Development and Validation of a Fast DNA Extraction Protocol for Fish Products
Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and ef...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Xiong, Xiong [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2019 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2019 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Food analytical methods - New York, NY : Springer, 2008, 12(2019), 9 vom: 04. Juni, Seite 1998-2008 |
|---|---|
| Übergeordnetes Werk: |
volume:12 ; year:2019 ; number:9 ; day:04 ; month:06 ; pages:1998-2008 |
| Links: |
|---|
| DOI / URN: |
10.1007/s12161-019-01554-z |
|---|
| Katalog-ID: |
SPR025269607 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | SPR025269607 | ||
| 003 | DE-627 | ||
| 005 | 20230519172514.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 201007s2019 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s12161-019-01554-z |2 doi | |
| 035 | |a (DE-627)SPR025269607 | ||
| 035 | |a (SPR)s12161-019-01554-z-e | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Xiong, Xiong |e verfasserin |0 (orcid)0000-0001-7965-5859 |4 aut | |
| 245 | 1 | 0 | |a Development and Validation of a Fast DNA Extraction Protocol for Fish Products |
| 264 | 1 | |c 2019 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a © Springer Science+Business Media, LLC, part of Springer Nature 2019 | ||
| 520 | |a Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. | ||
| 650 | 4 | |a DNA extraction |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a DNA barcoding |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fish products |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Boiling protocol |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Huang, Manhong |4 aut | |
| 700 | 1 | |a Yuan, Fangying |4 aut | |
| 700 | 1 | |a Lu, Lixia |4 aut | |
| 700 | 1 | |a Xiong, Xiaohui |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Food analytical methods |d New York, NY : Springer, 2008 |g 12(2019), 9 vom: 04. Juni, Seite 1998-2008 |w (DE-627)566007320 |w (DE-600)2424728-5 |x 1936-976X |7 nnns |
| 773 | 1 | 8 | |g volume:12 |g year:2019 |g number:9 |g day:04 |g month:06 |g pages:1998-2008 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s12161-019-01554-z |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_SPRINGER | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a GBV_ILN_11 | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_32 | ||
| 912 | |a GBV_ILN_39 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_60 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_63 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_74 | ||
| 912 | |a GBV_ILN_90 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_100 | ||
| 912 | |a GBV_ILN_101 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_120 | ||
| 912 | |a GBV_ILN_138 | ||
| 912 | |a GBV_ILN_150 | ||
| 912 | |a GBV_ILN_151 | ||
| 912 | |a GBV_ILN_161 | ||
| 912 | |a GBV_ILN_170 | ||
| 912 | |a GBV_ILN_171 | ||
| 912 | |a GBV_ILN_187 | ||
| 912 | |a GBV_ILN_213 | ||
| 912 | |a GBV_ILN_224 | ||
| 912 | |a GBV_ILN_230 | ||
| 912 | |a GBV_ILN_250 | ||
| 912 | |a GBV_ILN_281 | ||
| 912 | |a GBV_ILN_285 | ||
| 912 | |a GBV_ILN_293 | ||
| 912 | |a GBV_ILN_370 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_636 | ||
| 912 | |a GBV_ILN_702 | ||
| 912 | |a GBV_ILN_2001 | ||
| 912 | |a GBV_ILN_2003 | ||
| 912 | |a GBV_ILN_2004 | ||
| 912 | |a GBV_ILN_2005 | ||
| 912 | |a GBV_ILN_2006 | ||
| 912 | |a GBV_ILN_2007 | ||
| 912 | |a GBV_ILN_2008 | ||
| 912 | |a GBV_ILN_2009 | ||
| 912 | |a GBV_ILN_2010 | ||
| 912 | |a GBV_ILN_2011 | ||
| 912 | |a GBV_ILN_2014 | ||
| 912 | |a GBV_ILN_2015 | ||
| 912 | |a GBV_ILN_2020 | ||
| 912 | |a GBV_ILN_2021 | ||
| 912 | |a GBV_ILN_2025 | ||
| 912 | |a GBV_ILN_2026 | ||
| 912 | |a GBV_ILN_2027 | ||
| 912 | |a GBV_ILN_2031 | ||
| 912 | |a GBV_ILN_2034 | ||
| 912 | |a GBV_ILN_2037 | ||
| 912 | |a GBV_ILN_2038 | ||
| 912 | |a GBV_ILN_2039 | ||
| 912 | |a GBV_ILN_2044 | ||
| 912 | |a GBV_ILN_2048 | ||
| 912 | |a GBV_ILN_2049 | ||
| 912 | |a GBV_ILN_2050 | ||
| 912 | |a GBV_ILN_2055 | ||
| 912 | |a GBV_ILN_2057 | ||
| 912 | |a GBV_ILN_2059 | ||
| 912 | |a GBV_ILN_2061 | ||
| 912 | |a GBV_ILN_2064 | ||
| 912 | |a GBV_ILN_2065 | ||
| 912 | |a GBV_ILN_2068 | ||
| 912 | |a GBV_ILN_2070 | ||
| 912 | |a GBV_ILN_2086 | ||
| 912 | |a GBV_ILN_2088 | ||
| 912 | |a GBV_ILN_2093 | ||
| 912 | |a GBV_ILN_2106 | ||
| 912 | |a GBV_ILN_2107 | ||
| 912 | |a GBV_ILN_2108 | ||
| 912 | |a GBV_ILN_2110 | ||
| 912 | |a GBV_ILN_2111 | ||
| 912 | |a GBV_ILN_2112 | ||
| 912 | |a GBV_ILN_2113 | ||
| 912 | |a GBV_ILN_2116 | ||
| 912 | |a GBV_ILN_2118 | ||
| 912 | |a GBV_ILN_2119 | ||
| 912 | |a GBV_ILN_2122 | ||
| 912 | |a GBV_ILN_2129 | ||
| 912 | |a GBV_ILN_2143 | ||
| 912 | |a GBV_ILN_2144 | ||
| 912 | |a GBV_ILN_2147 | ||
| 912 | |a GBV_ILN_2148 | ||
| 912 | |a GBV_ILN_2152 | ||
| 912 | |a GBV_ILN_2153 | ||
| 912 | |a GBV_ILN_2188 | ||
| 912 | |a GBV_ILN_2190 | ||
| 912 | |a GBV_ILN_2232 | ||
| 912 | |a GBV_ILN_2336 | ||
| 912 | |a GBV_ILN_2446 | ||
| 912 | |a GBV_ILN_2470 | ||
| 912 | |a GBV_ILN_2472 | ||
| 912 | |a GBV_ILN_2507 | ||
| 912 | |a GBV_ILN_2522 | ||
| 912 | |a GBV_ILN_2548 | ||
| 912 | |a GBV_ILN_4035 | ||
| 912 | |a GBV_ILN_4037 | ||
| 912 | |a GBV_ILN_4046 | ||
| 912 | |a GBV_ILN_4112 | ||
| 912 | |a GBV_ILN_4125 | ||
| 912 | |a GBV_ILN_4242 | ||
| 912 | |a GBV_ILN_4246 | ||
| 912 | |a GBV_ILN_4249 | ||
| 912 | |a GBV_ILN_4251 | ||
| 912 | |a GBV_ILN_4305 | ||
| 912 | |a GBV_ILN_4306 | ||
| 912 | |a GBV_ILN_4307 | ||
| 912 | |a GBV_ILN_4313 | ||
| 912 | |a GBV_ILN_4322 | ||
| 912 | |a GBV_ILN_4323 | ||
| 912 | |a GBV_ILN_4324 | ||
| 912 | |a GBV_ILN_4325 | ||
| 912 | |a GBV_ILN_4326 | ||
| 912 | |a GBV_ILN_4333 | ||
| 912 | |a GBV_ILN_4334 | ||
| 912 | |a GBV_ILN_4335 | ||
| 912 | |a GBV_ILN_4336 | ||
| 912 | |a GBV_ILN_4338 | ||
| 912 | |a GBV_ILN_4393 | ||
| 912 | |a GBV_ILN_4700 | ||
| 951 | |a AR | ||
| 952 | |d 12 |j 2019 |e 9 |b 04 |c 06 |h 1998-2008 | ||
| author_variant |
x x xx m h mh f y fy l l ll x x xx |
|---|---|
| matchkey_str |
article:1936976X:2019----::eeomnadaiainffsdaxrcinrt |
| hierarchy_sort_str |
2019 |
| publishDate |
2019 |
| allfields |
10.1007/s12161-019-01554-z doi (DE-627)SPR025269607 (SPR)s12161-019-01554-z-e DE-627 ger DE-627 rakwb eng Xiong, Xiong verfasserin (orcid)0000-0001-7965-5859 aut Development and Validation of a Fast DNA Extraction Protocol for Fish Products 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. DNA extraction (dpeaa)DE-He213 DNA barcoding (dpeaa)DE-He213 Fish products (dpeaa)DE-He213 Boiling protocol (dpeaa)DE-He213 Huang, Manhong aut Yuan, Fangying aut Lu, Lixia aut Xiong, Xiaohui aut Enthalten in Food analytical methods New York, NY : Springer, 2008 12(2019), 9 vom: 04. Juni, Seite 1998-2008 (DE-627)566007320 (DE-600)2424728-5 1936-976X nnns volume:12 year:2019 number:9 day:04 month:06 pages:1998-2008 https://dx.doi.org/10.1007/s12161-019-01554-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2019 9 04 06 1998-2008 |
| spelling |
10.1007/s12161-019-01554-z doi (DE-627)SPR025269607 (SPR)s12161-019-01554-z-e DE-627 ger DE-627 rakwb eng Xiong, Xiong verfasserin (orcid)0000-0001-7965-5859 aut Development and Validation of a Fast DNA Extraction Protocol for Fish Products 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. DNA extraction (dpeaa)DE-He213 DNA barcoding (dpeaa)DE-He213 Fish products (dpeaa)DE-He213 Boiling protocol (dpeaa)DE-He213 Huang, Manhong aut Yuan, Fangying aut Lu, Lixia aut Xiong, Xiaohui aut Enthalten in Food analytical methods New York, NY : Springer, 2008 12(2019), 9 vom: 04. Juni, Seite 1998-2008 (DE-627)566007320 (DE-600)2424728-5 1936-976X nnns volume:12 year:2019 number:9 day:04 month:06 pages:1998-2008 https://dx.doi.org/10.1007/s12161-019-01554-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2019 9 04 06 1998-2008 |
| allfields_unstemmed |
10.1007/s12161-019-01554-z doi (DE-627)SPR025269607 (SPR)s12161-019-01554-z-e DE-627 ger DE-627 rakwb eng Xiong, Xiong verfasserin (orcid)0000-0001-7965-5859 aut Development and Validation of a Fast DNA Extraction Protocol for Fish Products 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. DNA extraction (dpeaa)DE-He213 DNA barcoding (dpeaa)DE-He213 Fish products (dpeaa)DE-He213 Boiling protocol (dpeaa)DE-He213 Huang, Manhong aut Yuan, Fangying aut Lu, Lixia aut Xiong, Xiaohui aut Enthalten in Food analytical methods New York, NY : Springer, 2008 12(2019), 9 vom: 04. Juni, Seite 1998-2008 (DE-627)566007320 (DE-600)2424728-5 1936-976X nnns volume:12 year:2019 number:9 day:04 month:06 pages:1998-2008 https://dx.doi.org/10.1007/s12161-019-01554-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2019 9 04 06 1998-2008 |
| allfieldsGer |
10.1007/s12161-019-01554-z doi (DE-627)SPR025269607 (SPR)s12161-019-01554-z-e DE-627 ger DE-627 rakwb eng Xiong, Xiong verfasserin (orcid)0000-0001-7965-5859 aut Development and Validation of a Fast DNA Extraction Protocol for Fish Products 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. DNA extraction (dpeaa)DE-He213 DNA barcoding (dpeaa)DE-He213 Fish products (dpeaa)DE-He213 Boiling protocol (dpeaa)DE-He213 Huang, Manhong aut Yuan, Fangying aut Lu, Lixia aut Xiong, Xiaohui aut Enthalten in Food analytical methods New York, NY : Springer, 2008 12(2019), 9 vom: 04. Juni, Seite 1998-2008 (DE-627)566007320 (DE-600)2424728-5 1936-976X nnns volume:12 year:2019 number:9 day:04 month:06 pages:1998-2008 https://dx.doi.org/10.1007/s12161-019-01554-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2019 9 04 06 1998-2008 |
| allfieldsSound |
10.1007/s12161-019-01554-z doi (DE-627)SPR025269607 (SPR)s12161-019-01554-z-e DE-627 ger DE-627 rakwb eng Xiong, Xiong verfasserin (orcid)0000-0001-7965-5859 aut Development and Validation of a Fast DNA Extraction Protocol for Fish Products 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. DNA extraction (dpeaa)DE-He213 DNA barcoding (dpeaa)DE-He213 Fish products (dpeaa)DE-He213 Boiling protocol (dpeaa)DE-He213 Huang, Manhong aut Yuan, Fangying aut Lu, Lixia aut Xiong, Xiaohui aut Enthalten in Food analytical methods New York, NY : Springer, 2008 12(2019), 9 vom: 04. Juni, Seite 1998-2008 (DE-627)566007320 (DE-600)2424728-5 1936-976X nnns volume:12 year:2019 number:9 day:04 month:06 pages:1998-2008 https://dx.doi.org/10.1007/s12161-019-01554-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 12 2019 9 04 06 1998-2008 |
| language |
English |
| source |
Enthalten in Food analytical methods 12(2019), 9 vom: 04. Juni, Seite 1998-2008 volume:12 year:2019 number:9 day:04 month:06 pages:1998-2008 |
| sourceStr |
Enthalten in Food analytical methods 12(2019), 9 vom: 04. Juni, Seite 1998-2008 volume:12 year:2019 number:9 day:04 month:06 pages:1998-2008 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
DNA extraction DNA barcoding Fish products Boiling protocol |
| isfreeaccess_bool |
false |
| container_title |
Food analytical methods |
| authorswithroles_txt_mv |
Xiong, Xiong @@aut@@ Huang, Manhong @@aut@@ Yuan, Fangying @@aut@@ Lu, Lixia @@aut@@ Xiong, Xiaohui @@aut@@ |
| publishDateDaySort_date |
2019-06-04T00:00:00Z |
| hierarchy_top_id |
566007320 |
| id |
SPR025269607 |
| 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">SPR025269607</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519172514.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2019 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12161-019-01554-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR025269607</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12161-019-01554-z-e</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="100" ind1="1" ind2=" "><subfield code="a">Xiong, Xiong</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0001-7965-5859</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Development and Validation of a Fast DNA Extraction Protocol for Fish Products</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</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">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">DNA extraction</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">DNA barcoding</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fish products</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Boiling protocol</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Manhong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yuan, Fangying</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lu, Lixia</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xiong, Xiaohui</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Food analytical methods</subfield><subfield code="d">New York, NY : Springer, 2008</subfield><subfield code="g">12(2019), 9 vom: 04. Juni, Seite 1998-2008</subfield><subfield code="w">(DE-627)566007320</subfield><subfield code="w">(DE-600)2424728-5</subfield><subfield code="x">1936-976X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:12</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:9</subfield><subfield code="g">day:04</subfield><subfield code="g">month:06</subfield><subfield code="g">pages:1998-2008</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s12161-019-01554-z</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_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</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_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_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</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_60</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_63</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_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_101</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_636</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</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_2005</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_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</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_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</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_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2039</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2070</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2086</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2093</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2107</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2108</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2116</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2119</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2144</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2188</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2446</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2472</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2548</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_4037</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_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4246</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</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_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">12</subfield><subfield code="j">2019</subfield><subfield code="e">9</subfield><subfield code="b">04</subfield><subfield code="c">06</subfield><subfield code="h">1998-2008</subfield></datafield></record></collection>
|
| author |
Xiong, Xiong |
| spellingShingle |
Xiong, Xiong misc DNA extraction misc DNA barcoding misc Fish products misc Boiling protocol Development and Validation of a Fast DNA Extraction Protocol for Fish Products |
| authorStr |
Xiong, Xiong |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)566007320 |
| format |
electronic Article |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut |
| collection |
springer |
| remote_str |
true |
| illustrated |
Not Illustrated |
| issn |
1936-976X |
| topic_title |
Development and Validation of a Fast DNA Extraction Protocol for Fish Products DNA extraction (dpeaa)DE-He213 DNA barcoding (dpeaa)DE-He213 Fish products (dpeaa)DE-He213 Boiling protocol (dpeaa)DE-He213 |
| topic |
misc DNA extraction misc DNA barcoding misc Fish products misc Boiling protocol |
| topic_unstemmed |
misc DNA extraction misc DNA barcoding misc Fish products misc Boiling protocol |
| topic_browse |
misc DNA extraction misc DNA barcoding misc Fish products misc Boiling protocol |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Food analytical methods |
| hierarchy_parent_id |
566007320 |
| hierarchy_top_title |
Food analytical methods |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)566007320 (DE-600)2424728-5 |
| title |
Development and Validation of a Fast DNA Extraction Protocol for Fish Products |
| ctrlnum |
(DE-627)SPR025269607 (SPR)s12161-019-01554-z-e |
| title_full |
Development and Validation of a Fast DNA Extraction Protocol for Fish Products |
| author_sort |
Xiong, Xiong |
| journal |
Food analytical methods |
| journalStr |
Food analytical methods |
| lang_code |
eng |
| isOA_bool |
false |
| recordtype |
marc |
| publishDateSort |
2019 |
| contenttype_str_mv |
txt |
| container_start_page |
1998 |
| author_browse |
Xiong, Xiong Huang, Manhong Yuan, Fangying Lu, Lixia Xiong, Xiaohui |
| container_volume |
12 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Xiong, Xiong |
| doi_str_mv |
10.1007/s12161-019-01554-z |
| normlink |
(ORCID)0000-0001-7965-5859 |
| normlink_prefix_str_mv |
(orcid)0000-0001-7965-5859 |
| title_sort |
development and validation of a fast dna extraction protocol for fish products |
| title_auth |
Development and Validation of a Fast DNA Extraction Protocol for Fish Products |
| abstract |
Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| abstractGer |
Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| abstract_unstemmed |
Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 |
| container_issue |
9 |
| title_short |
Development and Validation of a Fast DNA Extraction Protocol for Fish Products |
| url |
https://dx.doi.org/10.1007/s12161-019-01554-z |
| remote_bool |
true |
| author2 |
Huang, Manhong Yuan, Fangying Lu, Lixia Xiong, Xiaohui |
| author2Str |
Huang, Manhong Yuan, Fangying Lu, Lixia Xiong, Xiaohui |
| ppnlink |
566007320 |
| mediatype_str_mv |
c |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s12161-019-01554-z |
| up_date |
2024-07-03T14:56:27.536Z |
| _version_ |
1803570210443100160 |
| 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">SPR025269607</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519172514.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2019 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12161-019-01554-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR025269607</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12161-019-01554-z-e</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="100" ind1="1" ind2=" "><subfield code="a">Xiong, Xiong</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0001-7965-5859</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Development and Validation of a Fast DNA Extraction Protocol for Fish Products</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</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">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Fish species mislabeling is a typical form of food fraud widely reported around the world. The most applied technique in the detection of fish species mislabeling is based on DNA and the primary step of most DNA-based methods is to obtain sufficient amount of high-quality DNA quickly and efficiently. However, traditional DNA extraction method, for instance the salting-out method, can be greatly compromised by the fundamental step of cell lysis that generally costs hours or even overnight. Boiling protocol (BP), which can be achieved by an incubation for 10–15 min at 95–100 °C in a heat block or boiling water bath, is one of the simplest protocols for cell lysis. In this study, we applied BP method, together with a modified lysate, for DNA extraction from simulated fresh, frozen, and roasted fish products. Traditional proteinase K-based lysis method (TP) was used as the control and compared with BP method in DNA concentration, purity, conventional PCR, and real time PCR. Finally, BP method was validated on commercial fish products, followed by DNA barcoding to identify the labeling accuracy. The results highlighted a lower concentration and $ A_{260} $/$ A_{230} $ ratio for DNA extracted by BP method than TP method for most species, regardless of the simulation methods. While conventional PCR amplification of 650 bp COI barcode can be achieved for all species in all simulations. Moreover, no significant difference (p > 0.05) was observed with Ct value for the same species between BP method and TP method. Total DNA can be successfully extracted with BP method for all commercial fish products and poor labeling accuracy was revealed for commercial roasted fish fillet products, 72.7% of which were identified as containing multiple species. Therefore, in light of the lower demand for time and cost, BP method can be considered as a valid alternative of TP method.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">DNA extraction</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">DNA barcoding</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fish products</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Boiling protocol</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Manhong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yuan, Fangying</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lu, Lixia</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xiong, Xiaohui</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Food analytical methods</subfield><subfield code="d">New York, NY : Springer, 2008</subfield><subfield code="g">12(2019), 9 vom: 04. Juni, Seite 1998-2008</subfield><subfield code="w">(DE-627)566007320</subfield><subfield code="w">(DE-600)2424728-5</subfield><subfield code="x">1936-976X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:12</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:9</subfield><subfield code="g">day:04</subfield><subfield code="g">month:06</subfield><subfield code="g">pages:1998-2008</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s12161-019-01554-z</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_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</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_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_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</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_60</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_63</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_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_101</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_636</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</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_2005</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_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</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_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</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_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2039</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2070</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2086</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2093</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2107</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2108</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2116</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2119</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2144</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2188</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2446</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2472</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2548</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_4037</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_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4246</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</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_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">12</subfield><subfield code="j">2019</subfield><subfield code="e">9</subfield><subfield code="b">04</subfield><subfield code="c">06</subfield><subfield code="h">1998-2008</subfield></datafield></record></collection>
|
| score |
7.400529 |