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Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface methodology approach
Accepted Manuscript Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface methodology approach Shweta Deshaware, Sumit Gupta, Rekha S. Singhal, Prasad S. Variyar PII:
S0023-6438(17)30607-2
DOI:
10.1016/j.lwt.2017.08.037
Reference:
YFSTL 6459
To appear in:
LWT - Food Science and Technology
Received Date: 18 May 2017 Revised Date:
9 August 2017
Accepted Date: 12 August 2017
Please cite this article as: Deshaware, S., Gupta, S., Singhal, R.S., Variyar, P.S., Enhancing antidiabetic potential of bitter gourd juice using pectinase: A response surface methodology approach, LWT - Food Science and Technology (2017), doi: 10.1016/j.lwt.2017.08.037. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface
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methodology approach
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Shweta Deshaware1, Sumit Gupta2#, Rekha S. Singhal1#*, Prasad S. Variyar2 1
Department of Food Engineering and Technology, Institute of Chemical Technology, Mumbai400019, India
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Food Technology Division, Bhabha Atomic Research Centre, Mumbai-400085, India
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ABSTRACT
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Bitter gourd exhibits significant anti-diabetic activity. In the present study, pectinase
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concentration (4.04 – 15.92 ml kg-1), incubation time (48 to 191 min) and temperature (31 to
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55°C) were optimized using response surface methodology (RSM) for obtaining increased juice
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yield with higher anti-diabetic (α-amylase and α-glucosidase inhibition) activity, total phenolics
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and antioxidant activity. The optimum conditions i.e. pectinase concentration (10.2 ml kg-1),
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incubation time (140 min) and temperature (48.8°C) resulted in juice yield of 82 %, α–amylase
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and α-glucosidase inhibition activity of 23 and 59 %, respectively, with total phenolic and
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antioxidant content of 710 and 198 µg GAE ml-1, respectively. In comparison, control (prepared
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without enzyme treatment) had significantly (p<0.05) lower juice yield, α–amylase and α-
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glucosidase inhibition activity of 59, 8 and 17 %, respectively. Control samples also
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demonstrated significantly (p<0.05) lower total phenolic and antioxidant content of 464 and 162
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µg GAE ml-1, respectively. RSM optimized juice also demonstrated significantly (p>0.05) higher
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contents of phenolic acids as compared to control juice.
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Keywords:
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Momordica charantia L.
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# These authors contributed equally Corresponding authors: Dr. Rekha Singhal; email: [email protected], phone: +91-22-33612501 Dr. Sumit Gupta; email: [email protected], phone: +91-22-25590560
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Antioxidant capacity
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Anti-hyperglycemic activity
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Phenolic acids
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Central composite rotatable design
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1. Introduction
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Occurrence and prevalence of obesity and associated metabolic disorders such as
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cardiovascular diseases and type 2 diabetes mellitus are on the rise worldwide. Based on a
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collective study from different parts of the world, the World Health Organization (WHO) has
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projected that maximum increase in incidence of diabetes could occur in India, China and US
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(King, Aubert, & Herman, 1998).
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Bitter gourd (Momordica charantia L.), an annual climbing plant belonging to the
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Cucurbitaceae family, is an extensively investigated tropical medicinal plant. Its fruit, also
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known as balsam pear, bitter melon or karela has a distinct bitter taste which enhances as the
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fruit ripens. Bitter gourd has been popular as a natural remedy in Ayurvedic systems owing to its
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anti-diabetic, anti-malarial, anti-inflammatory, antiviral, contraceptive and insecticidal properties
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(Grover & Yadav, 2004). Bitter gourd juice (BGJ) has a rich array of bioactive phytochemicals
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including vitamins, minerals and phenolic compounds (Horax, Hettiarachchy, & Islam, 2005).
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Phenolic compounds have been widely reported to have both high antioxidant potential (Wu &
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Ng, 2007) and anti-diabetic activity (Vinayagam, Jayachandran, & Xu, 2016). Other bioactive
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molecules in bitter gourd include steroidal saponins, charantin, insulin like peptides,
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glycoalkaloids, vicine, momorcharin, oleanolic acids, triterpenes, trehalose and momordin
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(Grover & Yadav, 2004). There is a need to develop protocols for juice preparation with enhanced extraction of
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bioactives which is simple, cost effective as well as rapid. Microbial pectinases have been widely
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used in preparation of vegetable and fruit juices for higher yield, higher clarity, lower viscosity
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and cloudiness, reduced bitterness and improved nutrient profile (Kashyap, Vohra, Chopra, &
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Tewari, 2001). It may be hypothesized that the use of pectinase for treating bitter gourd pulp
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would enhance juice yield and facilitate the release of bioactive compounds.
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Response surface methodology is a statistically designed tool which uses minimum
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number of experiments to provide an optimized response outcome by comparing net interactions
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of various parameters. Taking into consideration the immense potential of bitter gourd to become
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a dietary beverage for diabetic and pre-diabetic patients, this study aimed at optimization of
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parameters (incubation time, incubation temperature and enzyme concentration) for extraction of
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BGJ with desirable responses (yield, total phenols, total antioxidant potential, α-glucosidase
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inhibition and α-amylase inhibition) using enzymatic pretreatment of pulp. It also attempts to
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identify and quantify the phenolic content in native and enzyme pretreated BGJ.
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2. Materials and methods
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2.1. Plant material
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Bitter gourd fruits were purchased from a local grower on the outskirts of Mumbai
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(India). Fruits were brought to the laboratory within 12-14 h after harvesting and immediately
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stored at refrigerated temperature (10 ºC). Selection of fruits was based on maturity (14-16 days
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after fruit set), free from visual defects, dark green color, 20-25 cm long, pendulous in shape.
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2.2. Chemicals and enzymes Pectinase from Aspergillus niger (specific activity 70.4 µKat/ml, protein concentration
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10.6 mg/ml), α-amylase from porcine pancreas (Type IV-B), α-glucosidase from Saccharomyces
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cerevisiae and p-nitrophenyl-α-D-glucopyranoside were procured from Sigma-Aldrich (St.
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Louis, MO, USA). Folin-Ciocalteau’s phenol reagent (FC), 2,2-diphenyl-1-picrylhydrazyl
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(DPPH), standard phenolic acids (gallic acid, protocatechuic acid, gentisic acid, (+) catechin,
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vanillic acid, caffeic acid, tannic acid, (-) epicatechin, ferulic acid, and o-coumaric acid) and
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HPLC grade solvents (acetonitrile, o-phosphoric acid and glacial acetic acid) were also procured
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from Sigma-Aldrich (Mumbai, India). All the other chemicals and reagents were of analytical
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grade and obtained from Merck (Mumbai, India).
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2.3. Methods
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2.3.1. Preparation of bitter gourd juice
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Bitter gourd fruits were washed with running tap water to remove all adhering dust.
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Whole fruit including the rind were diced into small pieces (approximately 3 cm × 3 cm). Pulp
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was then prepared using a high speed homogenizer (BUCHI Mixer B-400, Switzerland). For
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each trial, 50 g of pulp was subjected to different treatments according to experimental design
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(section 2.3.2). At the end of each experimental trial, pectinase was inactivated by heating the
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pulp in a water bath at 90ºC for 5 min. After cooling to room temperature (24 ± 2oC) using ice
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cold water bath, the pulp was immediately centrifuged at 1699 x g at 25°C for 20 min to obtain a
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clear supernatant. Juice samples were stored at -20ºC till all further analysis to prevent any
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deterioration or spoilage by microbial contamination.
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2.3.2. Experimental design
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Experiments were designed and analysis was performed using Design expert 8.0 software
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(Stat-Ease Inc., USA). A central composite rotatable design was used to study the combined 4
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X2) and incubation time (X3) coded at five levels (-α, -1, 0, +1 and +α ). Based on preliminary
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experiments, the range of variables selected was as follows: incubation temperature: 25 to 50°C,
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enzyme concentration: 0 to 20 ml kg-1 and time: 0 to 240 min. The natural pH of the juice was
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maintained at 4.1 which falls in the optimal pH range for acidic pectinases. The complete design
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consisted of 19 experimental points including 5 replications of center point (all variables coded
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as zero) (Table 1). The experiments were carried out in triplicates to ensure repeatability of
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experiments.
Juice yield was determined in terms of percentage.
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2.4. Determination of juice yield
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Yield percent = [Juice weight/Total pulp weight] x 100
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2.5. Determination of total phenolic content (TPC)
The total phenolic content was determined using the Folin-Ciocalteau method (Singleton,
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Orthofer, & Lamuela-Raventós, 1999) with slight modification. In brief, 100 µl of aqueous
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dilution of juice (20 ml l-1) was added to 650 µl of 1:10 diluted FC reagent (2 mol l-1). The
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mixture was incubated for 5 min and then 650 µl of 60 g l-1 Na2CO3 was added. This mixture
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was then allowed to stand for 90 min in dark at room temperature. Absorbance (y) was measured
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against blank at 750 nm. A calibration curve of gallic acid (0 to 18 µg ml-1) was plotted. TPC
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was calculated using regression equation (y=0.0714x - 0.0225, R2 = 0.9954) obtained from gallic
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acid standard curve and expressed as µg gallic acid equivalents (GAE) ml-1 of juice.
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2.6. Determination of total antioxidant capacity (TAC)
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A DPPH radical scavenging assay was used to evaluate total antioxidant activity using a
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method described by Brand-Williams, Cuvelier, & Berset (1995) with slight modification. In
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brief, 100 µl of juice was incubated with 900 µl of DPPH (1.2 mol l-1 in distilled methanol) in
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calibration curve of gallic acid (0 to 30 µg ml-1) was plotted. TAC was calculated using
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regression equation (y = -0.2016x + 0.9117, R2 = 0.9524) obtained from gallic acid standard
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curve and expressed as µg gallic acid equivalents (GAE) ml-1 of juice.
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2.7. Pancreatic α–amylase inhibition assay
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α-Amylase inhibition assay was performed as described by Telagari & Hullatti (2015)
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with certain modifications. In brief, the reagents used were as follows: α-amylase enzyme
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solution (1.6 µkat ml-1), 20 g l-1 (aqueous solution) starch, dinitrosalicylic acid (DNS) reagent.
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Juice sample (100 µl) was pre-incubated at 25ºC for 10 min with 100 µl of 0.02 mol l-1 sodium
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phosphate buffer (pH 6.9) and 100 µl α-amylase solution. Then 100 µl of 20 g l-1 starch solution
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was added and resulting mixture was incubated at 25ºC for 10 min following which 100 µl of
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0.02 mol l-1 sodium phosphate buffer (pH 6.9) was added.
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Since the inherent carbohydrate content of the juice was high, protocol was suitably
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modified by preparing two control tubes - control A (control without juice) and control B
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(control with juice) for accurately estimating the change specifically due to starch degradation by
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amylase in presence of juice (acting as inhibitor). All the reactions (test, control A and control B)
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were stopped by adding 1 ml DNS reagent and incubating in a boiling water bath for 5 min.
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After cooling the tubes to room temperature, reaction mixture was diluted 10 fold using distilled
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water and absorbance was recorded at 540 nm (UV 3000+, LABINDIA analytical, Mumbai,
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India). α-Amylase inhibition activity was calculated relative to controls and expressed in terms
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of percentage of that value.
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The α-amylase inhibition activity was calculated according to the following equation:
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Percent α-amylase inhibition = [(Control B – Test) / Control A] x 100 6
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2.8 α-Glucosidase inhibition assay α-Glucosidase inhibition activity was estimated using a modified version of the assay
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described by Telagari & Hullatti (2015) . The reagents used were sodium phosphate buffer (0.02
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mol l-1, pH 6.9), α-glucosidase enzyme (16.67 nkat ml-1), p-nitrophenyl–α-D–glucopyranoside
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(PNPG) substrate (5 mmol l-1 solution in 0.02 mol l-1 sodium phosphate buffer) and 0.2 mol l-1
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glycine NaOH buffer (pH 10). A volume of 50 µl of α-glucosidase enzyme was pre-incubated
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with 25 µl of juice in 96-well plates at 37°C for 5 min. After pre-incubation, 25 µl of PNPG
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substrate was added to each well at timed intervals and the plate was incubated at 37°C for
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10 min. Then 25 µl of sodium phosphate buffer was added. To account for the inherent
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carbohydrate content, two controls were used as previously described in section 2.7. All the
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reactions (test, control A and control B) were stopped by adding 175 µl of glycine NaOH buffer.
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expressed as percentage of inhibition as follows:
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α-Glucosidase inhibition activity was also estimated relative to two controls and
Percent α-Glucosidase inhibition = [(Control B – Test) / Control A] x 100 2.9 Chromatographic analysis of phenolic acids
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HPLC (Ultimate 3000, Dionex) equipped with UV-vis detector and reversed-phase
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Hypersil C18 column (5 µm particle size, 250 × 4.6 mm, Thermo Electron corporation, New
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Delhi, India) was used for analysis. The solvent system used was a gradient of mobile phase A
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containing o- phosphoric acid (15 ml l-1) in water and solution B containing a mixture of
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acetonitrile (200 ml l-1), glacial acetic acid (240 ml l-1), o-phosphoric acid (15 ml l-1) and water
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(545 ml l-1). The following gradient was used: 0-5 min, 100 % A, 5-10 min; from 100 % A, 0 %
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B to 80 % A , 20 % B; 10-40 min, from 80 % A, 20 % B to 62 % A, 38 % B ; 40-45 min, from
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62 % A , 38 % B to 0 % A and 100 % B with flow rate of 1 ml min-1. Column temperature was
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wavelength of 280 nm. Each phenolic acid was identified by its retention time and spiking with
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each standard under similar conditions. Quantification was done using calibration curves of each
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standard phenolics prepared. Data are reported as mean ± standard deviation (SD) of replicate
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measurements.
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2.10 Statistical analysis
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Statistical analysis was performed using Design expert software 8.0 (Stat-Ease, USA).
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Experimental data were fitted into third order polynomial (quadratic) following which models for
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each response were generated. Backward regression method was used to remove insignificant
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terms. The model was evaluated at 0.05 significance using analysis of variance (ANOVA).
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Coefficient of determination (R2) was used to quantify predictive ability of the model. Equations
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obtained after fitting the data in polynomial equations were used to generate 3D response surface
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plots to elucidate relationship between response and experimental levels. Numerical optimization
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was performed to get the desired response outcome. The differences in phenolic acid content
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between control and RSM optimized juice were compared using unpaired t test.
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3. Results and discussion
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The optimum process parameters for maximizing the responses were obtained using
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numerical optimization using Stat-Ease Design Expert software (v8). Statistical analyses were
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performed using ANOVA. It revealed that the models generated by RSM were significant
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(p<0.05) while lack of fit was insignificant (p > 0.05). Adequacy precision which measures the
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signal to noise ratio were above 4 for all the responses (Supplementary file Table 1). It is
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suggested that this model could be used to navigate the design space.
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shown in Supplementary file - Table 2. High R2 values (at least 0.80) imply that the empirical
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models are a good fit to actual data.
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3.1. Impact of enzyme concentration, time and temperature on juice yield
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The yield of juice varied from 58 to 77 % (Supplementary Table 3). All the three
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variables i.e. temperature, time and enzyme concentration had a significant (p<0.05) effect on
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juice yield. Response curves in the form of contour plots have been represented in Fig. 1. Each
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plot represents the effect of two factors while keeping the third at centre point. Fig. 1a
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demonstrates effect of temperature and enzyme concentration on juice yield when incubation
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time was at centre point.
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It was observed that juice yield increased from 66 to 72 % due to an increase in enzyme
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concentration from 4 -16 ml kg-1 when other two factors i.e. time and temperature were at their
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respective centre point values of 120 min and 121.93°C, respectively. Aziz, Roy, Sarker, &
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Yusof (2011) reported that bitter gourd contained pectin (12 %), hemicellulose (13 %) and
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cellulose (27.5 %) as major polysaccharides. It is known that pectinase helps in increasing the
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juice yield by degradation of cell wall polysaccharides and improving the press-ability of pulp
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(Tapre & Jain, 2014). Pectinase treatment has been earlier reported to markedly improve juice
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yield of various fruits and vegetable juices (Kashyap et al., 2001).
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Effect of temperature and time on juice yield is shown in Fig. 1b. No change in juice
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yield was observed in the temperature range of 30 to 40ºC when the other two factors were at
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their respective centre point values. A juice yield of 70 % was observed up to temperature of
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40ºC. However, further increase in temperature beyond 40ºC resulted in a higher juice yield of
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76 %. Higher temperature in the range of 40ºC – 50ºC may have favored higher enzyme activity 9
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by findings of Singh, Sharma, Kumar, Upadhyay, & Mishra, (2013) and Kaur, Sarkar, Sharma,
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Singh, (2009) where maximum juice yield from pectinase treated pulp from bael fruit and guava
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were obtained at 45.8°C and 43.3°C, respectively.
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Juice yield was also found to increase with incubation time. An enhancement in yield
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from 69 % to 73 % was observed as a result of increase in the time of incubation from 48 to 191
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min when temperature and enzyme concentration were at their respective centre point values. A
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similar trend of increase in yield with increasing incubation time was observed for banana juice
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(Tapre & Jain, 2014) and bael fruit juice (Singh, Kumar, & Sharma, 2012).
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3.2 Impact of enzyme concentration, temperature and time on Total Phenolic Content (TPC) and
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Total Antioxidant Capacity (TAC)
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The response curves for total phenolics and total antioxidant activity are shown in Fig. 2
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and 3, respectively; each demonstrating effect of two factors while keeping the third at centre
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point. Maximum recovery of polyphenols (798 µg GAE/ml) as well as antioxidant activity (355
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µg GAE/ml) was evident when 10 ml kg-1 pectinase was used for 240 min at 40°C
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(Supplementary Table 3). Incubation temperature and enzyme concentration were most
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significant (p<0.05) factors while incubation time did not have a significant (p>0.05) effect on
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TPC and TAC.
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With increasing temperature, the concentration of phenolic compounds increased
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significantly (p<0.05) from 550 to 725 µg GAE ml-1 up to 40°C. However a decrease in TPC
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was observed above 40°C (Fig 2a). Similarly, TAC increased from 200 to 275 µg GAE ml-1 in
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the range of 30 - 40°C, and then decreased with further increase in temperature to 50°C (Fig. 3a).
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An increase in temperature may have resulted in increased diffusion coefficients of water soluble 10
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De Faveri, 2007). However at higher temperatures, polyphenol oxidase gets activated during
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processing of juice as plant cells are ruptured. This enzyme has the ability to oxidize polyphenols
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resulting in loss of antioxidant activity. Gradual degradation of certain phenolics such as caffeic
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acid, sinapic, p–coumaric and ferulic acids have been reported to occur beyond 40°C, while
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cinnnamic acids and benzoic acids are more stable at these temperatures (Ma et al., 2008).
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With respect to enzyme concentration, increasing pectinase concentration (10 – 12.8 ml
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kg-1) enhanced the TPC from 630 to a maximum of 725 µg GAE ml-1. However, an increase in
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pectinase concentration beyond 12.8 ml kg-1 did not result in any further increase in TPC (Fig 2a
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and 2b). Improved extraction efficiency of phenolics may occur via two mechanisms viz.
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hydrolytic degradation of cell wall polysaccharides or enzyme catalyzed fissure of ether and
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ester linkages between the phenols and cell wall polymers (Pinelo, Zornoza, & Meyer , 2008).
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Our results are in accordance with previous works on carrot juice (Khandare, Walia, Singh, &
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Kaur , 2011) and dragon fruit juice (Nur‘Alia, Siti Mazlina, & Taip , 2010) where an increase in
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polyphenols was obtained with pectinase treatment.
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The TAC increased from 118 to 296 µg GAE ml-1 with increasing concentrations from 4
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– 10 ml kg-1. However, interestingly, further rise in pectinase concentration showed a marked
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decrease in the antioxidant activity to 136 µg GAE ml-1 when enzyme concentration was 16 ml
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kg-1 (Fig 3a). Antioxidant activity depends on both total phenolic content and types of phenolic
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acids (Shian, Abdullah, NurKartinee, & Ariffin, 2015) with different phenolic compounds
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demonstrating varying degrees of antioxidant activity (Nuutila, Puupponen-Pimiä, Aarni, &
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Oksman-Caldentey , 2003). The observed decrease in antioxidant activity may have occurred due
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to degradation and settling of polyphenolics, primarily those with high antioxidant potential
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owing to combined effect of higher temperatures and greater enzyme concentration (Makris &
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Rossiter, 2001). Incubation time had no significant (p>0.05) effect on TPC and TAC. Only a small
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increment for TPC from 700 to 725 µg GAE/ml with increase in time from 50 to 190 min was
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observed (Fig. 2b). Similarly, only a minor increment of antioxidant capacity from 280 to 310 µg
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GAE ml-1 was observed in the aforementioned time. These results imply that 50 min would
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possibly be sufficient time along with pectinase concentration of 4 – 12 ml and incubation
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temperature in the range 35-45°C for maximum recovery of TPC and TAC in BGJ.
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Independent investigations by Wu & Ng (2008) and Kubola & Siriamornpun (2008) have
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reported water extracts of bitter gourd to contain 516 µg GAE ml-1 and 202 µg GAE ml-1,
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respectively. Recently, Jain & De (2016) performed optimization of aqueous extraction of BGJ
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and reported to contain 23.1 mg GAE per100 ml (231 µg GAE ml-1) of polyphenols. A higher
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extraction efficiency of polyphenols (798 µg GAE ml-1) in enzyme pretreated juice than the cited
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literature for aqueous extract of bitter gourd was obtained in this study.
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3.3 Impact of enzyme concentration, temperature and time on anti-hyperglycemic (α-amylase
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and α-glucosidase inhibition) activity
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α-Amylase (EC 3.2.1.1), a prominent pancreatic enzyme randomly cleaves α-(1–4)
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glycosidic linkages in polysaccharides such as starch and glycogen yielding dextrin, maltose and
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maltotriose. α-Glucosidase which is secreted near the mucosal brush border of small intestine
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hydrolyzes the terminal non-reducing 1-4 linked α- glucose to yield glucose molecules.
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Inhibition of α–amylase and α-glucosidase is an effective therapeutic approach to combat
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diabetes by reducing the rate of glucose release in the blood.
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inhibition activity varied between 5 to 25 % (Supplemenatry Table 3) and all the three factors
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had a significant (p<0.05) effect on the inhibition activity of BGJ. Fig. 4 shows the contour plots
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for variation in α-amylase inhibition activity as a function of temperature and enzyme keeping
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the incubation temperature at centre point.
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A significant (p<0.05) 8 % increase in α–amylase inhibition activity from 13 % to 25 % was observed when the pectinase concentration was increased from 4 ml
to 16 ml
and
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incubation time and temperature were kept at their centre point values 120 min and 40 ºC
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(Fig.4a). A statistically significant improvement in α-amylase inhibition activity (16 % – 22 %)
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was observed when incubation time was increased from 50 to 150 min (Fig. 4b). However, no
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change in activity was observed when incubation time was further increased to 190 min. α–
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Amylase inhibition significantly (p<0.05) increased from 17 % to 23 % when temperature was
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raised from 30 to 50 ºC when other two factors were at their respective centre point values.
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The α-glucosidase inhibition activity was found to be significantly (p < 0.05) affected by
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temperature. The effect of incubation temperature and enzyme on α-glucosidase inhibition
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activity, while keeping time at its centre point value is presented in Fig. 5a.
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The α-glucosidase inhibition activity varied from 20 % to 90 % (Supplemenatry Table 3).
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When temperature was increased from 30 to 50°C, α-glucosidase inhibition activity
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demonstrated a significant (p < 0.05) increase in a linear manner from 40 % to 60 % (Fig 5a).The
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inhibition activity was observed to increase from 40 % to 43 % in the enzyme concentration
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range 4 -16 ml. Similarly, α-glucosidase inhibition activity increased from 40 % to 45 % with
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increase in incubation time from 48 to 190 min. It was remarkable to observe that a combined
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effect of higher temperature (50°C) and lower incubation time of 48 min, a significant increase
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(from 54 to 81 % ) was observed with
enzyme
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concentration increasing from 4 – 16 ml. However, with increase in time from 50 to 190 min, in
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spite of providing high enzyme concentration (16 ml) and higher temperature (50°C), an overall
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decrease of α-glucosidase inhibition activity from 82 to 53 % was observed. These results
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suggest that treatment with pectinase at higher enzyme concentration and temperature for a
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longer duration facilitates release of compounds that may oxidize and destroy phenolic
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compounds.
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It was previously demonstrated that phenolic compounds are capable of inhibiting α-
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amylase and α-glucosidase enzymes due to their ability to non-specifically bind with proteins
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(McDougall et al., 2005). Different phenolic compounds have been formerly identified in bitter
308
gourd fruit (Kwon, Apostolidis, & Shetty, 2008) and its aqueous extract (Wongsa, Chaiwarit, &
309
Zamaludien, 2012). The effect of phenolic constituents on mediating inhibition of α–amylase has
310
also been demonstrated by Vinayagam et al., (2016). In the present study (section 3.2) higher
311
extraction of phenolic constituents was observed due to pectinase treatment and higher
312
temperatures (40ºC). Therefore, an increased α–amylase and α–glucosidase inhibition might be
313
due to higher extraction of phenolic compounds under the given conditions.
314
3.4. Numerical optimization
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desired bioactive profile of juice and then solving model equations. The criteria set for
317
optimization of parameters and solutions obtained are given in Table 2. Solution A corresponds
318
to criteria 1 while solution B corresponds to criteria 2. Both the solutions were experimentally
319
performed to validate the models generated. Table 2 shows both predicted and actual values for
320
responses under study. Close agreement between predicted and actual values indicate suitability
14
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of the model. Solution B (48.80°C, enzyme concentration – 10.2 ml kg-1, incubation time –
322
140.39 min) demonstrated higher juice yield along with greater α-amylase and α-glucosidase
323
inhibition potential.
324
3.5 Comparison of control and RSM optimized juice
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The juice obtained with optimized parameters was compared with aqueous extract of
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bitter gourd (control) obtained without any treatment for anti-diabetic potential, juice yield and
329
total phenolics and antioxidants. Due to optimization a significant (p < 0.05) improvement in all
330
quality attributes was observed (Table 3). As shown in Table 3, juice yield increased 1.4 - fold,
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while 2.7 and 3.5 - fold increase were obtained for α-amylase inhibition and α-glucosidase
332
inhibition activity, respectively.
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Phenolic constituents present in control and RSM optimized BGJ were identified and
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quantified (Table 4). The phenolic profile obtained was similar to that of already reported for
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bitter gourd (Horax et al., 2005; Singh, Maurya, & Singh, 2011; Kubola & Siriamornpun, 2008).
336
Phenolic contents of RSM optimized juice were significantly higher than control juice (p>0.05).
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Highest significant (p<0.0001) increase of 2.4 and 2.6 times in RSM optimized juice as
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compared to control was observed in context of gallic acid (from 63 to 152 µg ml-1) and
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protocatechuic acid (18 to 47 µg ml-1) respectively (Table 4).
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Further this study indicates that there was a significant (p<0.05) increase of 1.3, 1.7 and
341
1.1 fold for gentisic acid, catechin and epicatechin, respectively. Interestingly, ferulic acid
342
vanillic acid, caffeic acid and o coumaric acid which were not detected in control juice were
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found in concentrations of 42 µg ml-1, 28 µg ml-1, 13 µg ml-1 and 9 µg ml-1, respectively, in the
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RSM optimized BGJ (Table 4). 15
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The observed differences in anti-hyperglycemic activities in RSM optimized and control
346
juice may be due to increased extraction of bioactive phenolic compounds responsible for α–
347
amylase and α–glucosidase inhibition at different temperature and enzyme concentrations. Synthetic oral hypoglycemic drugs particularly α-glucosidase inhibitors such as acarbose
349
and miglitol are often associated with various side effects such as flatulence, abdominal pain,
350
hepatotoxicity and diarrhoea (Fujisawa, Ikegami, Inoue, Kawabata, & Ogihara, 2005). It is also
351
important to note that excessive inhibition of pancreatic amylase leads to abnormal fermentation
352
of undigested carbohydrates by bacteria. Hence an effective strategy to manage type II diabetes
353
is formulation of a phenolic rich extract from plants with strong α-glucosidase inhibition and
354
mild α-amylase inhibition (Kwon et al., 2008). Results from the present study harmonize with
355
these requirements as RSM optimized juice showed a maximum of 25 % and 90 % inhibition
356
activity of α-amylase and α-glucosidase, respectively (Supplemenatry Table 3). Wongsa et al.
357
(2012) reported aqueous extracts of bitter melon to exhibit potential inhibition against α- amylase
358
and α-glucosidase in the range of 10-15 % and 30-35 %, respectively. It is therefore noteworthy
359
to mention that the approach used in the present study for juice preparation provided comparable
360
α-amylase (25 %) while superior α- glucosidase (89 %) inhibition activity.
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4. Conclusions
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The primary goal of this study was to increase the efficiency of bitter gourd juice since it
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offers an alternative and/or complementary medicine therapy for diabetes. The present study was
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therefore aimed at optimizing the extraction conditions (incubation temperature, enzyme
366
concentration and incubation time) of bitter gourd juice for improved antioxidant and anti-
367
diabetic activity using pectinase. At optimum conditions of enzyme concentration of 10.2 ml kg-1 16
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369
yield, α-amylase inhibition and α-glucosidase inhibition activity, respectively, as compared to
370
control. A significant increase in concentrations of phenolic acids was observed with pectinase
371
treatment. Finally, these promising results confirm the potential of using this approach to obtain
372
a high quality juice contributing to better utilization of bitter gourd fruit in the form of juice for
373
diabetes treatment. Further, using this approach for juice production, dietetic and functional
374
beverages may be prepared that will increase the palatability of bitter gourd juice. Carefully
375
designed clinical studies are warranted to determine the dosage, safety and efficacy of this juice
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for in vivo studies.
377
Acknowledgements
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This work was funded by Department of Biotechnology, Government of India (DBT-JRF/2012-
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2013/109) and carried out at Bhabha Atomic Research Centre (BARC), Mumbai, India.
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Figure Captions
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Fig. 1. Effect of enzymatic treatment on the yield of bitter gourd juice (% w/w) (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
474 475 476 477
Fig. 2. Effect of enzymatic treatment on total phenolic content (µg gallic acid equivalent ml-1) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
478 479 480 481
Fig. 3. Effect of enzymatic treatment on total antioxidant capacity (µg gallic acid equivalent ml1 ) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
482 483 484 485
Fig. 4. Effect of enzymatic treatment on α-amylase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point value (10 ml kg-1).
486 487
Fig. 5. Effect of enzymatic treatment on α-glucosidase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre
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point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml /kg) is at centre point (10 ml kg-1).
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Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface methodology approach Shweta Deshaware1, Sumit Gupta2#, Rekha S. Singhal1#*, Prasad S. Variyar2 Department of Food Engineering and Technology, Institute of Chemical Technology, Mumbai-400019, India Food Technology Division, Bhabha Atomic Research Centre, Mumbai-400085, India
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Table 1
Experimental design indicating coded and actual values of independent variables for enzymatic treatment of bitter gourd
Factors Standard
Run
1
X1
(Incubation X2
(Enzyme X3 (Incubation Time)
concentration) ml kg-1
min
8
31.08 (-1)
4.05 (-1)
48.65 (-1)
2
10
48.92 (+1)
4.05 (-1)
3
1
31.08 (-1)
15.92 (+1)
4
14
48.92 (+1)
15.92 (+1)
48.65 (-1)
5
5
31.08 (-1)
4.05 (-1)
191.35 (+1)
6
19
48.92 (+1)
4.05 (-1)
191.35 (+1)
7
12
31.08 (-1)
15.92 (+1)
191.35 (+1)
8
16
48.92 (+1)
15.92 (+1)
191.35 (+1)
9
6
25 (-α)a
10 (0)
120 (0)
10
17
55 (+α)a
11
15
40 (0)
12
18
40 (0)
13
13
40 (0)
14
7
40 (0)
15
4
40 (0)
16
3
17
2
18
9
19
11
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Temperature) º C
48.65 (-1)
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48.65 (-1)
120 (0)
0 (-α)a
120 (0)
20 (+α)a
120 (0)
10 (0)
0 (-α)a
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10 (0)
240 (+α)a
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
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10 (0)
Actual values for various factors are shown along with their coded form (in parenthesis) a
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juice
α = 1.682)
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Table 2
Criteria for various factors and responses for optimization of enzymatic treatment of bitter gourd juice and their
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corresponding solutions Criteria 1
Criteria 2
Solution A
Incubation temperature (°C)
Minimize
In range (31.1 – 48.9)
45.7
Enzyme concentration (ml kg-1 )
Minimize
Minimize
12.0
Incubation time (min)
Minimize
In range (48 .6 – 191.3)
102.2
140.4
Yield (%)
Maximize
Maximize
72.1a (80 ± 1)b
73.5a (82 ± 2)b
693.0a (753 ± 8)b
637.0a (710 ± 15)b
240.1a (189 ± 13)b
238.2a (198 ± 15)b
Maximize
21.9a (22 ± 2)b
21.6a (23 ± 2)b
Maximize
58.1a (53 ± 4)b
63.9a (59 ± 3)b
Maximize
TAC (µg GAE/ml)
Maximize
Maximize
α-Amylase inhibition (%)
Maximize
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α-Glucosidase inhibition (%)
Maximize
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48.8
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TPC (µg GAE/ml)
Solution B
10.2
a – Predicted values; b – Actual values. Data represent the mean ± SD of three experimental replicates.
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Table 3 Bioactivity profile for RSM optimized enzymatically treated vis-à-vis control bitter gourd juice
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RSM optimized Response
Control juice
Fold increase
1.4
juice Yield (%)
82 ± 2
59 ± 3
Total phenolic content (µg GAE/ml)
710 ± 15
464 ± 16
Total antioxidant capacity (µg GAE/ml)
198 ± 15
162 ± 13
α-Amylase inhibition (%)
23 ± 2
8±2
2.7
α-Glucosidase inhibition (%)
59 ± 3
17 ± 3
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Data represent the mean ± SD of triplicate values of three experimental replicates GAE – Gallic acid equivalent
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1.2
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Table 4 Phenolic acid content (µg/ml) in RSM optimized enzymatically treated vis-à-vis control bitter gourd juice RSM optimized juice
Phenolic acid
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Control juice
P value 63 ± 5a
152 ± 8b
< 0.0001
Protocatechuic acid
18 ± 1a
47 ± 3b
< 0.0001
Gentisic acid
598 ± 16a
766 ± 32b
Catechin
120 ± 26a
201 ± 5b
Vanillic acid
Not detecteda
28 ± 1b
-
Caffeic acid
Not detecteda
13 ± 1b
-
Tannic acid
148 ± 2a
142 ± 2b
0.0168
(-)Epicatechin
1078 ± 53a
1216 ± 33b
0.0183
Ferulic acid
Not detecteda
42 ± 3b
-
o-Coumaric acid
Not detecteda
9 ± 1b
-
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Gallic acid
0.0012
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0.0213
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Data represent the mean ± SD of triplicates of three experimental replicates. At any time point, different letters (a, b) correspond to statistically significant differences between control and RSM optimized juice according to one-way ANOVA followed by Tukey post hoc test (P ≤ 0.05).
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Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface methodology approach Shweta Deshaware1, Sumit Gupta2#, Rekha S. Singhal1#*, Prasad S. Variyar2
400019, India
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Food Technology Division, Bhabha Atomic Research Centre, Mumbai-400085, India
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Department of Food Engineering and Technology, Institute of Chemical Technology, Mumbai-
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Fig. 1. Effect of enzymatic treatment on the yield of bitter gourd juice (% w/w) (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
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Fig. 2. Effect of enzymatic treatment on total phenolic content (µg gallic acid equivalent ml-1) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
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Fig. 3. Effect of enzymatic treatment on total antioxidant capacity (µg gallic acid equivalent ml1 ) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
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Fig. 4. Effect of enzymatic treatment on α-amylase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point value (10 ml kg-1).
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Fig. 5. Effect of enzymatic treatment on α-glucosidase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml /kg) is at centre point (10 ml kg-1).
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Highlights Extraction of bitter gourd juice was optimized using Response Surface Methodology
•
Phenolic content was 1.5 times higher in pectinase treated juice
•
2.47 and 3.74 fold higher α-amylase and α-glucosidase inhibition was obtained
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Nature of phenolic constituents was identified using HPLC
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S0023-6438(17)30607-2
DOI:
10.1016/j.lwt.2017.08.037
Reference:
YFSTL 6459
To appear in:
LWT - Food Science and Technology
Received Date: 18 May 2017 Revised Date:
9 August 2017
Accepted Date: 12 August 2017
Please cite this article as: Deshaware, S., Gupta, S., Singhal, R.S., Variyar, P.S., Enhancing antidiabetic potential of bitter gourd juice using pectinase: A response surface methodology approach, LWT - Food Science and Technology (2017), doi: 10.1016/j.lwt.2017.08.037. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface
2
methodology approach
3 4 5
Shweta Deshaware1, Sumit Gupta2#, Rekha S. Singhal1#*, Prasad S. Variyar2 1
Department of Food Engineering and Technology, Institute of Chemical Technology, Mumbai400019, India
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2
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Food Technology Division, Bhabha Atomic Research Centre, Mumbai-400085, India
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ABSTRACT
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Bitter gourd exhibits significant anti-diabetic activity. In the present study, pectinase
11
concentration (4.04 – 15.92 ml kg-1), incubation time (48 to 191 min) and temperature (31 to
12
55°C) were optimized using response surface methodology (RSM) for obtaining increased juice
13
yield with higher anti-diabetic (α-amylase and α-glucosidase inhibition) activity, total phenolics
14
and antioxidant activity. The optimum conditions i.e. pectinase concentration (10.2 ml kg-1),
15
incubation time (140 min) and temperature (48.8°C) resulted in juice yield of 82 %, α–amylase
16
and α-glucosidase inhibition activity of 23 and 59 %, respectively, with total phenolic and
17
antioxidant content of 710 and 198 µg GAE ml-1, respectively. In comparison, control (prepared
18
without enzyme treatment) had significantly (p<0.05) lower juice yield, α–amylase and α-
19
glucosidase inhibition activity of 59, 8 and 17 %, respectively. Control samples also
20
demonstrated significantly (p<0.05) lower total phenolic and antioxidant content of 464 and 162
21
µg GAE ml-1, respectively. RSM optimized juice also demonstrated significantly (p>0.05) higher
22
contents of phenolic acids as compared to control juice.
23
Keywords:
24
Momordica charantia L.
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# These authors contributed equally Corresponding authors: Dr. Rekha Singhal; email: [email protected], phone: +91-22-33612501 Dr. Sumit Gupta; email: [email protected], phone: +91-22-25590560
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Antioxidant capacity
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Anti-hyperglycemic activity
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Phenolic acids
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Central composite rotatable design
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1. Introduction
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Occurrence and prevalence of obesity and associated metabolic disorders such as
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cardiovascular diseases and type 2 diabetes mellitus are on the rise worldwide. Based on a
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collective study from different parts of the world, the World Health Organization (WHO) has
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projected that maximum increase in incidence of diabetes could occur in India, China and US
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(King, Aubert, & Herman, 1998).
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Bitter gourd (Momordica charantia L.), an annual climbing plant belonging to the
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Cucurbitaceae family, is an extensively investigated tropical medicinal plant. Its fruit, also
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known as balsam pear, bitter melon or karela has a distinct bitter taste which enhances as the
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fruit ripens. Bitter gourd has been popular as a natural remedy in Ayurvedic systems owing to its
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anti-diabetic, anti-malarial, anti-inflammatory, antiviral, contraceptive and insecticidal properties
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(Grover & Yadav, 2004). Bitter gourd juice (BGJ) has a rich array of bioactive phytochemicals
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including vitamins, minerals and phenolic compounds (Horax, Hettiarachchy, & Islam, 2005).
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Phenolic compounds have been widely reported to have both high antioxidant potential (Wu &
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Ng, 2007) and anti-diabetic activity (Vinayagam, Jayachandran, & Xu, 2016). Other bioactive
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molecules in bitter gourd include steroidal saponins, charantin, insulin like peptides,
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glycoalkaloids, vicine, momorcharin, oleanolic acids, triterpenes, trehalose and momordin
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(Grover & Yadav, 2004). There is a need to develop protocols for juice preparation with enhanced extraction of
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bioactives which is simple, cost effective as well as rapid. Microbial pectinases have been widely
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used in preparation of vegetable and fruit juices for higher yield, higher clarity, lower viscosity
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and cloudiness, reduced bitterness and improved nutrient profile (Kashyap, Vohra, Chopra, &
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Tewari, 2001). It may be hypothesized that the use of pectinase for treating bitter gourd pulp
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would enhance juice yield and facilitate the release of bioactive compounds.
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Response surface methodology is a statistically designed tool which uses minimum
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number of experiments to provide an optimized response outcome by comparing net interactions
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of various parameters. Taking into consideration the immense potential of bitter gourd to become
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a dietary beverage for diabetic and pre-diabetic patients, this study aimed at optimization of
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parameters (incubation time, incubation temperature and enzyme concentration) for extraction of
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BGJ with desirable responses (yield, total phenols, total antioxidant potential, α-glucosidase
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inhibition and α-amylase inhibition) using enzymatic pretreatment of pulp. It also attempts to
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identify and quantify the phenolic content in native and enzyme pretreated BGJ.
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2. Materials and methods
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2.1. Plant material
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Bitter gourd fruits were purchased from a local grower on the outskirts of Mumbai
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(India). Fruits were brought to the laboratory within 12-14 h after harvesting and immediately
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stored at refrigerated temperature (10 ºC). Selection of fruits was based on maturity (14-16 days
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after fruit set), free from visual defects, dark green color, 20-25 cm long, pendulous in shape.
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2.2. Chemicals and enzymes Pectinase from Aspergillus niger (specific activity 70.4 µKat/ml, protein concentration
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10.6 mg/ml), α-amylase from porcine pancreas (Type IV-B), α-glucosidase from Saccharomyces
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cerevisiae and p-nitrophenyl-α-D-glucopyranoside were procured from Sigma-Aldrich (St.
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Louis, MO, USA). Folin-Ciocalteau’s phenol reagent (FC), 2,2-diphenyl-1-picrylhydrazyl
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(DPPH), standard phenolic acids (gallic acid, protocatechuic acid, gentisic acid, (+) catechin,
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vanillic acid, caffeic acid, tannic acid, (-) epicatechin, ferulic acid, and o-coumaric acid) and
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HPLC grade solvents (acetonitrile, o-phosphoric acid and glacial acetic acid) were also procured
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from Sigma-Aldrich (Mumbai, India). All the other chemicals and reagents were of analytical
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grade and obtained from Merck (Mumbai, India).
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2.3. Methods
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2.3.1. Preparation of bitter gourd juice
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Bitter gourd fruits were washed with running tap water to remove all adhering dust.
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Whole fruit including the rind were diced into small pieces (approximately 3 cm × 3 cm). Pulp
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was then prepared using a high speed homogenizer (BUCHI Mixer B-400, Switzerland). For
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each trial, 50 g of pulp was subjected to different treatments according to experimental design
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(section 2.3.2). At the end of each experimental trial, pectinase was inactivated by heating the
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pulp in a water bath at 90ºC for 5 min. After cooling to room temperature (24 ± 2oC) using ice
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cold water bath, the pulp was immediately centrifuged at 1699 x g at 25°C for 20 min to obtain a
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clear supernatant. Juice samples were stored at -20ºC till all further analysis to prevent any
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deterioration or spoilage by microbial contamination.
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2.3.2. Experimental design
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Experiments were designed and analysis was performed using Design expert 8.0 software
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(Stat-Ease Inc., USA). A central composite rotatable design was used to study the combined 4
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X2) and incubation time (X3) coded at five levels (-α, -1, 0, +1 and +α ). Based on preliminary
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experiments, the range of variables selected was as follows: incubation temperature: 25 to 50°C,
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enzyme concentration: 0 to 20 ml kg-1 and time: 0 to 240 min. The natural pH of the juice was
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maintained at 4.1 which falls in the optimal pH range for acidic pectinases. The complete design
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consisted of 19 experimental points including 5 replications of center point (all variables coded
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as zero) (Table 1). The experiments were carried out in triplicates to ensure repeatability of
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experiments.
Juice yield was determined in terms of percentage.
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2.4. Determination of juice yield
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Yield percent = [Juice weight/Total pulp weight] x 100
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2.5. Determination of total phenolic content (TPC)
The total phenolic content was determined using the Folin-Ciocalteau method (Singleton,
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Orthofer, & Lamuela-Raventós, 1999) with slight modification. In brief, 100 µl of aqueous
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dilution of juice (20 ml l-1) was added to 650 µl of 1:10 diluted FC reagent (2 mol l-1). The
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mixture was incubated for 5 min and then 650 µl of 60 g l-1 Na2CO3 was added. This mixture
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was then allowed to stand for 90 min in dark at room temperature. Absorbance (y) was measured
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against blank at 750 nm. A calibration curve of gallic acid (0 to 18 µg ml-1) was plotted. TPC
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was calculated using regression equation (y=0.0714x - 0.0225, R2 = 0.9954) obtained from gallic
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acid standard curve and expressed as µg gallic acid equivalents (GAE) ml-1 of juice.
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2.6. Determination of total antioxidant capacity (TAC)
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A DPPH radical scavenging assay was used to evaluate total antioxidant activity using a
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method described by Brand-Williams, Cuvelier, & Berset (1995) with slight modification. In
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brief, 100 µl of juice was incubated with 900 µl of DPPH (1.2 mol l-1 in distilled methanol) in
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ACCEPTED MANUSCRIPT dark for 30 min at room temperature. Absorbance (y) was measured against blank at 517 nm. A
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calibration curve of gallic acid (0 to 30 µg ml-1) was plotted. TAC was calculated using
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regression equation (y = -0.2016x + 0.9117, R2 = 0.9524) obtained from gallic acid standard
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curve and expressed as µg gallic acid equivalents (GAE) ml-1 of juice.
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2.7. Pancreatic α–amylase inhibition assay
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α-Amylase inhibition assay was performed as described by Telagari & Hullatti (2015)
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with certain modifications. In brief, the reagents used were as follows: α-amylase enzyme
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solution (1.6 µkat ml-1), 20 g l-1 (aqueous solution) starch, dinitrosalicylic acid (DNS) reagent.
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Juice sample (100 µl) was pre-incubated at 25ºC for 10 min with 100 µl of 0.02 mol l-1 sodium
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phosphate buffer (pH 6.9) and 100 µl α-amylase solution. Then 100 µl of 20 g l-1 starch solution
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was added and resulting mixture was incubated at 25ºC for 10 min following which 100 µl of
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0.02 mol l-1 sodium phosphate buffer (pH 6.9) was added.
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Since the inherent carbohydrate content of the juice was high, protocol was suitably
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modified by preparing two control tubes - control A (control without juice) and control B
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(control with juice) for accurately estimating the change specifically due to starch degradation by
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amylase in presence of juice (acting as inhibitor). All the reactions (test, control A and control B)
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were stopped by adding 1 ml DNS reagent and incubating in a boiling water bath for 5 min.
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After cooling the tubes to room temperature, reaction mixture was diluted 10 fold using distilled
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water and absorbance was recorded at 540 nm (UV 3000+, LABINDIA analytical, Mumbai,
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India). α-Amylase inhibition activity was calculated relative to controls and expressed in terms
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of percentage of that value.
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The α-amylase inhibition activity was calculated according to the following equation:
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Percent α-amylase inhibition = [(Control B – Test) / Control A] x 100 6
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2.8 α-Glucosidase inhibition assay α-Glucosidase inhibition activity was estimated using a modified version of the assay
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described by Telagari & Hullatti (2015) . The reagents used were sodium phosphate buffer (0.02
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mol l-1, pH 6.9), α-glucosidase enzyme (16.67 nkat ml-1), p-nitrophenyl–α-D–glucopyranoside
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(PNPG) substrate (5 mmol l-1 solution in 0.02 mol l-1 sodium phosphate buffer) and 0.2 mol l-1
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glycine NaOH buffer (pH 10). A volume of 50 µl of α-glucosidase enzyme was pre-incubated
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with 25 µl of juice in 96-well plates at 37°C for 5 min. After pre-incubation, 25 µl of PNPG
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substrate was added to each well at timed intervals and the plate was incubated at 37°C for
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10 min. Then 25 µl of sodium phosphate buffer was added. To account for the inherent
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carbohydrate content, two controls were used as previously described in section 2.7. All the
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reactions (test, control A and control B) were stopped by adding 175 µl of glycine NaOH buffer.
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α-Glucosidase inhibition activity was also estimated relative to two controls and
Percent α-Glucosidase inhibition = [(Control B – Test) / Control A] x 100 2.9 Chromatographic analysis of phenolic acids
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HPLC (Ultimate 3000, Dionex) equipped with UV-vis detector and reversed-phase
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Hypersil C18 column (5 µm particle size, 250 × 4.6 mm, Thermo Electron corporation, New
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Delhi, India) was used for analysis. The solvent system used was a gradient of mobile phase A
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containing o- phosphoric acid (15 ml l-1) in water and solution B containing a mixture of
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acetonitrile (200 ml l-1), glacial acetic acid (240 ml l-1), o-phosphoric acid (15 ml l-1) and water
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(545 ml l-1). The following gradient was used: 0-5 min, 100 % A, 5-10 min; from 100 % A, 0 %
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B to 80 % A , 20 % B; 10-40 min, from 80 % A, 20 % B to 62 % A, 38 % B ; 40-45 min, from
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62 % A , 38 % B to 0 % A and 100 % B with flow rate of 1 ml min-1. Column temperature was
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ACCEPTED MANUSCRIPT maintained at 30°C and the injection volume was 20 µl. Chromatograms were acquired at
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wavelength of 280 nm. Each phenolic acid was identified by its retention time and spiking with
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each standard under similar conditions. Quantification was done using calibration curves of each
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standard phenolics prepared. Data are reported as mean ± standard deviation (SD) of replicate
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measurements.
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2.10 Statistical analysis
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Statistical analysis was performed using Design expert software 8.0 (Stat-Ease, USA).
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Experimental data were fitted into third order polynomial (quadratic) following which models for
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each response were generated. Backward regression method was used to remove insignificant
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terms. The model was evaluated at 0.05 significance using analysis of variance (ANOVA).
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Coefficient of determination (R2) was used to quantify predictive ability of the model. Equations
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obtained after fitting the data in polynomial equations were used to generate 3D response surface
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plots to elucidate relationship between response and experimental levels. Numerical optimization
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was performed to get the desired response outcome. The differences in phenolic acid content
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between control and RSM optimized juice were compared using unpaired t test.
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3. Results and discussion
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The optimum process parameters for maximizing the responses were obtained using
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numerical optimization using Stat-Ease Design Expert software (v8). Statistical analyses were
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performed using ANOVA. It revealed that the models generated by RSM were significant
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(p<0.05) while lack of fit was insignificant (p > 0.05). Adequacy precision which measures the
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signal to noise ratio were above 4 for all the responses (Supplementary file Table 1). It is
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suggested that this model could be used to navigate the design space.
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ACCEPTED MANUSCRIPT The coefficients for predicted regression models and coefficient of determination (R2) is
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shown in Supplementary file - Table 2. High R2 values (at least 0.80) imply that the empirical
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models are a good fit to actual data.
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3.1. Impact of enzyme concentration, time and temperature on juice yield
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The yield of juice varied from 58 to 77 % (Supplementary Table 3). All the three
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variables i.e. temperature, time and enzyme concentration had a significant (p<0.05) effect on
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juice yield. Response curves in the form of contour plots have been represented in Fig. 1. Each
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plot represents the effect of two factors while keeping the third at centre point. Fig. 1a
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demonstrates effect of temperature and enzyme concentration on juice yield when incubation
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time was at centre point.
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It was observed that juice yield increased from 66 to 72 % due to an increase in enzyme
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concentration from 4 -16 ml kg-1 when other two factors i.e. time and temperature were at their
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respective centre point values of 120 min and 121.93°C, respectively. Aziz, Roy, Sarker, &
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Yusof (2011) reported that bitter gourd contained pectin (12 %), hemicellulose (13 %) and
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cellulose (27.5 %) as major polysaccharides. It is known that pectinase helps in increasing the
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juice yield by degradation of cell wall polysaccharides and improving the press-ability of pulp
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(Tapre & Jain, 2014). Pectinase treatment has been earlier reported to markedly improve juice
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yield of various fruits and vegetable juices (Kashyap et al., 2001).
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Effect of temperature and time on juice yield is shown in Fig. 1b. No change in juice
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yield was observed in the temperature range of 30 to 40ºC when the other two factors were at
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their respective centre point values. A juice yield of 70 % was observed up to temperature of
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40ºC. However, further increase in temperature beyond 40ºC resulted in a higher juice yield of
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76 %. Higher temperature in the range of 40ºC – 50ºC may have favored higher enzyme activity 9
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by findings of Singh, Sharma, Kumar, Upadhyay, & Mishra, (2013) and Kaur, Sarkar, Sharma,
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Singh, (2009) where maximum juice yield from pectinase treated pulp from bael fruit and guava
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were obtained at 45.8°C and 43.3°C, respectively.
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Juice yield was also found to increase with incubation time. An enhancement in yield
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from 69 % to 73 % was observed as a result of increase in the time of incubation from 48 to 191
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min when temperature and enzyme concentration were at their respective centre point values. A
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similar trend of increase in yield with increasing incubation time was observed for banana juice
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(Tapre & Jain, 2014) and bael fruit juice (Singh, Kumar, & Sharma, 2012).
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3.2 Impact of enzyme concentration, temperature and time on Total Phenolic Content (TPC) and
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Total Antioxidant Capacity (TAC)
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The response curves for total phenolics and total antioxidant activity are shown in Fig. 2
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and 3, respectively; each demonstrating effect of two factors while keeping the third at centre
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point. Maximum recovery of polyphenols (798 µg GAE/ml) as well as antioxidant activity (355
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µg GAE/ml) was evident when 10 ml kg-1 pectinase was used for 240 min at 40°C
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(Supplementary Table 3). Incubation temperature and enzyme concentration were most
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significant (p<0.05) factors while incubation time did not have a significant (p>0.05) effect on
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TPC and TAC.
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With increasing temperature, the concentration of phenolic compounds increased
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significantly (p<0.05) from 550 to 725 µg GAE ml-1 up to 40°C. However a decrease in TPC
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was observed above 40°C (Fig 2a). Similarly, TAC increased from 200 to 275 µg GAE ml-1 in
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the range of 30 - 40°C, and then decreased with further increase in temperature to 50°C (Fig. 3a).
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An increase in temperature may have resulted in increased diffusion coefficients of water soluble 10
ACCEPTED MANUSCRIPT compounds and thereby increasing the extraction efficiency of phenolic compounds (Spigno &
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De Faveri, 2007). However at higher temperatures, polyphenol oxidase gets activated during
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processing of juice as plant cells are ruptured. This enzyme has the ability to oxidize polyphenols
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resulting in loss of antioxidant activity. Gradual degradation of certain phenolics such as caffeic
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acid, sinapic, p–coumaric and ferulic acids have been reported to occur beyond 40°C, while
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cinnnamic acids and benzoic acids are more stable at these temperatures (Ma et al., 2008).
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With respect to enzyme concentration, increasing pectinase concentration (10 – 12.8 ml
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kg-1) enhanced the TPC from 630 to a maximum of 725 µg GAE ml-1. However, an increase in
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pectinase concentration beyond 12.8 ml kg-1 did not result in any further increase in TPC (Fig 2a
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and 2b). Improved extraction efficiency of phenolics may occur via two mechanisms viz.
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hydrolytic degradation of cell wall polysaccharides or enzyme catalyzed fissure of ether and
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ester linkages between the phenols and cell wall polymers (Pinelo, Zornoza, & Meyer , 2008).
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Our results are in accordance with previous works on carrot juice (Khandare, Walia, Singh, &
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Kaur , 2011) and dragon fruit juice (Nur‘Alia, Siti Mazlina, & Taip , 2010) where an increase in
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polyphenols was obtained with pectinase treatment.
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The TAC increased from 118 to 296 µg GAE ml-1 with increasing concentrations from 4
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– 10 ml kg-1. However, interestingly, further rise in pectinase concentration showed a marked
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decrease in the antioxidant activity to 136 µg GAE ml-1 when enzyme concentration was 16 ml
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kg-1 (Fig 3a). Antioxidant activity depends on both total phenolic content and types of phenolic
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acids (Shian, Abdullah, NurKartinee, & Ariffin, 2015) with different phenolic compounds
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demonstrating varying degrees of antioxidant activity (Nuutila, Puupponen-Pimiä, Aarni, &
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Oksman-Caldentey , 2003). The observed decrease in antioxidant activity may have occurred due
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to degradation and settling of polyphenolics, primarily those with high antioxidant potential
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owing to combined effect of higher temperatures and greater enzyme concentration (Makris &
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Rossiter, 2001). Incubation time had no significant (p>0.05) effect on TPC and TAC. Only a small
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increment for TPC from 700 to 725 µg GAE/ml with increase in time from 50 to 190 min was
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observed (Fig. 2b). Similarly, only a minor increment of antioxidant capacity from 280 to 310 µg
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GAE ml-1 was observed in the aforementioned time. These results imply that 50 min would
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possibly be sufficient time along with pectinase concentration of 4 – 12 ml and incubation
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temperature in the range 35-45°C for maximum recovery of TPC and TAC in BGJ.
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Independent investigations by Wu & Ng (2008) and Kubola & Siriamornpun (2008) have
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reported water extracts of bitter gourd to contain 516 µg GAE ml-1 and 202 µg GAE ml-1,
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respectively. Recently, Jain & De (2016) performed optimization of aqueous extraction of BGJ
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and reported to contain 23.1 mg GAE per100 ml (231 µg GAE ml-1) of polyphenols. A higher
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extraction efficiency of polyphenols (798 µg GAE ml-1) in enzyme pretreated juice than the cited
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literature for aqueous extract of bitter gourd was obtained in this study.
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3.3 Impact of enzyme concentration, temperature and time on anti-hyperglycemic (α-amylase
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and α-glucosidase inhibition) activity
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α-Amylase (EC 3.2.1.1), a prominent pancreatic enzyme randomly cleaves α-(1–4)
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glycosidic linkages in polysaccharides such as starch and glycogen yielding dextrin, maltose and
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maltotriose. α-Glucosidase which is secreted near the mucosal brush border of small intestine
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hydrolyzes the terminal non-reducing 1-4 linked α- glucose to yield glucose molecules.
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Inhibition of α–amylase and α-glucosidase is an effective therapeutic approach to combat
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diabetes by reducing the rate of glucose release in the blood.
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inhibition activity varied between 5 to 25 % (Supplemenatry Table 3) and all the three factors
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had a significant (p<0.05) effect on the inhibition activity of BGJ. Fig. 4 shows the contour plots
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for variation in α-amylase inhibition activity as a function of temperature and enzyme keeping
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the incubation temperature at centre point.
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A significant (p<0.05) 8 % increase in α–amylase inhibition activity from 13 % to 25 % was observed when the pectinase concentration was increased from 4 ml
to 16 ml
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incubation time and temperature were kept at their centre point values 120 min and 40 ºC
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(Fig.4a). A statistically significant improvement in α-amylase inhibition activity (16 % – 22 %)
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was observed when incubation time was increased from 50 to 150 min (Fig. 4b). However, no
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change in activity was observed when incubation time was further increased to 190 min. α–
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Amylase inhibition significantly (p<0.05) increased from 17 % to 23 % when temperature was
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raised from 30 to 50 ºC when other two factors were at their respective centre point values.
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The α-glucosidase inhibition activity was found to be significantly (p < 0.05) affected by
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temperature. The effect of incubation temperature and enzyme on α-glucosidase inhibition
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activity, while keeping time at its centre point value is presented in Fig. 5a.
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The α-glucosidase inhibition activity varied from 20 % to 90 % (Supplemenatry Table 3).
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When temperature was increased from 30 to 50°C, α-glucosidase inhibition activity
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demonstrated a significant (p < 0.05) increase in a linear manner from 40 % to 60 % (Fig 5a).The
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inhibition activity was observed to increase from 40 % to 43 % in the enzyme concentration
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range 4 -16 ml. Similarly, α-glucosidase inhibition activity increased from 40 % to 45 % with
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increase in incubation time from 48 to 190 min. It was remarkable to observe that a combined
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effect of higher temperature (50°C) and lower incubation time of 48 min, a significant increase
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(from 54 to 81 % ) was observed with
enzyme
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concentration increasing from 4 – 16 ml. However, with increase in time from 50 to 190 min, in
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spite of providing high enzyme concentration (16 ml) and higher temperature (50°C), an overall
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decrease of α-glucosidase inhibition activity from 82 to 53 % was observed. These results
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suggest that treatment with pectinase at higher enzyme concentration and temperature for a
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longer duration facilitates release of compounds that may oxidize and destroy phenolic
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compounds.
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It was previously demonstrated that phenolic compounds are capable of inhibiting α-
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amylase and α-glucosidase enzymes due to their ability to non-specifically bind with proteins
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(McDougall et al., 2005). Different phenolic compounds have been formerly identified in bitter
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gourd fruit (Kwon, Apostolidis, & Shetty, 2008) and its aqueous extract (Wongsa, Chaiwarit, &
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Zamaludien, 2012). The effect of phenolic constituents on mediating inhibition of α–amylase has
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also been demonstrated by Vinayagam et al., (2016). In the present study (section 3.2) higher
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extraction of phenolic constituents was observed due to pectinase treatment and higher
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temperatures (40ºC). Therefore, an increased α–amylase and α–glucosidase inhibition might be
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due to higher extraction of phenolic compounds under the given conditions.
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3.4. Numerical optimization
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desired bioactive profile of juice and then solving model equations. The criteria set for
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optimization of parameters and solutions obtained are given in Table 2. Solution A corresponds
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to criteria 1 while solution B corresponds to criteria 2. Both the solutions were experimentally
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performed to validate the models generated. Table 2 shows both predicted and actual values for
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responses under study. Close agreement between predicted and actual values indicate suitability
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of the model. Solution B (48.80°C, enzyme concentration – 10.2 ml kg-1, incubation time –
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140.39 min) demonstrated higher juice yield along with greater α-amylase and α-glucosidase
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inhibition potential.
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3.5 Comparison of control and RSM optimized juice
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The juice obtained with optimized parameters was compared with aqueous extract of
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bitter gourd (control) obtained without any treatment for anti-diabetic potential, juice yield and
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total phenolics and antioxidants. Due to optimization a significant (p < 0.05) improvement in all
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quality attributes was observed (Table 3). As shown in Table 3, juice yield increased 1.4 - fold,
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while 2.7 and 3.5 - fold increase were obtained for α-amylase inhibition and α-glucosidase
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inhibition activity, respectively.
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Phenolic constituents present in control and RSM optimized BGJ were identified and
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quantified (Table 4). The phenolic profile obtained was similar to that of already reported for
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bitter gourd (Horax et al., 2005; Singh, Maurya, & Singh, 2011; Kubola & Siriamornpun, 2008).
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Phenolic contents of RSM optimized juice were significantly higher than control juice (p>0.05).
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Highest significant (p<0.0001) increase of 2.4 and 2.6 times in RSM optimized juice as
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compared to control was observed in context of gallic acid (from 63 to 152 µg ml-1) and
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protocatechuic acid (18 to 47 µg ml-1) respectively (Table 4).
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Further this study indicates that there was a significant (p<0.05) increase of 1.3, 1.7 and
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1.1 fold for gentisic acid, catechin and epicatechin, respectively. Interestingly, ferulic acid
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vanillic acid, caffeic acid and o coumaric acid which were not detected in control juice were
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found in concentrations of 42 µg ml-1, 28 µg ml-1, 13 µg ml-1 and 9 µg ml-1, respectively, in the
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RSM optimized BGJ (Table 4). 15
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The observed differences in anti-hyperglycemic activities in RSM optimized and control
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juice may be due to increased extraction of bioactive phenolic compounds responsible for α–
347
amylase and α–glucosidase inhibition at different temperature and enzyme concentrations. Synthetic oral hypoglycemic drugs particularly α-glucosidase inhibitors such as acarbose
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and miglitol are often associated with various side effects such as flatulence, abdominal pain,
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hepatotoxicity and diarrhoea (Fujisawa, Ikegami, Inoue, Kawabata, & Ogihara, 2005). It is also
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important to note that excessive inhibition of pancreatic amylase leads to abnormal fermentation
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of undigested carbohydrates by bacteria. Hence an effective strategy to manage type II diabetes
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is formulation of a phenolic rich extract from plants with strong α-glucosidase inhibition and
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mild α-amylase inhibition (Kwon et al., 2008). Results from the present study harmonize with
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these requirements as RSM optimized juice showed a maximum of 25 % and 90 % inhibition
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activity of α-amylase and α-glucosidase, respectively (Supplemenatry Table 3). Wongsa et al.
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(2012) reported aqueous extracts of bitter melon to exhibit potential inhibition against α- amylase
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and α-glucosidase in the range of 10-15 % and 30-35 %, respectively. It is therefore noteworthy
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to mention that the approach used in the present study for juice preparation provided comparable
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α-amylase (25 %) while superior α- glucosidase (89 %) inhibition activity.
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4. Conclusions
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The primary goal of this study was to increase the efficiency of bitter gourd juice since it
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offers an alternative and/or complementary medicine therapy for diabetes. The present study was
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therefore aimed at optimizing the extraction conditions (incubation temperature, enzyme
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concentration and incubation time) of bitter gourd juice for improved antioxidant and anti-
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diabetic activity using pectinase. At optimum conditions of enzyme concentration of 10.2 ml kg-1 16
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yield, α-amylase inhibition and α-glucosidase inhibition activity, respectively, as compared to
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control. A significant increase in concentrations of phenolic acids was observed with pectinase
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treatment. Finally, these promising results confirm the potential of using this approach to obtain
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a high quality juice contributing to better utilization of bitter gourd fruit in the form of juice for
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diabetes treatment. Further, using this approach for juice production, dietetic and functional
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beverages may be prepared that will increase the palatability of bitter gourd juice. Carefully
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designed clinical studies are warranted to determine the dosage, safety and efficacy of this juice
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for in vivo studies.
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Acknowledgements
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This work was funded by Department of Biotechnology, Government of India (DBT-JRF/2012-
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2013/109) and carried out at Bhabha Atomic Research Centre (BARC), Mumbai, India.
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Figure Captions
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Fig. 1. Effect of enzymatic treatment on the yield of bitter gourd juice (% w/w) (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
474 475 476 477
Fig. 2. Effect of enzymatic treatment on total phenolic content (µg gallic acid equivalent ml-1) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
478 479 480 481
Fig. 3. Effect of enzymatic treatment on total antioxidant capacity (µg gallic acid equivalent ml1 ) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
482 483 484 485
Fig. 4. Effect of enzymatic treatment on α-amylase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point value (10 ml kg-1).
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Fig. 5. Effect of enzymatic treatment on α-glucosidase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre
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point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml /kg) is at centre point (10 ml kg-1).
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Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface methodology approach Shweta Deshaware1, Sumit Gupta2#, Rekha S. Singhal1#*, Prasad S. Variyar2 Department of Food Engineering and Technology, Institute of Chemical Technology, Mumbai-400019, India Food Technology Division, Bhabha Atomic Research Centre, Mumbai-400085, India
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Table 1
Experimental design indicating coded and actual values of independent variables for enzymatic treatment of bitter gourd
Factors Standard
Run
1
X1
(Incubation X2
(Enzyme X3 (Incubation Time)
concentration) ml kg-1
min
8
31.08 (-1)
4.05 (-1)
48.65 (-1)
2
10
48.92 (+1)
4.05 (-1)
3
1
31.08 (-1)
15.92 (+1)
4
14
48.92 (+1)
15.92 (+1)
48.65 (-1)
5
5
31.08 (-1)
4.05 (-1)
191.35 (+1)
6
19
48.92 (+1)
4.05 (-1)
191.35 (+1)
7
12
31.08 (-1)
15.92 (+1)
191.35 (+1)
8
16
48.92 (+1)
15.92 (+1)
191.35 (+1)
9
6
25 (-α)a
10 (0)
120 (0)
10
17
55 (+α)a
11
15
40 (0)
12
18
40 (0)
13
13
40 (0)
14
7
40 (0)
15
4
40 (0)
16
3
17
2
18
9
19
11
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Temperature) º C
48.65 (-1)
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48.65 (-1)
120 (0)
0 (-α)a
120 (0)
20 (+α)a
120 (0)
10 (0)
0 (-α)a
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10 (0)
240 (+α)a
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
40 (0)
10 (0)
120 (0)
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Actual values for various factors are shown along with their coded form (in parenthesis) a
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juice
α = 1.682)
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Table 2
Criteria for various factors and responses for optimization of enzymatic treatment of bitter gourd juice and their
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corresponding solutions Criteria 1
Criteria 2
Solution A
Incubation temperature (°C)
Minimize
In range (31.1 – 48.9)
45.7
Enzyme concentration (ml kg-1 )
Minimize
Minimize
12.0
Incubation time (min)
Minimize
In range (48 .6 – 191.3)
102.2
140.4
Yield (%)
Maximize
Maximize
72.1a (80 ± 1)b
73.5a (82 ± 2)b
693.0a (753 ± 8)b
637.0a (710 ± 15)b
240.1a (189 ± 13)b
238.2a (198 ± 15)b
Maximize
21.9a (22 ± 2)b
21.6a (23 ± 2)b
Maximize
58.1a (53 ± 4)b
63.9a (59 ± 3)b
Maximize
TAC (µg GAE/ml)
Maximize
Maximize
α-Amylase inhibition (%)
Maximize
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α-Glucosidase inhibition (%)
Maximize
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TPC (µg GAE/ml)
Solution B
10.2
a – Predicted values; b – Actual values. Data represent the mean ± SD of three experimental replicates.
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Table 3 Bioactivity profile for RSM optimized enzymatically treated vis-à-vis control bitter gourd juice
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RSM optimized Response
Control juice
Fold increase
1.4
juice Yield (%)
82 ± 2
59 ± 3
Total phenolic content (µg GAE/ml)
710 ± 15
464 ± 16
Total antioxidant capacity (µg GAE/ml)
198 ± 15
162 ± 13
α-Amylase inhibition (%)
23 ± 2
8±2
2.7
α-Glucosidase inhibition (%)
59 ± 3
17 ± 3
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1.2
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Table 4 Phenolic acid content (µg/ml) in RSM optimized enzymatically treated vis-à-vis control bitter gourd juice RSM optimized juice
Phenolic acid
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Control juice
P value 63 ± 5a
152 ± 8b
< 0.0001
Protocatechuic acid
18 ± 1a
47 ± 3b
< 0.0001
Gentisic acid
598 ± 16a
766 ± 32b
Catechin
120 ± 26a
201 ± 5b
Vanillic acid
Not detecteda
28 ± 1b
-
Caffeic acid
Not detecteda
13 ± 1b
-
Tannic acid
148 ± 2a
142 ± 2b
0.0168
(-)Epicatechin
1078 ± 53a
1216 ± 33b
0.0183
Ferulic acid
Not detecteda
42 ± 3b
-
o-Coumaric acid
Not detecteda
9 ± 1b
-
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Gallic acid
0.0012
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Data represent the mean ± SD of triplicates of three experimental replicates. At any time point, different letters (a, b) correspond to statistically significant differences between control and RSM optimized juice according to one-way ANOVA followed by Tukey post hoc test (P ≤ 0.05).
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Enhancing anti-diabetic potential of bitter gourd juice using pectinase: A response surface methodology approach Shweta Deshaware1, Sumit Gupta2#, Rekha S. Singhal1#*, Prasad S. Variyar2
400019, India
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Department of Food Engineering and Technology, Institute of Chemical Technology, Mumbai-
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Fig. 1. Effect of enzymatic treatment on the yield of bitter gourd juice (% w/w) (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
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Fig. 2. Effect of enzymatic treatment on total phenolic content (µg gallic acid equivalent ml-1) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
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Fig. 3. Effect of enzymatic treatment on total antioxidant capacity (µg gallic acid equivalent ml1 ) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point (10 ml kg-1).
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Fig. 4. Effect of enzymatic treatment on α-amylase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml kg-1) is at centre point value (10 ml kg-1).
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Fig. 5. Effect of enzymatic treatment on α-glucosidase inhibition (%) of bitter gourd juice (a) impact of enzyme concentration (ml kg-1) and temperature (°C) when time (min) is at centre point (120 min), and (b) impact of time (min) and temperature (°C) when enzyme concentration (ml /kg) is at centre point (10 ml kg-1).
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Highlights Extraction of bitter gourd juice was optimized using Response Surface Methodology
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Phenolic content was 1.5 times higher in pectinase treated juice
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2.47 and 3.74 fold higher α-amylase and α-glucosidase inhibition was obtained
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Nature of phenolic constituents was identified using HPLC
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•