Discrimination of Acacia seeds at species and subspecies levels using an image analyzer

Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp....
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Gespeichert in:

Autor*in:	Sivakumar, V. [verfasserIn] Anandalakshmi, R. Warrier, Rekha R. Singh, B. G. Tigabu, M. Nagarajan, B.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	image analyzer discriminant analysis seed identification

Anmerkung:	© Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013

Übergeordnetes Werk:	Enthalten in: Forestry studies in China - Beijing : BFU, 1999, 15(2013), 4 vom: Dez., Seite 253-260
Übergeordnetes Werk:	volume:15 ; year:2013 ; number:4 ; month:12 ; pages:253-260

Links:	Volltext

DOI / URN:	10.1007/s11632-013-0414-4

Katalog-ID:	SPR021283907

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520			\|a Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias.
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allfields	10.1007/s11632-013-0414-4 doi (DE-627)SPR021283907 (SPR)s11632-013-0414-4-e DE-627 ger DE-627 rakwb eng Sivakumar, V. verfasserin aut Discrimination of Acacia seeds at species and subspecies levels using an image analyzer 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013 Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. image analyzer (dpeaa)DE-He213 discriminant analysis (dpeaa)DE-He213 seed identification (dpeaa)DE-He213 Anandalakshmi, R. aut Warrier, Rekha R. aut Singh, B. G. aut Tigabu, M. aut Nagarajan, B. aut Enthalten in Forestry studies in China Beijing : BFU, 1999 15(2013), 4 vom: Dez., Seite 253-260 (DE-627)518632393 (DE-600)2253236-5 1993-0372 nnns volume:15 year:2013 number:4 month:12 pages:253-260 https://dx.doi.org/10.1007/s11632-013-0414-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_32 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_161 GBV_ILN_293 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2700 GBV_ILN_2817 AR 15 2013 4 12 253-260
spelling	10.1007/s11632-013-0414-4 doi (DE-627)SPR021283907 (SPR)s11632-013-0414-4-e DE-627 ger DE-627 rakwb eng Sivakumar, V. verfasserin aut Discrimination of Acacia seeds at species and subspecies levels using an image analyzer 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013 Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. image analyzer (dpeaa)DE-He213 discriminant analysis (dpeaa)DE-He213 seed identification (dpeaa)DE-He213 Anandalakshmi, R. aut Warrier, Rekha R. aut Singh, B. G. aut Tigabu, M. aut Nagarajan, B. aut Enthalten in Forestry studies in China Beijing : BFU, 1999 15(2013), 4 vom: Dez., Seite 253-260 (DE-627)518632393 (DE-600)2253236-5 1993-0372 nnns volume:15 year:2013 number:4 month:12 pages:253-260 https://dx.doi.org/10.1007/s11632-013-0414-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_32 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_161 GBV_ILN_293 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2700 GBV_ILN_2817 AR 15 2013 4 12 253-260
allfields_unstemmed	10.1007/s11632-013-0414-4 doi (DE-627)SPR021283907 (SPR)s11632-013-0414-4-e DE-627 ger DE-627 rakwb eng Sivakumar, V. verfasserin aut Discrimination of Acacia seeds at species and subspecies levels using an image analyzer 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013 Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. image analyzer (dpeaa)DE-He213 discriminant analysis (dpeaa)DE-He213 seed identification (dpeaa)DE-He213 Anandalakshmi, R. aut Warrier, Rekha R. aut Singh, B. G. aut Tigabu, M. aut Nagarajan, B. aut Enthalten in Forestry studies in China Beijing : BFU, 1999 15(2013), 4 vom: Dez., Seite 253-260 (DE-627)518632393 (DE-600)2253236-5 1993-0372 nnns volume:15 year:2013 number:4 month:12 pages:253-260 https://dx.doi.org/10.1007/s11632-013-0414-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_32 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_161 GBV_ILN_293 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2700 GBV_ILN_2817 AR 15 2013 4 12 253-260
allfieldsGer	10.1007/s11632-013-0414-4 doi (DE-627)SPR021283907 (SPR)s11632-013-0414-4-e DE-627 ger DE-627 rakwb eng Sivakumar, V. verfasserin aut Discrimination of Acacia seeds at species and subspecies levels using an image analyzer 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013 Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. image analyzer (dpeaa)DE-He213 discriminant analysis (dpeaa)DE-He213 seed identification (dpeaa)DE-He213 Anandalakshmi, R. aut Warrier, Rekha R. aut Singh, B. G. aut Tigabu, M. aut Nagarajan, B. aut Enthalten in Forestry studies in China Beijing : BFU, 1999 15(2013), 4 vom: Dez., Seite 253-260 (DE-627)518632393 (DE-600)2253236-5 1993-0372 nnns volume:15 year:2013 number:4 month:12 pages:253-260 https://dx.doi.org/10.1007/s11632-013-0414-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_32 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_161 GBV_ILN_293 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2700 GBV_ILN_2817 AR 15 2013 4 12 253-260
allfieldsSound	10.1007/s11632-013-0414-4 doi (DE-627)SPR021283907 (SPR)s11632-013-0414-4-e DE-627 ger DE-627 rakwb eng Sivakumar, V. verfasserin aut Discrimination of Acacia seeds at species and subspecies levels using an image analyzer 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013 Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. image analyzer (dpeaa)DE-He213 discriminant analysis (dpeaa)DE-He213 seed identification (dpeaa)DE-He213 Anandalakshmi, R. aut Warrier, Rekha R. aut Singh, B. G. aut Tigabu, M. aut Nagarajan, B. aut Enthalten in Forestry studies in China Beijing : BFU, 1999 15(2013), 4 vom: Dez., Seite 253-260 (DE-627)518632393 (DE-600)2253236-5 1993-0372 nnns volume:15 year:2013 number:4 month:12 pages:253-260 https://dx.doi.org/10.1007/s11632-013-0414-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_32 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_161 GBV_ILN_293 GBV_ILN_374 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2014 GBV_ILN_2700 GBV_ILN_2817 AR 15 2013 4 12 253-260
language	English
source	Enthalten in Forestry studies in China 15(2013), 4 vom: Dez., Seite 253-260 volume:15 year:2013 number:4 month:12 pages:253-260
sourceStr	Enthalten in Forestry studies in China 15(2013), 4 vom: Dez., Seite 253-260 volume:15 year:2013 number:4 month:12 pages:253-260
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authorswithroles_txt_mv	Sivakumar, V. @@aut@@ Anandalakshmi, R. @@aut@@ Warrier, Rekha R. @@aut@@ Singh, B. G. @@aut@@ Tigabu, M. @@aut@@ Nagarajan, B. @@aut@@
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author	Sivakumar, V.
spellingShingle	Sivakumar, V. misc image analyzer misc discriminant analysis misc seed identification Discrimination of Acacia seeds at species and subspecies levels using an image analyzer
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topic_title	Discrimination of Acacia seeds at species and subspecies levels using an image analyzer image analyzer (dpeaa)DE-He213 discriminant analysis (dpeaa)DE-He213 seed identification (dpeaa)DE-He213
topic	misc image analyzer misc discriminant analysis misc seed identification
topic_unstemmed	misc image analyzer misc discriminant analysis misc seed identification
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title	Discrimination of Acacia seeds at species and subspecies levels using an image analyzer
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title_full	Discrimination of Acacia seeds at species and subspecies levels using an image analyzer
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author_browse	Sivakumar, V. Anandalakshmi, R. Warrier, Rekha R. Singh, B. G. Tigabu, M. Nagarajan, B.
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title_sort	discrimination of acacia seeds at species and subspecies levels using an image analyzer
title_auth	Discrimination of Acacia seeds at species and subspecies levels using an image analyzer
abstract	Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013
abstractGer	Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013
abstract_unstemmed	Abstract Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa (75.0%), A. tortilis subsp. spirocarpa (75.0%) and A. raddiana (87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias. © Beijing Forestry University and Springer-Verlag Berlin Heidelberg 2013
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title_short	Discrimination of Acacia seeds at species and subspecies levels using an image analyzer
url	https://dx.doi.org/10.1007/s11632-013-0414-4
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author2	Anandalakshmi, R. Warrier, Rekha R. Singh, B. G. Tigabu, M. Nagarajan, B.
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