Extraction of Pectin from Citrus Sinensis Peels ...jakraya.com/journal/download.php?file=1-epArticle_1.pdf · concluded that the Nigerian citrus sinensis peel is a potential source

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ORIGINAL ARTICLE

Extraction of Pectin from Citrus Sinensis Peels: Optimization Using Statistical Experimental Design Igbokwe K. Philomena and Udokwelu Ogochukwu* Nnamdi Azikiwe University Awka, Nigeria. *Corresponding Author: Udokwelu Ogochukwu Email: [email protected] Received: 28/12/2017 Accepted: 11/01/2018

Abstract In the present study, peels and pectin extracted from the Nigerian

citrus sinensis peel was investigated for their physic-chemical characteristics. The yields of pectin from the citrus peels were optimized using the Response Surface Method (RSM) via the Central Composite Design (CCD) and the process variables were extraction temperature (50-90ºC), extraction pH (1-4.2), extract to ethanol ratio (EER) (1:0.5-1:2) and extraction time (30-120 minutes). The results of the physio-chemical characterization revealed that the Nigerian citrus sinensis peels has moisture content (11%), ash (2.33%), titratable acidity (0.23%), crude protein content (3.68%), reducing sugars (2.24%), total sugars (4.42%), and fat content (0.43%). The pectin has an average moisture content (9.23%), pH 4.5 (for high-methoxyl, HM) pectin), pH 2.5 (for low-methoxyl, LM) pectin), ash content (1.04%-1.096%), protein content (1.62%-3.33%), acetyl content value (1.20%-1.344%), methyl content value (0.992%-12.245%). The values of the methoxyl content of the citrus pectins extracted at different extraction condition revealed that the Nigerian citrus pectin could be classified into HM and LM pectin. The optimization results show that temperature, pH, EER and time strongly influenced the pectin yield. The optimized conditions for the extraction of HM-pectin and LM-pectin were (temp., (90ºC), pH 1; EER 0.53; extraction time (120 min)) and (temp., (70ºC), pH 2.6; EER 1.25; extraction time (75 min)), respectively. The optimum yield for LM and HM pectin were 45.66% and 2.8%. The experimentally validated pectin yields were 55% and 5.9% for LM and HM pectin, respectively. The pectin yield value, moisture content, pH, Degree of acetylation (DAc), methoxyl content (meO%), the ash content and the protein content values indicate that the pectin extracted from the Nigerian citrus sinensis peels is suitable for industrial application. Hence, it can be concluded that the Nigerian citrus sinensis peel is a potential source of pectin for commercial purpose. Keywords: Citrus-sinensis peels, Pectin, Extraction, Optimization.

1. Introduction Pectin, chemically, is a polysaccharide present

in cell walls of all land plants, in different quantity or amount. Pectin is produced commercially in the form of white to light brown powder used in food as a gelling agent particularly in jams and jellies. It is also used in fillings, sweets, as a stabilizer in fruit juices and milk drinks and as a source of dietary fiber (Tobias et al., 2011; Kanmani et al., 2014). Several studies have reported novel pectin usages, like biodegradable water-soluble films, bulking agents, coating agents, chelators, emulsifiers and viscosity modifiers (Kanmani et al., 2014). Arantzazu et al. (2015) reviewed the properties

and possible applications of pectin in the manufacture of edible films for food packaging. Pectin is a texturing agent in the food industry (Rascón-Chu et al., 2009; Pek-Yee et al., 2011). It has been widely applied as thickening, gelling and emulsifying agents for jams, soft drinks, fish and meat products, fruit juice, desserts and dairy products (May, 1990; Ralet et al., 2005; Pek-Yee et al., 2011). Pectin is also useful in medicinal applications, in which it helps in lowering serum cholesterol level, removing heavy metal ions from the body, stabilizing blood pressure and restoring intestinal functions (Voragen et al., 1995; Pek-Yee et al., 2011) and helping in weight reduction (Jitpukdeebodintra and

Ogochukwu and Philomena…Extraction of Pectin from Citrus Sinensis Peels: Optimization Using Statistical Experimental Design


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Jangwang, 2009; Pek-Yee et al., 2011). Other medical uses are anti-diarrhea, detoxification and blood glucose reducer (Voragen et al., 1995; Quoc et al., 2015). Savary et al. (2003) reported the worldwide annual consumption of pectin at approximately 45,000 tones yearly, which occupies the global market value of at least 400 million Euros (Quoc et al., 2015). With the growing demand for products in food science and nutrition, cosmetics and pharmaceutics (Pilnik, 1990; Pek-Yee et al., 2011), worldwide pectin consumption grows constantly and has already exceeded 20,000 tons a year (Ptichkina et al., 2008; Pek-Yee et al., 2011).

Among other polysaccharides that are extracted from plant materials, pectin is an extremely complex polysaccharide (Quoc et al., 2015). The amount, structure and chemical composition of the pectin differs between plants, within a plant over time and in different parts of a single plant (Krishnamurthi et al., 2003; Kanmani et al., 2014). There are many sources of pectin in nature such as pomelo peel, apple pomace, citrus peel, sugar beets, dragon fruit peel, and sunflower heads (Quoc et al., 2015).

The citrus fruit is very rich in pectin and can be used as source for its production commercially (Salam et al., 2012). At present, commercial pectin are almost exclusively derived from citrus peel or apple pomace, both of which are by-products of juice manufacturing units (Kanmani et al., 2014). Usually, dried lemon (Masmoudi et al., 2008; Pek-Yee et al., 2011) or orange peel (Rezzoug et al., 2008; Pek-Yee et al., 2011), citrus albedo (Liu et al., 2006; Pek-Yee et al., 2011) and apple pomace (May, 1990; Pek-Yee et al., 2011) are the main raw materials that have been utilized in pectin production all around the world. Recently, non-traditional pectin sources such as cocoa husk (Mollea et al., 2008; Pek-Yee et al., 2011) and banana peel (Emaga et al., 2007; Pek-Yee et al., 2011) have been investigated (Pek-Yee et al., 2011). Although pectin occurs commonly in most of the plant tissues, the number of sources that may be used for commercial manufacture of pectin is limited. This is because the ability of pectin to form a gel depends on molecular size and the degree of esterification (DE). The extracted pectin can be categorized into two major types depending on its degree of esterification (DE): high-methoxyl pectin (HMP, >50% DE) and low-methoxyl pectin (LMP, <50% DE) (Kanmani et al., 2014). The methoxyl content is an important factor in controlling the setting time of pectin and ability of pectin to form gel (Constenla and Lozano, 2003; Mohamed, 2016). The methoxyl content of pectin vary with the source of raw material used, the method used for extraction (Mohamed, 2016) and in addition to the method, the operating conditions employed. Furthermore, pectin has a very complex structure

which depends on both its source and the extraction process (Leroux et al., 2003), the georgraphical location and the extraction conditions.

Commercially, pectin is extracted by treating the raw material with hot dilute mineral acid at suitable pH, for 2-4 h duration and pectic substances are precipitated using ethanol or isopropyl alcohol (Joye and Luzio, 2000; Kanmani et al., 2014). The precipitated pectin is separated and washed with alcohol to remove impurities. It is dried, ground to a powder and blended with other additives, if necessary (Kanmani et al., 2014).

The citrus sinensis peel was selected in this study as a representative of the citrus fruit family to extract pectin because of the abundance of the fruit in Nigeria. Currently, the available information on recovery of pectin from citrus sinensis peel is very scarce and limited. To the best our knowledge no work has been done on the optimization of pectin extraction from citrus sinensis peels. The enormous importance of pectin in industry justifies a great deal of basic research to understand the favourable and optimum process conditions for the optimum extraction of pectin from citrus sinensis peels.

The present investigation aims to extract pectin from the Nigerian citrus sinensis peels using citric acid; to optimize the yield of pectin using Response Surface Methodology (RSM); and to characterize the extracted pectin by both qualitative and quantitative methods, to evaluate its potential for industrial application.

2. Materials and Method

2.1 Materials

2.1.1 Citrus Sinensis Peels These were purchased from Orange vendours in

Eke Awka Market in Awka, Anambra state, Nigeria.

2.1.2 Reagents and Chemicals Majority of the cosmetic raw materials

including Emulsifying wax, stearic acid, vitamin E, Glycerin, and preservative which were of cosmetic grade were purchased from Saffire Blue Inc., Canada, disodium EDTA, Citric acid, Absolute Ethanol, Aloe Vera Extract, Titanium dioxide, Isopropyl Myristate, Sodium Chloride, Magnesium Sulphate Pentahydrate, Sulphuric acid and Hydrochloric acid were of analytical grade and purchased from local vendors in Onitsha, Anambra State. All were used without any further treatment or modification.

2.2 Method 2.2.1 Physicochemical Analysis of Citrus Sinensis

Peels



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Proximate analysis were carried out on the peels to determine their nutrient and non-nutrient constituents including moisture and ash content, crude protein content, titratable acidity, reducing and total sugar content. 2.2.1.1 Moisture Content Determination

1g±0.01 of peel was weighed on a Sartorius acculab precision weighing balance and placed in an aluminium petri dish and dried in a Haraeus W6100 hot air oven for 4 hours at 1000C±30C, cooled to room temperature in a desiccator and then weighed. The moisture content was computed thus: Moisture content % =

(W1-W2) Weight of the residue) x 100

(W1-W) Weight of the sample) Where, w1 = weight in gram before drying, w2 = weight in gram after drying, w = weight in gram of the empty dish. 2.2.1.2 Ash Content Determination

3g±0.01 of Orange peel was weighed on a Sartorius acclab precision weighing balance into dry weighed crucible and put into a carbolite muffle furnace set at 6000C for two hours after which the ash was cooled in a dessicator for 10 minutes. Weight of cooled ash and crucible was taken and ash content calculated as follows:

Ash content % =

(W3-W1) Weight of the ash) x 100 (W2-W1) Weight of the peel)

Where W1 is weight of the empty crucible, W2 is weight of empty crucible and peel and W3 is weight of ash and crucible. 2.2.1.3 Titratable Acidity

6g±0.01 of peels was weighed on a Sartorius acculab precision balance and thoroughly crushed in a commercial blender on high for 60 seconds and added to 10ml distilled water in a 250ml conical flask with 3 drops of phenolphthalein indicator and titrated with 0.1M sodium hydroxide to a pink end point. The titratble acidity was calculated based on citric acid as follows:

Titratable acidity % =

(Titre value ×0.007) x 100 (Weight of the peel)

2.2.1.4 Crude Protein Content Determination

This is carried out in four steps according to the Kjeldahl procedure; 2g±0.01 of thoroughly crushed orange peel is digested with 25ml concentrated

sulphuric acid in the presence of two Kjeldahl tablets as catalysts in a 500ml Kjeldahl flask to convert available nitrogen into ammonia. This ammonia is in the form of ammonium ion. The ammonium ion thus formed binds to the sulphate ion released and thus, remains in solution. This solution is allowed to cool and 200ml distilled water, 5 pieces of zinc metal and 20 beads of antibump are added.

The solution is further made alkaline by addition of 50% sodium hydroxide solution which converts the ammonium sulphate into ammonia gas. The ammonia gas is liberated from the solution by distilling using the Kjeldahl apparatus. About 150ml distillate is collected into a receiving flask which contains about 50 ml (2% w/v) boric acid solutions. The ammonium ion in the distillate binds to the borate ion released in the form of ammonium borate.

The Nitrogen content is then estimated by titration of the ammonium borate formed with 0.1M sulphuric acid using methyl orange as indicator. The concentration of hydrogen ions required to reach the end point is equivalent to the concentration of nitrogen that was in the peel and is calculated thus:

Nitrogen % =

(Titre value ×0.0014) x 100

(Weight of the peel)

The protein content is calculated as: Protein content % = Nitrogen % × 6.25 2.2.1.5 Reducing Sugar Content Determination

In a 250ml conical flask containing 5ml each of zinc acetate and potassium ferrocyanide, 30g±0.01 of thoroughly crushed orange peels were added and total volume made up to the mark with distilled water and allowed to seep for 5 minutes. The mixture thus obtained is filtered into another 250ml conical flask using a muslin cloth. 25ml of filtrate is put into a 25ml burette and titrated with fehlings solutions I and II on a hotplate stirrer; until brick red colouration is observed. Reducing sugar is calculated thus:

Reducing Sugar % =

Vol. of flask × titre value factor equivalent × 1 x 100

weight of peel × titre value × 1000

2.2.1.6 Total Sugar Content Determination

50ml of filtrate from reducing sugar analysis is pipette into a clean, dry 100ml volumetric flask. 5ml of concentrated HCl is added into the flask. The mixture is covered and swirled gently and allowed to stand overnight to hydrolyze all the disaccharides in the peel to monosaccharides. 3 drops of phenolphthalein



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indicator is added after 24 hours and neutralized with 5ml of 5N NaOH. The neutralized solution is made up to the 100ml mark of the volumetric flask with distilled water and titrated with mixed fehling’s solution to brick red colour endpoint. Total sugar is calculated thus:

Total Sugar % =

Vol. of flask × titre value factor equivalent × 1 x 100 x 100

weight of peel × titre value × 1000 x 50 ml

2.2.2 Extraction Process 2.2.2.1 Peels Preparation

Fresh peels weighing about 2000g were manually reduced to size, washed severally with distilled water until effluent water was pale green and dried in a Heraeus W6100 oven between 400C-600C ±30C. Dried peels were further reduced to size in a laboratory dry blender commercial heavy duty set at medium for 30 seconds to a consistency intermediate to coarse and fine (to avoid clumping during solvent extraction). 2.2.2.2 Pretreatment (Alcohol Insoluble Solid)

2000g±0.1 dried, crushed peels from peels preparation above were treated with 5000ml 96% ethanol according to the method employed by Yordan et al. (2012) with slight modification. The dried peels-in-ethanol mixture was preheated to 650C. The mixture is kept for 1h at 650C and additionally for 24 hours at room temperature, then filtered with double folded muslin cloth. The resulting residue was washed twice with normal 96% ethanol and dried at 500C±30C in a Heraeus W6100 hot air oven. The AIS thus obtained was stored at room temperature until use. 2.2.2.3 Pectin Extraction

Pectin extraction was conducted according to Khule et al. (2012), with slight modifications. Citric acid in distilled water solutions of desired pH values 1, 2.6 and 4.2 was prepared using a Jenway 3505 pH meter. Orange AIS weighing 30g±0.01 each are mixed with 300ml solution and heated in a Stuart SBB28 water bath at temperatures 500C, 700C and 900C for 30mins, 75mins, and 120mins. The solutions were allowed between 10-15 minutes to reach said temperatures before timing. The temperatures were regulated with a digital thermometer. After heating, solutions were immediately brought to cool in another water bath filled halfway with ice cold water to reduce any further reaction and filtered with a double muslin cloth. 80% ethanol is added to the filtrate and allowed to stand overnight to facilitate filtration of pectin.

Thick jelly-like pectin was simply scooped off, washed twice with 70% and 96% ethanol while watery jelly-like pectin was centrifuged at 4000rpm for 1 hour at 100C in a Heraeus Megafuge 1.0R. Obtained pectin was treated as before and all dried at 500C for at least 2 hours in a hot air oven. Dried pectin is grounded and yield calculated as follows:

Pectin Yield % =

Weight (g) of dried pectin x 100 weight (g) of dried AIS used in

extraction

2.2.3 Optimization of Pectin Extraction 2.2.3.1 Experimental Design and Statistical Analysis

Statistical optimization was used to investigate the effects of different independent variables and their interactions, on the response, pectin yield (Y).

A response surface experimental design (RSM), with four independent variables, was used to determine the optimum processing conditions for pectin extraction from citrus peel. The variables used were extraction temperature (50-90°C), extraction pH (1-4.2), extract to ethanol ratio (1:0.5-1:2) and extraction time (30-120 minutes).

The levels of each variable were selected based on literature (Rolin, 2002) and preliminary experiments (Kanman et al., 2014; Li et al., 2013).

Actual values of the experimental design for the optimization of the pectin extraction are shown in Table 2. One response yield of pectin was measured for optimization. Yield was defined as the percentage of the extracted dried pectin to total dry matter of the orange peel used for extraction. The experimental design comprised of a total of 30 experiments with 6 center points and 24 factorial points. The experiments were performed in random order. Design and data analysis were carried out using Design Expert statistical software.

The analysis of variance (ANOVA) was performed to validate the models for the process optimization. The optimal extraction conditions were estimated through regression analysis and three-dimensional response surface plots of the independent variables and each dependent variable.

The experimental design consisted of a set of points lying at the midpoint of each edge and the replicated center point of a multidimensional cube. The polynomial equation generated by the software is as follows: Yi = b0 + b1X1 + b2X2 + b3X3 + b12X1X2 + b13X2X3 +

b11X11 + b22X22 + b33X33 … (1) where, Y is the dependent variable, b is the intercept,



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b1 to b33 are the regression coefficients and X1 to X33 are the independent variables (Kanman et al., 2014). The experimental design set up is summarized in Table 1.

2.2.4 Characterization of Pectin The extracted pectin was characterized in terms

of moisture content, ash content, methoxyl content, degree of acetylation, intrinsic viscosity and molecular weight. The dried pectin samples obtained from orange peels were subjected to the following quantitative and qualitative tests in order to characterize them.

2.2.4.1 Color This was done by visual observation.

2.2.4.2 Qualitative Test for Pectin Test for pectin was carried out according to USP

(2007) standard method.

2.2.4.2.1 Stiff Gel Test 1g±0.01 of desirable pectin was heated with 9ml

of water in a water bath till a solution I formed. On cooling, stiff gel formation is taken as positive.

2.2.4.2.2 Test with 95% Ethanol On adding an equal volume of 95% ethanol to

1% w/v desirable pectin solution, the formation of a translucent, gelatinous precipitate (distinction from most gums) is a positive indication of pectin. 2.2.4.2.3 Test with Sodium Hydroxide and

Hydrochloric Acid 1ml of 2N NaOH was added to 5ml of a 1% w/v

solution of desirable pectin solution and set aside for 15 minutes. The gel produced after 15 minutes was acidified with 3N HCl and shaken well which produces a voluminous, gelatinous precipitate. This precipitate upon boiling becomes white and flocculent indicating the presence of pectic acid. 2.2.4.3 Moisture Content Determination

One gram of pectin sample was weighed and placed into a dried and weighed glass petri dish. The sample was dried in an oven for 4 hours at 100°C, cooled to room temperature in a desiccator and then weighed. This sample was not used for subsequent measurement, as pectin tends to degrade in the process (Owens et al., 1952). One percent was added to the moisture percent observed to obtain agreement with the Fischer method (Johnson, 1945). The moisture content was computed thus:

Moisture content % =

(W1-W2) Weight of the residue x 100 (W1-W) Weight of the sample

Where, w1 = weight in gram before drying, w2= weight in gram after drying, w = weight in gram of the empty dish. 2.2.4.4 Ash Content Determination

1g±0.01 of pectin was weighed into a crucible, and then heated in a muffle furnace at 600°C for 4 hours. The crucible was cooled to room temperature in a desiccator and weighed (Owens et al., 1952). The ash content was determined as follows:

Ash content % =

(W1-W2) Weight of the Ash x 100 (W1-W) Weight of the sample

Where, W1 is weight of the empty crucible, W2 is weight of empty crucible and peel and W3 is weight of ash and crucible. 2.2.4.5 Methoxyl Content (MeO) (Titration B)

25 ml of 0.25 M NaOH was added to the neutralized solution (Titration A) and the mixture was stirred thoroughly and allowed to stand for 30 min at ambient temperature in a stoppered flask. 25 ml volume of 0.25N HCl (or an amount equal to the base) was added. The resulting mixture was titrated with 0.1N NaOH to the same end point as earlier (Kanman et al., 2014; Norziah et al., 2000; Owens et al., 1952; Hinton, 1940) and the methoxyl content calculated thus:

MeO % =

Molarity of NaOH × Titre value × 31 x 100 Weight of pectin sample

Where, 31 is the formular weight of Methoxyl (CH3O). 2.2.4.6 Acetyl Content

Degree of acetylation (DAc) was determined using the Clarke method. 0.5g±0.01 of pectin was weighed into a 250ml conical flask containing 25ml 0.1N NaOH. The flask was stoppered and its content shaken vigorously to ensure complete mixing. The flask was set aside for at least 1 hour and its content diluted to 50ml with distilled water. 20ml aliquot was with drawn and placed in a steam distillation apparatus. 20ml of magnesium sulphate-sulphuric acid solution (100g magnesium sulphate pentahydrate and 0.8ml sulphuric acid diluted to 180ml with distilled water) was added.

The solution was steam distilled and about 100ml distillate collected while keeping the volume in the distillation flask low. The acetic acid collected is titrated with 0.05N NaOH to a phenol red endpoint. A blank titration on distilled was carried out and acetyl content determined thus:



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Table 1: Actual and coded values of variation levels

Design Summary Study Type: Response Surface Runs: 30 Initial Design: Central Composite Design Model: Quadratic Factor Name Units Low Actual High Actual Low Coded High Coded Mean

X I Temp. oC 50 90 -1 1 70 X2 Ph 1 4.2 -1 1 2.6 X3 Extract to ethanol ratio 0.5 2 -1 1 1.25 X4 Extraction time Min 30 120 -1 1 75

Table 2: Experimental design for the optimization of the pectin extraction

Factor 1 Factor 2 Factor 3 Factor 4

Run A:Temp.( oC) B:Ph C:Extract to ethanol ratio D:Extraction time (Min) 1.00 90.00 1.00 2.00 120.00 2.00 70.00 2.60 1.25 75.00 3.00 90.00 4.20 0.50 120.00 4.00 70.00 2.60 1.25 75.00 5.00 47.72 2.60 1.25 75.00 6.00 50.00 4.20 0.50 120.00 7.00 70.00 2.60 1.25 24.86 8.00 50.00 1.00 2.00 120.00 9.00 50.00 1.00 0.50 30.00 10.00 70.00 4.38 1.25 75.00 11.00 50.00 1.00 0.50 120.00 12.00 90.00 1.00 0.50 30.00 13.00 70.00 2.60 2.09 75.00 14.00 50.00 4.20 0.50 30.00 15.00 50.00 4.20 2.00 120.00 16.00 70.00 2.60 1.25 75.00 17.00 70.00 2.60 0.41 75.00 18.00 90.00 1.00 0.50 120.00 19.00 90.00 1.00 2.00 30.00 20.00 70.00 0.82 1.25 75.00 21.00 70.00 2.60 1.25 125.14 22.00 50.00 1.00 2.00 30.00 23.00 50.00 4.20 2.00 30.00 24.00 92.28 2.60 1.25 75.00 25.00 90.00 4.20 0.50 30.00 26.00 70.00 2.60 1.25 75.00 27.00 70.00 2.60 1.25 75.00 28.00 90.00 4.20 2.00 120.00 29.00 70.00 2.60 1.25 75.00 30.00 90.00 4.20 2.00 30.00

Acetyl content =

Normality of NaOH × Titre value × 4.3

Weight of pectin in the aliquot (g) 2.2.4.7 Protein Content Determination

This was carried out in four steps according to the Kjeldahl procedure; 2g±0.01 of thoroughly crushed orange peel is digested with 25ml concentrated

sulphuric acid in the presence of two Kjeldahl tablets as catalysts in a 500ml Kjeldahl flask to convert available nitrogen into ammonia. This ammonia is in the form of ammonium ion. The ammonium ion thus formed binds to the sulphate ion released and thus, remains in solution. This solution is allowed to cool



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and 200ml distilled water, 5 pieces of zinc metal and 20 beads of anti-bump are added.

The solution is further made alkaline by addition of 50% sodium hydroxide solution which converts the ammonium sulphate into ammonia gas. The ammonia gas is liberated from the solution by distilling using the Kjeldahl apparatus. About 150ml distillate is collected into a receiving flask which contains about 50 ml (2% w/v) boric acid solutions. The ammonium ion in the distillate binds to the borate ion released in the form of ammonium borate.

The Nitrogen content is then estimated by titration of the ammonium borate formed with 0.1M sulphuric acid using methyl orange as indicator. The concentration of hydrogen ions required to reach the end point is equivalent to the concentration of nitrogen that was in the peel and is calculated thus:

Nitrogen % =

(Titre value ×0.0014) x 100

(Weight of the peel)

The protein content is calculated as: Protein content % = Nitrogen % × 6.25 2.2.4.8 Intrinsic Viscosity Measurements and

Molecular Weight Determination Molecular weight of orange peel pectin (OPP) is

estimated from its intrinsic viscosity. Viscosities of dilute OPP solutions (1, 0.5, 0.25 and 0.125% w/v) in 0.1 M NaCl were determined using au-tube Ostwald viscometer at 27°±0.020C. The intrinsic viscosity ([η]) of pectin was determined by extrapolation of the Huggins equation plot. The viscosity-average molecular weight (Mv) was obtained according to the Mark-Houwink-Sakurada equation:

[η] = K(Mv)α

Where, [η] is intrinsic viscosity while K and α are constants for pectins, and assumed to be 1.4 × 10−6 and 1.4, respectively (Sayah et al., 2016). 2.2.4.9 pH Determination

Pectin solutions (1%w/v) were prepared and pH was determined with a Jenway 3505 pH meter whose glass electrode was calibrated with standard buffer solutions 4 and 7 at 280C, rinsed afterwards with distilled water before inserting into the pectin solutions and pH readings taken. 3. Results and Discussion 3.1 Physicochemical Analysis of Citrus Sinensis

Peels

3.1.1 Physicochemical Analysis The Nigerian citrus sinensis peels were analyzed

for different characteristic properties such as moisture, ash, titratable acidity, crude protein content, reducing sugars, total sugars, and fat content. The results of the analysis are presented in the table 3.

From the result of the analysis of orange peels used in pectin extraction presented in Table 3, the moisture content of citrus sinensis peel sample recorded was 11%. This is in close agreement with moisture content value of 10% for lime orange reported by Brigida et al. (2015).

The ash content value for the Nigerian citrus sinensis peel was 2.33%. This is in close agreement with the reported ash contents of orange peel (2.61%) (Nassar et al., 2008; Mohamed, 2016). Similarly, Annon et al. (2010) stated that orange by product powder consists of 3.43% ash (Mohamed, 2016). The ash content values for white type (1.50%) and red type (1.60%) grape fruit peel was reported by Mohamed, (2016), which were lower than the value of other researchers (Kohajdova et al., 2013; Annon et al., 2010) who reported that grapefruit peel comprises 3.55%, 3.7% ash respectively, and 12.8% ash content was reported for banana (Wachirasiri et al., 2009; Mohamed, 2016).

The crude protein and the fat content of the Nigerian citrus sinensis peel is 3.68% and 0.43%, respectively. Higher values has been reported for the protein and fat content value (9.1 and 2.6 g/100 g dry matter, respectively) for sweet orange (Kohajdova et al., 2013; Annon et al., 2010; Mohamed, 2016), and orange peel crude fat (4.53%) (Annon et al., 2010; Nassar et al., 2008; Mohamed, 2016).

The results revealed a titrable acidity value of 0.23% which is similar with the titrable acidity value of 0.22% for red type and 0.16% for white type grapefruit reported by Mohamed, (2016), which differs from the value of 0.74% as citric acid obtained by other researchers (Poore, 1934; Mohamed, 2016). This could be referred to the presence of a comparatively small amount of organic acids and salts in the peel of grapefruit (Sinclair, 1972; Mohamed, 2016).

In comparison with other fruit peels, the protein content value was higher than the white type (1.05%) and red type (1.15%) grape fruit peel reported by (Mohamed, 2016). Furthermore, the protein and fat content of the Nigerian citrus peel was lower than those of lemon peel (7 and 2.5 g / 100 g dry matter, respectively) (Kohajdova et al., 2013; Annon et al., 2010; Mohamed, 2016). The lemon peel was reported to contain crude fiber (15.18%) and protein (9.42%) and crude fat (4.98%) (Janat et al., 2012; Mohamed, 2016). Whereas for grapefruit peel it was reported to contains 4.9% crude fat (Nassar et al., 2008; Annon et



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al., 2010; Mohamed, 2016). The reducing sugar value recorded was 2.24% while the total sugar value determined was 4.42%. The total sugars (19.78% for white type and 18.89% for red type) and total reducing sugar (10.4% for white type and 10.2% for red type) values for the grape fruit peels was reported by Mohamed, (2016) which is in contrast with other researcher who reported lower value of 6.35% as reducing sugars (Poore, 1934; Mohamed, 2016).

The observed variation in all these reported results could be attributed to the type of soil, varieties, season, maturity and environmental changes (Mohamed, 2016).

Table 3: Analysis of orange peels used in pectin

extraction

Parameter Value Moisture content 11.00% Ash content 2.33% Titrable Acidity 0.23% Crude Protein content 3.68% Reducing Sugars 2.24% Total Sugars 4.42% Fat 0.43%

3.2 Optimization of the Process Parameters on

the Yield of Pectin Using Response Surface Methodology

The interactive effects of the four important factors which are temperature, pH, EER and extraction time were examined on pectin yield from citrus sinensis, and derive a model, using a Central Composite Design (CCD). The four important factors are the independent variables while the pectin yield is the dependent variable or the response. This was done to determine the best conditions for optimum pectin yield. Using the CCD involves varying the independent variables at five different levels (-α, -1, 0, +1, +α). In this work, a set of 30 experiments were performed consisting of 6 centre points or null points. The distance of the star like point α used was 1.402. The experiments were performed at random order to avoid systematic error. 3.2.1 Statistical Analysis on the Optimization of the

Pectin Yield from Nigerian Citrus Sinensis The design matrix and output response for the

optimization of the pectin extraction from Nigerian citrus sinensis is presented in Table 4.

The summary of P-values indicates that a quadratic model fitted the ANOVA analysis and hence it was suggested. The cubic model is always aliased because the CCD does not contain enough runs to support a full cubic model. A significance level of 95%

was used hence all terms whose P-value are less than 0.05 are considered significant. The temperature and pH will have more significant effect in the increment of the response since their coefficients were higher. The adequacy of the models was tested using the sequential model sum of squares and the model summary statistics as shown in tables 5.

The initial quadratic model equations obtained for pectin yield from Nigerian citrus sinensis peel; Pectin yield (%) = +62.40058 -2.59750X1 +4.89854 X2

+7.08315 X3 + 0.16506 X4 - 0.12533 X1 X2 - 0.08044X1X3 + 0.001734X1 X4 + 2.60885 X2 X3 -0.037700 X2 X4 - 0.11298 X3 X4 + 0.023682 X12 - 0.29283X2 2- 1.32466 X32 - 2.6541X42

… (2) The ANOVA table is given in Table 6. A

significance level of 5% was used hence all terms whose P-value are less than 0.05 are considered significant. From Table 6, the regression F-values of 10.63 implies that the model is significant which was validated by the P-value being less than 0.05. The P-values were used as a tool to check the significance of each of the coefficients, which in turn are necessary to understand the pattern of the mutual interactions between the test variables (Shrivastava et al., 2008). The larger the magnitude of F-test value and the smaller the magnitude of P-values, the higher the significance of the corresponding coefficient (Alam et al., 2008). ANOVA for Response Surface Reduced Quadratic Model is presented in Table 6. The Model F-value of 10.63 implies the model is significant. There is only a 0.01% chance that a "Model F-Value" this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case X1, X2, X1X2, X2X3, X3X4, X12 are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve the model. The "Lack of Fit F-value" of 1.25 implies the Lack of Fit is not significant relative to the pure error. There is a 43.20% chance that a "Lack of Fit F-value" this large could occur due to noise. Non-significant lack of fit is good -- we want the model to fit. The initial "Pred R-Squared" was not as close to the "Adj R-Squared" as one might normally expect. This may indicate a large block effect or a possible problem with the model and/or data. Model reduction and response transformation were considered, but model reduction gave a better "Pred R-Squared" of 0.81409 which is in reasonable agreement with the "Adj R-Squared" of 0.85094. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 13.300 indicates an adequate signal. This model can be used to navigate the design space.



9

Table 4 Design matrix with output response for the optimization of the pectin yield from Nigerian citrus sinensis

Factor 1 Factor 2 Factor 3 Factor 4 Response Run X1:Temp.( oC) X2:pH X3 : Extract to ethanol ratio X4 : Extraction time (mins.) Pectin yield (%) 1.00 90.00 1.00 2.00 120.00 29.00 2.00 70.00 2.60 1.25 75.00 1.00 3.00 90.00 4.20 0.50 120.00 12.10 4.00 70.00 2.60 1.25 75.00 2.77 5.00 47.72 2.60 1.25 75.00 5.53 6.00 50.00 4.20 0.50 120.00 0.63 7.00 70.00 2.60 1.25 24.86 4.87 8.00 50.00 1.00 2.00 120.00 8.60 9.00 50.00 1.00 0.50 30.00 2.17 10.00 70.00 4.38 1.25 75.00 2.00 11.00 50.00 1.00 0.50 120.00 5.33 12.00 90.00 1.00 0.50 30.00 22.10 13.00 70.00 2.60 2.09 75.00 6.33 14.00 50.00 4.20 0.50 30.00 0.87 15.00 50.00 4.20 2.00 120.00 2.50 16.00 70.00 2.60 1.25 75.00 2.70 17.00 70.00 2.60 0.41 75.00 2.60 18.00 90.00 1.00 0.50 120.00 56.10 19.00 90.00 1.00 2.00 30.00 29.97 20.00 70.00 0.82 1.25 75.00 10.43 21.00 70.00 2.60 1.25 125.14 8.43 22.00 50.00 1.00 2.00 30.00 5.43 23.00 50.00 4.20 2.00 30.00 3.43 24.00 92.28 2.60 1.25 75.00 28.77 25.00 90.00 4.20 0.50 30.00 0.87 26.00 70.00 2.60 1.25 75.00 15.70 27.00 70.00 2.60 1.25 75.00 2.67 28.00 90.00 4.20 2.00 120.00 15.90 29.00 70.00 2.60 1.25 75.00 2.80 30.00 90.00 4.20 2.00 30.00 30.03

Table 5: Fit summary

Sequential Model Sum of Squares Sum of Mean F p-value

Source Squares Df Square Value Prob > F Mean vs Total 3448.195 1 3448.195 Linear vs Mean 2704.089 4 676.0221 8.163897 0.0002 2FI vs Linear 804.1472 6 134.0245 2.01141 0.1143 Quadratic vs 2FI 632.3282 4 158.0821 3.741988 0.0264 Suggested Cubic vs Quadratic 471.419 8 58.92737 2.542117 0.1181 Aliased Residual 162.2631 7 23.18044 Total 8222.441 30 274.0814 Lack of Fit Tests

Sum of Mean F p-value Source Squares Df Square Value Prob > F Linear 1920.064 20 96.0032 3.198112 0.1005 2FI 1115.917 14 79.70834 2.655289 0.1436 Quadratic 483.5885 10 48.35885 1.610957 0.3122 Suggested Cubic 12.16953 2 6.084763 0.202699 0.8229 Aliased Pure Error 150.0935 5 30.01871 Model Summary Statistics

Std. Adjusted Predicted Source Dev. R-Squared R-Squared R-Squared PRESS Linear 9.099797 0.566391 0.497013 0.312547 3282.069 2FI 8.16285 0.734825 0.595259 -0.11189 5308.426 Quadratic 6.499651 0.867271 0.854339 0.81734 4118.582 Suggested Cubic 4.814607 0.966013 0.859196 0.490995 2430.115 Aliased



10

Table 6: ANOVA table for the optimization of pectin yield from Nigerian citrus sinensis

Sum of Mean F p-value Source Squares Df Square Value Prob > F Model 4137.411 11 376.1282 10.63117 < 0.0001 Significant X1-Temp. 2015.408 1 2015.408 56.96502 < 0.0001 X2-Ph 560.2827 1 560.2827 15.83626 0.0009 X3-Extract to ethanol ratio 45.01949 1 45.01949 1.272465 0.0274 X4-Extraction time 83.37855 1 83.37855 2.356675 0.0142 X1 X2 257.3618 1 257.3618 7.27427 0.0147 X1 X4 38.96881 1 38.96881 1.101444 0.03078 X2X3 156.813 1 156.813 4.432282 0.0496 X2X4 117.8853 1 117.8853 3.332 0.0085 X3X4 232.6388 1 232.6388 6.575479 0.0195 X1^2 442.3914 1 442.3914 12.50409 0.0024 X3^2 2.73726 1 2.73726 0.077368 0.0041 Residual 636.8354 18 35.37974 Lack of Fit 486.7419 13 37.44168 1.247278 0.4320 Not significant Pure Error 150.0935 5 30.01871 Cor Total 4774.246 29 Std. Dev. 5.948087 R-Squared 0.86661 Mean 10.721 Adj R-Squared 0.85094 C.V. % 55.48071 Pred R-Squared 0.81409 PRESS 2953.306 Adeq Precision 13.29953

The final quadratic model equations obtained for the pectin extraction from Nigerian citrus sinensis after eliminating the insignificant model terms becomes as expressed in equations (3). Pectin yield (%) = +5.34 +10.44 X1 - 5.51 X2 +1.56 X3 +

2.12 X4 - 4.01 X1 X2 +1.56 X1 X4 + 3.13 X2X3 - 2.71 X2 X4 - 3.81 X3 X4 + 9.47 X12 -0.75 X32

… (3)

The coefficient of regression R2 was used to validate the fitness of the model equation. The R2 has a high value of 0.8666 showing that 86.66% of the variability in the response can be explained by the model. This implies that the prediction of experimental data is quite satisfactory. Table 7 presents a combination of the actual experimental response and the predicted response from the mathematical equations. It can be seen that there is a close correlation between the actual experimental response and the predicted response. This confirms the effectiveness of the pectin extraction from Nigerian citrus sinensis peels.

Leverage of a point varies from 0 to 1 and indicates how much an individual design point influences the model's predicted values. A leverage of 1 means the predicted value at that particular case will exactly equal the observed value of the experiment, i.e., the residual will be 0. The sum of leverage values

across all cases equals the number of coefficients (including the constant) fit by the model. The maximum leverage an experiment can have is 1/k, where k is the number of times the experiment is replicated. Leverage represents the fraction of the error variance, associated with the point estimate, carried into the model. A leverage of 1 means that any error (experimental, measurement, etc.) associated with an observation is carried into the model and included in all predictions. An experiment with leverage greater than 2 times the average is generally regarded as having high leverage, i.e., compared to the other experiments, it is an outlier in the independent variable space. Studentized residuals versus predicted values checks for constant error. Internally Studentized Residual is the residual divided by the estimated standard deviation (Std Dev) of that residual. This measures the number of standard deviations separating the actual and predicted values. Externally student zed Residuals looks for outliers, i.e., influential values. The Externally Studentized Residual (Outlier-t value, R-Student) is calculated by leaving the run in question out of the analysis and estimating the response from the remaining runs, where the t value is the number of standard deviations difference between this predicted value and the actual response. This tests whether the run in question follows the model with coefficients estimated from the rest of the runs, that is, whether this run is consistent with the rest of the data –



11

Table 7: Actual and predicted yield result for pectin extraction from Nigerian citrus sinensis peels

Diagnostics Case Statistics

Internally Externally Standard Actual Predicted Studentized Studentized

Order Value Value Residual Leverage Residual Residual 1 2.17 0.40 2.5665 0.586198 0.670761 0.660165 2 22.10 25.39 -3.2881 0.586198 -0.85935 -0.85282 3 0.87 4.22 5.089295 0.586198 1.3301 1.361251 4 0.87 5.52 -4.6528 0.586198 -1.21602 -1.23351 5 5.43 4.09 1.340133 0.586198 0.350247 0.341545 6 29.97 29.87 0.095537 0.586198 0.024969 0.024266 7 3.43 12.79 -9.35957 0.586198 -2.44615 -2.90951 8 30.03 22.53 7.498332 0.586198 1.959707 2.147291 9 5.33 13.79 -8.45512 0.586198 -2.20977 -2.51568 10 56.10 45.81 10.28778 0.586198 2.688736 3.37793 11 0.63 0.90 1.525169 0.586198 0.398607 0.389097 12 12.10 15.09 -2.98943 0.586198 -0.78129 -0.77249 13 8.60 3.02 5.581008 0.586198 1.45861 1.509529 14 29.00 35.05 -6.04609 0.586198 -1.58016 -1.65469 15 2.50 0.86 1.638802 0.586198 0.428305 0.418375 16 15.90 16.85 -0.94579 0.586198 -0.24719 -0.24063 17 5.53 5.47 0.060966 0.350505 0.012718 0.01236 18 28.77 28.74 0.031141 0.350505 0.006496 0.006313 19 10.43 11.48 -1.04857 0.162182 -0.1926 -0.18736 20 2.00 0.79 2.7906 0.162182 0.512561 0.501795 21 2.60 2.68 -0.08002 0.350505 -0.01669 -0.01622 22 6.33 6.16 0.172124 0.350505 0.035907 0.034896 23 4.87 2.98 1.892526 0.162182 0.347608 0.338954 24 8.43 7.71 0.719501 0.162182 0.132154 0.128493 25 2.80 5.34 -2.54399 0.095013 -0.44959 -0.4394 26 1.00 5.34 -4.34399 0.095013 -0.7677 -0.75859 27 2.77 5.34 -2.57399 0.095013 -0.45489 -0.44464 28 2.70 5.34 -2.64399 0.095013 -0.46726 -0.45688 29 15.70 5.34 10.35601 0.095013 1.830182 1.971485 30 2.67 5.34 -2.67399 0.095013 -0.47256 -0.46213

* Exceeds limits

for this model. Runs with large t values should be investigated. The Normal plot of Residuals and the Predicted vs. Actual plots were used to check if the points follow a straight line in which we conclude that the residuals follow a normal distribution. It was seen that the points were closely distributed to the straight line of the plot; it confirms the good correlation between the experimental values and the predicted values of the response. These plots equally confirm that the selected model was adequate in predicting the response variables in the experimental values. Definite patterns like an “S-shaped” curve indicate that a model reduction or transformation of the response may provide a better analysis. 3.2.2 The Three Dimensional (3-D) Response

Surface Plots for Pectin Yield from Nigerian Citrus Sinensis Peels

The 3-D response surface plots for pectin yield from Nigerian citrus sinensis peels are presented in Fig 4-9. The 3-D response surface plots are graphical representation of the interactive effects of any two variable factors.

Response surface estimation plots for maximum pectin yield from citrus peels as a function of two factors at a time, maintaining all other factors at fixed levels are more helpful in understanding both the main and the interaction effects of these two factors. These plots can be easily obtained by calculating from the model, the values taken by one factor where the second varies with constraint of a given Y value. The response surface curves were plotted to understand the interaction of the variables and to determine the optimum level of each variable for maximum response. The nature of the response surface curves shows the interaction between the variables. Figs 4, 5 and 6 -



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Fig 1: Normal plot of Residuals for pectin yield from

citrus sinensis peels.

Fig 2: Externally Studentized Residuals vs Run

Number.

Fig 3: Normal plots of the Predicted vs Actual for

pectin yield from citrus sinensis.

Fig 4: 3D Surface plot for pectin yield from citrus

sinensis showing combined effects of temperature and pH.


sinensis showing combined effects of temperature and EER.


sinensis showing combined effects of temperature and extraction time.


sinensis showing combined effects of pH and EER.

Internally Studentized Residuals

Norm

al %

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babili

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Normal Plot of Residuals

-2.45 -1.16 0.12 1.41 2.69

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13


sinensis showing combined effects of pH and extraction time.


sinensis showing combined effects of EER and extraction time.

show that pectin yield increases with increase in temperature while increase in the pH leads to decrease in pectin yield (Figs 4, 7 and 8). The pectin yield increases with increase in EER up 1.25 (Figs 5, 7 and 9). Figs 6, 8 and 9 show that increases in extraction time favours pectin yield. The optimum values of pectin yield were recorded at the temperature, pH, EER and extraction time, 70ºC, 2.6, 1.25 and 75 (mins), respectively. 3.2.3 Optimization and Validation of Result

Determination of the optimum process conditions for maximizing pectin yield is very crucial in this present study. Table 8, shows that, temperature: 90 (ºC); pH: 1; EER: 0.53 and extraction time: 120 (mins) are the optimum conditions required for optimum LM-pectin yield. Under these conditions, the predicted LM-pectin yield was 45.66 (%), which was in good agreement with the experimental value of 56.00 (%) performed at the same optimum values of the process variables. It could be also observed that, temperature: 90 (ºC); pH: 4.2; EER: 2 and extraction time: 120 (mins) are the optimum conditions required for optimum HM-pectin yield. Under these conditions, the predicted HM-pectin yield was 2.8 (%), which was in good agreement with the experimental value of 5.90 (%) performed at the same optimum values of the process variables. The HM and LM pectin values were 9.77 and 2.58, respectively. The HM-LM pectin blends were subsequently used for cosmetic emulsion formulation. The optimization was performed using the numerical method of the Design Expert version 10.0 by State Ease U.S.A. 3.3 Physical and Chemical Properties of Pectin

The optimized pectin was characterized for their physical and chemical properties which include acetyl content, protein content, intrinsic viscosity, molecular weight, ash content, moisture content and pH (Table

10). Table 9 presents the results of the qualitative tests on pectin extracted from the orange peels. 3.3.1 Moisture Content

At different operating conditions the range of moisture content of the Nigerian citrus sinensis peel pectin determined is 8% - 12%. The average pectin moisture content was noted to be 9.33%. This observed result is consistent with the reports of the existing literature. The pectin is very hygroscopic (Salam et al., 2012). Salam et al. (2012) reported that the moisture absorbed by isolated lemon peel pectin in his work was found to be 12.2% against 9.4 - 11.3% for commercial pectin and those reported in the literature. This value seems too high (for a material, which is easily susceptible to microbial attack) to be preserved in open atmosphere. For this reason, it must be preserved in closed dry atmosphere (Salam et al., 2012). Literature data on the moisture content of pectin extracted from dragon fruit (Ismail and Ramli, 2012) as well as different citrus peel like Kinnow, Musambi, Malta and Feutral (Addosio et al., 2005) lies in the range of 9.4 - 11.3% (Salam et al., 2012). It is important to keep in mind that high moisture content could enhance the growth of microorganisms and production of pectinase enzymes that can further affect the pectin quality (Muhamadzadeh et al., 2010; Azad et al., 2014). The average moisture content of the citrus peel pectin (9.3%), is higher than that of commercial pectin (1.86%) (Mohamed, 2016). The Sudanese grape fruit peel pectin was reported to have a moisture content value of 8.42% without mentioning the type of grape fruit investigated (El Mubarak, 1974; Mohamed, 2016). The moisture content of the Nigerian citrus sinensis peel pectin is in agreement with the literature data on moisture content of pectin extracted from different citrus peel, which lies in the range of 6.4-10% (Devi et al., 2014; Rehman et al., 2004; Mohamed, 2016). Pectin should have low moisture content as possible for

1.00

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14

safe storage and to inhibit the growth of micro-organism that can affect the pectin quality due to the production of pectinase enzymes (Muhamadzadeh et al., 2010; Mohamed, 2016). Pectin has a very complex structure which depends on both its source and the extraction process (Leroux et al., 2003). 3.3.2 pH

The pH determination for the HM and LM pectins were found to be 4.5 and 2.5. This is consistent with the literature. It has been reported that the pH determination for the lemon pectins, grape and sweet orange were found to be (4.1), (4.0) and (3.6), respectively (Aina et al., 2012). The aqueous solutions of pectins are slightly acidic (Fishman et al., 1984; Aina et al., 2012). The range of skin pH values is between 5 and 6, and 5.5 is considered to be the average pH of the skin. Therefore, the formulations intended for dermal application should have a pH value around this range (Naveed et al., 2010). 3.3.3 The Ash Content

The ash content of the Nigerian citrus sinensis peel pectin extracted at different operating condition was ranged from 1.041% - 1.124%. The average ash content value is 1.096%. The result is in agreement with the existing literature. The ash content value ranged from 1.8% - 2% for red and white grape fruit peel pectin respectively, was reported by Mohamed (2014) while citrus pectin had low ash content (0.852%). Low ash content is good for gel formation (Mohamed, 2014). The maximum limit for ash content for good quality gel criteria is 10% (Ismail et al., 2012; Mohamed, 2014). The pectin yield decreases with increase in the ash content value. At the ash content values of 1.041% and 1.124%, the corresponding pectin yield recorded were 56.10% and 5.90%, respectively. The increase in ash content as the pectin yield decreases is in agreement with the reports of Azad et al. (2014) and Mohamed (2016). 3.3.4 The Protein Content

The protein content of pectin is reported to have a great influence on the emulsifying capacity of pectin (Gladys, 2015). The protein content values determined was ranged from 1.619% to 3.325% at different process conditions. The average value of 2.7% of protein content was recorded for the Nigerain citrus peel pectin. The values of protein content is, generally, in agreement with the protein content value reported for the commercial pectin, which usually have protein content below 2% since it’s prepared from sources of low protein content (Mohamed, 2016). The lower protein content value of 1.6% in this study is also the

same with the protein content value (1.6%) reported for citrus pectin and 3.5% for sugar, by Gladys (2015). 3.3.5 Acetyl Content Value

The acetyl value recorded for the citrus pectin ranges from 1.20% - 1.344%. The average acetyl value determined was 1.233%. This is in close agreement to the existing reports. Acetyl content values of white grape fruit peel pectin (1.634%), red grapefruit peel pectin (0.455%) and commercial citrus pectin (0.55% - 0.624%) was reported by Mohamed (2016). Gladys (2015) reported the acetyl content value of 2.5% for citrus pectin and 20.7% for sugar beet pectin. Result of other researchers indicated that the gelling capacity of pectin decreased with increase in the degree of acetylation and samples containing 3.5%-4.0% acetyl gives weak gels while gelling power restored at levels around 2.4% acetyl (Ranganna, 2002; Schult, 1965; Mohamed, 2016). The acetyl values in this study show that Nigerian citrus sinensis peel pectin have good gelling power and emulsifying capacity. According to Endress and Rentschler (1999), the emulsifying ability of beet pectin can be explained by the presence of acetyl groups (4-5%) (Leroux et al., 2003). Akhtar et al. (2001) studied emulsifying properties of citrus pectins and concluded that citrus pectin, with low acetyl content value, may have an interesting emulsifying capacity (Leroux et al., 2003). 3.3.6 The Methoxyl Content Value

The methoxyl content values of citrus pectin determined at different extraction conditions was in the range of 0.992% - 12.245%, indicating the extraction of high and low methoxy pectins (Yapo et al., 2007) from the Nigerian citrus peel pectin. The methoxyl content value of pectin depends on the raw material, extraction process and the extraction conditions. The average methoxyl content value for the Nigerian citrus peel pectin recorded was 6.973%, at the average exctaction condition of: temperature (70ºC); time (120 min); pH (2.6); EER (1.25).

This is equal to the methoxyl content value of the commercial pectin value (6.987%) (Mohamed, 2016). A similar methoxyl content value (6.84%) for citrus cinensis pectin was published by Kanmani et al. (2014). The methoxyl content is an important factor in controlling the setting time of pectin and ability of pectin to form gel (Constenla and Lozano, 2003; Mohamed, 2016). The methoxyl content values of the Nigerian citrus peel pectin recorded in this study is similar to the existing literature. Mohamed (2016) reported the methoxyl content of red and white grapefruit peel pectin were (8.875 - 7.542%) respectively, higher than that of commercial pectin (6.987%).



15

Table 8: The predicted optimum conditions and experimental validated result

Optimum Conditions Predicted

Sample Temp. (oC) pH

Extract to ethanol ratio (EER)

Extraction time (min.)

Predicted Pectin yield (%)

Experimental Validated Result (%) MeO%

LM-pectin 90 1 0.53 120 45.66 55.00 2.58 HM-pectin 70 2.6 1.25 75 2.8 5.90 9.77

Table 9: Qualitative tests of pectin extracted from orange peels

Test Description

Stiff gel test Test with 95% Ethanol Test with 2N KOH for 15mins Test with 3N HCl

Formation of a sticky gel

Formation of a translucent, gelatinous precipitate

Formation of a translucent, semi gel

Upon heating forms a voluminous gelatinous precipitate which upon boiling becomes white and flocculent

Table 10: Characterization of the optimized pectin yield

Pectin type

Acetyl content

Protein content (%)

Intrinsic viscosity

Molecular weight

Ash content (%)

Moisture content (%) MeO% pH

LM 1.32 1.60 9.89 61.68 1.02 11.98 2.58 2.48 HM 1.22 3.31 146.45 405.61 1.10 7.98 9.77 4.48 HM 1.10 3.14 97.84 305.93 1.10 7.98 9.77 4.48 Ave. 1.21 2.68 84.73 257.74 1.08 9.31 3.81

This was also higher than the methoxyl reported as, 4.11% for lime, 3.9% for orange and 4.2% for grape fruit by El Mubarak, (1974) (Mohamed, 2016). Alexander et al. (1980) reported 8.62% for lime, 7.6% for orange, 7.73% for sweet orange and 7.4% for grape fruit (Mohamed, 2016). Azad et al. (2014) reported contrast results for methoxyl content in his findings for dragon fruit pectin which showed lower methoxyl content and degree of esterification as compared to commercial apple pectin (Mohamed, 2016). Hence, it could be seen that the methoxyl content of pectin can vary with the source of raw material used, the method used for extraction in addition to the method (Mohamed, 2016) and operating conditions used for determination of methoxyl content. The methoxyl content of pectin has been repoted to vary from 0.2 - 12% depending on the source and mode of extraction Kanmani et al. (2014).

With respect to the methoxyl content values recorded in this study the citrus peel pectin extracted at different operating conditions could be categorized as low methoxly pectin (LM) pectin (Methoxyl content <7%) and high methoxly pectin (HM) pectin (Methoxyl content >7%) (Mohamed, 2016). Pectin has a very complex structure which depends on both its source and the extraction process (Leroux et al., 2003). 4. Conclusion

A detailed study on the optimization of pectin extraction from Nigerian citrus sinensis peels has been successfully carried out. Detailed characterization of the citrus sinensis peels has been reported. The extraction/synthesis and characterization of pectin from citrus peels was carried out. The optimization of the process parameters on the yield of pectin using Response Surface Methodology was studied. The results of the physio-chemical characterization revealed that the Nigerian citrus sinensis peels contain: moisture (11%), ash (2.33%), titratable acidity (0.23%), crude protein content (3.68%), reducing sugars (2.24%), total sugars (4.42%), and fat content (0.43%). From the characterization of the extracted pectins, the results show that the citrus pectin has an average moisture content (9.23%), pH 4.5 (HM), pH 2.5 (LM), ash content (1.04% - 1.096%), protein content (1.62% - 3.33%), acetyl content value (1.20% - 1.344%), methyl content value (0.992% - 12.245%). The optimum condition for HM-pectin and LM-pectin were (temp., (90ºC), pH 1; EER 0.53; extraction time (120 min)) and (temp., (70ºC), pH 2.6; EER 1.25; extraction time (75 min)), respectively. The optimized yield for LM and HM pectins were 45.66% and 2.8%, respectively. The experimentally validated pectin yields were 55% and 5.9% for LM and HM pectins, respectively. The values of the methoxyl content of the citrus pectins extracted at different extraction condition



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revealed that the Nigerian citrus pectin could be classified into HM and LM pectins. The extracted

pectin from the Nigerian citrus sinensis peels exhibited desirable properties for industrial application.

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Extraction of Pectin from Citrus Sinensis Peels ...jakraya.com/journal/download.php?file=1-epArticle_1.pdf · concluded that the Nigerian citrus sinensis peel is a potential source