n7p126 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072959869
122 rdf:type schema:CreativeWork
123 https://doi.org/10.5539/jas.v7n3p49 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072960680
124 rdf:type schema:CreativeWork
125 https://www.grid.ac/institutes/grid.10251.37 schema:alternateName Mansoura University
126 schema:name Botany Department, Faculty of Science, Mansoura University, Mansoura, Egypt
127 rdf:type schema:Organization
 




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


...