Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis

Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed f...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Larrechi, M. Soledad [verfasserIn] Rius, F. Xavier

Format:	Artikel
Sprache:	Englisch

Erschienen:	1987

Schlagwörter:	Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis

Anmerkung:	© Springer-Verlag 1987

Übergeordnetes Werk:	Enthalten in: Zeitschrift für Lebensmittel-Untersuchung und -Forschung - Springer-Verlag, 1943, 185(1987), 3 vom: Sept., Seite 181-184
Übergeordnetes Werk:	volume:185 ; year:1987 ; number:3 ; month:09 ; pages:181-184

Links:	Volltext

DOI / URN:	10.1007/BF01042043

Katalog-ID:	OLC202993478X

Internformat


LEADER	01000caa a22002652 4500
001	OLC202993478X
003	DE-627
005	20230323191239.0
007	tu
008	200819s1987 xx \|\|\|\|\| 00\| \|\|eng c
024	7		\|a 10.1007/BF01042043 \|2 doi
035			\|a (DE-627)OLC202993478X
035			\|a (DE-He213)BF01042043-p
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
082	0	4	\|a 630 \|a 640 \|q VZ
100	1		\|a Larrechi, M. Soledad \|e verfasserin \|4 aut
245	1	0	\|a Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis
264		1	\|c 1987
336			\|a Text \|b txt \|2 rdacontent
337			\|a ohne Hilfsmittel zu benutzen \|b n \|2 rdamedia
338			\|a Band \|b nc \|2 rdacarrier
500			\|a © Springer-Verlag 1987
520			\|a Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name.
650		4	\|a Span Tree
650		4	\|a Minimal Span Tree
650		4	\|a Wine Sample
650		4	\|a Data Analysis Method
650		4	\|a Multivariate Data Analysis
700	1		\|a Rius, F. Xavier \|4 aut
773	0	8	\|i Enthalten in \|t Zeitschrift für Lebensmittel-Untersuchung und -Forschung \|d Springer-Verlag, 1943 \|g 185(1987), 3 vom: Sept., Seite 181-184 \|w (DE-627)12947407X \|w (DE-600)203000-7 \|w (DE-576)01485192X \|x 0044-3026 \|7 nnns
773	1	8	\|g volume:185 \|g year:1987 \|g number:3 \|g month:09 \|g pages:181-184
856	4	1	\|u https://doi.org/10.1007/BF01042043 \|z lizenzpflichtig \|3 Volltext
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_OLC
912			\|a SSG-OLC-TEC
912			\|a SSG-OLC-CHE
912			\|a SSG-OPC-FOR
912			\|a GBV_ILN_11
912			\|a GBV_ILN_20
912			\|a GBV_ILN_21
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_40
912			\|a GBV_ILN_62
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_183
912			\|a GBV_ILN_252
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2018
912			\|a GBV_ILN_2066
912			\|a GBV_ILN_2360
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4027
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4036
912			\|a GBV_ILN_4046
912			\|a GBV_ILN_4103
912			\|a GBV_ILN_4193
912			\|a GBV_ILN_4219
912			\|a GBV_ILN_4247
912			\|a GBV_ILN_4277
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4310
912			\|a GBV_ILN_4319
912			\|a GBV_ILN_4328
951			\|a AR
952			\|d 185 \|j 1987 \|e 3 \|c 09 \|h 181-184

Indexfelder

author_variant	m s l ms msl f x r fx fxr
matchkey_str	article:00443026:1987----::utvraeaanlsspletteeiiinfwctlniiutr
hierarchy_sort_str	1987
publishDate	1987
allfields	10.1007/BF01042043 doi (DE-627)OLC202993478X (DE-He213)BF01042043-p DE-627 ger DE-627 rakwb eng 630 640 VZ Larrechi, M. Soledad verfasserin aut Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis 1987 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1987 Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis Rius, F. Xavier aut Enthalten in Zeitschrift für Lebensmittel-Untersuchung und -Forschung Springer-Verlag, 1943 185(1987), 3 vom: Sept., Seite 181-184 (DE-627)12947407X (DE-600)203000-7 (DE-576)01485192X 0044-3026 nnns volume:185 year:1987 number:3 month:09 pages:181-184 https://doi.org/10.1007/BF01042043 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_183 GBV_ILN_252 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2066 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4027 GBV_ILN_4035 GBV_ILN_4036 GBV_ILN_4046 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4319 GBV_ILN_4328 AR 185 1987 3 09 181-184
spelling	10.1007/BF01042043 doi (DE-627)OLC202993478X (DE-He213)BF01042043-p DE-627 ger DE-627 rakwb eng 630 640 VZ Larrechi, M. Soledad verfasserin aut Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis 1987 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1987 Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis Rius, F. Xavier aut Enthalten in Zeitschrift für Lebensmittel-Untersuchung und -Forschung Springer-Verlag, 1943 185(1987), 3 vom: Sept., Seite 181-184 (DE-627)12947407X (DE-600)203000-7 (DE-576)01485192X 0044-3026 nnns volume:185 year:1987 number:3 month:09 pages:181-184 https://doi.org/10.1007/BF01042043 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_183 GBV_ILN_252 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2066 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4027 GBV_ILN_4035 GBV_ILN_4036 GBV_ILN_4046 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4319 GBV_ILN_4328 AR 185 1987 3 09 181-184
allfields_unstemmed	10.1007/BF01042043 doi (DE-627)OLC202993478X (DE-He213)BF01042043-p DE-627 ger DE-627 rakwb eng 630 640 VZ Larrechi, M. Soledad verfasserin aut Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis 1987 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1987 Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis Rius, F. Xavier aut Enthalten in Zeitschrift für Lebensmittel-Untersuchung und -Forschung Springer-Verlag, 1943 185(1987), 3 vom: Sept., Seite 181-184 (DE-627)12947407X (DE-600)203000-7 (DE-576)01485192X 0044-3026 nnns volume:185 year:1987 number:3 month:09 pages:181-184 https://doi.org/10.1007/BF01042043 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_183 GBV_ILN_252 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2066 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4027 GBV_ILN_4035 GBV_ILN_4036 GBV_ILN_4046 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4319 GBV_ILN_4328 AR 185 1987 3 09 181-184
allfieldsGer	10.1007/BF01042043 doi (DE-627)OLC202993478X (DE-He213)BF01042043-p DE-627 ger DE-627 rakwb eng 630 640 VZ Larrechi, M. Soledad verfasserin aut Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis 1987 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1987 Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis Rius, F. Xavier aut Enthalten in Zeitschrift für Lebensmittel-Untersuchung und -Forschung Springer-Verlag, 1943 185(1987), 3 vom: Sept., Seite 181-184 (DE-627)12947407X (DE-600)203000-7 (DE-576)01485192X 0044-3026 nnns volume:185 year:1987 number:3 month:09 pages:181-184 https://doi.org/10.1007/BF01042043 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_183 GBV_ILN_252 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2066 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4027 GBV_ILN_4035 GBV_ILN_4036 GBV_ILN_4046 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4319 GBV_ILN_4328 AR 185 1987 3 09 181-184
allfieldsSound	10.1007/BF01042043 doi (DE-627)OLC202993478X (DE-He213)BF01042043-p DE-627 ger DE-627 rakwb eng 630 640 VZ Larrechi, M. Soledad verfasserin aut Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis 1987 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1987 Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis Rius, F. Xavier aut Enthalten in Zeitschrift für Lebensmittel-Untersuchung und -Forschung Springer-Verlag, 1943 185(1987), 3 vom: Sept., Seite 181-184 (DE-627)12947407X (DE-600)203000-7 (DE-576)01485192X 0044-3026 nnns volume:185 year:1987 number:3 month:09 pages:181-184 https://doi.org/10.1007/BF01042043 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_183 GBV_ILN_252 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2066 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4027 GBV_ILN_4035 GBV_ILN_4036 GBV_ILN_4046 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4319 GBV_ILN_4328 AR 185 1987 3 09 181-184
language	English
source	Enthalten in Zeitschrift für Lebensmittel-Untersuchung und -Forschung 185(1987), 3 vom: Sept., Seite 181-184 volume:185 year:1987 number:3 month:09 pages:181-184
sourceStr	Enthalten in Zeitschrift für Lebensmittel-Untersuchung und -Forschung 185(1987), 3 vom: Sept., Seite 181-184 volume:185 year:1987 number:3 month:09 pages:181-184
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis
dewey-raw	630
isfreeaccess_bool	false
container_title	Zeitschrift für Lebensmittel-Untersuchung und -Forschung
authorswithroles_txt_mv	Larrechi, M. Soledad @@aut@@ Rius, F. Xavier @@aut@@
publishDateDaySort_date	1987-09-01T00:00:00Z
hierarchy_top_id	12947407X
dewey-sort	3630
id	OLC202993478X
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC202993478X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230323191239.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s1987 xx \|\|\|\|\| 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/BF01042043</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC202993478X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)BF01042043-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">630</subfield><subfield code="a">640</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Larrechi, M. Soledad</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">1987</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag 1987</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Span Tree</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Minimal Span Tree</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Wine Sample</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data Analysis Method</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multivariate Data Analysis</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rius, F. Xavier</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Zeitschrift für Lebensmittel-Untersuchung und -Forschung</subfield><subfield code="d">Springer-Verlag, 1943</subfield><subfield code="g">185(1987), 3 vom: Sept., Seite 181-184</subfield><subfield code="w">(DE-627)12947407X</subfield><subfield code="w">(DE-600)203000-7</subfield><subfield code="w">(DE-576)01485192X</subfield><subfield code="x">0044-3026</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:185</subfield><subfield code="g">year:1987</subfield><subfield code="g">number:3</subfield><subfield code="g">month:09</subfield><subfield code="g">pages:181-184</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/BF01042043</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_183</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_252</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2066</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2360</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4036</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4103</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4193</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4219</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4247</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4277</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4310</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4319</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4328</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">185</subfield><subfield code="j">1987</subfield><subfield code="e">3</subfield><subfield code="c">09</subfield><subfield code="h">181-184</subfield></datafield></record></collection>
author	Larrechi, M. Soledad
spellingShingle	Larrechi, M. Soledad ddc 630 misc Span Tree misc Minimal Span Tree misc Wine Sample misc Data Analysis Method misc Multivariate Data Analysis Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis
authorStr	Larrechi, M. Soledad
ppnlink_with_tag_str_mv	@@773@@(DE-627)12947407X
format	Article
dewey-ones	630 - Agriculture & related technologies 640 - Home & family management
delete_txt_mv	keep
author_role	aut aut
collection	OLC
remote_str	false
illustrated	Not Illustrated
issn	0044-3026
topic_title	630 640 VZ Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis Span Tree Minimal Span Tree Wine Sample Data Analysis Method Multivariate Data Analysis
topic	ddc 630 misc Span Tree misc Minimal Span Tree misc Wine Sample misc Data Analysis Method misc Multivariate Data Analysis
topic_unstemmed	ddc 630 misc Span Tree misc Minimal Span Tree misc Wine Sample misc Data Analysis Method misc Multivariate Data Analysis
topic_browse	ddc 630 misc Span Tree misc Minimal Span Tree misc Wine Sample misc Data Analysis Method misc Multivariate Data Analysis
format_facet	Aufsätze Gedruckte Aufsätze
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	nc
hierarchy_parent_title	Zeitschrift für Lebensmittel-Untersuchung und -Forschung
hierarchy_parent_id	12947407X
dewey-tens	630 - Agriculture 640 - Home & family management
hierarchy_top_title	Zeitschrift für Lebensmittel-Untersuchung und -Forschung
isfreeaccess_txt	false
familylinks_str_mv	(DE-627)12947407X (DE-600)203000-7 (DE-576)01485192X
title	Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis
ctrlnum	(DE-627)OLC202993478X (DE-He213)BF01042043-p
title_full	Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis
author_sort	Larrechi, M. Soledad
journal	Zeitschrift für Lebensmittel-Untersuchung und -Forschung
journalStr	Zeitschrift für Lebensmittel-Untersuchung und -Forschung
lang_code	eng
isOA_bool	false
dewey-hundreds	600 - Technology
recordtype	marc
publishDateSort	1987
contenttype_str_mv	txt
container_start_page	181
author_browse	Larrechi, M. Soledad Rius, F. Xavier
container_volume	185
class	630 640 VZ
format_se	Aufsätze
author-letter	Larrechi, M. Soledad
doi_str_mv	10.1007/BF01042043
dewey-full	630 640
title_sort	multivariate data analysis applied to the definition of two catalan viticultural regions i. cluster analysis
title_auth	Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis
abstract	Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. © Springer-Verlag 1987
abstractGer	Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. © Springer-Verlag 1987
abstract_unstemmed	Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name. © Springer-Verlag 1987
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OPC-FOR GBV_ILN_11 GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_183 GBV_ILN_252 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2066 GBV_ILN_2360 GBV_ILN_4012 GBV_ILN_4027 GBV_ILN_4035 GBV_ILN_4036 GBV_ILN_4046 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4319 GBV_ILN_4328
container_issue	3
title_short	Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis
url	https://doi.org/10.1007/BF01042043
remote_bool	false
author2	Rius, F. Xavier
author2Str	Rius, F. Xavier
ppnlink	12947407X
mediatype_str_mv	n
isOA_txt	false
hochschulschrift_bool	false
doi_str	10.1007/BF01042043
up_date	2024-07-04T00:35:37.781Z
_version_	1803606648741167105
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC202993478X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230323191239.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s1987 xx \|\|\|\|\| 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/BF01042043</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC202993478X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)BF01042043-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">630</subfield><subfield code="a">640</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Larrechi, M. Soledad</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">1987</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag 1987</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Summary Five multivariate data analysis methods, namely principal components analysis, non-linear mapping, hierarchical clustering, minimal spanning tree and mode analysis, were used to analyse the natural structure of red wines from Tarragona (Catalonia, Spain). Seventeen parameters were analysed for each sample to determine the multi-dimensional spectrum in which the wines are studied. In spite of the homogeneity of the wine samples which resulted from the similarity of the edaphic, varietal factors as well as the cultural conditions of the producing areas, two different clusters can be distinguished on the basis of all the methods used. The groups of wine samples obtained coincide with two viticultural zones that differ with regard to climate and geographical conditions. Therefore, a natural distinction can bei made between the wines produced in each adjacent zone, forming the basis for future differentiation according to brand name.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Span Tree</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Minimal Span Tree</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Wine Sample</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data Analysis Method</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multivariate Data Analysis</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rius, F. Xavier</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Zeitschrift für Lebensmittel-Untersuchung und -Forschung</subfield><subfield code="d">Springer-Verlag, 1943</subfield><subfield code="g">185(1987), 3 vom: Sept., Seite 181-184</subfield><subfield code="w">(DE-627)12947407X</subfield><subfield code="w">(DE-600)203000-7</subfield><subfield code="w">(DE-576)01485192X</subfield><subfield code="x">0044-3026</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:185</subfield><subfield code="g">year:1987</subfield><subfield code="g">number:3</subfield><subfield code="g">month:09</subfield><subfield code="g">pages:181-184</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/BF01042043</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_183</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_252</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2066</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2360</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4036</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4103</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4193</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4219</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4247</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4277</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4310</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4319</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4328</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">185</subfield><subfield code="j">1987</subfield><subfield code="e">3</subfield><subfield code="c">09</subfield><subfield code="h">181-184</subfield></datafield></record></collection>
score	7.400996

Nicht das Richtige dabei?

Schreiben Sie uns!

Multivariate data analysis applied to the definition of two Catalan viticultural regions I. Cluster analysis

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?