The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water
Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Chanakya, H. N. [verfasserIn] Khuntia, Himanshu Kumar [verfasserIn] Mukherjee, Niranjan [verfasserIn] Aniruddha, R [verfasserIn] Mudakavi, J. R. [verfasserIn] Thimmaraju, Preeti [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Environmental monitoring and assessment - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981, 187(2015), 12 vom: 26. Nov. |
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| Übergeordnetes Werk: |
volume:187 ; year:2015 ; number:12 ; day:26 ; month:11 |
| Links: |
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| DOI / URN: |
10.1007/s10661-015-4991-7 |
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| Katalog-ID: |
SPR01226136X |
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| 245 | 1 | 4 | |a The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water |
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| 520 | |a Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. | ||
| 650 | 4 | |a Coconut industry |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Waste water |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Lipids |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Anaerobic digestion |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Volatile fatty acids |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Biomethane potential |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Modified Gompertz model |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Khuntia, Himanshu Kumar |e verfasserin |4 aut | |
| 700 | 1 | |a Mukherjee, Niranjan |e verfasserin |4 aut | |
| 700 | 1 | |a Aniruddha, R |e verfasserin |4 aut | |
| 700 | 1 | |a Mudakavi, J. R. |e verfasserin |4 aut | |
| 700 | 1 | |a Thimmaraju, Preeti |e verfasserin |4 aut | |
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10.1007/s10661-015-4991-7 doi (DE-627)SPR01226136X (SPR)s10661-015-4991-7-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Chanakya, H. N. verfasserin aut The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. Coconut industry (dpeaa)DE-He213 Waste water (dpeaa)DE-He213 Lipids (dpeaa)DE-He213 Anaerobic digestion (dpeaa)DE-He213 Volatile fatty acids (dpeaa)DE-He213 Biomethane potential (dpeaa)DE-He213 Modified Gompertz model (dpeaa)DE-He213 Khuntia, Himanshu Kumar verfasserin aut Mukherjee, Niranjan verfasserin aut Aniruddha, R verfasserin aut Mudakavi, J. R. verfasserin aut Thimmaraju, Preeti verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 187(2015), 12 vom: 26. Nov. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:187 year:2015 number:12 day:26 month:11 https://dx.doi.org/10.1007/s10661-015-4991-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 30.00 ASE 43.00 ASE AR 187 2015 12 26 11 |
| spelling |
10.1007/s10661-015-4991-7 doi (DE-627)SPR01226136X (SPR)s10661-015-4991-7-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Chanakya, H. N. verfasserin aut The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. Coconut industry (dpeaa)DE-He213 Waste water (dpeaa)DE-He213 Lipids (dpeaa)DE-He213 Anaerobic digestion (dpeaa)DE-He213 Volatile fatty acids (dpeaa)DE-He213 Biomethane potential (dpeaa)DE-He213 Modified Gompertz model (dpeaa)DE-He213 Khuntia, Himanshu Kumar verfasserin aut Mukherjee, Niranjan verfasserin aut Aniruddha, R verfasserin aut Mudakavi, J. R. verfasserin aut Thimmaraju, Preeti verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 187(2015), 12 vom: 26. Nov. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:187 year:2015 number:12 day:26 month:11 https://dx.doi.org/10.1007/s10661-015-4991-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 30.00 ASE 43.00 ASE AR 187 2015 12 26 11 |
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10.1007/s10661-015-4991-7 doi (DE-627)SPR01226136X (SPR)s10661-015-4991-7-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Chanakya, H. N. verfasserin aut The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. Coconut industry (dpeaa)DE-He213 Waste water (dpeaa)DE-He213 Lipids (dpeaa)DE-He213 Anaerobic digestion (dpeaa)DE-He213 Volatile fatty acids (dpeaa)DE-He213 Biomethane potential (dpeaa)DE-He213 Modified Gompertz model (dpeaa)DE-He213 Khuntia, Himanshu Kumar verfasserin aut Mukherjee, Niranjan verfasserin aut Aniruddha, R verfasserin aut Mudakavi, J. R. verfasserin aut Thimmaraju, Preeti verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 187(2015), 12 vom: 26. Nov. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:187 year:2015 number:12 day:26 month:11 https://dx.doi.org/10.1007/s10661-015-4991-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 30.00 ASE 43.00 ASE AR 187 2015 12 26 11 |
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10.1007/s10661-015-4991-7 doi (DE-627)SPR01226136X (SPR)s10661-015-4991-7-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Chanakya, H. N. verfasserin aut The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. Coconut industry (dpeaa)DE-He213 Waste water (dpeaa)DE-He213 Lipids (dpeaa)DE-He213 Anaerobic digestion (dpeaa)DE-He213 Volatile fatty acids (dpeaa)DE-He213 Biomethane potential (dpeaa)DE-He213 Modified Gompertz model (dpeaa)DE-He213 Khuntia, Himanshu Kumar verfasserin aut Mukherjee, Niranjan verfasserin aut Aniruddha, R verfasserin aut Mudakavi, J. R. verfasserin aut Thimmaraju, Preeti verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 187(2015), 12 vom: 26. Nov. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:187 year:2015 number:12 day:26 month:11 https://dx.doi.org/10.1007/s10661-015-4991-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 30.00 ASE 43.00 ASE AR 187 2015 12 26 11 |
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10.1007/s10661-015-4991-7 doi (DE-627)SPR01226136X (SPR)s10661-015-4991-7-e DE-627 ger DE-627 rakwb eng 333.7 ASE 30.00 bkl 43.00 bkl Chanakya, H. N. verfasserin aut The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. Coconut industry (dpeaa)DE-He213 Waste water (dpeaa)DE-He213 Lipids (dpeaa)DE-He213 Anaerobic digestion (dpeaa)DE-He213 Volatile fatty acids (dpeaa)DE-He213 Biomethane potential (dpeaa)DE-He213 Modified Gompertz model (dpeaa)DE-He213 Khuntia, Himanshu Kumar verfasserin aut Mukherjee, Niranjan verfasserin aut Aniruddha, R verfasserin aut Mudakavi, J. R. verfasserin aut Thimmaraju, Preeti verfasserin aut Enthalten in Environmental monitoring and assessment Dordrecht [u.a.] : Springer Science + Business Media B.V, 1981 187(2015), 12 vom: 26. Nov. (DE-627)31281738X (DE-600)2012242-1 1573-2959 nnns volume:187 year:2015 number:12 day:26 month:11 https://dx.doi.org/10.1007/s10661-015-4991-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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 30.00 ASE 43.00 ASE AR 187 2015 12 26 11 |
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Chanakya, H. N. @@aut@@ Khuntia, Himanshu Kumar @@aut@@ Mukherjee, Niranjan @@aut@@ Aniruddha, R @@aut@@ Mudakavi, J. R. @@aut@@ Thimmaraju, Preeti @@aut@@ |
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N.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="4"><subfield code="a">The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</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="520" ind1=" " ind2=" "><subfield code="a">Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. 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Chanakya, H. N. |
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Chanakya, H. N. ddc 333.7 bkl 30.00 bkl 43.00 misc Coconut industry misc Waste water misc Lipids misc Anaerobic digestion misc Volatile fatty acids misc Biomethane potential misc Modified Gompertz model The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water |
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333.7 ASE 30.00 bkl 43.00 bkl The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water Coconut industry (dpeaa)DE-He213 Waste water (dpeaa)DE-He213 Lipids (dpeaa)DE-He213 Anaerobic digestion (dpeaa)DE-He213 Volatile fatty acids (dpeaa)DE-He213 Biomethane potential (dpeaa)DE-He213 Modified Gompertz model (dpeaa)DE-He213 |
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ddc 333.7 bkl 30.00 bkl 43.00 misc Coconut industry misc Waste water misc Lipids misc Anaerobic digestion misc Volatile fatty acids misc Biomethane potential misc Modified Gompertz model |
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ddc 333.7 bkl 30.00 bkl 43.00 misc Coconut industry misc Waste water misc Lipids misc Anaerobic digestion misc Volatile fatty acids misc Biomethane potential misc Modified Gompertz model |
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The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water |
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The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water |
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Chanakya, H. N. |
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Environmental monitoring and assessment |
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Environmental monitoring and assessment |
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300 - Social sciences |
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2015 |
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Chanakya, H. N. Khuntia, Himanshu Kumar Mukherjee, Niranjan Aniruddha, R Mudakavi, J. R. Thimmaraju, Preeti |
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Chanakya, H. N. |
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10.1007/s10661-015-4991-7 |
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physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water |
| title_auth |
The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water |
| abstract |
Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. |
| abstractGer |
Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. |
| abstract_unstemmed |
Abstract Desiccated coconut industries (DCI) create various intermediates from fresh coconut kernel for cosmetic, pharmaceutical and food industries. The mechanized and non-mechanized DCI process between 10,000 and 100,000 nuts/day to discharge 6–150 $ m^{3} $ of malodorous waste water leading to a discharge of 264–6642 kg chemical oxygen demand (COD) daily. In these units, three main types of waste water streams are coconut kernel water, kernel wash water and virgin oil waste water. The effluent streams contain lipids (1–55 g/l), suspended solids (6–80 g/l) and volatile fatty acids (VFA) at concentrations that are inhibitory to anaerobic bacteria. Coconut water contributes to 20–50 % of the total volume and 50–60 % of the total organic loads and causes higher inhibition of anaerobic bacteria with an initial lag phase of 30 days. The lagooning method of treatment widely adopted failed to appreciably treat the waste water and often led to the accumulation of volatile fatty acids (propionic acid) along with long-chain unsaturated free fatty acids. Biogas generation during biological methane potential (BMP) assay required a 15-day adaptation time, and gas production occurred at low concentrations of coconut water while the other two streams did not appear to be inhibitory. The anaerobic bacteria can mineralize coconut lipids at concentrations of 175 mg/l; however; they are severely inhibited at a lipid level of ≥350 mg/g bacterial inoculum. The modified Gompertz model showed a good fit with the BMP data with a simple sigmoid pattern. However, it failed to fit experimental BMP data either possessing a longer lag phase and/or diauxic biogas production suggesting inhibition of anaerobic bacteria. |
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| title_short |
The physicochemical characteristics and anaerobic degradability of desiccated coconut industry waste water |
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https://dx.doi.org/10.1007/s10661-015-4991-7 |
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Khuntia, Himanshu Kumar Mukherjee, Niranjan Aniruddha, R Mudakavi, J. R. Thimmaraju, Preeti |
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| score |
7.399596 |