Modeling and Optimization of Artificial Neural Network and Response Surface Methodology in Ultra-high-Pressure Extraction of Artemisia argyi Levl. et Vant and its antifungal activity

Ni, Zheng; Chen, Feng; Wang, Zhaoyu; Lin, Jiantao

doi:10.1007/s12161-012-9439-x

Cited by 16 publications

(3 citation statements)

References 28 publications

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“…In the present study, all quadratic coefficients (β ii ) were the opposite of the corresponding linear coefficients (β i ). A similar phenomenon has been reported in previous studies on the optimization of HPAE conditions using RSM [ 32 , 33 ]. This result indicated that all factors had dual positive and negative effects on Pb removal efficiency.…”

Section: Resultssupporting

confidence: 87%

Optimization of High-Pressure-Assisted Extraction of Cadmium and Lead from Kelp (Laminaria japonica) Using Response Surface Methodology

Wang

Zhu

et al. 2022

Foods

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Kelp (Laminaria japonica) is a popular and nutritious sea vegetable, but it has a strong biosorption capacity for heavy metals. The high content of cadmium (Cd) and lead (Pb) is a threat to the quality of kelp. The objective of this study was to investigate the effects of high-pressure-assisted extraction (HPAE) conditions on Cd and Pb removal efficiency from kelp. Pressure intensity (0.1–200 MPa), the number of HPAE cycles (one to five) and acetic acid concentration (0–10%) were optimized using response surface methodology. The pressure intensity had the most significant positive effects on Cd and Pb removal efficiency, while the correlation between acetic acid concentration and removal efficiency was positive for Cd and negative for Pb. The optimum conditions for the removal of Cd and Pb were attained at 188 MPa, with four cycles and with an acetic acid concentration of 0%. At optimum conditions, the experimental values of removal efficiency were 61.14% (Cd) and 70.97% (Pb), and this was consistent with the predicted value, confirming the validity of the predictive model.

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Section: Resultssupporting

confidence: 87%

Optimization of High-Pressure-Assisted Extraction of Cadmium and Lead from Kelp (Laminaria japonica) Using Response Surface Methodology

Wang

Zhu

et al. 2022

Foods

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“…In our study, the decolorization rate of Rose Bengal dye of 0.18 g l −1 by A. niger TF05 reached 100% after 120 h, and the removal effect was enhanced. The factor method can quickly and screen the most significant factors and consequently avoid wasting experimental resources because too many factors or some factors are not significant in later optimization experiments [36,37]. The PBD is generally used with a central composite design (CCD) or a Box-Behnken design (BBD) in the response surface method (RSM) to obtain optimal values for significant factors and response surface graphs [38].…”

Section: Discussionmentioning

confidence: 99%

Optimization of the decolorization conditions of Rose Bengal by using Aspergillus niger TF05 and a decolorization mechanism

et al. 2022

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Aspergillus niger TF05 was applied to decolorize Rose Bengal dye. The effects of carbon source, nitrogen source, metal ion and spore concentration on Rose Bengal treatment with A. niger TF05 were studied. A Plackett–Burman design (PBD) and a uniform design (UD) were used to optimize the decolorization conditions of A. niger TF05 and enhance its decolorization effect. The mechanism of Rose Bengal decolorization by A. niger TF05 was examined by analysing degradation products via UV–visible light spectroscopy, IR spectroscopy and GC-MS. The best decolorization effect was achieved in the single factor test with glucose and ammonium chloride as carbon and nitrogen sources, respectively. Mg2+ was an essential ion that could improve the mould ball state and adsorption efficiency if the spore concentration was maintained at 106 spores ml–1. The optimal decolorization conditions obtained using the PBD and UD methods were 11.5 g l−1 glucose, 6.5 g l−1 ammonium chloride, 0.4 g l−1 magnesium sulphate, pH 5.8, 28 °C, 140 r.p.m. rotational speed, 0.18 g l−1 dye concentration, 0.5 ml of inocula and 120 h decolorization time. Under these conditions, the maximum decolorization rate was 106%. Spectral analysis suggested that the absorption peak of the product changed clearly after decolorization; GC-MS analysis revealed that the intermediate product tetrachlorophthalic anhydride formed after decolorization. The combined use of the PBD and UD methods can optimize multi-factor experiments. A. niger TF05 decolorized Rose Bengal during intracellular enzymatic degradation after adsorption.

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“…ANNs can use RSM experimental data to build an effective ANN model and literature data support models developed with RSM and ANNs based on the same design of experiment (DoE). These studies highlight how a neural network model can be successfully constructed using RSM experimental data, and the predictive capability of the ANN model can be better than that of the RSM [12,13].…”

Section: Introductionmentioning

confidence: 99%

Exploitation of Kiwi Juice Pomace for the Recovery of Natural Antioxidants through Microwave-Assisted Extraction

2020

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In a completely green approach to the exploitation of kiwi juice pomace (KP), a microwaved-assisted extraction (MAE) process was performed to extract antioxidant compounds present in KP, evaluating the influence of four independent process variables (temperature (T), extraction time (E), solvent composition (C), and solid-to-solvent ratio (R)) on the response of total phenolic content (TPC). The optimal conditions for the green extraction of total polyphenols from KP were obtained using a three-level fractional factorial design under response surface methodology (RSM) coupled with desirability optimization, and a feed-forward multilayered perceptron artificial neural network (ANN) with a back-propagation algorithm. Data were analyzed by ANOVA and fitted to a second-order polynomial equation using the regression method. Results showed that T was the most influential factor, followed by R and C, whereas the extraction time (E) was not shown to have a significant linear effect on the extraction yield of total polyphenols (TPs). The optimal conditions based on both individual and combinations of all responses were found out (T: 75 °C; E: 15 min; C: 50% ethanol:water; R: 1:15), and under these conditions the obtained extract showed both a high bioactive compound content and a high antioxidant potential, pointing out how this by-product could become an inexpensive source of compounds with high added value. A very good agreement was observed between experimental and calculated extraction yields, thus supporting the use of these models to quantitatively describe the recovery of natural antioxidants from KP. Finally, the ANN model exhibited more accurate prediction and better generalization capabilities than the RSM model (R2: 0.90 and 0.99, for RSM and ANN, respectively).

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Modeling and Optimization of Artificial Neural Network and Response Surface Methodology in Ultra-high-Pressure Extraction of Artemisia argyi Levl. et Vant and its antifungal activity

Cited by 16 publications

References 28 publications

Optimization of High-Pressure-Assisted Extraction of Cadmium and Lead from Kelp (Laminaria japonica) Using Response Surface Methodology

Optimization of High-Pressure-Assisted Extraction of Cadmium and Lead from Kelp (Laminaria japonica) Using Response Surface Methodology

Optimization of the decolorization conditions of Rose Bengal by using Aspergillus niger TF05 and a decolorization mechanism

Exploitation of Kiwi Juice Pomace for the Recovery of Natural Antioxidants through Microwave-Assisted Extraction

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