Ultrasound assisted extraction of phenolic compounds from P. lentiscus L. leaves: Comparative study of artificial neural network (ANN) versus degree of experiment for prediction ability of phenolic compounds recovery

Dahmoune, Farid; Remini, Hocine; Dairi, Sofiane; Aoun, Omar; Moussi, Kamal; Bouaoudia-Madi, Nadia; Adjeroud, Nawel; Kadri, Nabil; Lefsih, Khalef; Boughani, Lhadi; Mouni, Lotfi; Nayak, Balunkeswar; Madani, Khodir

doi:10.1016/j.indcrop.2015.08.062

Cited by 73 publications

(39 citation statements)

References 27 publications

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“…Denatured protein molecules will aggregate and/or crosslink to form larger clusters and, at high concentrations, will result in the formation of crosslinked amino acids such as lysinoalanine, ornithinoalanine, lanthionine and so on. In particular, ultrasound has been commercially used in different food science applications such as emulsification (Kara et al 2015), dispersion of solids (Pereira et al 2016), crystallization (Sheikh & Patel 2014), acceleration of mass transport processes in mixing (Ozuna et al 2013) and extraction (Dahmoune et al 2015;Kadam et al 2015). As a result, new safe and effective methods of food processing and preservation are being developed.…”

Section: Introductionmentioning

confidence: 99%

“…Acoustic waves can be applied to materials in the form of low intensity waves to passively monitor physical changes in the material caused by non-acoustic sources; or as high intensity waves where disruption of molecular entities or changes in the physicochemical characteristics of the materials are originated. In particular, ultrasound has been commercially used in different food science applications such as emulsification (Kara et al 2015), dispersion of solids (Pereira et al 2016), crystallization (Sheikh & Patel 2014), acceleration of mass transport processes in mixing (Ozuna et al 2013) and extraction (Dahmoune et al 2015;Kadam et al 2015). For the food industry, ultrasound technology could be of significant interest, as it allows 'green' chemistry to be conducted, that is conducting chemical reactions using environmentally benign solvents and reactants (Mahmoodi et al 2010).…”

Section: Introductionmentioning

confidence: 99%

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Optimization and physicochemical properties of nutritional protein isolate from pork liver with ultrasound‐assisted alkaline extraction

Zou

Bian

et al. 2017

Animal Science Journal

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The aim of this study was to investigate the optimal conditions of ultrasound-assisted alkaline extraction (UAAE) on pork liver protein isolate (UPLPI) and its physico-chemical properties. Response surface methodology was used to determine the optimal conditions for UAAE, which were at ultrasonic power 265 W, ultrasonic time 42 min, NaOH concentration 0.80%, temperature 50°C, and solvent/raw material ratio 70. The extraction yield and efficiency of UPLPI were significantly improved over the conventional alkaline extraction (PLPI). The results of amino acid composition showed that UAAE could increase serine (36.5 g/kg), arginine (38.1 g/kg), alanine (37.5 g/kg), proline (48.7 g/kg), phenylalanine (55.6 g/kg) and lysine (47.2 g/kg) elution amount. The changes in fourier transform infrared spectra indicated unfolding and destruction of the protein structure in UPLPI. The differential scanning calorimetry analysis presented UPLPI with a slightly lower onset and peak denaturation temperature over PLPI. Surface hydrophobicity increased and the microstructures presented larger and more pores of UPLPI, therefore, it had better in vitro digestibility than PLPI. Therefore, UPLPI might have a potential application prospect in the food field due to its changes on molecular structure as well as on the microstructure of protein by UAAE.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization and physicochemical properties of nutritional protein isolate from pork liver with ultrasound‐assisted alkaline extraction

Zou

Bian

et al. 2017

Animal Science Journal

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“…Besides that, ANNdoes not require standard experimental design to build a model like RSM model [12]. So, ANN-GA approach is more trustable, flexible and permits to add new experimental data.…”

Section: Optimization Using the Hybridartificial Neural Network-genetmentioning

confidence: 99%

“…The use of prediction techniques such as artificial neural network (ANN), fuzzy inference system (FIS), genetic programming (GP), and response surface methodology (RSM) were highlighted [11]. Several studies have attempted to compare an ANN and RSM model for evaluating, predicting, modeling, and simulating extraction using UAE on phenolic substances from safranin O (SO) substances [11] and P lenticus L. leaves [12]. ANN has high accuracy, generalization capability for the extraction model, and able to solve non-linearityform compared with RSM.…”

Section: Introductionmentioning

confidence: 99%

Ultrasound–assisted extraction optimization of phenolic compounds from Psidium guajava L. using artificial neural network-genetic algorithm

Amalia

Suryono

Suseno

et al. 2018

J. Phys.: Conf. Ser.

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“…These advantages include shorter time, less solvent, higher extraction yield, and lower cost. [21][22][23] However, to the best of our knowledge, there is yet no report on the ultrasound-assisted extraction of industrial waste, especially the ones that form a hydrophobic paste. We believe that ultrasound waves could help to disrupt the film formed by oils and wax and disperse the paste into many small particles, increasing the surface of interaction between plant matrix and the solvent, thus improving DHAA extraction efficiency.…”

Section: )mentioning

confidence: 99%

Isolation of Dihydroartemisinic Acid from <i>Artemisia annua</i> L. By-Product by Combining Ultrasound-Assisted Extraction with Response Surface Methodology

Liu

Ferreira

Liu

et al. 2017

CHEMICAL & PHARMACEUTICAL BULLETIN

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Malaria is the most devastating parasitic disease worldwide. Artemisinin is the only drug that can cure malaria that is resistant to quinine-derived drugs. After the commercial extraction of artemisinin from Artemisia annua, the recovery of dihydroartemisinic acid (DHAA) from artemisinin extraction by-product has the potential to increase artemisinin commercial yield. Here we describe the development and optimization of an ultrasound-assisted alkaline procedure for the extraction of DHAA from artemisinin production waste using response surface methodology. Our results using this methodology established that NaOH at 0.36%, extraction time of 67.96 min, liquid-solid ratio of 5.89, and ultrasonic power of 83.9 W were the optimal conditions to extract DHAA from artemisinin production waste. Under these optimal conditions, we achieved a DHAA yield of 2.7%. Finally, we conducted a validation experiment, and the results confirmed the prediction generated by the regression model developed in this study. This work provides a novel way to increase the production of artemisinin per cultivated area and to reduce artemisinin production costs by recycling its commercial waste to obtain DHAA, an immediate precursor of artemisinin. The use of this technology may reduce the costs of artemisinin-based antimalarial medicines.Key words dihydroartemisinic acid; ultrasound-assisted extraction; response surface; Artemisia annua L.; alkaline extraction; acid precipitation Malaria is one of the world's most important parasitic diseases, affects approximately 300-500 million people worldwide, and causes more than one million deaths per year (WHO: World Malaria Report 2015, http://www.who.int/ malaria/publications/world-malaria-report-2015/report/en/). 1)Artemisia annua, L. is currently the only commercial source of artemisinin, the raw material for the production of artemisinin combination therapies (ACTs). ACTs are the frontline and life-saving medicine to treat malaria where Plasmodium falciparum is endemic and resistant to quinine-derived medicines. ACTs cost between US$ 1.0 and 3.50 per treatment and can be required many times a year by people living in malaria-endemic areas. However, at the current cost ACTs are unaffordable for people living in economically-stricken countries, and who need it the most.2) Thus, it is of paramount importance and urgency to reduce the production costs of artemisinin-derived antimalarial medicines. One way to achieve this goal is by increasing artemisinin yield per cultivated area and by improving the extraction efficiency of artemisinin and its related compounds from leaves of A. annua. Although the production of one of the artemisinin precursors (artemisinic acid) in genetically-engineered yeast was developed, no economically feasible artemisinin product is yet available from this technology, and its predicted cost is higher than current market prices for plant-based artemisinin. The production of artemisinin in planta surpasses what can be achieved by microorganisms engineered to produce the precurs...

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Ultrasound assisted extraction of phenolic compounds from P. lentiscus L. leaves: Comparative study of artificial neural network (ANN) versus degree of experiment for prediction ability of phenolic compounds recovery

Cited by 73 publications

References 27 publications

Optimization and physicochemical properties of nutritional protein isolate from pork liver with ultrasound‐assisted alkaline extraction

Optimization and physicochemical properties of nutritional protein isolate from pork liver with ultrasound‐assisted alkaline extraction

Ultrasound–assisted extraction optimization of phenolic compounds from Psidium guajava L. using artificial neural network-genetic algorithm

Isolation of Dihydroartemisinic Acid from <i>Artemisia annua</i> L. By-Product by Combining Ultrasound-Assisted Extraction with Response Surface Methodology

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