Modified Sample Preparation Approach for the Determination of the

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A modified sample preparation approach for the determination of the phenolic and humic-like substances in natural organic materials by the Folin Ciocalteu Method Ludovico Pontoni, Antonio Panico, Alessia Matanò, Eric D van Hullebusch, Massimiliano Fabbricino, Giovanni Esposito, and Francesco Pirozzi J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b04942 • Publication Date (Web): 14 Nov 2017 Downloaded from http://pubs.acs.org on November 15, 2017

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Journal of Agricultural and Food Chemistry

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A modified sample preparation approach for the determination of the phenolic and humic-like

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substances in natural organic materials by the Folin Ciocalteu Method

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Ludovico Pontonia*, Antonio Panicob, Alessia Matanòa, Eric D. van Hullebuschc, Massimiliano Fabbricinoa,

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Giovanni Espositod, Francesco Pirozzia.

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a

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Claudio 21, 80125 Naples, Italy

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b

Telematic University Pegaso, piazza Trieste e Trento 48, 80132 Naples, Italy

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c

Department of Environmental Engineering and Water Technology, IHE Delft Institute for Water Education,

Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, via

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Westvest 7, 2611 AX Delft, the Netherlands

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d

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43, 03043 Cassino (FR), Italy;

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* corresponding author

Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, via Di Biasio

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[email protected]

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ACS Paragon Plus Environment


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Abstract

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A novel modification of the Folin–Ciocalteu colorimetric assay sample preparation for the determination of

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total phenolic compounds in natural solid and semi-solid organic materials (e.g., foods, organic solid waste,

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soils, plant tissues, agricultural residues, manure, etc.) is proposed. In this method the sample is prepared

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by adding sodium sulfate as solid diluting agent before homogenization. The method allows the

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determination of total phenols (TP) in samples with high solids content, and it provides good accuracy and

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reproducibility. Additionally, this method permits analyses of significant amounts of sample, which reduces

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problems related to heterogeneity. We applied this method to phenols-rich lignocellulosic and humic-like

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solids and semi-solid samples, including rice straw (RS), peat-rich soil (PS) and food waste (FW). The TP

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concentrations measured with solid dilution (SD) preparation were substantially higher (increases of 41.4,

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15.5, and 59.4 % in RS, PS and FW, respectively) than those obtained with the traditional method (solids

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suspended in water). These results showed that the traditional method underestimates phenolic content in

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the studied solids.

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Keywords: Solid dilution, total phenols in solids, Lignocellulose characterization, organic waste

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characterization, soil humic substances

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1. Introduction

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The determination of total phenolic (TP) content in liquid and solid organic matrices has received increasing

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attention in the last few decades. The field of applications have extended from simple environmental

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monitoring, agri-food characterization 1, and soil quality assessment 2, to recently developed field of bio-

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resource technologies, which includes lignocellulosic materials widely studied as renewable energy sources

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Lignocellulosic materials are rich in lignin, a complex polymer of three so-called monolignols (p-coumaryl,

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conyferil, synapyl alcohols). Monolignols have been chemically well characterized as polyphenols, due to

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the presence of more than one phenolic hydroxyl. It is well known that lignin rich wastes are not readily

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biodegradable 4. Thus, when improperly discarded in the environment, these wastes give rise to slow

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prolonged release of phenolic compounds in the environment, which can lead to groundwater’s pollution

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and loss of soil fertility 5-6. Moreover polymeric phenolic compounds have been scrutinised in the last few

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decades due to the detrimental effects incurred when lignocellulosic substances are subjected to anaerobic

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digestion with excessively high loading rates 7-8. On the other hand there is a good evidence to show that

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polyphenols possess very good anti-oxidant properties 9, and thus, more and more studies have been

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conducted to characterize foods and beverages in terms of polyphenols content 10-13.

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Noticeable amounts of phenolic moieties contribute to the structure of humic substances. Humic

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substances are strongly involved in many processes related to soil chemistry and biochemistry, such as

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contaminants transport through soil, microbial distribution, soil water retention and consequently soil

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fertility 14-15. On the other hand, phenol-rich biosolids are often spread onto agricultural soils to increase

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their fertility. The presence of aromatic moieties in the polymers relates to the capacity of soil to

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immobilize micro-pollutants (organic and inorganic). Thus aromatic moieties of bio-solids spread on natural

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soils have serious consequences on micro-pollutants mobility and bioavailability in the environment 16-18.

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The analytical challenges in achieving precise and effective quantification of the TP in all these matrices are

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mostly related to the high solid content. Indeed phenolic groups are heterogeneously speciated; they can

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occur as small hydrophilic molecules, often described as “free phenols”; they can be dissolved; or they can

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form colloidal or suspended macromolecules and aggregates 7. Thus the target analytes might be

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distributed into different phases of a solid or semi-solid matrix 19; moreover they may be more or less

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water-soluble.

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The Folin-Ciocalteu (F-C) method has been validated and standardized for determining TP and lignin

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contents in water and wastewater 20 and is widely used as part of the Lowry protocol for determination of

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total proteins 21. Although several attempts have been reported in the recent literature 22, to the best of

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our knowledge, there is no reliable standard F-C procedure for analyzing solid or semi-solid samples. Most

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of the proposed methods involve TP quantification after extraction with various solvents from the

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analytical matrix 10, 13, 23-28. Analytical results are highly dependent on the effectiveness of the used phenols

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extraction technique. The extraction method yield is indeed intimately related to the matrix composition

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and physical / molecular structure of the phenolic compounds. As a consequence, non-extractable phenols

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are not detected by such methods. Thus, depending on sample preparation/extraction and analysis

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method, different TP estimations in given substrate type might range over several orders of magnitude.

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This is mainly related to underestimation or absence of the targeted compounds which, in many cases, may

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display major biological activities or relevance29. Hence, a method is still needed for a rapid and accurate

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quantification of TP by directly analysing the solid sample, regardless the fractionation of phenols in the

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samples. In such direction, the recently developed QUENCHER (Quick, Easy, New, Cheap and Reproducible

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treatment) methods 30-31 are based on direct colorimetric measurement of solid samples by mixing them

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with free radicals 29 or other oxidants 32. Authors report that QUENCHER methods allow direct calculation of

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the TAC (Total Antioxidant Capacity) without preliminary extraction of their reducing moieties because

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extraction of bound phenols occurs simultaneously with the oxidation. The idea is that bound phenolics

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from the matrix may be forced to dissolve by TAC oxidizing reagents. F-C is reported as one of the reagents

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capable to do that 33-35. F-C assay is, indeed, an indirect method which gives an estimation of the species

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capable to be oxidized by the F-C reagent (namely molibdo tungstic heteropolyacid). The F-C reactions lead

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to the formation of the reduced molybdenum blue which is finally revealed by visible optical spectroscopy


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effectiveness is the accessibility of the suspended oxidizable functions to the reagent. Hence, sample

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preparation plays an essential role in determination related to this kind of samples when the analysis is

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aiming at the quantification of insoluble components of the matrix.

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The aim of this study was to demonstrate the applicability of solid dilution (SD) preparative method to this

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analytical method. SD consists of mixing and homogenizing a sample with a known amount of a salt that

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will remain inert during the analytical reactions. The SD method was previously successfully applied to the

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determinations of the chemical oxygen demand (COD) in solid and semisolid samples with very good results

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in terms of recoveries and repeatability 37.

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Here, we optimized and validated this method on three matrices: rice straw (RS), peat soil (PS) and food

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waste (FW). The results, expressed as mg equivalents of phenol (C6H5OH), were compared to those

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obtained when the homogenized sample was suspended in water (traditional method). We analysed the

. Therefore, in such heterogeneous reaction conditions, the main factor affecting the F-C reaction

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performances of these two methods with Grubbs’ test and Student-T test. Grubb’s test was used to exclude

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anomalous data that could have distorted the results (e.g. outliers related to experimental errors). The

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Student-T test was used to verify that the two methods generated two different sample populations.

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2. Materials and methods

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RS was harvested from rice fields in Pavia (Italy). FW was prepared in the laboratory according to previous

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Valorgas report 38 as described in details by Ariunbataar et al. 39. PS was purchased from a local gardening

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store.

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F-C reagent was purchased from Carlo Erba Reagenti (Italy). Sodium tartrate, sodium carbonate and sodium

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sulfate anhydrous were purchased from Sigma Aldrich (USA). A sodium carbonate and tartrate solution was

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prepared by dissolving 200 g Na2CO3 and 12 g Na2C4H4O6·2H20 in 750 mL of hot ultrapure (Elga Option-q,

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USA) water. The solution was cooled down to 20 °C, then adjusted to 1 L with ultrapure water. The

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calibration curve was constructed with pure phenol in crystals from Carlo Erba Reagenti (Italy).



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Spectrophotometric measures were acquired with a Photolab 6600 UV-Vis spectrophotometer from WTW

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(Germany).

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2.1 Analytical procedure

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Raw samples were accurately weighed and mixed with diluting agent at a dilution ratio of 1:20 by weight.

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This ratio was previously reported to be the most effective for COD analysis 37. The salt-sample mixture was

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finely crushed in a ceramic mortar until no particles were visible anymore. The overall dilution procedure

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was similar to that described to be effective for COD by Noguerol-Arias et al. 37, except for the choice of

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diluting agent. Instead of magnesium sulfate, which forms a precipitate of magnesium carbonate after

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adding sodium carbonate and tartrate solution, we used sodium sulfate anhydrous, and no precipitation

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was observed. The homogenized samples were divided into aliquots expected to have TP concentrations

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within the linear range of the method (i.e. 0.25-2.5 mg/L). These aliquots (≈100 mg each) were accurately

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weighted on a microbalance (Mettler-Toledo, Switzerland) and suspended in water for a final volume of 50

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mL. For the traditional method, separate raw samples, which had not been subjected to SD were finely

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homogenized in the ceramic mortar. For testing, aliquots (≈5 mg each) expected to have TP concentrations

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similar to the ones previously prepared were suspended in water. All the suspensions were maintained in

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perfect mixing conditions and continuously stirred with magnetic stir-bars during sample withdrawal for the

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F-C testing procedure. In a 2.5 mL disposable spectrophotometry cuvette, we added in sequence 2 mL of

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the described suspension and 15 µL of F-C reagent. The mixture was shaken upside-down by hand to

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ensure the reagent dissolved uniformly. Finally, 600 µL of the tartrate and carbonate solution was added,

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and the sample was mixed again. A bright blue colour developed as a function of the amount TP present in

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the sample.

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When the 2 mL sample was withdrawn from the flask, the mixture was continuously stirred with magnetic

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stir-bar to ensure that the suspended particles did not settle. However, immediately after mixing in the

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cuvette, a residue was visible due to incomplete solubilisation of the compound. Therefore, samples were


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filtered before absorbance reading (λ=700 nm). We selected a filter that would minimize loss in the

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absorbance read. We tested various filtering pore sizes and materials (laboratory filter paper, glass fibers,

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glass wool, polypropylene, cellulose acetate, regenerated cellulose, TFE). Among these, we found that the

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mixed cellulose ester with a pore size of 0.8 µm provided the least reduction absorbance. Absorbance

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measured after filtering was less than 0.01 compared to the unfiltered sample in case of phenol standards.

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The overall procedure is summarized in Fig. 1.

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Figure 1 near here

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We also evaluated the time required to reach a complete reagents reaction. After 15 min triplicate

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measurements of a single cuvette showed a high variation, and the absorbance continued to increase,

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which indicated that the reaction was incomplete. After 30 min, the measurements showed consistency.

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Hence we filtered the samples and measured the absorbance after a 30 min reaction time. To exclude any

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deviation from the Lambert Beer law due to differently speciated phenols F-C reaction kinetics as reported

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by Magalhães, et al. 40, we also verified that absorbance remain stable for at least 2 hours after the reading.

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Potential interference from the added sodium sulfate was excluded by comparing the absorbance of

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solutions prepared with and without added salt to the absorbance of pure phenol and a commercial sample

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of soluble lignin (Carlo Erba Reagenti, Italy). We found that the linearity interval of the method was

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between 0.25 to 2.5 mg/L of phenol. We constructed a seven-point calibration curve within this linear

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interval with increasing concentrations of phenol standards (Fig. 2).

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Figure 2 near here

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We prepared eight replicates of the suspensions of the raw homogenized sample (traditional method) and

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eight replicate suspensions of the SD sample (test method). Each suspension was analysed in triplicate by

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the described F-C assay, for total 48 analyses for each of the tested matrices. Results were compared

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between the two methods (traditional and SD).

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2.2 Statistical analysis

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To compare phenol concentration measurements between the two different methods (i.e. the traditional

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method with water dilution and the new method with SD), we performed a statistical analysis of

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experimentally collected data as follows: A normal distribution was plotted for each sets of data; a Grubbs’

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test was performed to remove data affected by experimental errors; a Student’s t-test was performed to

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verify that the data sets obtained with the two methods were significantly different.

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3. Results and discussion

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The proposed SD method was successfully implemented to quantify the TP content in all tested solid

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matrices. However, we encountered several differences in precision and accuracy among samples prepared

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according the SD method.

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None of the experimentally collected values were excluded with Grubbs’ test, because none were

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statistically out of range. The results comparing the two preparation methods are shown in Fig. 3a-c and

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summarized in Table 1.

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The normal distributions of phenol values measured with the two methods were clearly different (Fig. 3 a-

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c). The difference was statistically significant, based on the t-test, (Table 1). Thus the two methods

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generated values that belonged to different populations.

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Table 1 near here

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Our results clearly showed that diluting the sample with salt drastically increased the recovery of phenols

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for the F-C assay. A comparison of the average TPs (Table 1) showed that for all substrates, the

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concentration recovered with the SD process was substantially greater than the one obtained with the

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traditional method (41.4, 15.5, 59.4 % recovery increases for RS, PS and FW, respectively). These findings

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indicated that the traditional method, where the solids are only suspended in water, tends to

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underestimate the actual phenolic compounds content. With the SD method, more accurate estimate was ACS Paragon Plus Environment

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achieved. This may be due to an improvement in the homogenization of the targeted substance. The added

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salt may increase the efficiency of breaking up macroscopic particles, because during homogenization, the

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salt crystals may act as micro-blades, finely crumbling even high compressive strength substrates, such as

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lignocellulosic materials 37. The smaller particles could disperse better when suspended in water and allow

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more efficient contact between the phenolic components and the reagents. Another possible explanation

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may be related to the very high salinity, which can expose the hydrophobic core of organic matter 41

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Kosmotrope anion sulfate is reported to cause such effect in organic macromolecules 42. Hence sulfate

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interaction with macromolecules surface could expose the core and the phenols within, which would

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otherwise be sequestrated away from the water phase and thus inaccessible to the reagent. On the other

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side the presence of sodium sulfate could give place to an increased solubilisation of sparingly soluble

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humic-like salts due to the well-known inert-electrolyte effect 43.

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The standard deviation of the RS substrate measurement was much lower in the SD method than in the

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traditional method. In fact, the standard deviation value for the SD method was nearly half the value

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obtained with the traditional method. In the PS sample, the difference between methods was slightly less,

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but the SD method (Fig. 3b) displayed less dispersion in the data (i.e. higher precision). Conversely, for the

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FW substrate (Fig. 3c), the standard deviations value obtained with the SD method showed slightly greater

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data dispersion (i.e. lower precision) than that obtained with the traditional method, although the values

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were comparable. On the other hand, when compared the coefficients of variation (σ* in Table 1), the SD

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method displayed more precision than the traditional method. As expected a higher variance was observed

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in the FW values compared to the other tested matrices, due the greater heterogeneity in FW (both in

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composition and in macroscopic shape) than the other tested matrices. The simultaneous presence of

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different organic macromolecules 39 (i.e. carbohydrates, proteins, lipids) which could give rise to higher

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uncertainties in the sampling phase 37.

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Figure 3(a-c) near here



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Concerning the reported improvement in data distribution, the obtained results were comparable with

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those reported by Noguerol-Arias et al. 37, who applied the SD method to COD analysis. The authors applied

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the SD method to a certified reference material, and obtained a reduction of σ* ranging from 0.104 to

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0.014. When the SD method was applied to “real” pig slaughterhouse waste samples, the authors obtained

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an average reduction of σ* from 0.27 to 0.08. Here we verified that the SD method applied to TP measures

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reduced the relative standard deviation in all tested samples. The reduction ranged: i) from 0.25 to 0.05 for

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RS; ii) from 0.13 to 0.09 for PS; and iii) from 0.48 to 0.23 for FW (Table 1).

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It is worth noting that COD analysis does not depend on oxidizable matter solid/liquid fractionation in the

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matrix, therefore the SD method applied to COD simply allows to withdraw a greater amount of sample,

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increasing its representativeness and improving the precision and the accuracy of the estimate. In contrast

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TP analysis has intrinsically a high variance and is subject to several interferences 24. The aim of the present

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work was to obtain a quantification of TP in very complex matrices, regardless their fractionation. This

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meant that the F-C reagent had to interact with phenols bound to suspended particles or sequestrated in

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hydrophobic moieties and micelles. Although several published studies and protocols suggest to perform F-

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C assay on sample extracts to increase precision 1, 23-25, 44, our results ascertain that a complete analysis of

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the matrix “as is”, except for the only SD preparation, provides more accurate results due to the higher

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recovery obtained.This is consistent with what was previously reported by the developers of QUENCHER

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methods with some main conceptual difference to be highlighted. QUENCHER F-C method uses the F-C

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reaction to “solubilize phenols” exploiting the oxidation capabilities of F-C reagent 33. The issue faced in this

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work was simply that, insoluble phenols, although capable of reacting with the Folin reagent when

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suspended, might be not easily accessible to the reagent. To the total effectiveness of the F-C method, the

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phenols extraction yield and their consequential dissolution are merely uninfluential. In other words, the

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oxidation of phenolic functions by F-C reagent does not necessarily imply their dissolution but certainly

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provokes the reduction of F-C which finally allows better TP detection. In the light of what was discussed

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above, the main point affecting the F-C assay recovery becomes the accessibility of oxidizable functions to

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the reagent, which is demonstrated to be enhanced by the solid dilution procedure discussed in the present


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study. These results showed good reproducibility and acceptable relative standard deviation even for very

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heterogeneous samples. The work done presents several possible future developments. SD dilution might

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be successfully applied as a sample preparation method for other analytical techniques available in the

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literature and directed to TP quantification (i.e. ABTS 29, CUPRAC 30, silver 25, gold nanoparticles33, and many

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others 22). Further improvement of the method might involve optimization of the particle size distribution

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of the pretreated samples. The particle size of the sample after the SD preparation certainly played primary

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role in the enhanced accessibility of phenolic compounds to the F-C reagent and hence improved its

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recovery. The smaller being the particle size the higher the F-C reagent effectiveness against bound

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phenols. Particle size after homogenization strongly depends on the analyzed matrix. In this study we tried

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to homogenize the sample as better as it was possible with “basic laboratory equipment”. It is reasonable

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to retain that using more advanced homogenization techniques (i.e. Polytron homogenizer, spheres mill

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etc.) would further reduce the particle size while increasing the recovery and precision of the method.

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In conclusion, the study has highlighted some aspects of new SD preparative method for measuring

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phenolic compounds in solid and semisolid matrices, which make this method preferable compared to the

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traditional one. The SD sample preparation method reduced time for performing analyses, because it did

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not require the extra time needed to solubilize or extract in water and other solvents phenolic compounds.

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Moreover, for all the substrates, (i.e. RS, PS and FW), the SD method yielded higher concentrations of

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phenolic compounds than the traditional method. This was probably due to the effect of salt addition that

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improved sample homogenisation and disrupted hydrophobic aggregates, favouring the contact of

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sequestrated phenols with the F-C reagent. This result proved that the proposed method was more

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accurate than the traditional method. Finally, the proposed method was also more precise than the

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traditional method, because exhibited less relative data dispersion for all the substrates tested. Although

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for FW the absolute standard deviation was higher than the traditional method, this result was not

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conflicting with our other findings, because the coefficient of variation was smaller with the SD method

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than with the traditional method. Furthermore, the wide dispersion in FW data could be reasonably

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attributed to the heterogeneity of the matrix investigated (i.e. FW) rather than method used.



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Acknowledgements

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The authors would like to thank the European Commission for providing financial support through the

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Erasmus Mundus Joint Doctorate Program ETeCoS3 (Environmental Technologies for Contaminated Solids,

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Soils and Sediments) under the grant agreement FPA n°2010–0009. This research was also conducted

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within the framework of the project “Emerging contaminants in soil and water: from source to marine

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environment”, which was funded by the Italian Ministry of Education, University and Research (MIUR) in

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the context of the Research Programmes of National Interest (PRIN) 2010–2011.

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14. Paramashivam, D.; Clough, T. J.; Carlton, A.; Gough, K.; Dickinson, N.; Horswell, J.; Sherlock, R. R.; Clucas, L.; Robinson, B. H., The effect of lignite on nitrogen mobility in a low-fertility soil amended with biosolids and urea. Sci. Total Environ. 2016, 543, 601-608. 15. Roosta, H.; Hosseinkhani, M.; Shahrbabaki, M. V., Effects of foliar application of nano-fertile fertilizer containing humic acid on growth, yield and nutrient concentration of mint (Mentha sativa) in aquaponic system. Journal of Science and Technology of Greenhouse Culture 2016, 6 (24), Pe1-Pe9, En10. 16. Komprdová, K.; Komprda, J.; Menšík, L.; Vaňková, L.; Kulhavý, J.; Nizzetto, L., The influence of tree species composition on the storage and mobility of semivolatile organic compounds in forest soils. Sci. Total Environ. 2016, 553, 532-540. 17. Tang, J.; Li, X.; Luo, Y.; Li, G.; Khan, S., Spectroscopic characterization of dissolved organic matter derived from different biochars and their polycylic aromatic hydrocarbons (PAHs) binding affinity. Chemosphere 2016, 152, 399-406. 18. Pontoni, L.; van Hullebusch, E. D.; Fabbricino, M.; Esposito, G.; Pirozzi, F., Assessment of trace heavy metals dynamics during the interaction of aqueous solutions with the artificial OECD soil: Evaluation of the effect of soil organic matter content and colloidal mobilization. Chemosphere 2016, 163, 382-391. 19. Pontoni, L.; van Hullebusch, E.; Pechaud, Y.; Fabbricino, M.; Esposito, G.; Pirozzi, F., Colloidal Mobilization and Fate of Trace Heavy Metals in Semi-Saturated Artificial Soil (OECD) Irrigated with Treated Wastewater. Sustainability 2016, 8 (12), 1257. 20. APHA, W., AWWA (1998) Standard methods for the examination of water and wastewater. Amer. Pub. Health Association. Washington DC 1998. 21. Waterborg, J. H., The Lowry method for protein quantitation. In The protein protocols handbook, Humana Press: Totowa, USA, 2002; pp 7-9. 22. Prior, R. L.; Wu, X.; Schaich, K., Standardized methods for the determination of antioxidant capacity and phenolics in foods and dietary supplements. J. Agric. Food Chem. 2005, 53 (10), 4290-4302. 23. Blainski, A.; Lopes, G.; de Mello, J., Application and Analysis of the Folin Ciocalteu Method for the Determination of the Total Phenolic Content from Limonium Brasiliense L. Molecules 2013, 18 (6), 6852. 24. Ainsworth, E. A.; Gillespie, K. M., Estimation of total phenolic content and other oxidation substrates in plant tissues using Folin-Ciocalteu reagent. Nat. Protocols 2007, 2 (4), 875-877. 25. Cicco, N.; Lanorte, M. T.; Paraggio, M.; Viggiano, M.; Lattanzio, V., A reproducible, rapid and inexpensive Folin–Ciocalteu micro-method in determining phenolics of plant methanol extracts. Microchem. J. 2009, 91 (1), 107-110. 26. Budini, R.; Tonelli, D.; Girotti, S., Analysis of total phenols using the Prussian Blue method. J. Agric. Food Chem. 1980, 28 (6), 1236-1238. 27. Eskin, N. A. M.; Hoehn, E.; Frenkel, C., A simple and rapid quantitative method for total phenols. J. Agric. Food Chem. 1978, 26 (4), 973-975. 28. Hinojosa-Nogueira, D.; Muros, J.; Rufián-Henares, J. A.; Pastoriza, S., New Method To Estimate Total Polyphenol Excretion: Comparison of Fast Blue BB versus Folin–Ciocalteu Performance in Urine. J. Agric. Food Chem. 2017, 65 (20), 4216-4222. 29. Serpen, A.; Capuano, E.; Fogliano, V.; Gökmen, V., A New Procedure To Measure the Antioxidant Activity of Insoluble Food Components. J. Agric. Food Chem. 2007, 55 (19), 7676-7681. 30. Tufan, A. N.; Çelik, S. E.; Özyürek, M.; Güçlü, K.; Apak, R., Direct measurement of total antioxidant capacity of cereals: QUENCHER-CUPRAC method. Talanta 2013, 108 (Supplement C), 136-142. 31. Del Pino-García, R.; García-Lomillo, J.; Rivero-Pérez, M. D.; González-SanJosé, M. L.; Muñiz, P., Adaptation and Validation of QUick, Easy, New, CHEap, and Reproducible (QUENCHER) Antioxidant Capacity Assays in Model Products Obtained from Residual Wine Pomace. J. Agric. Food Chem. 2015, 63 (31), 6922-6931. 32. Özyürek, M.; Güngör, N.; Baki, S.; Güçlü, K.; Apak, R., Development of a Silver Nanoparticle-Based Method for the Antioxidant Capacity Measurement of Polyphenols. Anal. Chem. 2012, 84 (18), 8052-8059. 33. Karadirek, Ş.; Kanmaz, N.; Balta, Z.; Demirçivi, P.; Üzer, A.; Hızal, J.; Apak, R., Determination of total antioxidant capacity of humic acids using CUPRAC, Folin–Ciocalteu, noble metal nanoparticle- and solid– liquid extraction-based methods. Talanta 2016, 153 (Supplement C), 120-129.



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381 382 383 384

Figure 1 General scheme of the proposed procedure: a) sample homogenisation with (Test model) and without SD (Traditional model); b) addition of the F-C reagents to the water suspension; c) reaction time; d) 0.8 µm filtration; e) absorbance reading at 700 nm.

b)

a) c)

d) 385 386 387 ACS Paragon Plus Environment

e)

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Page 15 of 20

388 389 390


Figure 2 Phenol calibration curve. Phenol standards of known concentrations were measured on a spectrophotometer to determine the absorbance at 700 nm after 30 min reaction time and 0.8 µm filtration. Each point represents the average of three measurements.

391 0.30

Absorbance [AU]

0.25

y = 0.0944x + 0.0127 R² = 0.9989

0.20 0.15 0.10 0.05 0.00 0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75

Phenol [mg/l]

392 393 394 395



396 397 398

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Figure 3. Normal distribution of phenol measured in: RS (a); PS (b); FW (c). The two different methods were compared. We represented Traditional method with triangles and dotted lines and SD method with squares and continue lines.

399

a) 1.2 traditional method SD method

1.0

data from traditional method data from SD method

0.8 f(x) 0.6 0.4 0.2 0.0 0.0

1.0

2.0

3.0

4.0

5.0

x 400 401 402 403 404 405 406 407 408 409 410


6.0

7.0

8.0

9.0

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b) 0.7 traditional method

0.6

SD method data from traditional method

0.5

data from SD method

0.4 f(x) 0.3 0.2 0.1 0.0 0.0

2.0

4.0

6.0

x 411 412


8.0

10.0


Page 18 of 20

c) 0.4 traditional method

0.4

SD method data from traditional method

0.3

data from SD method

0.3 f(x) 0.2 0.2 0.1 0.1 0.0 -2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

x 413 414

Table 1. Main values of TP for the investigated matrices compared between two preparation methods.

Sample

Sample preparation

Number of tests

TP g/Kg

σ2

s

σ*

Traditional

24

4.239

1.167

1.080

0.25

t-test

2.51×10-13

RS Test (SD)

24

7.219

0.146

0.382

0.05

Traditional

24

5.961

0.624

0.790

0.13 1.47×10-5

PS Test (SD)

24

7.053

0.390

0.625

0.09

Traditional

24

2.422

1.379

1.174

0.48 1.66×10-11

FW Test (SD)

24

6.016

1.839

1.356

TP = Total phenols; RS = rice straw; PS = peat rich soil; FW = food waste; SD = solid dilution 2 σ = variance s= standard deviation σ*= coefficient of variation

415


0.23

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416



417

TOC Graphic

418


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Modified Sample Preparation Approach for the Determination of the

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