Optimization of extraction yield and chemical characterization of optimal extract from Juglans nigra L. leaves
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2020
Authors
Rajković, Katarina MVasić, Marijana
Drobac, Milica
Mutić, Jelena
Jeremić, Sanja
Simić, Valentina
Stanković, Jovan
Article (Published version)
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The extraction yield of Juglans nigra L. leaves was assessed at different ethanol concen-trations (0–96% (v/v)) and solvent-to-solid ratios (5–20 kg kg−1). The response surfacemethodology (RSM) and artificial neural network with genetic algorithms (ANN-GA) weredeveloped to optimize the extraction variables. The RSM and ANN-GA models determined50% (v/v) ethanol concentration and 20 kg kg−1solvent-to-solid ratio as optimal conditions,ensuring an extraction yield of 27.69 and 27.19 g 100 g−1of dry leaves. The phenolic com-pounds in optimal extract were quantified: 3-O-caffeoylquinic acid (2.27 mg g−1of dry leaves),quercetin-3-O-galactoside (10.99 mg g−1of dry leaves) and quercetin-3-O-rhamnoside (15.07mg g−1of dry leaves) using high-performance liquid chromatography (HPLC). The mineralsin optimal extract were quantified: macro-elements (the relative order by content was: K> Mg > Ca) using inductively coupled plasma optical emission spectrometry (ICP-OES) andmicro-elements (the relative or...der by content was: Zn > Rb > Mn > I>Sr > Ni > Cu > Co >V > Ag > Se) using inductively coupled plasma mass spectrometry (ICP-MS). The extrac-tion coefficients for minerals were determined and were highest for K (64.3%) and I (53.5%).Optimization of extraction process resulted in high extraction yield from J. nigra leaves andoptimal extract containing different phytochemical compounds.
Keywords:
Artificial neural network / Juglans nigra / Minerals / Phenolic constituents / Response surface methodologySource:
Chemical Engineering Research and Design, 2020, 157, 25-33Publisher:
- Elsevier
Funding / projects:
- info:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/175034/RS (-175034)
- Signaling molecules in diabetes: search for potential targets in intrinsic pathways for prediction and intervention in diabetes (RS-173020)
- Investigation on the medicinal plants: morphological, chemical and pharmacological characterisation (RS-173021)
DOI: doi.org/10.1016/j.cherd.2020.03.002
ISSN: 0263-8762
WoS: 000528193200003
Scopus: 2-s2.0-85081647717
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Institution/Community
PharmacyTY - JOUR AU - Rajković, Katarina M AU - Vasić, Marijana AU - Drobac, Milica AU - Mutić, Jelena AU - Jeremić, Sanja AU - Simić, Valentina AU - Stanković, Jovan PY - 2020 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3604 AB - The extraction yield of Juglans nigra L. leaves was assessed at different ethanol concen-trations (0–96% (v/v)) and solvent-to-solid ratios (5–20 kg kg−1). The response surfacemethodology (RSM) and artificial neural network with genetic algorithms (ANN-GA) weredeveloped to optimize the extraction variables. The RSM and ANN-GA models determined50% (v/v) ethanol concentration and 20 kg kg−1solvent-to-solid ratio as optimal conditions,ensuring an extraction yield of 27.69 and 27.19 g 100 g−1of dry leaves. The phenolic com-pounds in optimal extract were quantified: 3-O-caffeoylquinic acid (2.27 mg g−1of dry leaves),quercetin-3-O-galactoside (10.99 mg g−1of dry leaves) and quercetin-3-O-rhamnoside (15.07mg g−1of dry leaves) using high-performance liquid chromatography (HPLC). The mineralsin optimal extract were quantified: macro-elements (the relative order by content was: K> Mg > Ca) using inductively coupled plasma optical emission spectrometry (ICP-OES) andmicro-elements (the relative order by content was: Zn > Rb > Mn > I>Sr > Ni > Cu > Co >V > Ag > Se) using inductively coupled plasma mass spectrometry (ICP-MS). The extrac-tion coefficients for minerals were determined and were highest for K (64.3%) and I (53.5%).Optimization of extraction process resulted in high extraction yield from J. nigra leaves andoptimal extract containing different phytochemical compounds. PB - Elsevier T2 - Chemical Engineering Research and Design T1 - Optimization of extraction yield and chemical characterization of optimal extract from Juglans nigra L. leaves VL - 157 SP - 25 EP - 33 DO - doi.org/10.1016/j.cherd.2020.03.002 ER -
@article{ author = "Rajković, Katarina M and Vasić, Marijana and Drobac, Milica and Mutić, Jelena and Jeremić, Sanja and Simić, Valentina and Stanković, Jovan", year = "2020", abstract = "The extraction yield of Juglans nigra L. leaves was assessed at different ethanol concen-trations (0–96% (v/v)) and solvent-to-solid ratios (5–20 kg kg−1). The response surfacemethodology (RSM) and artificial neural network with genetic algorithms (ANN-GA) weredeveloped to optimize the extraction variables. The RSM and ANN-GA models determined50% (v/v) ethanol concentration and 20 kg kg−1solvent-to-solid ratio as optimal conditions,ensuring an extraction yield of 27.69 and 27.19 g 100 g−1of dry leaves. The phenolic com-pounds in optimal extract were quantified: 3-O-caffeoylquinic acid (2.27 mg g−1of dry leaves),quercetin-3-O-galactoside (10.99 mg g−1of dry leaves) and quercetin-3-O-rhamnoside (15.07mg g−1of dry leaves) using high-performance liquid chromatography (HPLC). The mineralsin optimal extract were quantified: macro-elements (the relative order by content was: K> Mg > Ca) using inductively coupled plasma optical emission spectrometry (ICP-OES) andmicro-elements (the relative order by content was: Zn > Rb > Mn > I>Sr > Ni > Cu > Co >V > Ag > Se) using inductively coupled plasma mass spectrometry (ICP-MS). The extrac-tion coefficients for minerals were determined and were highest for K (64.3%) and I (53.5%).Optimization of extraction process resulted in high extraction yield from J. nigra leaves andoptimal extract containing different phytochemical compounds.", publisher = "Elsevier", journal = "Chemical Engineering Research and Design", title = "Optimization of extraction yield and chemical characterization of optimal extract from Juglans nigra L. leaves", volume = "157", pages = "25-33", doi = "doi.org/10.1016/j.cherd.2020.03.002" }
Rajković, K. M., Vasić, M., Drobac, M., Mutić, J., Jeremić, S., Simić, V.,& Stanković, J.. (2020). Optimization of extraction yield and chemical characterization of optimal extract from Juglans nigra L. leaves. in Chemical Engineering Research and Design Elsevier., 157, 25-33. https://doi.org/doi.org/10.1016/j.cherd.2020.03.002
Rajković KM, Vasić M, Drobac M, Mutić J, Jeremić S, Simić V, Stanković J. Optimization of extraction yield and chemical characterization of optimal extract from Juglans nigra L. leaves. in Chemical Engineering Research and Design. 2020;157:25-33. doi:doi.org/10.1016/j.cherd.2020.03.002 .
Rajković, Katarina M, Vasić, Marijana, Drobac, Milica, Mutić, Jelena, Jeremić, Sanja, Simić, Valentina, Stanković, Jovan, "Optimization of extraction yield and chemical characterization of optimal extract from Juglans nigra L. leaves" in Chemical Engineering Research and Design, 157 (2020):25-33, https://doi.org/doi.org/10.1016/j.cherd.2020.03.002 . .