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Keywords = response surface methodology (RSM)

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34 pages, 10034 KiB  
Article
Effects of Pulsed Electric Fields on the Elimination of Fusarium oxysporum in Greenhouse Soil
by Jie Chen, Yingjian Sun, Qingliang Cui, Xiaojuan Hao, Zhenyu Liu and Guang Li
Agriculture 2024, 14(12), 2158; https://doi.org/10.3390/agriculture14122158 - 27 Nov 2024
Viewed by 211
Abstract
In greenhouses, high humidity, low light, and inadequate ventilation conditions, along with continuous and high-density planting, promote the proliferation of soilborne pathogens. Among these pathogens, Fusarium oxysporum Schltdl (F. oxysporum) is a notably challenging one, causing root rot of tomato plants [...] Read more.
In greenhouses, high humidity, low light, and inadequate ventilation conditions, along with continuous and high-density planting, promote the proliferation of soilborne pathogens. Among these pathogens, Fusarium oxysporum Schltdl (F. oxysporum) is a notably challenging one, causing root rot of tomato plants in greenhouse cultivation. To address this issue, this study applied a pulsed electric field (PEF) to target the elimination of F. oxysporum in suspension and soil media. Initially, PEF parameters were systematically explored in suspensions to determine the effective ranges for the elimination of F. oxysporum. The results revealed that the effective ranges for achieving the desired microbial reduction were an electric field strength (EFS) between 5–15 kV·cm−1, a pulse number within the range of 100–500, and a pulse width of 10–20 µs. Subsequently, the impact of soil moisture content, soil bulk density, and soil type on soil dielectric breakdown field strength was analyzed within the range from previous results. Based on these findings, the soil experiments were conducted with parameters designed to prevent dielectric breakdown. Specifically, for sampling soil with a moisture content of 16.2% and a bulk density of 1.31 g·cm−3, the maximum effective application of electric field strength was 9.5 kV·cm−1, accompanied by 1000 pulses and a pulse width of 20 µs. Finally, building on these results, soil samples were sterilized within a parameter range that spanned an electric field strength of 5–9.5 kV·cm−1, a pulse number between 100–500, and a pulse width of 10–20 µs. Response surface methodology (RSM) analysis further identified the optimal parameter combination: an electric field strength of 8.2 kV·cm−1, 306 pulses, and a pulse width of 15 µs, resulting in an average lethal rate of 76.16% for F. oxysporum sterilization in soil. These findings suggest the potential use of PEF against F. oxysporum and other pathogens in greenhouse soils, and provide theoretical foundations for further experiments, thereby contributing to the sustainable advancement of greenhouse agriculture. Full article
(This article belongs to the Section Agricultural Soils)
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Figure 1
<p>Experiment design flowchart.</p>
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<p>Effect of PEF treatment on the lethality of <span class="html-italic">F. oxysporum</span> in suspension; (<b>a</b>) concentration of <span class="html-italic">F. oxysporum</span> after PEF treatments with an EFS ranging from 5 to 30 kV·cm<sup>−1</sup>, with inc. of 5 kV·cm<sup>−1</sup>; (<b>b</b>) linear regression analysis of electric field strength and <span class="html-italic">Log</span><sub>10</sub> value of survival rate of <span class="html-italic">F. oxysporum</span>, with a confidence level of 95% (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect parameters of PEF treatment on the lethality of <span class="html-italic">F. oxysporum</span> in suspension, (<b>a</b>) Lethal rate of <span class="html-italic">F. oxysporum</span> after PEF treatments with pulse counts ranging from 100 to 1000 under an EFS of 7, 8, and 9 kV·cm<sup>−1</sup>, with inc. of 100 pulses; (<b>b</b>) Pearson correlation coefficient heatmap of EFS, pulse counts, and lethal rate of <span class="html-italic">F. oxysporum</span>; (<b>c</b>) linear regression analysis of pulse counts and <span class="html-italic">Log</span><sub>10</sub> of survival rate; (<b>d</b>) the impact of pulse width on sterilization efficacy from 10 to 30 µs, with a confidence level of 95% (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Impact of soil moisture content on the soil dielectric breakdown strength; (<b>a</b>) soil breakdown strength with soil moisture content ranging from 0 to 30%, with inc. of 5%; (<b>b</b>) average soil break strength and electric field strength maintained in soil after dielectric breakdown with different soil moisture content; (<b>c</b>) maximum pulse width under maximum electric field strength maintained in soil with different soil moisture content; (<b>d</b>) a Pearson correlation heatmap illustrating the relationship between soil moisture content, average breakdown strength, median breakdown strength, soil field strength after breakdown, and the maximum pulse width when breakdown does not occur, where A is soil moisture content, B is average soil breakdown strength (kV·cm<sup>−1</sup>), C is median soil breakdown strength, D is soil EFS after breakdown, and E represents the maximum pulse width that can be utilized without causing soil dielectric breakdown.</p>
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<p>Quadratic regression analysis of soil dielectric breakdown strength at different moisture contents; (<b>a</b>) average soil breakdown strength; (<b>b</b>) median soil breakdown strength.</p>
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<p>Impact of soil bulk density on the dielectric breakdown strength of soil; (<b>a</b>) soil breakdown strength with soil bulk density ranging from 1 to 2.2 g·cm<sup>−3</sup>, with inc. of 0.3 g·cm<sup>−3</sup>; (<b>b</b>) quadratic regression analysis of average soil dielectric breakdown strength at different soil bulk density levels.</p>
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<p>Impact of different proportions of matrix soil added on dielectric breakdown strength of soil; (<b>a</b>) soil breakdown strength with proportions of matrix soil ranging from 0 to 100%; (<b>b</b>) polynomial regression analysis of average and median soil dielectric breakdown strength with different proportions of matrix soil in samples.</p>
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<p>Effect of PEF treatment on the lethality of <span class="html-italic">F. oxysporum</span> in soil; (<b>a</b>) lethal rate of <span class="html-italic">F. oxysporum</span> after PEF treatments with EFS ranging from 5 to 9.5 kV·cm<sup>−1</sup>, with inc. of 0.5 kV·cm<sup>−1</sup>, in different media; (<b>b</b>) polynomial regression of lethal rate of <span class="html-italic">F. oxysporum</span> under different electric field strengths from 5 to 9.5 kV·cm<sup>−1</sup> in suspension and soil; (<b>c</b>) linear regression of Log<sub>10</sub> of survival rate of <span class="html-italic">F. oxysporum</span> under different electric field strengths from 5 to 9.5 kV·cm<sup>−1</sup> in suspension; (<b>d</b>) linear regression of <span class="html-italic">Log<sub>10</sub></span> survival rate of <span class="html-italic">F. oxysporum</span> under different electric field strengths from 5 to 9.5 kV·cm<sup>−1</sup> in soil.</p>
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<p>Effects of pulse number and pulse width on <span class="html-italic">F. oxysporum</span> sterilization in soil; (<b>a</b>) lethal rate of <span class="html-italic">F. oxysporum</span> treated by varied pulse number under pulse width from 10–20 µs, with inc. of 2 µs; (<b>b</b>) lethal rate of <span class="html-italic">F. oxysporum</span> treated by varied pulse width under 100–600 pulses, with inc. of 100 pulses.</p>
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<p>RSM analysis results of orthogonal experiment. R1 represents lethal rate of <span class="html-italic">F. oxysporum</span>; (<b>a<sub>1</sub></b>–<b>a<sub>3</sub></b>) response surface plots of the effects of number of pulses B and pulse with C on lethal rate of <span class="html-italic">F. oxysporum</span>, with levels of −0.1, 0, and 1 for electric field strength A; (<b>b<sub>1</sub></b>–<b>b<sub>3</sub></b>) surface plots of the effects of electric field strength and pulse with on sterilization rate, level of pulse count are −1, 0, and 1; (<b>c<sub>1</sub></b>–<b>c<sub>3</sub></b>) surface plots of the effects of electric field strength and number of pulses on lethal rates of <span class="html-italic">F. oxysporum</span>, with levels of pulse width −1, 0, and 1; (<b>d<sub>1</sub></b>–<b>d<sub>3</sub></b>) represent the contour lines when A = 0.2, B = 0.03, and C = 0, respectively.</p>
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<p>RSM analysis results of orthogonal experiment. R1 represents lethal rate of <span class="html-italic">F. oxysporum</span>; (<b>a<sub>1</sub></b>–<b>a<sub>3</sub></b>) response surface plots of the effects of number of pulses B and pulse with C on lethal rate of <span class="html-italic">F. oxysporum</span>, with levels of −0.1, 0, and 1 for electric field strength A; (<b>b<sub>1</sub></b>–<b>b<sub>3</sub></b>) surface plots of the effects of electric field strength and pulse with on sterilization rate, level of pulse count are −1, 0, and 1; (<b>c<sub>1</sub></b>–<b>c<sub>3</sub></b>) surface plots of the effects of electric field strength and number of pulses on lethal rates of <span class="html-italic">F. oxysporum</span>, with levels of pulse width −1, 0, and 1; (<b>d<sub>1</sub></b>–<b>d<sub>3</sub></b>) represent the contour lines when A = 0.2, B = 0.03, and C = 0, respectively.</p>
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<p>Plate cultivation of <span class="html-italic">F. oxysporum</span> at 25 °C for 5 days after treatment with PEF, where a and b represent suspension and soil; (CK) control group of untreated samples; (<b>a<sub>1</sub></b>) treated by 5 kV·cm<sup>−1</sup>, 20 µs, and 100 pulses; (<b>a<sub>2</sub></b>) treated by 9 kV·cm<sup>−1</sup>, 20 µs, and 100 pulses; (<b>a<sub>3</sub></b>) treated by 15 kV·cm<sup>−1</sup>, 10 µs, and 300 pulses; (<b>a<sub>4</sub></b>) treated by 25 kV·cm<sup>−1</sup>, 20 µs, and 100 pulses; (<b>b<sub>1</sub></b>) treated by 5 kV·cm<sup>−1</sup>, 20 µs, and 100 pulses; (<b>b<sub>2</sub></b>) treated by 7 kV·cm<sup>−1</sup>, 10 µs, and 300 pulses; (<b>b<sub>3</sub></b>) treated by 9 kV·cm<sup>−1</sup>, 20 µs, and 100 pulses; (<b>b<sub>4</sub></b>) treated by 8.2 kV·cm<sup>−1</sup>, 15 µs, and 306 pulses.</p>
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15 pages, 3908 KiB  
Article
Mechanism and Experimental Study on the Recovery of Rare Earth Elements from Neodymium Iron Boron Waste Using the ZnF2 Fluorination Method
by Youwei Liu, Yuan Zhong, Xiang Lei and Jinliang Wang
Materials 2024, 17(23), 5807; https://doi.org/10.3390/ma17235807 - 27 Nov 2024
Viewed by 231
Abstract
We conducted a mechanistic and experimental study on zinc fluoride roasting for the recovery of NdFeB waste to address the difficulties faced during this pyrometallurgical recovery process, such as the high dependence on the quality of raw materials, the high energy consumption involved [...] Read more.
We conducted a mechanistic and experimental study on zinc fluoride roasting for the recovery of NdFeB waste to address the difficulties faced during this pyrometallurgical recovery process, such as the high dependence on the quality of raw materials, the high energy consumption involved in roasting transformations, and the low added value of mixed rare earth products. Thermodynamic calculations showed the feasibility of fluorinating rare earths in NdFeB waste, and one-factor experiments were performed. The results showed that at a roasting temperature of 850 °C, a reaction time of 90 min, and 100% ZnF2 addition, the fluorination rate of rare earths could reach 95.69%. In addition, after analyzing the mesophase composition of a clinker under different roasting temperature conditions, it was found that, when the roasting temperature exceeded 850 °C, the fluorination rate of rare earths was reduced, which was consistent with the thermodynamic results. On this basis, response surface methodology (RSM) was used to carry out experiments to investigate in depth the effects of various factors and their interactions on the fluorination rate of rare earths, which provides a sufficient experimental basis for the recovery of NdFeB waste via fluorination roasting. The results of this study show that ZnF2 addition had the greatest influence on the rare earth fluorination reaction, followed by roasting temperature and roasting time. According to the optimization results of the model, the optimal roasting conditions were determined as follows: 119% ZnF2 addition at 828 °C, a roasting time of 91 min, and a rare earth element fluorination rate of 97.29%. The purity of the mixed fluorinated rare earths was as high as 98.92% after leaching the roasted clinker with 9 M hydrochloric acid at a leaching temperature of 80 °C, a liquid–solid ratio of 4 mL/g, and a leaching time of 2.5 h. This study will lay the foundation for promoting the application of pyrometallurgical technology in the recycling of NdFeB waste. Full article
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<p>XRD pattern of NdFeB waste.</p>
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<p>Plot of the reaction <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="sans-serif">Δ</mi> <mi>G</mi> </mrow> <mrow> <mi>T</mi> </mrow> <mrow> <mi>θ</mi> </mrow> </msubsup> </mrow> </semantics></math> versus T for the roasting process.</p>
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<p>(<b>a</b>) Effect of the ZnF<sub>2</sub>-to-raw material mass ratio on rare earth element fluorination rate; (<b>b</b>) XRD spectra of the clinker with different ZnF<sub>2</sub> dosages.</p>
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<p>(<b>a</b>) Effect of roasting temperature on rare earth element fluorination rate; (<b>b</b>) XRD spectra of the clinker with different roasting temperatures.</p>
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<p>(<b>a</b>) Effect of roasting time on leaching; (<b>b</b>) XRD spectra of the clinker with different roasting times.</p>
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<p>Comparison between predicted and actual values of rare earth element fluorination rates.</p>
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<p>Surface plot of the response of the interaction between different factors on the rare earth element fluorination rate: (<b>a</b>) roasting temperature and roasting time, (<b>b</b>) roasting temperature and mass ratio of ZnF<sub>2</sub> to raw material, and (<b>c</b>) mass ratio of ZnF<sub>2</sub> to raw material and roasting time.</p>
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<p>XRD graph of leached products.</p>
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<p>Scanning electron microscope images of the leachate product at different scales: (<b>a</b>) 1 µm; (<b>b</b>) 500 nm; (<b>c</b>) 200 nm; (<b>d</b>) 100 nm.</p>
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<p>Process flow for recovering rare earths from NdFeB waste through the fluorination reaction.</p>
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16 pages, 4499 KiB  
Article
Preparation of PLA Nanoparticles and Study of Their Influencing Factors
by Xinyu Zhang, Qing Luo, Fengying Zhang, Xinye Zhao, Ying Li, Ning Yang and Liangshan Feng
Molecules 2024, 29(23), 5566; https://doi.org/10.3390/molecules29235566 - 25 Nov 2024
Viewed by 262
Abstract
Nanoparticles (NPs) have attractive properties that have received impressive consideration in the last few decades. Polylactic acid nanoparticles (PLA-NPs) stand out as a biodegradable polyester with excellent biocompatibility. This investigation introduces PLA-NPs prepared by using the emulsification-solvent volatilization (O/W) method. The effects of [...] Read more.
Nanoparticles (NPs) have attractive properties that have received impressive consideration in the last few decades. Polylactic acid nanoparticles (PLA-NPs) stand out as a biodegradable polyester with excellent biocompatibility. This investigation introduces PLA-NPs prepared by using the emulsification-solvent volatilization (O/W) method. The effects of ultrasonication time, organic-to-aqueous phase volume ratio, surfactant Tween-20, and PLA on particle size as well as the polydispersity index (PDI) were investigated using a one-factor combination with Response Surface Methodology (RSM). The result indicates that, on the one hand, PLA was the key factor affecting particle size, which gradually increased as the amount of PLA increased from 0.01 to 0.1 g. The particle size of NPs gradually decreased as the surfactant Tween-20 increased from 0.25 mL to 1 mL in the aqueous phase. The volume ratio of the organic phase to the aqueous phase increased from 1:10 to 1:1, with the particle size initially decreasing (from 1:10 to 1:5) and subsequently increasing (from 1:5 to 1:1). As the ultrasonication time increased from 20 min to 40 min, the particle size initially increased (from 25 to 30 min) and then decreased (from 30 to 40 min). On the other hand, Tween-20 was the main factor of PDI, and with the increase of Tween-20, PDI changed significantly and increased rapidly. The volume ratio of the organic phase to the aqueous phase increased from 1:10 to 1:1, resulting in the stabilization and subsequent gradual decrease of the PDI. With the increase of ultrasonication time (20–40 min), PDI tended to be stable after the increase. The effect of PLA on PDI was not significant, and the change of PLA concentration did not cause a significant change in the size of PDI. Full article
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<p>Optimization of PLA-NPs and PDI one-factor conditions.</p>
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<p>A diagram of the protocol carried out step by step.</p>
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<p>RSM (<b>a</b>) shows the relationship between average particle size and PLA, (<b>b</b>) Tween-20, (<b>c</b>) organic phase to aqueous phase volume.</p>
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<p>RSM (<b>a</b>) relationship between PDI and PLA, (<b>b</b>) relationship between PDI and Tween-20, (<b>c</b>) relationship between PDI and organic phase to aqueous phase volume.</p>
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<p>10 k- and 5 k-times SEM images of PLA with different particle sizes: (<b>a</b>) 50 nm PLA, (<b>b</b>) 100 nm PLA, (<b>c</b>) 200 nm PLA.</p>
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<p>Histogram of particle size distribution of PLA-NPs: (<b>a</b>) 50 nm PLA, (<b>b</b>) 100 nm PLA, (<b>c</b>) 200 nm PLA.</p>
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<p>FT-IR plots of PLA particles with different particle sizes.</p>
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15 pages, 3618 KiB  
Article
Mathematical Modeling and Optimization of Seed Distribution Uniformity in Planting of Sage Seeds Using a Micro-Granular Applicator
by Gulin Turkusay and Arzu Yazgi
Appl. Sci. 2024, 14(23), 10910; https://doi.org/10.3390/app142310910 - 25 Nov 2024
Viewed by 275
Abstract
The objective of this study was to determine the seed flow characteristics and in-row seed distribution uniformity under different operating conditions to develop mathematical models and to optimize the seed distribution uniformity in the seeding of sage seeds by a micro-granule applicator equipped [...] Read more.
The objective of this study was to determine the seed flow characteristics and in-row seed distribution uniformity under different operating conditions to develop mathematical models and to optimize the seed distribution uniformity in the seeding of sage seeds by a micro-granule applicator equipped with a conveyor belt seed-metering unit. In this study, weighing tests were used to determine the seed flow characteristics, while sticky belt tests were used to determine the in-row seed distribution uniformity. While the evaluations of flow uniformity were carried out depending on the coefficient of variation values (CVs), in-row seed distribution uniformity evaluations were carried out using the values of the variation factor (Vf) and goodness criterion (λ). Central Composite Design (CCD) was used as the experimental design. Based on the analysis of data obtained from the experiments, the polynomial functions were developed for Vf and λ values and the models were optimized. The forward speed was determined as 2.14 m s−1, the seed rate was 13.9 kg ha−1, and the seed falling angle was 42.73° for the Vf model, while these values were determined as 2.43 m s−1, 14.7 kg ha−1, and 33.11°, respectively, for the λ model. All these findings reveal that the metering unit equipped with conveyor belt could be used for the seeding of sage seeds successfully. Data and information found in this work would have great potential to be used as a guide for farmers, manufacturers, and scientists who work in such areas. Full article
(This article belongs to the Section Agricultural Science and Technology)
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<p>Micro-granule applicator equipped with a conveyor belt seed-metering unit.</p>
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<p>Experimental test stands.</p>
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<p>Seed rate-setting mechanism.</p>
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<p>Seed rate variation based on scale value.</p>
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<p>Variation factor (V<sub>f</sub>) as a function of coded values of forward speed (X<sub>1</sub>), seed rate (X<sub>2</sub>), and seed falling angle (X<sub>3</sub>). (<b>a</b>) V<sub>f</sub> as a function of coded X<sub>2</sub> and coded X<sub>3</sub> (coded X<sub>1</sub>: 0.1902). (<b>b</b>) V<sub>f</sub> as a function of coded X<sub>1</sub> and coded X<sub>3</sub> (coded X<sub>2</sub>: −0.2109). (<b>c</b>) V<sub>f</sub> as a function of coded X<sub>1</sub> and coded X<sub>2</sub> (coded X<sub>3</sub>: 0.3865).</p>
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<p>Goodness criteria (λ) as a function of coded values of forward speed (X<sub>1</sub>), seed rate (X<sub>2</sub>), and seed falling angle (X<sub>3</sub>). (<b>a</b>) λ as a function of coded X<sub>2</sub> and coded X<sub>3</sub> (coded X<sub>1</sub>: 0.7082). (<b>b</b>) λ as a function of coded X<sub>1</sub> and coded X<sub>3</sub> (coded X<sub>2</sub>: −0.0569). (<b>c</b>) λ as a function of coded X<sub>1</sub> and coded X<sub>2</sub> (coded X<sub>3</sub>: −0.0942).</p>
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<p>Sensitivity analysis of the V<sub>f</sub> and λ models.</p>
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20 pages, 1906 KiB  
Article
Optimization of the Microwave-Assisted Extraction Conditions for Phenolic Compounds from Date Seeds
by Asma Khalfi, María Carmen Garrigós, Marina Ramos and Alfonso Jiménez
Foods 2024, 13(23), 3771; https://doi.org/10.3390/foods13233771 - 25 Nov 2024
Viewed by 425
Abstract
Date seeds, often discarded during industrial processing, are an underexploited by-product rich in polyphenols with significant antioxidant potential. This study explores the extraction of polyphenols from date seeds using microwave-assisted extraction (MAE) with an organic solvent. The extraction process was optimized using response [...] Read more.
Date seeds, often discarded during industrial processing, are an underexploited by-product rich in polyphenols with significant antioxidant potential. This study explores the extraction of polyphenols from date seeds using microwave-assisted extraction (MAE) with an organic solvent. The extraction process was optimized using response surface methodology (RSM), focusing on extraction time, ethanol concentration, and temperature. The optimal extraction conditions were 46% (v/v) of ethanol, at 62 °C and for 27.3 min. Under these optimized conditions, the extraction yield and total phenolic content of the extract are 12.5% and 59 mg gallic acid equivalent g−1 of date seed, respectively, as confirmed by the experimental tests. The extract’s antioxidant activity was confirmed through DPPH, ABTS, and FRAP assays. High-performance liquid chromatography with diode–array detection (HPLC–DAD) identified major phenolic compounds, including procyanidin B1, catechin, quercetin-3,5′-di-O-glucoside, epicatechin, procyanidin B, and syringic acid, alongside eight other tentatively identified compounds. These findings underscore the potential of MAE as an environmentally friendly technique for producing polyphenol-rich extracts from date seeds, adding value to this by-product and opening avenues for its application in food and nutritional products. Full article
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<p>TG (blue) and DTG (orange) curves of DSP.</p>
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<p>Response surface plot of significant interactions between independent variables on yield (% of ethanol concentration vs. time).</p>
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<p>Response surface plot of significant interactions between independent variables on TPC (% of ethanol concentration vs. time).</p>
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<p>(<b>a</b>) TGA (blue) and DTG (orange) curves from EX<sub>poly</sub> and (<b>b</b>) TPC in date seed extracts treated at different temperatures.</p>
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<p>Chromatogram and chemical structures of the six identified compounds by HPLC–MS in EXpoly. (<b>1</b>) Procyanidin B1; (<b>2</b>) catechin; (<b>3</b>) syringic acid; (<b>4</b>) procyanidin B2; (<b>5</b>) epicatechin; (<b>6</b>) quercetin-3,5′-di-<span class="html-italic">O</span>-glucoside.</p>
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19 pages, 4616 KiB  
Article
Optimization of Vacuum Impregnation with Aqueous Extract from Hibiscus sabdariffa Calyces in Apple Slices by Response Surface Methodology: Effect on Soluble Phenols, Flavonoids, Antioxidant Activity, and Physicochemical Parameters
by Luis Miguel Anaya-Esparza, Ernesto Rodríguez-Lafitte, Zuamí Villagrán, Edward F. Aurora-Vigo, José Martín Ruvalcaba-Gómez, Walter Bernardo Símpalo-López, Fernando Martínez-Esquivias and Cristhian Henry Sarango-Córdova
Appl. Sci. 2024, 14(23), 10850; https://doi.org/10.3390/app142310850 - 23 Nov 2024
Viewed by 303
Abstract
Vacuum impregnation (VI) of natural extracts is often used as a pretreatment for fruit dehydration. Apple slices were subjected to VI [XVP: vacuum pressure (−0.4 to −0.2 mbar), XIT: impregnation time (2–10 min), and XRT: restoration time [...] Read more.
Vacuum impregnation (VI) of natural extracts is often used as a pretreatment for fruit dehydration. Apple slices were subjected to VI [XVP: vacuum pressure (−0.4 to −0.2 mbar), XIT: impregnation time (2–10 min), and XRT: restoration time (1–3 min)] of Hibiscus sabdariffa (HS) calyces aqueous extract and optimized using response surface methodology (RSM). Total soluble phenols (TSP) and flavonoids, antioxidant capacity, and physicochemical parameters were evaluated before and after vacuum impregnation. Also, optimized VI apple slices were heat air-dried and characterized for all the mentioned parameters. Under the experimental conditions, all vacuum-impregnated apple slices increased in TSP content, with impregnation time, restoration time, and the interaction between impregnation time and vacuum pressure being the key factors. According to RSM, the optimal VI conditions for TSP (R2 = 0.99) were XVP −0.4 bar, XIT: 6.73 min, and XRT 3 min. VI also improved flavonoid and antioxidant activities (DPPH and ABTS) of apple slices and promoted changes in total soluble solids, pH, titratable acidity, water activity, moisture, and color (luminosity, a*, and b*) parameters. Additionally, vacuum-impregnated apple slices (under optimized conditions) were further dehydrated, resulting in an increase in soluble phenols, flavonoids, and antioxidant activity. VI with HS extract is an effective alternative for developing dehydrated apple slices with an increase in antioxidant compounds. Full article
(This article belongs to the Special Issue Natural Products and Bioactive Compounds)
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<p>Visual appearance of fresh apple slices before (C+) and after vacuum impregnation (T1–T15) of aqueous extract from <span class="html-italic">Hibiscus sabdariffa</span> calyces.</p>
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<p>Response surface plots indicating the vacuum impregnation effect on the soluble phenols content, using −0.2 bar (<b>A</b>), −0.3 bar (<b>B</b>), and −0.4 bar (<b>C</b>) of vacuum pressure, and Pareto Chart (<b>D</b>). <span class="html-italic">X<sub>IT</sub></span>: Impregnation time; <span class="html-italic">X<sub>RT</sub></span>: Restoration time, and <span class="html-italic">X<sub>VP</sub></span>: Vacuum pressure.</p>
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<p>Optimization (<b>A</b>) and desirability (<b>B</b>) profiles of vacuum-impregnated soluble phenols from <span class="html-italic">H. sabdariffa</span> aqueous extracts in apple slices. The red lines in the figure indicate the optimal vacuum impregnation conditions for each predictor.</p>
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<p>Visual appearance of apple slices before and after vacuum impregnation of aqueous extract of <span class="html-italic">Hibiscus sabdariffa</span> calyces (<b>A</b>,<b>B</b>), and before and after dehydration (<b>C</b>,<b>D</b>).</p>
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30 pages, 14383 KiB  
Article
Experimental Study on Preparation of Nano ZnO by Hydrodynamic Cavitation-Enhanced Carbonization Method and Response Surface Optimization
by Jinyuan Guo, Honglei Yu, Dexi Wang, Gong Chen, Lin Fan and Hanshuo Yang
Processes 2024, 12(11), 2601; https://doi.org/10.3390/pr12112601 - 19 Nov 2024
Viewed by 443
Abstract
The carbonization method for preparing Nano ZnO is characterized by its simplicity, ease of reaction control, high product purity, environmental friendliness, and potential for CO2 recycling. However, traditional carbonization processes suffer from poor heat and mass transfer, leading to in situ growth [...] Read more.
The carbonization method for preparing Nano ZnO is characterized by its simplicity, ease of reaction control, high product purity, environmental friendliness, and potential for CO2 recycling. However, traditional carbonization processes suffer from poor heat and mass transfer, leading to in situ growth and agglomeration, resulting in low carbonization efficiency, small specific surface area, and inferior product performance. To enhance micro-mixing and mass transfer efficiency, ZnO derived from zinc ash calcination was used as the raw material, and hydrodynamic cavitation technology was employed to intensify the carbonization reaction process. The reaction mechanism of hydrodynamic cavitation was analyzed, and a single-factor experimental study investigated the effects of reaction time, reaction temperature, solid–liquid ratio, calcination temperature, incident angle, cavitation number, and position height on the specific surface area and carbonization rate of Nano ZnO. The response surface method was utilized to explore the significance of the three most influential factors—solid–liquid ratio, cavitation number, and position height—on the carbonization rate and specific surface area. The products were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), laser particle size analysis, and specific surface area analysis. The results showed that the optimal process parameters were a reaction temperature of 80 °C, a reaction time of 120 min, a solid–liquid ratio of 5.011:100, a calcination temperature of 500 °C for 1 h, an incident angle of 60°, a cavitation number of 0.366, and a position height of 301.128 mm. The interaction between solid–liquid ratio and position height significantly influenced the process parameter variations. Under these conditions, the specific surface area and carbonization rate were 63.190 m2/g and 94.623%, respectively. The carbonized product was flaky Nano ZnO with good dispersion and small particle size. Compared to traditional mechanical stirring and bubbling methods, the specific surface area increased by 1.5 times, the carbonization rate improved by 10%, and the particle size decreased by half, significantly enhancing the product performance. Full article
(This article belongs to the Section Materials Processes)
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<p>Hydrodynamic cavitation-enhanced ZnO carbonation reaction experimental apparatus.</p>
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<p>Schematic diagram of hydrodynamic cavitation reactor structure (α is the inlet angle, β (40°) is the outlet cone angle, L (10 mm) is the throat length, d<sub>0</sub> is the throat diameter, d<sub>1</sub> (20 mm) is the inlet diameter, d<sub>2</sub> (20 mm) is the outlet diameter, d<sub>3</sub> (15 mm) is the carbon dioxide gas inlet diameter).</p>
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<p>Process flow chart for preparing Nano ZnO.</p>
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<p>Thermogravimetric curve.</p>
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<p>(<b>a</b>) XRD of Zn<sub>5</sub>(CO<sub>3</sub>)<sub>2</sub>(OH)<sub>6</sub>; (<b>b</b>) Raman spectrum of Zn<sub>5</sub>(CO<sub>3</sub>)<sub>2</sub>(OH)<sub>6</sub>.</p>
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<p>(<b>a</b>) XRD of Zn<sub>5</sub>(CO<sub>3</sub>)<sub>2</sub>(OH)<sub>6</sub>; (<b>b</b>) Raman spectrum of Zn<sub>5</sub>(CO<sub>3</sub>)<sub>2</sub>(OH)<sub>6</sub>.</p>
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<p>Effect of reaction time on specific surface area and carbonization ratio of Nano ZnO.</p>
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<p>Effect of reaction temperature on specific surface area and carbonization ratio of Nano ZnO.</p>
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<p>Effects of solid–liquid ratio on specific surface area and carbonization ratio of Nano ZnO.</p>
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<p>Effect of calcination temperature on specific surface area and carbonization ratio of Nano ZnO.</p>
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<p>Effect of incident angle on specific surface area and carbonization ratio of Nano ZnO.</p>
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<p>Effect of cavitation number on specific surface area and carbonization ratio of Nano ZnO.</p>
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<p>Effects of different position heights on specific surface area and carbonization ratio of Nano ZnO.</p>
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<p>Schematic diagram of nucleation and growth of basic zinc carbonate.</p>
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<p>Hydraulic cavitation strengthens carbonization mechanism.</p>
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<p>(<b>a</b>) Formation of basic zinc carbonate by hydro-cavitation-enhanced carbonization; (<b>b</b>) particle size distribution graph of basic zinc carbonate.</p>
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<p>Residual normal distribution diagram. (<b>a</b>) BET; (<b>b</b>) Φ.</p>
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<p>Scatter plot between residuals and predicted values. (<b>a</b>) BET; (<b>b</b>) Φ.</p>
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<p>Influence of interaction of three factors on specific surface area of BET. (<b>a</b>) AB; (<b>b</b>) AC; (<b>c</b>) BC.</p>
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<p>Influence of interaction of three factors on specific surface area of carbonization rate. (<b>a</b>) AB; (<b>b</b>) AC; (<b>c</b>) BC.</p>
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<p>Influence of interaction of three factors on specific surface area of carbonization rate. (<b>a</b>) AB; (<b>b</b>) AC; (<b>c</b>) BC.</p>
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<p>Product SEM image. (<b>a</b>) High resolution; (<b>b</b>) Low resolution.</p>
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<p>Product XRD pattern.</p>
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<p>Product absorption and desorption curve.</p>
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<p>Product particle size distribution map.</p>
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<p>Product Raman spectrum.</p>
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17 pages, 4110 KiB  
Article
Optimization Design of Cotton-Straw-Fiber-Modified Asphalt Mixture Performance Based on Response Surface Methodology
by Guihua Hu, Xiaowei Chen, Zhonglu Cao and Lvzhen Yang
Buildings 2024, 14(11), 3670; https://doi.org/10.3390/buildings14113670 - 18 Nov 2024
Viewed by 394
Abstract
This research explored the application of cotton straw fiber in asphalt mixtures, aiming to optimize the asphalt mixtures’ performance. Firstly, 17 experiments were designed using Response Surface Methodology (RSM). Subsequently, the Box–Behnken Design (BBD) was used to examine how the asphalt content, fiber [...] Read more.
This research explored the application of cotton straw fiber in asphalt mixtures, aiming to optimize the asphalt mixtures’ performance. Firstly, 17 experiments were designed using Response Surface Methodology (RSM). Subsequently, the Box–Behnken Design (BBD) was used to examine how the asphalt content, fiber length, and cotton straw fiber content interacted to affect the modified asphalt mixes’ pavement performance. Based on the experimental findings, performance prediction models were created to direct optimization. The optimized design was then validated through pavement performance tests and bending fatigue tests. The findings revealed that cotton straw fiber content, length, and asphalt content significantly influence the performance of modified asphalt mixtures. The inclusion of cotton straw fibers enhanced various properties of the mixtures. When the fiber content was set at 0.3%, fiber length at 6 mm, and asphalt content at 5.3%, the response indicators, including Marshall stability, dynamic stability, flexural strength, and freeze–thaw strength ratio, were measured at 12.246 kN, 2452.396 times/mm, 12.30 MPa, and 92.76%, respectively. These results indicate that the cotton-straw-fiber-modified asphalt mixture achieved optimal performance while meeting regulatory requirements. Additionally, fatigue tests showed that the cotton-straw-fiber-modified asphalt mixture exhibited superior fatigue resistance compared with the SBS-modified asphalt mixture. The maximum error between the RSM predictions and the experimental measurements was within 10%, demonstrating the accuracy of the predictive models in estimating the impact of different factors on asphalt mixture performance. The application of RSM in designing and optimizing cotton-straw-fiber-modified asphalt mixtures proved to be highly effective, offering valuable insights for utilizing cotton straw fibers in road construction. Full article
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<p>AC-13 gradation curve.</p>
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<p>Test specimen preparation schema.</p>
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<p>Effect of different factors on stability (<b>a</b>) fiber content and length (<b>b</b>) fiber and asphalt content (<b>c</b>) fiber length and asphalt content.</p>
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<p>Effect of different factors on dynamic stability (<b>a</b>) fiber content and length (<b>b</b>) fiber and asphalt content (<b>c</b>) fiber length and asphalt content.</p>
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<p>Effect of different factors on flexural tensile strength (<b>a</b>) fiber content and length (<b>b</b>) fiber and asphalt content (<b>c</b>) fiber length and asphalt content.</p>
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<p>Effect of different factors on flexural tensile strength (<b>a</b>) fiber content and length (<b>b</b>) fiber and asphalt content (<b>c</b>) fiber length and asphalt content.</p>
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<p>Effect of different factors on freeze–thaw strength ratio (<b>a</b>) fiber content and length (<b>b</b>) fiber and asphalt content (<b>c</b>) fiber length and asphalt content.</p>
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<p>Fatigue test results of different asphalt mixtures.</p>
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23 pages, 7923 KiB  
Article
Response Surface Methodology Approach for the Prediction and Optimization of the Mechanical Properties of Sustainable Laterized Concrete Incorporating Eco-Friendly Calcium Carbide Waste
by Auwal Ahmad Khalid, Abdurra’uf. M. Gora, A. D. Rafindadi, Sadi I. Haruna and Yasser E. Ibrahim
Infrastructures 2024, 9(11), 206; https://doi.org/10.3390/infrastructures9110206 - 17 Nov 2024
Viewed by 540
Abstract
This study investigated the combined effects of calcium carbide waste (CCW) and lateritic soil (LS) on sustainable concrete’s fresh and mechanical properties as a construction material for infrastructure development. The study will explore the possibility of using easily accessible materials, such as lateritic [...] Read more.
This study investigated the combined effects of calcium carbide waste (CCW) and lateritic soil (LS) on sustainable concrete’s fresh and mechanical properties as a construction material for infrastructure development. The study will explore the possibility of using easily accessible materials, such as lateritic soils and calcium carbide waste. Therefore, laterite soil was used to replace some portions of fine aggregate at 0% to 40% (interval of 10%) by weight, while CCW substituted the cement content at 0%, 5%, 10%, 15%, and 20% by weight. A response surface methodology/central composite design (RSM/CCD) tool was applied to design and develop statistical models for predicting and optimizing the properties of the sustainable concrete. The LS and CCW were input variables, and compressive strength and splitting tensile properties are response variables. The results indicated that the combined effects of CCW and LS improve workability by 18.2% compared to the control mixture. Regarding the mechanical properties, the synergic effects of CCW as a cementitious material and LS as a fine aggregate have improved the concrete’s compressive and splitting tensile strengths. The contribution of LS is more pronounced than that of CCW. The established models have successfully predicted the mechanical behavior and fresh properties of sustainable concrete utilizing LS and CCW as the independent variables with high accuracy. The optimized responses can be achieved with 15% CCW and 10% lateritic soil as a substitute for fine aggregate weight. These optimization outcomes produced the most robust possible results, with a desirability of 81.3%. Full article
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<p>Grading curves of aggregate materials.</p>
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<p>Slump flow test setup.</p>
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<p>Experimental setup for (<b>a</b>) compressive and (<b>b</b>) splitting tensile test.</p>
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<p>Central composite design (CCD) frameworks.</p>
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<p>Slump test result of laterite concrete containing CCW.</p>
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<p>Compressive strength of laterite concrete modified with CCW.</p>
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<p>Splitting tensile strength of laterite concrete modified with CCW.</p>
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<p>Predicted <span class="html-italic">F</span><sub>C</sub> vs. experimental values at (<b>a</b>) 7 days, (<b>b</b>) 14 days, and (<b>c</b>) 28 days ages.</p>
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<p>Contour and 3D plots for compressive strength at different ages of curing.</p>
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<p>Predicted <span class="html-italic">F</span><sub>s</sub> vs. experimental values at ages of: (<b>a</b>) 7 days, (<b>b</b>) 14 days, and (<b>c</b>) 28 days.</p>
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<p>Contour and 3D plots for splitting tensile strength at different curing ages.</p>
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<p>Externally studentized residuals vs. runs plots for: (<b>a</b>) <span class="html-italic">F</span><sub>c</sub>-<sub>28</sub>, (<b>b</b>) <span class="html-italic">F</span><sub>c</sub>-<sub>28</sub>, (<b>c</b>) <span class="html-italic">F</span><sub>c</sub>-<sub>28</sub> (MPa).</p>
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<p>Externally studentized residuals vs. runs plots for: (<b>a</b>) F<sub>s-28</sub>, (<b>b</b>) F<sub>s-28</sub>, (<b>c</b>) F<sub>s-28</sub> (MPa).</p>
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<p>Surface plot for desirability in 3D.</p>
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19 pages, 4919 KiB  
Article
Pulsed Electric Field for Quick-Cooking Rice: Impacts on Cooking Quality, Physicochemical Properties, and In Vitro Digestion Kinetics
by Saban Thongkong, Supaluck Kraithong, Jaspreet Singh, Pipat Tangjaidee, Artit Yawootti, Wannaporn Klangpetch, Pornchai Rachtanapun, Saroat Rawdkuen and Suphat Phongthai
Processes 2024, 12(11), 2577; https://doi.org/10.3390/pr12112577 - 17 Nov 2024
Viewed by 499
Abstract
Pulsed electric field (PEF) is one of the emerging technologies that has been applied in many aspects of the food industry. This study examined the impacts of a PEF on the cooking quality, physicochemical properties, nutritional factors, and in vitro protein and starch [...] Read more.
Pulsed electric field (PEF) is one of the emerging technologies that has been applied in many aspects of the food industry. This study examined the impacts of a PEF on the cooking quality, physicochemical properties, nutritional factors, and in vitro protein and starch digestion of two varieties of rice, including Jasmine 105 (white non-glutinous rice) and San Pa Tong 1 (white glutinous rice). Response surface methodology (RSM) and a three-level, three-factor Box–Behnken design were employed to assess the effects of the pulse number, electric field strength, and frequency on cooking time. The findings demonstrated that the number of pulses was a crucial factor influencing cooking time. Under optimal conditions (3347–4345 pulses, electric field strengths of 6–8 kV/cm, and frequencies ranging from 6 to 15 Hz), the rice cooking time was significantly reduced by 40–50% (p < 0.05) when compared to a conventional method. Moreover, PEF-treated rice showed a significant enhancement in in vitro protein and starch digestibility (p < 0.05), as well as retained a higher content of rapidly digestible starch. These results suggested that PEF treatment is a promising green technology for producing a novel quick-cooking rice with an improved eating quality. Full article
(This article belongs to the Special Issue Green Technologies for Food Processing)
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Graphical abstract
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<p>Three-dimensional response surface contour plots demonstrating the impacts of the field strength and number of pulses (<b>a</b>), the frequency and the number of pulses (<b>b</b>), the frequency and the field strength (<b>c</b>), on the cooking time of Jasmine 105 rice.</p>
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<p>Three-dimensional response surface contour plots demonstrating the impacts of the field strength and number of pulses (<b>a</b>), the frequency and the number of pulses (<b>b</b>), the frequency and the field strength (<b>c</b>), on the cooking time of Jasmine 105 rice.</p>
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<p>Three-dimensional response surface contour plots demonstrating the impacts of the field strength and number of pulses (<b>a</b>), the frequency and the number of pulses (<b>b</b>), the frequency and the field strength (<b>c</b>), on the cooking time of San Pa Tong 1 rice.</p>
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<p>Three-dimensional response surface contour plots demonstrating the impacts of the field strength and number of pulses (<b>a</b>), the frequency and the number of pulses (<b>b</b>), the frequency and the field strength (<b>c</b>), on the cooking time of San Pa Tong 1 rice.</p>
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<p>SEM images of Jasmine 105 rice samples: control (<b>A</b>, 500× and <b>D</b>, 1000×), freeze–thawing (<b>B</b>, 500× and <b>E</b>, 1000×), and optimized PEF treatments (<b>C</b>, 500× and <b>F</b>, 1000×). SEM images of San Pa Tong 1 rice samples: control (<b>G</b>, 500× and <b>J</b>, 1000×), freeze–thawing (<b>H</b>, 500× and <b>K</b>, 1000×), and optimized PEF treatments (<b>I</b>, 500× and <b>L</b>, 1000×).</p>
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<p>SEM images of Jasmine 105 rice samples: control (<b>A</b>, 500× and <b>D</b>, 1000×), freeze–thawing (<b>B</b>, 500× and <b>E</b>, 1000×), and optimized PEF treatments (<b>C</b>, 500× and <b>F</b>, 1000×). SEM images of San Pa Tong 1 rice samples: control (<b>G</b>, 500× and <b>J</b>, 1000×), freeze–thawing (<b>H</b>, 500× and <b>K</b>, 1000×), and optimized PEF treatments (<b>I</b>, 500× and <b>L</b>, 1000×).</p>
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<p>Starch digestion curves for Jasmine 105 (<b>a</b>) and San Pa Tong 1 (<b>b</b>). The single-phase logarithm of slope (LOS) plots of the starch digestibility data for Jasmine 105 (<b>c</b>–<b>e</b>) and San Pa Tong 1 (<b>f</b>–<b>h</b>) rice under control, freeze–thawing, and optimized PEF treatments.</p>
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<p>Starch digestion curves for Jasmine 105 (<b>a</b>) and San Pa Tong 1 (<b>b</b>). The single-phase logarithm of slope (LOS) plots of the starch digestibility data for Jasmine 105 (<b>c</b>–<b>e</b>) and San Pa Tong 1 (<b>f</b>–<b>h</b>) rice under control, freeze–thawing, and optimized PEF treatments.</p>
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<p>XRD patterns and crystallinity of rice samples (JC; Jasmine 105-control, JF; Jasmine 105-frozen and thawed; JP; Jasmine 105-PEF, SC; San Pa Tong 1-control; SF; San Pa Tong 1-frozen and thawed, and SP; San Pa Tong 1-PEF.</p>
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21 pages, 3854 KiB  
Article
Optimization of a Gorlov Helical Turbine for Hydrokinetic Application Using the Response Surface Methodology and Experimental Tests
by Juan Camilo Pineda, Ainhoa Rubio-Clemente and Edwin Chica
Energies 2024, 17(22), 5747; https://doi.org/10.3390/en17225747 - 17 Nov 2024
Viewed by 384
Abstract
The work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine’s power coefficient (C [...] Read more.
The work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine’s power coefficient (CP): the number of blades (N), helix angle (γ), and aspect ratio (AR). Central composite design (CCD) was used for the design of experiments (DOE). For the CFD simulations, a three-dimensional computational domain was established in the Ansys Fluent software, version 2021R1 utilizing the k-ω SST turbulence model and the sliding mesh method to perform unsteady flow simulations. The objective function was to achieve the maximum CP, which was obtained using a high-correlation quadratic mathematical model. Under the optimum conditions, where N, γ, and AR were 5, 78°, and 0.6, respectively, a CP value of 0.3072 was achieved. The optimal turbine geometry was validated through experimental testing, and the CP curve versus tip speed ratio (TSR) was determined and compared with the numerical results, which showed a strong correlation between the two sets of data. Full article
(This article belongs to the Section B: Energy and Environment)
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<p>Geometric factors involved in the Gorlov helical turbine (GHT) design.</p>
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<p>Dimensions of the computational domain and the setup of boundary conditions for the Ansys Fluent simulation.</p>
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<p>Mesh of computational domain dimensions.</p>
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<p>Experimental setup of the recirculating water channel. (1) Motor of 14.9 kW, (2) impeller, (3) water inlet value, (4) channel, (5) gate, (6) model vertical-axis hydrokinetic turbine, (7) connection axis to the sensor, (8) weir assembly, and (9) feed tank.</p>
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<p>Response surface plots for the power coefficient (<math display="inline"><semantics> <msub> <mi>C</mi> <mi>P</mi> </msub> </semantics></math>) by using the regression model. (<b>a</b>) Effects of N and <math display="inline"><semantics> <mi>γ</mi> </semantics></math>; (<b>b</b>) effects of N and AR; (<b>c</b>) effects of <math display="inline"><semantics> <mi>γ</mi> </semantics></math> and AR. The other factors were set at the optimal values.</p>
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<p>(<b>a</b>) Frequency distribution and (<b>b</b>) normal probability plots for the power coefficient (<math display="inline"><semantics> <msub> <mi>C</mi> <mi>P</mi> </msub> </semantics></math>).</p>
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<p>Numerical and experimental comparison of the power coefficient (<math display="inline"><semantics> <msub> <mi>C</mi> <mi>P</mi> </msub> </semantics></math>) vs. tip speed ratio (<math display="inline"><semantics> <mi>λ</mi> </semantics></math>) curves.</p>
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18 pages, 4598 KiB  
Article
Establishment of Betalain-Producing Cell Line and Optimization of Pigment Production in Cell Suspension Cultures of Celosia argentea var. plumosa
by Thapagorn Sang A Roon, Poramaporn Klanrit, Poramate Klanrit, Pornthap Thanonkeo, Jirawan Apiraksakorn, Sudarat Thanonkeo and Preekamol Klanrit
Plants 2024, 13(22), 3225; https://doi.org/10.3390/plants13223225 - 16 Nov 2024
Viewed by 397
Abstract
The prevalence of synthetic colorants in commercial products has raised concerns regarding potential risks, including allergic reactions and carcinogenesis, associated with their use or consumption. Natural plant extracts have gained attention as potential alternatives. This research focuses on callus induction and the establishment [...] Read more.
The prevalence of synthetic colorants in commercial products has raised concerns regarding potential risks, including allergic reactions and carcinogenesis, associated with their use or consumption. Natural plant extracts have gained attention as potential alternatives. This research focuses on callus induction and the establishment of cell suspension cultures from Celosia argentea var. plumosa. Friable callus was successfully induced using hypocotyl explants cultured on semi-solid Murashige and Skoog (MS) medium supplemented with 1 mg/L 2,4-dichlorophenoxyacetic acid (2,4-D) and 0.1 mg/L 6-benzylaminopurine (BAP). The friable callus cell line was used to establish a suspension culture. The effects of sucrose, BAP, and tyrosine concentrations on betalain production were investigated using response surface methodology (RSM) based on central composite design (CCD). Optimal conditions (43.88 g/L sucrose, 0.15 mg/L tyrosine, and 0.77 mg/L BAP) yielded 43.87 mg/L total betalain content after 21 days, representing a threefold increase compared to the control. BAP had a significant positive impact on betalain production, and increasing BAP and sucrose concentrations generally led to higher betalain production. However, tyrosine was not a significant factor for betalain production in cell suspension cultures. Additionally, antioxidant assays showed that suspension-cultured cells (SCCs) under optimized conditions exhibited free radical scavenging activity comparable to that observed in C. argentea var. plumosa flower extract. This study indicates the potential for further research on betalain production using C. argentea var. plumosa cell cultures, which may have commercial applications. Full article
(This article belongs to the Section Plant Development and Morphogenesis)
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<p><span class="html-italic">C. argentea</span> var. <span class="html-italic">plumosa</span> plant and callus cultures: (<b>A</b>) <span class="html-italic">C. argentea</span> var. <span class="html-italic">plumosa</span> with red inflorescence; (<b>B</b>) 30-day-old seedlings; (<b>C</b>) callus initiation from explants after 2 weeks; (<b>D</b>) callus growth on callus induction medium, CIM (Murashige and Skoog (MS) medium supplemented with 1 mg/L 2,4-dichlorophenoxyacetic acid (2,4-D) and 0.1 mg/L 6-benzylaminopurine (BAP)) after 4 weeks; (<b>E</b>) proliferation of different callus colors on CIM after 15 days of starting new subculture; (<b>F</b>) red callus proliferation on CIM after 15 days of starting new subculture.</p>
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<p>Cell suspension cultures of <span class="html-italic">C. argentea</span> var. <span class="html-italic">plumosa</span>: (<b>A</b>) friable callus from the red cell line; (<b>B</b>) suspension-cultured cells (SCCs) at 15 days of culture; (<b>C</b>) bright-field microscopy of 15-day friable pigmented callus; (<b>D</b>) bright-field microscopy of non-pigmented cells; (<b>E</b>–<b>G</b>) SCCs stained with Hoechst 33342 under fluorescent microscopy to visualize nuclei in different channels, the images were captured in the same field of view; (<b>E</b>) cells under RGB bright-field; (<b>F</b>) cells under fluorescent filter (excitation: 357 nm/emission: 447 nm); (<b>G</b>) merged RGB bright-field and fluorescence images. Arrows indicate nuclear positions, magnification = 200×, scale bar = 150 μm.</p>
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<p>Three-dimensional response surface plots showing the effect of (<b>A</b>) sucrose, (<b>B</b>) BAP, and (<b>C</b>) tyrosine on betalain content.</p>
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<p>Growth profile and betalain production in <span class="html-italic">C. argentea</span> var. <span class="html-italic">plumosa</span> cell suspension cultures under optimized conditions. Bars indicate mean ± SD from triplicate experiments (n = 3).</p>
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<p>Antioxidant capacity of the SCC extracts of <span class="html-italic">C. argentea</span> var. <span class="html-italic">plumosa</span> determined by ABTS and DPPH assays. Data are presented as the means ± SD of the results of triplicate determinations. Different superscript letters within each assay indicate significant differences between samples (<span class="html-italic">p</span> ≤ 0.05) as determined by Duncan’s Multiple Range Test (DMRT). Control, the SCC extract from cells cultured under unoptimized conditions); SCC, the SCC extract from cells cultured under optimized conditions; Flower, the inflorescence extract, and Vitamin C (ascorbic acid).</p>
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18 pages, 3359 KiB  
Article
Development of a Dual-Stage CIM® CDI Reactor with Immobilized Glucuronan Lyases and Laccases for Sustainable Synthesis of Antioxidant Phenolized Oligoglucuronan
by Xiaoyang Hou, Pascal Dubessay, Gwendoline Christophe, Nicolas Bridiau, Pierre-Edouard Bodet, Mounir Traikia, Mugilan Damadoran Raja, Thierry Maugard, Aleš Štrancar, Fabrice Audonnet, Philippe Michaud and Guillaume Pierre
Polysaccharides 2024, 5(4), 743-760; https://doi.org/10.3390/polysaccharides5040047 - 15 Nov 2024
Viewed by 462
Abstract
Immobilized enzyme reactors (IMERs) are critical tools for developing novel oligosaccharides based on the enzymatic catalysis of polysaccharides. In this paper, a novel glucuronan lyase from Peteryoungia rosettiformans was produced, purified, and then immobilized on a CIM® CDI disk for cleaving glucuronan. [...] Read more.
Immobilized enzyme reactors (IMERs) are critical tools for developing novel oligosaccharides based on the enzymatic catalysis of polysaccharides. In this paper, a novel glucuronan lyase from Peteryoungia rosettiformans was produced, purified, and then immobilized on a CIM® CDI disk for cleaving glucuronan. The results showed that around 63.6% of glycuronan lyases (800.9 μg) were immobilized on the disk. The Vmax values of immobilized glucuronan lyases did not significantly change (56.9 ± 4.7 μM∙min−1), while the Km values (0.310 ± 0.075 g∙L−1) increased by 2.5 times. It is worth noting that immobilized glucuronan lyases overcame the catalytic inhibition of free enzymes observed under high glucuronan concentrations (0.5–2 g∙L−1). circumscribed central composite design (CCCD) and response surface methodology (RSM) showed that glucuronan concentration, flow rate, and reaction time significantly affected the yield of oligoglucuronans. The degree of polymerization (DP) of degraded glucuronan ranged from DP 2–8 according to the results obtained by high performance anion exchange chromatography coupled with a pulsed amperometric detector (HPAEC-PAD). The IMER retained 50.9% activity after running 2373 column volumes of glucuronan. Finally, this glucuronan lyase reactor was tentatively connected to an immobilized laccase reactor to depolymerize, and gallic acid (GA) was added to glucuronan. Approximately 8.5 mg of GA was added onto 1 g of initial glucuronan, and the GA–oligoglucuronan conjugates showed notable antioxidant activity. Full article
(This article belongs to the Collection Bioactive Polysaccharides)
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<p>Schematic diagram of immobilized glucuronan lyases on the CIM<sup>®</sup> CDI disk system.</p>
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<p>Schematic diagram of the dual stage (immobilized glucuronan lyases and laccases) reactor.</p>
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<p>Saturation curves and Michaelis–Menten model fitting of free (<b>a</b>,<b>b</b>) and immobilized glucuronan lyases (<b>c</b>,<b>d</b>).</p>
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<p>Contour plots of concentration of oligoglucuronan under all pairs of continuous variables.</p>
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<p>Three-dimensional-mesh graphs highlighting the contribution of the three factors, i.e., [glucuronan] (%), flow rate (mL/min), and reaction time (min), on the producing of DP 3 and DP 7 oligoglucuronan.</p>
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<p>Relative activity of immobilized glucuronan lyase regarding (<b>a</b>) the number of column volumes that substrate passed through IMER and (<b>b</b>) the number of days.</p>
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<p>Depolymerization and phenolization of glucuronan, using the dual stage IMER, and the UV spectra of gallic acid at T0 and T6h.</p>
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<p>DPPH radical inhibition of ascorbic acid, gallic acid (GA) glucuronan, and GA–oligoglucuronan conjugates. The standard deviations correspond to three replicates. *** <span class="html-italic">p</span> &lt; 0.001, in comparison to ascorbic acid as the reference. ns: non-significant.</p>
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16 pages, 1106 KiB  
Article
Ultrasound-Assisted Extraction of Alginate from Fucus vesiculosus Seaweed By-Product Post-Fucoidan Extraction
by Viruja Ummat, Ming Zhao, Saravana Periaswamy Sivagnanam, Shanmugapriya Karuppusamy, Henry Lyons, Stephen Fitzpatrick, Shaba Noore, Dilip K. Rai, Laura G. Gómez-Mascaraque, Colm O’Donnell, Anet Režek Jambark and Brijesh Kumar Tiwari
Mar. Drugs 2024, 22(11), 516; https://doi.org/10.3390/md22110516 - 14 Nov 2024
Viewed by 693
Abstract
The solid phase byproduct obtained after conventional fucoidan extraction from the brown seaweed Fucus vesiculosus can be used as a source containing alginate. This study involves ultrasound-assisted extraction (UAE) of alginate from the byproduct using sodium bicarbonate. Response surface methodology (RSM) was applied [...] Read more.
The solid phase byproduct obtained after conventional fucoidan extraction from the brown seaweed Fucus vesiculosus can be used as a source containing alginate. This study involves ultrasound-assisted extraction (UAE) of alginate from the byproduct using sodium bicarbonate. Response surface methodology (RSM) was applied to obtain the optimum conditions for alginate extraction. The ultrasound (US) treatments included 20 kHz of frequency, 20–91% of amplitude, and an extraction time of 6–34 min. The studied investigated the crude alginate yield (%), molecular weight, and alginate content (%) of the extracts. The optimum conditions for obtaining alginate with low molecular weight were found to be 69% US amplitude and sonication time of 30 min. The alginate extracts obtained were characterized using Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). Ultrasound-assisted extraction involving a short treatment lasting 6–34 min was found to be effective in extracting alginate from the byproduct compared to the conventional extraction of alginate using stirring at 415 rpm and 60 °C for 24 h. The US treatments did not adversely impact the alginate obtained, and the extracted alginates were found to have similar characteristics to the alginate obtained from conventional extraction and commercial sodium alginate. Full article
(This article belongs to the Special Issue Green Extraction for Obtaining Marine Bioactive Products)
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<p>Response surface plots of experimental design showing the effect of ultrasonic amplitude and sonication treatment time on (<b>a</b>) crude alginate yield; (<b>b</b>) alginate content; and (<b>c</b>) Mw.</p>
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<p>TGA and DSC curves of crude alginate (O1 and O2 samples) obtained with optimum UAE conditions compared with reference sodium bicarbonate and commercial sodium alginate samples.</p>
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<p>The mean FTIR spectra of alginate samples extracted with UAE (T1–T13), conventional extraction (i.e., TCA and TCB), and a commercial sodium alginate sample.</p>
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<p>Schematic of alginate extraction workflow using the seaweed byproduct obtained from <span class="html-italic">Fucus vesiculosus</span> after fucoidan extraction.</p>
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18 pages, 3103 KiB  
Article
Study on the Pilot-Scale Technology of Ginkgolide B Synthesis by Coprinus comatus
by Zhicai Zhang, Feng Wang and Ling Xu
Fermentation 2024, 10(11), 579; https://doi.org/10.3390/fermentation10110579 - 12 Nov 2024
Viewed by 525
Abstract
Ginkgo biloba extract (EGB) has been approved by the Food and Drug Administration in the United States for clinical studies on memory disorders. Ginkgolide B (GB) is the major terpene lactone component of EGB and is a specific and potent antagonist of platelet-activating [...] Read more.
Ginkgo biloba extract (EGB) has been approved by the Food and Drug Administration in the United States for clinical studies on memory disorders. Ginkgolide B (GB) is the major terpene lactone component of EGB and is a specific and potent antagonist of platelet-activating factor (PAF). In a previous study, we reported the medium composition for the conversion of ginkgolides to GB by Coprinus comatus. In the present study, we applied the response surface methodology (RSM) to optimize the conversion conditions in a 20 L fermenter and applied HPLC-MS/MS, circular dichroism (CD) and infrared (IR) spectroscopy analyses, and nuclear magnetic resonance (NMR) to further confirm the sample structure. The optimal conversion conditions consisted of 12.7 L/min of ventilation, a 156 h conversion time, a 132 rpm rotating speed, a 0.04 MPa fermenter pressure, and a 27.8 °C conversion temperature. Under the optimal conditions, the GB conversion rate was 98.62%, and the GB content of the sample was higher than 98%. HPLC-MS/MS, CD, IR, and NMR analyses showed that the molecular formula of the sample was C20H24O10 and the chemical structure of the sample was in good agreement with the standard GB. Our current study lays the groundwork for the industrial production of GB. Full article
(This article belongs to the Section Industrial Fermentation)
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<p>Relationship between actual values and predicted values of the GB-CR. The color squares were the detected results of 46 runs in BBD-RSM design and the slant line was the theoretical values obtained based on Equation (1). Each small square represents a response value, and the color of the small squares ranges from blue to red indicating that the response surface values increase from the minimum value (17.88%) to the maximum value (98.63%).</p>
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<p>HPLC chromatogram (<b>a</b>), mass spectrum (<b>b</b>), and circular dichroism (CD) spectra (<b>c</b>) of the GB sample after purification.</p>
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<p>The structure of ginkgolide (G). GA: R<sub>1</sub> = R<sub>2</sub> = H, R<sub>3</sub> = OH; GB: R<sub>1</sub> = R<sub>3</sub> = OH, R<sub>2</sub> = H; GC: R<sub>1</sub> = R<sub>2</sub> = R<sub>3</sub> = OH; GJ: R<sub>1</sub> = H, R<sub>2</sub> = R<sub>3</sub> =OH; GM: R<sub>1</sub> = R<sub>2</sub> = OH, R<sub>3</sub> = H. Number 1–20 was consistent with the number in <a href="#fermentation-10-00579-t005" class="html-table">Table 5</a> and <a href="#fermentation-10-00579-t006" class="html-table">Table 6</a>.</p>
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<p>Contour plots of the GB-CR showing the effect of (<b>a</b>) ventilation and conversion time; (<b>b</b>) ventilation and rotating speed; (<b>c</b>) ventilation and fermenter pressure; (<b>d</b>) ventilation and temperature; (<b>e</b>) conversion time and rotation speed; (<b>f</b>) conversion time and fermenter pressure; (<b>g</b>) conversion time and temperature; (<b>h</b>) rotating speed and fermenter pressure; (<b>i</b>) rotating speed and temperature; and (<b>j</b>) fermenter pressure and temperature. The color in the figure ranges from blue to red indicating that the response surface values increase from the minimum value (17.88%) to the maximum value (98.63%).</p>
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<p>Contour plots of the GB-CR showing the effect of (<b>a</b>) ventilation and conversion time; (<b>b</b>) ventilation and rotating speed; (<b>c</b>) ventilation and fermenter pressure; (<b>d</b>) ventilation and temperature; (<b>e</b>) conversion time and rotation speed; (<b>f</b>) conversion time and fermenter pressure; (<b>g</b>) conversion time and temperature; (<b>h</b>) rotating speed and fermenter pressure; (<b>i</b>) rotating speed and temperature; and (<b>j</b>) fermenter pressure and temperature. The color in the figure ranges from blue to red indicating that the response surface values increase from the minimum value (17.88%) to the maximum value (98.63%).</p>
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<p>Contour plots of the GB-CR showing the effect of (<b>a</b>) ventilation and conversion time; (<b>b</b>) ventilation and rotating speed; (<b>c</b>) ventilation and fermenter pressure; (<b>d</b>) ventilation and temperature; (<b>e</b>) conversion time and rotation speed; (<b>f</b>) conversion time and fermenter pressure; (<b>g</b>) conversion time and temperature; (<b>h</b>) rotating speed and fermenter pressure; (<b>i</b>) rotating speed and temperature; and (<b>j</b>) fermenter pressure and temperature. The color in the figure ranges from blue to red indicating that the response surface values increase from the minimum value (17.88%) to the maximum value (98.63%).</p>
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<p>Contour plots of the GB-CR showing the effect of (<b>a</b>) ventilation and conversion time; (<b>b</b>) ventilation and rotating speed; (<b>c</b>) ventilation and fermenter pressure; (<b>d</b>) ventilation and temperature; (<b>e</b>) conversion time and rotation speed; (<b>f</b>) conversion time and fermenter pressure; (<b>g</b>) conversion time and temperature; (<b>h</b>) rotating speed and fermenter pressure; (<b>i</b>) rotating speed and temperature; and (<b>j</b>) fermenter pressure and temperature. The color in the figure ranges from blue to red indicating that the response surface values increase from the minimum value (17.88%) to the maximum value (98.63%).</p>
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<p>Contour plots of the GB-CR showing the effect of (<b>a</b>) ventilation and conversion time; (<b>b</b>) ventilation and rotating speed; (<b>c</b>) ventilation and fermenter pressure; (<b>d</b>) ventilation and temperature; (<b>e</b>) conversion time and rotation speed; (<b>f</b>) conversion time and fermenter pressure; (<b>g</b>) conversion time and temperature; (<b>h</b>) rotating speed and fermenter pressure; (<b>i</b>) rotating speed and temperature; and (<b>j</b>) fermenter pressure and temperature. The color in the figure ranges from blue to red indicating that the response surface values increase from the minimum value (17.88%) to the maximum value (98.63%).</p>
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