Effect Of Sample Particle Size Research Articles

Effect of particle size on phytochemical composition and antioxidant properties of Sargassum cristaefolium ethanol extract

Sample particle size is an important parameter in the solid–liquid extraction system of natural products for obtaining their bioactive compounds. This study evaluates the effect of sample particle size on the phytochemical composition and antioxidant activity of brown macroalgae Sargassum cristaefolium. The crude ethanol extract was extracted from dried powders of S.cristeafolium with various particle sizes (> 4000 µm, > 250 µm, > 125 µm, > 45 µm, and < 45 µm). The ethanolic extracts of S.cristaefolium were analysed for Total Phenolic Content (TPC), Total Flavonoid Content (TFC), phenolic compound concentration and antioxidant activities. The extract yield and phytochemical composition were more abundant in smaller particle sizes. Furthermore, the TPC (14.19 ± 2.08 mg GAE/g extract to 43.27 ± 2.56 mg GAE/g extract) and TFC (9.6 ± 1.8 mg QE/g extract to 70.27 ± 3.59 mg QE/g extract) values also significantly increased as particle sizes decreased. In addition, phenolic compounds epicatechin (EC), epicatechin gallate (ECG), epigallocatechin (EGC), and Epigallocatechin gallate (EGCG) concentration were frequently increased in samples of smaller particle sizes based on two-way ANOVA and Tukey’s multiple comparison analysis. These results correlate with the significantly stronger antioxidant activity in samples with smaller particle sizes. The smallest particle size (< 45 µm) demonstrated the strongest antioxidant activity based on DPPH, ABTS, hydroxyl assay and FRAP. In addition, ramp function graph evaluates the desired particle size for maximum phytochemical composition and antioxidant activity is 44 µm. In conclusion, current results show the importance of particle size reduction of macroalgae samples to increase the effectivity of its biological activity.

Multi-energy calibration and sample fusion as alternatives for quantitative analysis of high silicon content samples by laser-induced breakdown spectrometry

Calibration aiming at quantitative analysis of complex samples is one of the most difficult issues in laser-induced breakdown spectroscopy (LIBS) due to matrix interferences, heterogeneity, and sample particle size effects.

Analytical issue related to fumonisins: A matter of sample comminution?

The aim of the present work was to evaluate the effect of sample particle size on fumonisins recovery during the extraction step. Four maize samples were ground and the resulted flours were separated in six different fractions according to their particle size (1000-250 μm). Fumonisin B1 and B2 were quantified on each fraction, as well as on the unfractionated sample by HPLC-MS/MS. Furthermore, the proximate analysis was carried out to exclude the influence of macro-constituent on the mycotoxins distribution. Although the six maize fractions were found to be characterized by the same macro-constituent composition, a significant increase (p < 0.000) of fumonisins content was observed in all the analysed samples. Extraction yields up to five times higher were found in the finer flours. From the above, it is clear that the sample particle size has a significant impact on the fumonisins recovery. The outcomes suggest that sample granulometry should be standardized for ensuring accuracy and reliability of the analysis results. Overall, the results of this study, although still preliminary, may offer a reliable analytical solution to finally address the "hidden fumonisin issue".

Discovery of the Linear Region of Near Infrared Diffuse Reflectance Spectra Using the Kubelka-Munk Theory.

Particle size is of great importance for the quantitative model of the NIR diffuse reflectance. In this paper, the effect of sample particle size on the measurement of harpagoside in Radix Scrophulariae powder by near infrared diffuse (NIR) reflectance spectroscopy was explored. High-performance liquid chromatography (HPLC) was employed as a reference method to construct the quantitative particle size model. Several spectral preprocessing methods were compared, and particle size models obtained by different preprocessing methods for establishing the partial least-squares (PLS) models of harpagoside. Data showed that the particle size distribution of 125–150 μm for Radix Scrophulariae exhibited the best prediction ability with = 0.9513, RMSEP = 0.1029 mg·g−1, and RPD = 4.78. For the hybrid granularity calibration model, the particle size distribution of 90–180 μm exhibited the best prediction ability with = 0.8919, RMSEP = 0.1632 mg·g−1, and RPD = 3.09. Furthermore, the Kubelka-Munk theory was used to relate the absorption coefficient k (concentration-dependent) and scatter coefficient s (particle size-dependent). The scatter coefficient s was calculated based on the Kubelka-Munk theory to study the changes of s after being mathematically preprocessed. A linear relationship was observed between k/s and absorption A within a certain range and the value for k/s was >4. According to this relationship, the model was more accurately constructed with the particle size distribution of 90–180 μm when s was kept constant or in a small linear region. This region provided a good reference for the linear modeling of diffuse reflectance spectroscopy. To establish a diffuse reflectance NIR model, further accurate assessment should be obtained in advance for a precise linear model.

Comparison of Fused Glass Beads and Pressed Powder Pellets for the Quantitative Measurement of Al, Fe, Si and Ti in Bauxite by Laser‐Induced Breakdown Spectroscopy

Due to matrix interference and sample particle size effects, some of the most important and difficult issues in laser‐induced breakdown spectroscopy (LIBS) analysis are the calibration and quantitative measurement of a complex matrix. This study proposes the use of borate fusion as an alternative sample preparation procedure for the quantitative measurement of Al, Fe, Si and Ti in bauxite by LIBS. Analytical calibration curves were made using bauxite certified reference materials (CRM), and the precision and accuracy of the methods were evaluated by analysing an additional bauxite CRM, using two different approaches: pressed powder pellets and fused glass beads. The borate fusion method was the most suitable sample preparation technique, since particle size effects and matrix interference could be minimised, obtaining better linearity on the analytical calibration curves (r2), and more accurate and more precise results for bauxite analysis.

The effect of sample particle size on the determination of pore structure parameters in shales

The combination of low-pressure N2 and CO2 adsorption could provide an effective approach for characterizing the pore structure of shales. Although gas adsorption methods generally do not destroy the pore structure during experimental process, sample particle sizes could significantly affect experimental results that can approach or deviate from the real value. Therefore, the determination of pore structure is closely related to the sample particle size. In the current study, 4 fresh core samples of different compositions and total organic carbon (TOC) ranges collected from the Sichuan Basin were analyzed to elucidate the effect of sample particle size on the determination of pore structure parameters. Samples were ground and then sieved into seven groups based on particle size ranges, i.e., <60, 60–80, 80–100, 100–120, 120–140, 140–200 and >200 mesh, for measurements of low-pressure N2 and CO2 adsorption, TOC contents, and X-ray diffraction (XRD) mineralogy.TOC results show a slight enrichment whereas XRD minerals vary irregularly, with sample particle size decreases. Meanwhile, the TOC and mineral contents show insignificant statistical relation with pore structure parameters in all sample particle size ranges. Therefore, variations in organic matter content and mineral composition that result from sieving are unlikely to have a significant influence on the pore structure of shale. Rather, sample particle size may be the most important control on pore structure characteristics in the samples analyzed in this study.The relative standard deviations (RSDs) for Brunauer–Emmett–Teller (BET) N2 surface areas, Dubinin–Radushkevich (D–R) CO2 micropore surface areas and non-local density functional theory (NLDFT) N2 and CO2 nanopore surface areas measurements are <5%, within analytical error. Therefore, in the studied grain size range (60–200 mesh), the sample particle size shows insignificant effects on surface area results. However, samples with smaller particle size have a greater effect on pore volume and pore size, especially for pore size distribution (PSD) of N2 low-pressure adsorption. The RSDs of the Barrett–Joyner–Halenda (BJH) pore volumes and BET pore sizes of all samples in the 140–200 mesh range are obviously greater than the values of other mesh ranges. Moreover, in the dV/dlogw plots of PSD analysis, high N2 peaks and new N2 peaks appeared in the 10–100nm pore-width range, particularly for samples in the >140 mesh range. The 60–140 mesh particle-size range is therefore recommended for N2 low-pressure adsorption. Finally, the sample particle size has insignificant effect on the pore system parameters for grains in the 60–200 mesh range for CO2 low-pressure adsorption. Overall, the results confirm that the 60–140 mesh particle-size range can be used for both N2 and CO2 low-pressure adsorption measurements.

Ozonolysis pretreatment of maize stover: The interactive effect of sample particle size and moisture on ozonolysis process

Maize stover was ozonolyzed to improve the enzymatic digestibility. The interactive effect of sample particle size and moisture content on ozonolysis was studied. After ozonolysis, both lignin and xylan decreased while cellulose was only slightly affected in all experiments. It was also found that the smaller particle size is better for ozonolysis. The similar water activity of the different optimum moisture contents for ozonolysis reveals that the free and bound water ratio is a key factor of ozonolysis. The best result of ozonolysis was obtained at the mesh of −300 and the moisture of 60%, where up to 75% lignin was removed. The glucose yield after enzymatic hydrolysis increased from 18.5% to 80%. Water washing had low impact on glucose yield (less than 10% increases), but significantly reduced xylose yield (up to 42% decreases). The result indicates that ozonolysis leads to xylan solubilization.

EXTRACTION OF COCOA BUTTER BY SUPERCRITICAL CARBON DIOXIDE: OPTIMIZATION OF OPERATING CONDITIONS AND EFFECT OF PARTICLE SIZE

ABSTRACT The optimum operating conditions for the extraction of cocoa butter from cocoa liquor using supercritical carbon dioxide and the effect of sample particle size on cocoa butter extraction under optimized operating conditions were investigated. The optimization was conducted at 10–45 MPa and 35–75C, with extraction times of 1–12 h by response surface methodology. The effect of particle size was studied using cocoa liquor, ground cocoa nibs and crushed cocoa nibs with particle sizes of approximately 74 µm, 0.85–1 mm and 4–6 mm, respectively. The yield was analyzed for total fat content by gravimetric method and triacylglycerol (TAG) profile by high‐performance liquid chromatography. The results showed higher yield of cocoa butter with higher values of pressure, temperature and extraction time. The optimum conditions for cocoa butter extraction were 45 MPa, 75C and 12 h. The smaller particle size produced a higher yield of cocoa butter. 1,3‐Dipalmitoyl‐2‐oleoyl‐glycerol (POP), 1‐palmitoyl‐2‐oleoyl‐3‐stearoyl‐glycerol (POS) and 1,3‐distearoyl‐2‐oleoyl‐glycerol (SOS) were the major TAGs present in the extracted cocoa butter, with POS being the highest (&gt;30%) for all treatments studied.PRACTICAL APPLICATIONSThe application of supercritical carbon dioxide extraction offers a pollution‐free technology that will gain wide acceptance globally because of increasingly stringent environmental regulations. The results from the study would assist the industry in the production of cocoa butter that is safe for consumption and free from contaminants, in contrast to those produced by organic solvent and mechanical expression.

Análise estatística e optimização de perfis de redução termoprogramada (TPR)

The effect of operational variables and their interaction in TPR profiles was studied using a fractional factorial experimental design. The heating rate and the reducing agent concentration were found to be the most important variables determining the resolution and sensitivity of the technique. They showed opposite effects. Therefore, they should be manipulated preferentially in order to obtain optimized TPR profiles. The effect of sample particle size was also investigated. The tests were carried out within a Cu/Zn/Al2O3 catalyst used for the water-gas shift reaction that presented two distinct species of Cu2+ in TPR profiles.

Fluorination with polytetrafluoroethylene slurry in electrothermal vaporization-inductively coupled plasma-atomic emission spectrometry

A method was developed to determine refractory elements by inductively coupled plasma-atomic emission spectrometry (ICP-AES) with sample introduction by electrothermal vaporization (ETV). A slurry of polytetrafluoroethylene (PTFE) was used as fluorinating reagent to promote the vaporization of refractory elements from a graphite furnace and to avoid the formation of difficult volatile carbides. With this treatment the refractory elements can be efficiently vaporized, and subsequently introduced into the plasma. The detection limits of this method were in the picogram to sub-nanogram range and superior to those obtained with conventional nebulization systems, and were comparable with those obtained with similar ETV—ICP-AES techniques. The analyte vaporization and transport process was systematically explored, and the corresponding vaporization and transport mechanisms of refractory elements in this system have been proposed. The matrix effects and sample particle size effects in fluorination assisted ETV—ICP-AES were significantly reduced. Therefore, an effective method for lowering the matrix interferences has been proposed.

Factors affecting the prediction of organic matter Digestibility of grass silage by near infrared reflectance spectroscopy

Earlier studies (Barber et al., 1990) showed the superiority of near infrared reflectance spectroscopy (NIRS) for predicting the organic matter digestibility (OMD) in vivo of grass silage over fibre and in vitro procedures. However, during routine application occasional erroneous values were predicted for which there were no obvious reasons. Baker and Barnes (1990) reported that the likely sources of the problems contributing to the errors were instrumental and environmental noise, sample particle size effects and variable moisture content of the samples. These authors also reported that standard normal variate - detrend (SNV-D) scatter correction procedure of Barnes et al. (1989) could be used to reduce the effects of particle size variation and they also emphasised the need to test NIRS calibrations for repeatability. The purpose of the present work was to evaluate the use of the SNV-D scatter correction procedure, the techniques for reducing the sensitivity of calibrations to residual moisture and methods to improve the repeatability of the predicted OMD in vivo values of grass silage. In addition, a further objective was to compare three calibration methods, namely modified stepwise regression (MSR), modified partial least squares (MPLS) and principal component analysis (PCA).

Factors Influencing the Robustness and Accuracy of Near Infrared Reflectance Spectroscopy (NIRS) Calibrations for Ps5edicting the Digestibility of Grass Silages

Earlier studies showed the superiority of NIRS, over fibre measurements, for predicting organic matter digestibility (OMD) in vivo of grass silages. (Barber et al 1990). This system was put into routine use in ADAS in 1989 and after some initial doubts, due to the wider range of the predicted data seen, is now accepted as the best system available for routine use. However, occasional erroneous values were predicted for which there were no obvious explanations, and which resulted in occasional relatively poor repeatability. In common with all NIRS applications it was likely that the sources of the problems contributing to the errors were i) instrumental and environmental noise, ii) sample particle size effects and iii) variable moisture content of the samples. A course of investigation was undertaken with the objective of determining the effects of these on the predicted data.

Pore structure and kinetics of the thermal decomposition of Al(OH)3

AbstractThe isothermal decomposition of gibbsite (aluminum hydroxide) was studied under controlled, pure water vapor pressures from 50 to 3,000 Pa over the temperature range from 458 to 508 K; the effect of sample particle size was also investigated. The partial conversion to boehmite (AlOOH) and the subsequent formation of a ρ‐transition alumina product phase were followed with respect to the reactor operating conditions. Nitrogen and water vapor adsorption measurements were used to evaluate the chemical kinetics of the formation of ρ‐alumina in terms of an interface velocity, and to interpret the observed dependencies on temperature and water vapor pressure. An adsorption/decomposition model is presented for these kinetics. The interpretation is consistent with the observation that decomposition rate is inversely proportional to the square of the water vapor pressure. The apparent activation energy of 342 ± 15 kJ/mol includes a water adsorption energy, as well as the chemical decomposition contribution of 260 ± 20 kJ/mol.