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Antidiabetic Property Optimization from Green Leafy Vegetables Using Ultrasound-Assisted Extraction to Improve Cracker Production
1School of Food Industry, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
2Department of Food Technology, Faculty of Agriculture, Universitas Sumatera Utara, Medan 20155, Indonesia
3Division of Marine Product Technology, Faculty of Agro-Industry, Chiang Mai University, Chiang Mai 50100, Thailand
4Department of Postharvest Technology, Cranfield University, Bedford MK43 0AL, UK
5Faculty of Sustainable Agriculture, Universiti Malaysia Sabah, Sandakan 90509, Malaysia
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Prev Nutr Food Sci 2024; 29(1): 47-62
Published March 31, 2024 https://doi.org/10.3746/pnf.2024.29.1.47
Copyright © The Korean Society of Food Science and Nutrition.
Abstract
Keywords
INTRODUCTION
Diabetes mellitus is a complex metabolic disease characterized by increased blood glucose levels due to impaired insulin resistance or production (Bashkin et al., 2021). One aspect of diabetes management involves α-glucosidase regulation during carbohydrate digestion and absorption (Javadi et al., 2014). α-Glucosidase acts on carbohydrates such as starches and disaccharides and breaks them down into simpler sugars such as glucose, which are then absorbed into the bloodstream (Javadi et al., 2014). Medications to inhibit α-glucosidase are therefore frequently prescribed to manage diabetes (Li et al., 2022), but unfortunately α-glucosidase inhibitors are not suitable for everyone (Hedrington and Davis, 2019) since they pose side effects that limit their usage, including gastrointestinal discomfort, diarrhea, and flatulence (Liu et al., 2022). Recent studies have shown that natural inhibitors derived from plant-based sources offer promising blood sugar level regulation, improve insulin sensitivity, have fewer side effects, and reduce the risk of other complications associated with diabetes medications (Li et al., 2020; Li et al., 2022; Liu et al., 2022).
Many vegetables, especially green leafy vegetables (GLVs), contain bioactive compounds that offer diverse health-promoting properties (Sarkar et al., 2023). Several compounds found in GLV extracts, including essential oils, quercetin, and berberine, have been shown to modulate glucose metabolism, improve insulin signaling, and reduce insulin resistance (Randhawa et al., 2015). Plant extract-based formulations have also been studied (Parveen et al., 2021), and plant-derived compounds have been found to have synergistic effects by targeting multiple metabolic pathways (Martel et al., 2017). Recent research indicates that a combination of treatments may improve the effectiveness of specific medical products in controlling diseases and disorders, including atherosclerosis, cancer, and diabetes, each of which have complex pathophysiologies and etiologies and are therefore challenging to manage using single-agent strategies (Zhou et al., 2016). For example, a combination of the ethanolic extract
Ultrasound-assisted extraction (UAE) is emerging a promising technique for extracting bioactive compounds from various plant sources (Chotphruethipong et al., 2019). Esclapez et al. (2011) reported that UAE can save a considerable amount of energy compared to alternatives. Because it uses only moderate temperatures, its use can be advantageous when dealing with heat-sensitive compounds. Albero et al. (2019) also reported that UAE may be a more environmentally friendly method because it uses less solvent required and has a shorter extraction time than others. To maximize the extraction of desired compounds, UAE must be optimized with respect to extraction parameters, including the solvent-to-sample ratio, extraction time, and ultrasonic power (Li et al., 2020; Yancheshmeh et al., 2022).
Crackers are a common snack consumed throughout the world (Olagunju et al., 2018; Hu et al., 2022). However, there is increasing awareness that snack foods should not only satisfy consumer tastes but also contribute to overall health (Paciulli et al., 2023). One innovative approach is to incorporate plant extracts containing bioactive compounds with potent antidiabetic properties into snack foods (Olagunju et al., 2018; Indiarto et al., 2023). Other studies have tried to successfully incorporate plant extracts into crackers to influence α-glucosidase and α-amylase activities, including extracts from species such as
MATERIALS AND METHODS
Materials
Enzymes (i.e., α-glucosidase, α-amylase Type IV-B, and lipase Type II sourced from porcine pancreas), p-nitrophenyl-α-D-glucopyranoside (p-NPG), acarbose, and 4-methylumbelliferyl oleate (4MUO) were purchased from Sigma-Aldrich. DPPH was obtained from Thermo Fisher Scientific, and 2,4,6-tri(2-pyridyl)-s-triazine, gallic acid monohydrate, ethylenediaminetetraacetic acid (EDTA), 3-(2-pyridyl)-5,6-diphenyl-1,2,4-triazine-p,p-disulfonic acid monosodium salt hydrate (Ferrozine), L-ascorbic acid, and Folin-Ciocalteu reagent were purchased from Acros Organics. All chemicals employed were of analytical quality. Ten kilogram each of fresh GLVs, including spring onions (
Preparation of GLV powder
GLV powder was prepared using a method described by Maser et al. (2023b). Briefly, GLVs were first dehydrated in a WRH-100 drier (IKE Industrial Co., Ltd.) at 45°C until they reached a constant weight. The dried GLVs were then blended in a Philips HR2222 blender.
Preparation of extracts by conventional and UAE processes
Three types of GLV powder (100 g each) were mixed in equal proportion (1:1:1; w:w:w) then mixed with 0, 40, or 80% ethanol (1:10 w/v ratio). Samples were then homogenized at 4,000
The UAE process was optimized using a BBD with three factors (Table 1). Briefly, equal proportions (i.e., 100 g each) of powdered samples from spring onions, bunching onions, and celery were first combined (1:1:1; w:w:w) and mixed with 200 mL of solvent containing 0%, 40%, or 80% ethanol at a sonication amplitude of 40%, 60%, or 80%. Samples were then sonicated for 10, 20, or 30 min in an inert atmosphere using an ultrasound processor (Sonics & Material Vibra-Cell model), equipped with a 13-mm tip probe. Ultrasonic sonication proceeded at a power of 750 W and a frequency of 20 kHz, at 35°C±5°C; the pulsing mode used was 10 s on and 5 s off. After extraction, sample mixtures were centrifuged, filtered, concentrated, and dried as described above. The dependent variables measured to evaluate the UAE and conventional extraction processes include yield (%) and α-glucosidase inhibitory (AGI) activity [mmol acarbose equivalent (ACE)/g extract].
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Table 1 . Box-Behnken design parameters for ultrasound-assisted extraction of green leafy vegetable using response surface methodology
Run Standard Independent variable Dependent variable Factor X1 Ethanol concentration (%)Factor X2 Amplitude (%)Factor X3 Sonication time (min)Yield (%) α-Glucosidase inhibitory activity (mmol ACE/g extract) 1 2 80 40 20 20.01±0.18d 1,161.74±27.70b 2 1 0 40 20 25.20±2.44abc 1,070.39±60.08bcd 3 10 40 80 10 27.99±2.42a 1,045.24±39.03d 4 12 40 80 30 25.70±2.15abc 1,460.96±16.17a 5 8 80 60 30 17.45±1.28d 1,432.46±76.72a 6 14 40 60 20 25.50±1.70abc 964.46±59.73de 7 15 40 60 20 26.49±1.34abc 919.42±63.20e 8 4 80 80 20 19.07±2.43d 1,455.93±80.55a 9 6 80 60 10 18.03±0.72d 1,053.10±53.71cd 10 5 0 60 10 27.90±2.20ab 974.00±26.41de 11 3 0 80 20 24.46±2.40abc 1,059.49±53.77cd 12 11 40 40 30 26.37±1.41abc 1,150.01±66.64bc 13 9 40 40 10 23.89±1.16c 998.31±57.90de 14 7 0 60 30 24.36±2.35bc 989.66±49.17de 15 13 40 60 20 25.22±1.38abc 969.72±56.06de Values are presented as mean±SD of three technical replicates (i.e., n=3).
Different superscripts in the same column (a-e) indicate statistically significant differences (
P <0.05).ACE, acarbose equivalent.
RSM
Next, RSM was used to analyze and optimize extraction. RSM was performed using Design-Expert version 7.0.0 (Stat-Ease). Specifically, we used an ANOVA to determine the coefficients of regression,
Here
All data were then subjected to multiple regression analysis using Design-Expert version 7.0.0 to develop another polynomial model. This model described the relationship between the independent experimental conditions and response variables (e.g., extraction yield and AGI activity) and was represented using the Equations as follows:
To optimize the process, a desirability function (
Here,
Cracker preparation
Next, we prepared crackers using the obtained extracts. For all tests, acarbose (0.1% w/w) was used as a control. We tested different percentages of combination extracts (i.e., 0.625%, 1.25%, and 2.5% w/w; Table 2) during optimization testing. A kneading machine was then used to combine the ingredients, and the resulting dough was allowed to rest for 30 min at 4°C. After resting, the dough was then rolled into a 2 mm layer, cut into 35-mm disks, then baked for 15 min at one of the following temperatures: 140°C, 150°C, or 160°C. The crackers were then removed from the oven, allowed to cool to room temperature, and vacuum sealed in flexible polylaminate pouches for storage. Crackers were stored in the dark until further analysis.
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Table 2 . Ingredients of crackers enriched with green leafy vegetable extracts
Ingredient (% w/w) Control 0.1% acarbose 0.625% extract 1.25% extract 2.5% extract Egg 38.36 38.36 38.36 38.36 38.36 Soybean oil 8.70 8.70 8.70 8.70 8.70 Wheat flour 52.23 52.17 51.90 51.57 50.92 Combination extract 0.00 0.05 0.33 0.65 1.31 NaCl 0.30 0.30 0.30 0.30 0.30 Baking powder 0.40 0.40 0.40 0.40 0.40
Analysis of the combination extract
Extraction yield (%)=(
Here,
Cracker analysis
Moisture content (%)=[(
Percentage inhibition (%)=[(
Here,
Statistical analyses
All measurement results were presented as a mean plus or minus standard deviation. ANOVAs were then performed on the data, and significance levels were determined using Duncan Multiple Comparison tests. Here
RESULTS AND DISCUSSION
GLV extraction using UAE
Regarding the BBD experiment, 15 treatments were performed using three independent variables: ethanol concentration (
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Table 3 . ANOVA to evaluate fitted linear and quadratic polynomial models with respect to parameter optimization and desirability value
Source Degrees of freedom Sum of squares Mean square F -valueP -valueYield (%) Model 9 158.46 17.61 7.78 0.0180s Lack of fit 3 10.42 3.47 7.79 0.1159ns Pure error 2 0.89 0.45 Total error 14 169.77 R 20.9334 adj- R 20.8134 CV (%) 6.31 AGI activity (mmol ACE/g extract) Model 9 478,996.67 53,221.85 43.74 0.0003s Lack of fit 3 4,556.11 1,518.70 1.99 0.3520ns Pure error 2 1,528.45 764.22 Total error 14 485,081.23 R 20.9875 adj- R 20.9649 CV (%) 3.13 Desirability value1) Ethanol concentration Amplitude Time Yield AGI activity Desirability 44.08 80.00 30.00 24.21 1,460.96 0.801 43.65 80.00 30.00 24.24 1,457.60 0.800 43.31 80.00 30.00 24.27 1,454.95 0.800 44.42 80.00 29.92 24.19 1,460.96 0.800 44.38 79.89 30.00 24.18 1,460.96 0.799 41.72 80.00 30.00 24.40 1,442.85 0.798 44.95 80.00 29.80 24.16 1,460.96 0.798 44.76 79.76 30.00 24.15 1,460.96 0.797 45.40 80.00 29.69 24.14 1,460.96 0.796 45.38 79.53 30.00 24.10 1,460.95 0.794 sSignificant. nsNot significant.
1)Only the 10 highest of 43 values are shown.
adj-
R 2, the coefficient of adjusted determination; CV, coefficient of variance; AGI, α-glucosidase inhibitory; ACE, acarbose equivalent.
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Table 4 . Yield and α-glucosidase inhibitory activity of green leafy vegetable extracts produced using conventional processes at different ethanol concentrations
Ethanol concentration (%) Extraction yield (%) α-Glucosidase inhibitory activity (mmol ACE/g extract) 0 23.89±1.16a 794.27±36.84b 40 22.83±1.56a 869.19±72.51b 80 17.21±0.08b 974.46±81.57a Values are presented as mean±SD of three technical replicates.
Different superscripts in the same column (a,b) indicate statistically significant differences (
P <0.05).ACE, acarbose equivalent.
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Figure 1. Response surface plots indicate the effect of ethanol concentration, amplitude, and sonication time on green leafy vegetable extraction yield using ultrasound-assisted extraction.
The polynomial model was determined to not be significant (
Overall, our results demonstrated that lower ethanol concentrations resulted in AGI activity (Fig. 1). This finding confirmed the finding that ethanol concentration can have different effects on yield and inhibitory activity. This effect was observed in
We observed the maximum yield (27.99%) at an amplitude of 80%, an ethanol concentration of 40%, and a sonication time of 10 min. Moreover, our findings suggested that an increase in amplitude resulted in higher extraction yield. This finding is consistent with Calliari et al. (2020), who optimized
We further found that the extraction yield increased with sonication time at low amplitudes. However, increasing sonication time decreased the yield at high amplitudes. In general, cavitation is pivotal in disrupting cell walls and accelerating the extraction process (Ali et al., 2019). For example, Petcharat et al. (2021) reported that UAE under suitable conditions could enhance the yield when extraction was performed at 80% amplitude for 10 min. Moreover, extended exposure may result in the deterioration and impairment of the structural characteristics of the extracted compounds (Ali et al., 2019). Moreover, the strong molecular association between metabolites and the cell wall can hinder solvent penetration, resulting in incomplete extraction and reduced efficiency (Chotphruethipong et al., 2019).
Our results observed that the ultrasound-induced cavitation effect was the primarily regulator of the extraction of compounds from GLV cells. Intense cavitation waves have been shown to promote solvent infiltration into the tissue matrix, aiding in mass transfer (Ali et al., 2019). In addition, we also found that the yield was higher under the UAE treatment than the conventional method. High-intensity ultrasound appeared to effectively disrupt cell membranes and cause the release of metabolites from complex tissues, which also led to relatively high efficiency (Table 1 and 4).
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Figure 2. Response surface plots indicating the effect of ethanol concentration, amplitude, and sonication time on α-glucosidase inhibitory (AGI) activity of green leafy vegetable extracts obtained using ultrasound-assisted extraction.
Next, the reliability of the model in predicting responses was evaluated by examining the lack of fit value, which was determined to be insignificant (
Our findings also indicated that higher ethanol concentrations can result in increased AGI activity, as illustrated in Fig. 2. In addition, the combined effect of ethanol concentration, sonication time, and amplitude was also found to contribute to AGI activity. Interestingly, cavitation led to higher AGI activity at an ethanol concentration of 40%, which was higher than the activity observed at other concentrations (Table 1). Due to the principles of phase solubility and similarity, the release of compounds from the cell wall is enhanced when the solute and solvent have similar polarities (Li et al., 2022). Moreover, UAE influences the level of surface contact between the solvent and solute, thereby facilitating the general diffusion of target compounds (Li et al., 2022). UAE also promotes improved extraction, resulting in the optimal production of desired AGI-active compounds at a concentration of 40% ethanol. Similarly, Liu et al. (2022) reported that in a pomegranate peel system combined with UAE, the use of 40%∼50% ethanol enhanced the yield of compounds responsible for AGI activity.
We found that the highest level of AGI activity (i.e., 1,460.96 mmol ACE/g extract) was achieved at an amplitude of 80% using an ethanol concentration of 40% and a sonication time of 30 min. These findings indicated that increasing the amplitude resulted in an increase in AGI activity. Likewise, Gulzar and Benjakul (2019) reported the use of UAE at an ultrasonic amplitude of 80% to obtain extracts from
In general, we found that AGI activity increased as the sonication time increased. These findings are consistent with those of a study conducted by Wang et al. (2018), who reported that the extraction of metabolites from apple pomace peaked following being subjected to a sonication treatment for 30 min. Furthermore, Ma et al. (2022) reported that the AGI activity of glycosylated α-lactalbumin and α-lactalbumin digestive products in the intestine and stomach was significantly enhanced (
Conventional extraction yields of green vegetable combinations
The extraction yields of combined GLV samples at different concentrations of ethanol (Table 4) suggest that the polarity of the solvent plays a pivotal role in determining extraction yield, with more polar solvents resulting in higher yields. This finding indicates that water was the most effective solvent for extracting the desired yield. Similarly, previous studies have also reported that higher ethanol concentrations decrease yield (Javadi et al., 2014; Easmin et al., 2017). In addition, the AGI activity was found to be higher at higher ethanol concentrations (Table 4), which was consistent with the findings of Javadi et al. (2014) and Easmin et al. (2017). Since ethanol has a lower polarity than water, lipophilic compounds can be more easily extracted in ethanol than in water (Easmin et al., 2017). The highest activity was observed in the 80% ethanol extract, thereby suggesting that the presence of more lipophilic compounds in GLV samples may have contributed to the presence of inhibition.
Properties of cracker enriched in GLV extract
The results of our baking experiments revealed that crackers with higher amounts of GLV extract showed a significantly greener color relative to those with lower extract content (Fig. 3). Moreover, as the baking temperature increased, cracker color was darker (Fig. 3). Furthermore, our color analysis of crackers produced at different baking temperatures was performed using the following parameters:
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Table 5 . Properties of green leafy vegetable extract-enriched crackers
No. Formulation Baking temperature (°C) Color Hardness (g) Crispiness (mm) L* a* b* 1 Control 140 70.39±0.44a 3.65±0.24d 34.43±0.93hi 4,542.75±118.90c 0.48±0.10de 150 68.43±0.75b 4.56±0.18bc 34.57±1.46ghi 2,664.70±265.08f 1.35±0.30abc 160 65.47±0.36e 6.53±0.65a 35.73±0.59defg 1,409.91±364.03h 1.64±0.09a 2 0.1% acarbose 140 70.95±0.51a 3.34±0.14d 33.45±0.28i 4,561.14±178.49c 0.30±0.25def 150 67.04±0.63cd 4.93±0.36b 35.32±0.89fgh 2,765.63±182.85f 1.30±0.06abc 160 66.06±0.97de 6.63±0.65a 36.27±0.18cdef 1,467.14±264.07gh 1.59±0.34a 3 0.625% extract 140 67.48±0.96bc 1.32±0.30e 38.26±1.00a 4,808.20±239.32bc 0.22±0.06efg 150 61.69±0.85f 3.38±0.14d 37.25±0.39abc 3,229.86±185.40e 1.10±0.30bc 160 59.90±0.60g 4.01±0.26cd 36.87±0.18bcde 1,725.92±42.05gh 1.48±0.10a 4 1.25% extract 140 61.57±1.18f —1.41±0.62g 38.02±0.16ab 5,119.05±204.98b 0.09±0.04fg 150 59.19±0.89g —0.01±0.52f 36.05±0.59cdef 3,295.08±206.15e 1.03±0.25c 160 56.90±0.33h 0.60±0.38f 36.02±0.37cdef 1,830.40±97.04g 1.40±0.09ab 5 2.5% extract 140 59.02±0.57g —3.06±0.42h 36.95±0.45bcd 5,606.44±359.02a 0.02±0.09g 150 57.47±0.11h —1.95±0.35g 35.65±0.70efg 4,005.99±282.98d 0.62±0.07d 160 54.80±0.44i 0.18±0.08f 33.71±0.39i 2,764.07±58.80f 1.35±0.12abc Mean±SD of three technical replicates.
Different superscript letters in the same column (a-i) indicate statistically significant differences (
P <0.05).
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Figure 3. Green leafy vegetable (GLV) extract-enriched crackers produced at different baking temperatures.
Higher baking temperatures generally resulted in darker crackers (Table 5). A darker hue is common in baked biscuits (Al-Ansi et al., 2019). This is because the nonenzymatic Maillard reaction occurs between amino acids and reducing sugars during baking, leading to a brownish effect (Nabil et al., 2020). Moreover, at higher temperatures the green color of high-GLV crackers (Table 5) further because of the degradation of chlorophyll pigments. This agrees with the results of Galla et al. (2017) who reported that chlorophyll levels decline during cooking. In addition, Zheng et al. (2023) reported that elevated temperatures resulted in the increased chlorophyll release, which then undergoes conversion into a brown substance known as pheophytin.
Table 5 illustrates the hardness and crispiness values of crackers produced at different baking temperatures. The findings of this study differ slightly from those of Dhal et al. (2023), who showed a hardness level of approximately 5,872 g and crispiness of about 0.6 mm for their control crackers. These differences may be attributed to differences in constitutive ingredients. Furthermore, cracker hardness also increased with increased extract levels (
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Figure 4. Total phenolic content of green leafy vegetable extract-enriched crackers produced at different baking temperatures. Bars represent standard deviation (n=3). Different lowercase letters (a-h) indicate statistically significant differences (
P <0.05).
Higher baking temperature resulted in reduced hardness and an enhancement in the crispiness of crackers (Table 5). These results are consistent with those of Sazesh and Goli (2020), who reported that cracker hardness decreased when the baking temperature was lowered from 160°C to 185°C. This was thought to occur due to the protein network coagulating more rapidly as well as an increase in carbon dioxide gas entrapment within the cracker at higher baking temperatures, two processes that resulted in increased porosity and decreased cracker density (Sazesh and Goli, 2020). Here, these factors likely also affected the crispiness of the crackers. Furthermore, the low moisture content of the high-baking-temperature crackers also contributed to their increased crunchiness, as depicted in Fig. 5. Water plays a crucial role in many manufacturer foods, since it significantly influences the overall texture, appearance, and flavor (Setyaningsih et al., 2019).
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Figure 5. Moisture contents of green leafy vegetable extract-enriched crackers produced at different baking temperatures. Bars represent SD (n=3). Different lowercase letters (a-h) indicate statistically significant differences (
P <0.05).
The moisture content of crackers at various baking temperatures is illustrated in Fig. 5. Generally, an increase in the amount of extract used led to a rise in moisture content. In addition, higher moisture content is known to be related to hydrophilic content (Bolarinwa et al., 2019). Here, the use of the GLV extract may cause crackers to contain a higher level of hydrophilic compounds, including polyphenols and polyol (Maser et al., 2023a), thereby resulting in a greater ability to retain water (Al-Ansi et al., 2019). These moisture content results align with those reported by Jiang et al. (2022), who found that crackers supplemented with papaya seed and peel had moisture contents ranging from 7.83% to 15.42%. However, when the baking temperature increased, the moisture content of the crackers decreased (Fig. 5). During the baking process, the moisture within the dough vaporizes from the surface of the cracker, causing moisture deep within the cracker to migrate to the surface, after which it to vaporizes (Setyaningsih et al., 2019). This leads to a steep reduction in moisture content that is proportional to the temperature increase (Ranjbar et al., 2014).
Strongly correlated with moisture content was the water content of crackers, which also increased as the amount of the GLV extract used rose (Fig. 6). Similarly, as the baking temperature increased, we observed a corresponding decline in water activity. It is likely that reduced water activity is connected to the reduction in moisture content (Renshaw et al., 2019). Taken together, these findings align with previously reported results for olive leaf extract crackers, in which crackers with a moisture content of approximately 3.73 had a water activity of approximately 0.3 (Paciulli et al., 2023).
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Figure 6. Water activity (aw) of green leafy vegetable extract-enriched crackers produced at different baking temperatures. Bars represent standard deviation (n=3). Different lowercase letters (a-j) indicate statistically significant differences (
P <0.05).
Antioxidant activities of crackers enriched with GLV extract
Fig. 4 illustrates the TPC of crackers enriched in GLV extract at various baking temperatures. In general, a higher amount of GLV extracts corresponded to higher TPC values of the crackers. Moreover, the TPC results recorded here were slightly lower than those found in a prior study where wheat cookies exhibited a TPC of 19.23 mg GAE/100 g (Sharma et al., 2016). The observed differences in phenolic acid content can be accounted for by diverse factors, including variation in geographical conditions, species, and other environmental influences (Nabil et al., 2020). Furthermore, higher baking temperatures led reduced TPC content across all cracker batches. Similarly, Nabil et al. (2020) reported that baking Moroccan cladode flour biscuits at 160°C for a few minutes resulted in minimal phenolic compound (e.g., ferulic acid) content. This may be due to structural alterations in phenolics caused by heating, and the degree of polyphenol degradation is contingent on the material composition and processing conditions (Nabil et al., 2020).
Next, the DPPH activity of GLV extract-enriched crackers is presented in Table 6. Overall, we found that the DPPH activity of the crackers increased as the amount of extract increased. Similarly, Paciulli et al. (2023) noted that adding olive leaf extract significantly boosted DPPH activity relative to an unenriched control group. Next, a direct link between TPC (Fig. 4) and DPPH (Table 6) was established, which confirmed the antioxidative potential of the polyphenols present in the GLV extract. However, higher baking temperatures also decreased the DPPH activity of crackers. In one paper, Zheng et al. (2023) reported that the loss of antioxidant activity occurs due to the poor thermal stability of certain antioxidant compounds under prolonged exposure to heat. Changes in heat-sensitive antioxidants therefore led to an overall decline in antioxidant activity.
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Table 6 . Antioxidant and antidiabetic activities of green leafy vegetable extract-enriched crackers
No. Formulation Baking temperature (°C) DPPH (mg AEAC/100 g) Metal chelating (mg EECC/100 g) FRAP (mg AEAC/100 g) AAI (mmol ACE/100 g) AGI (mmol ACE/100 g) LPI (% inhibition) 1 Control 140 11.76±0.06c 0.79±0.08f 10.77±0.51d 40.07±3.38c 134.68±11.70de 22.26±0.97bcd 150 10.16±0.04e 0.40±0.03h 8.73±0.11f 35.47±2.38de 127.00±12.69e 19.61±1.27fgh 160 9.92±0.22e 0.24±0.02i 8.54±0.21f 29.79±2.20f 77.67±7.11f 17.73±1.24h 2 0.1% acarbose 140 12.28±0.16b 0.80±0.05f 11.06±0.49d 40.69±2.26bc 209.94±11.28a 22.32±0.56bcd 150 10.24±0.36e 0.42±0.04h 10.04±0.29e 37.43±2.64cd 152.25±9.58cd 19.69±1.62fgh 160 9.87±0.07e 0.21±0.03i 8.61±0.11f 30.67±0.71f 83.13±6.95f 19.13±1.08gh 3 0.625% extract 140 12.42±0.84b 1.45±0.06c 13.04±0.35b 41.25±1.64bc 225.30±15.21a 22.84±1.97bc 150 11.03±0.26d 0.97±0.10e 12.09±0.41c 39.81±1.98c 170.69±14.14bc 20.20±1.04def 160 9.98±0.21e 0.67±0.01g 11.23±0.42d 31.70±1.71ef 91.15±6.60f 19.19±1.37gh 4 1.25% extract 140 13.04±0.13a 1.59±0.01b 14.62±0.32a 44.45±4.19ab 226.84±19.76a 23.31±1.26b 150 11.11±0.22d 1.08±0.03d 12.14±0.43c 40.07±1.73c 183.83±17.66b 20.58±0.95cdef 160 10.16±0.04e 0.74±0.05fg 11.23±0.52d 32.11±1.17ef 98.83±4.11f 19.28±1.30gh 5 2.5% extract 140 13.38±0.05a 1.86±0.08a 14.95±0.17a 47.76±0.63a 227.35±12.29a 26.70±0.75a 150 11.29±0.20cd 1.10±0.02d 14.72±0.46a 45.59±2.06ab 189.46±12.33b 21.94±0.70bcde 160 10.94±0.40d 0.83±0.07f 13.69±0.86b 34.85±1.48de 142.70±9.97de 19.45±1.91gh Values are presented as mean±SD of three technical replicates.
Different superscript letters in the same column (a-i) indicate statistically significant differences (
P <0.05).DPPH, 2,2-diphenyl-1-picrylhydrazyl; AEAC, L-ascorbic acid equivalent antioxidant capacity; EECC, ethylenediaminetetraacetic acid equivalent chelating capacity; FRAP, ferric reducing antioxidant power; AAI, α-amylase inhibitory; ACE, acarbose equivalent; AGI, α-glucosidase inhibitory; LPI, lipase inhibitory.
Like DPPH activity, the metal chelating activity of the crackers was found to increase with increasing GLV extract but decreased with higher baking temperature (Table 6). This occurrence may be associated to the presence of phytochemical antioxidants within the GLV extract. We also observed that the metal chelating activity correlated with cracker TPC content (Fig. 4). In one recent study, Maser et al. (2023b) also reported a positive correlation in GLV extracts between metal chelating activity and TPC (
Next, Table 6 shows the FRAP activity of crackers enriched GLV extract baked at different temperatures. In general, higher GLV content correlated with higher FRAP activity, but higher baking temperatures were associated with lower FRAP activity. In this study, we identified a connection between TPC and FRAP activity; this is similar to the results of a prior investigation, which reported a linear correlation (
Antidiabetic activities of GLV-enriched crackers enriched with the combination extract
Table 6 presents the AAI activity of crackers enriched with GLV combination extracts. The control cracker demonstrated a relatively favorable AAI activity of 40.07 mmol ACE/100 g cracker. Similarly, a study by Olagunju et al. (2018) reported that their control (100% wheat) cracker exhibited an AAI activity of approximately 54.22% inhibition. Furthermore, we also found that AAI activity was contingent on the concentration of the combination extract. For example, incorporation of 0.1% acarbose displayed an inhibitory efficacy equivalent to the use of 0.625% GLV extract (
Next, we measured the inhibition of α-glucosidase in crackers enriched with GLV extracts at various baking temperatures; these results are presented in Table 6. The control crackers displayed a moderate AGI activity of 134.68 mmol ACE/100 g. This result slightly exceeds that reported by Olagunju et al. (2018), who documented 15.56% AGI activity in 100% wheat crackers. This difference may be attributed to variation in ingredients used, including the presence of soybean oil, which is known for its high oleic and linoleic acid contents and is widely recognized as increasing AGI activity (Su et al., 2013). Moreover, we also observed that the addition of 0.1% acarbose resulted in a significant improvement relative to control crackers (
The addition of various concentrations of GLV extract was associated with different increases in AGI activity, although this effect was not statistically significantly different from the addition of 0.1% acarbose (
Table 6 presents the LPI activity of crackers enriched with GLV extract at various baking temperatures. Here, adding 0.1% acarbose did not yield a significant difference in LPI activity compared to control crackers (
Proximate composition of crackers
Next, we selected the cracker formulation featuring the most potent antidiabetic, antiobesity, and antioxidant properties and determined their proximate composition. First, all crackers baked at 140°C were selected for proximate composition analysis (Table 7). The moisture content of these crackers was found to increase following supplementation with 0.1% acarbose and GLV extract (
-
Table 7 . Proximate composition of green leafy vegetable extract-enriched crackers produced at a baking temperature of 140°C
No. Formulation Moisture (%) Ash (%) Crude protein (%) Fat (%) Carbohydrate (%) 1 Control 11.80±0.12d 1.41±0.03c 18.12±0.62a 17.75±0.62a 50.92±0.47a 2 0.1% acarbose 12.97±0.19c 1.43±0.02c 17.80±0.79a 17.74±0.25a 50.06±0.42a 3 0.625% extract 13.57±0.16b 1.53±0.01b 17.52±0.14a 17.64±0.70a 49.74±0.34ab 4 1.25% extract 15.28±0.37a 1.54±0.01b 17.32±0.59a 17.46±0.85a 48.40±0.61b 5 2.5% extract 15.51±0.12a 1.69±0.00a 17.22±0.06a 17.28±0.62a 48.30±0.27b Values are presented as mean±SD of three technical replicates.
Different superscript letters in the same column (a-d) indicate statistically significant differences (
P <0.05).
Unlike moisture content, we found no significant differences in crude protein and fat content among cracker types (
In summary, in this study we report an optimized ultrasound-assisted process for extracting antidiabetic metabolites from GLVs. Overall, this method was more effective than conventional extraction methods in extracting these metabolites. The optimal extraction conditions for samples tested here were 44.08% ethanol concentration, 80% amplitude, and 30 min sonication time. These conditions resulted in a 24.16% increase in extraction yield compared to a conventional extraction method and an AGI activity of 1,449.73 mmol ACE/g extract. In addition, sonication improved yield while reducing solvent consumption and showed no detrimental effects on AGI activity. Next, when the GLV extract was used for the production of crackers at different baking temperatures, we observed a general increase in the amount of total phenolic compounds and their associated bioactivities, including antioxidant capacity and inhibitory effects on enzymes such as α-glucosidase, α-amylase, and lipase. However, higher baking temperatures (e.g., 160°C) reduced the amount of total phenolic compounds present as well as their bioactivity, and therefore lower baking temperatures such as 140°C or 150°C are recommended. Further research is recommended to examine the textural and sensory evaluations of GLV-supplemented crackers as well as to evaluate food safety and consumer acceptance.
FUNDING
This work was supported by King Mongkut’s Institute of Technology Ladkrabang Research Fund under the KMITL Doctoral Scholarship [KDS2020/031].
AUTHOR DISCLOSURE STATEMENT
The authors declare no conflict of interest.
AUTHOR CONTRIBUTIONS
Concept and design: AMMA, SCBB. Analysis and interpretation: WHM, NM, NH. Data collection: WHM, NM, SK. Writing the article: WHM, SK, PN. Critical revision of the article: PN, AKT, NH, AMMA, SCBB. Final approval of the article: all authors. Statistical analysis: WHM, NM. Obtained funding: WHM, AMMA, SCBB. Overall responsibility: PN, AMMA, SCBB.
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Article
Original
Prev Nutr Food Sci 2024; 29(1): 47-62
Published online March 31, 2024 https://doi.org/10.3746/pnf.2024.29.1.47
Copyright © The Korean Society of Food Science and Nutrition.
Antidiabetic Property Optimization from Green Leafy Vegetables Using Ultrasound-Assisted Extraction to Improve Cracker Production
Wahyu Haryati Maser1,2 , Nur Maiyah1
, Supatra Karnjanapratum3
, Pikunthong Nukthamna1
, Anthony Keith Thompson4
, Nurul Huda5
, Ali Muhammed Moula Ali1
, Sri Charan Bindu Bavisetty1
1School of Food Industry, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
2Department of Food Technology, Faculty of Agriculture, Universitas Sumatera Utara, Medan 20155, Indonesia
3Division of Marine Product Technology, Faculty of Agro-Industry, Chiang Mai University, Chiang Mai 50100, Thailand
4Department of Postharvest Technology, Cranfield University, Bedford MK43 0AL, UK
5Faculty of Sustainable Agriculture, Universiti Malaysia Sabah, Sandakan 90509, Malaysia
Correspondence to:Ali Muhammed Moula Ali, E-mail: ali-muhammed.mo@kmitl.ac.th, Pikunthong Nukthamna, E-mail: pikunthong.nu@kmitl.ac.th, Sri Charan Bindu Bavisetty, E-mail: sricharan.bvs@gmail.com
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Here we test a method of incorporating of plant extracts into popular snack foods to help control diabetes. Since some fresh vegetables contain antidiabetic compounds, ultrasound-assisted extraction was used to optimize their extraction of from spring onions, bunching onions, and celery for later incorporation into crackers. We compared various concentrations of ethanol used during extraction, after which they were exposed to an ultrasound processor whose amplitude and sonication time were also varied. The optimal extraction conditions were found to be an ethanol concentration of 44.08%, an amplitude of 80%, and a sonication time of 30 min. This resulted in the highest level of -glucosidase inhibitory activity (i.e., 1,449.73 mmol ACE/g) and the highest extraction yield (i.e., 24.16%). The extract produced from these optimum conditions was then used as a constituent component of crackers at 0.625%, 1.25%, or 2.5% w/w. These biscuits were then produced at baking temperatures of 140°C, 150°C, or 160°C. We then measured the physical characteristics and bioactivities of sample biscuits from each treatment. We found that biscuits containing 2.5% vegetable combination extract and baked at 140°C had the highest total phenolic content, the strongest antioxidant performance, and showed the most substantial antidiabetic and antiobesity effects. Here we establish conditions for the effective extraction of antidiabetic functional ingredients via ultrasound from green leafy vegetables. We also provide a method of using these ingredients to prepare crackers with the aim of developing a functional antidiabetic snack food.
Keywords: baking temperature, Box-Behnken design, functional food, glycoside hydrolase inhibitors
INTRODUCTION
Diabetes mellitus is a complex metabolic disease characterized by increased blood glucose levels due to impaired insulin resistance or production (Bashkin et al., 2021). One aspect of diabetes management involves α-glucosidase regulation during carbohydrate digestion and absorption (Javadi et al., 2014). α-Glucosidase acts on carbohydrates such as starches and disaccharides and breaks them down into simpler sugars such as glucose, which are then absorbed into the bloodstream (Javadi et al., 2014). Medications to inhibit α-glucosidase are therefore frequently prescribed to manage diabetes (Li et al., 2022), but unfortunately α-glucosidase inhibitors are not suitable for everyone (Hedrington and Davis, 2019) since they pose side effects that limit their usage, including gastrointestinal discomfort, diarrhea, and flatulence (Liu et al., 2022). Recent studies have shown that natural inhibitors derived from plant-based sources offer promising blood sugar level regulation, improve insulin sensitivity, have fewer side effects, and reduce the risk of other complications associated with diabetes medications (Li et al., 2020; Li et al., 2022; Liu et al., 2022).
Many vegetables, especially green leafy vegetables (GLVs), contain bioactive compounds that offer diverse health-promoting properties (Sarkar et al., 2023). Several compounds found in GLV extracts, including essential oils, quercetin, and berberine, have been shown to modulate glucose metabolism, improve insulin signaling, and reduce insulin resistance (Randhawa et al., 2015). Plant extract-based formulations have also been studied (Parveen et al., 2021), and plant-derived compounds have been found to have synergistic effects by targeting multiple metabolic pathways (Martel et al., 2017). Recent research indicates that a combination of treatments may improve the effectiveness of specific medical products in controlling diseases and disorders, including atherosclerosis, cancer, and diabetes, each of which have complex pathophysiologies and etiologies and are therefore challenging to manage using single-agent strategies (Zhou et al., 2016). For example, a combination of the ethanolic extract
Ultrasound-assisted extraction (UAE) is emerging a promising technique for extracting bioactive compounds from various plant sources (Chotphruethipong et al., 2019). Esclapez et al. (2011) reported that UAE can save a considerable amount of energy compared to alternatives. Because it uses only moderate temperatures, its use can be advantageous when dealing with heat-sensitive compounds. Albero et al. (2019) also reported that UAE may be a more environmentally friendly method because it uses less solvent required and has a shorter extraction time than others. To maximize the extraction of desired compounds, UAE must be optimized with respect to extraction parameters, including the solvent-to-sample ratio, extraction time, and ultrasonic power (Li et al., 2020; Yancheshmeh et al., 2022).
Crackers are a common snack consumed throughout the world (Olagunju et al., 2018; Hu et al., 2022). However, there is increasing awareness that snack foods should not only satisfy consumer tastes but also contribute to overall health (Paciulli et al., 2023). One innovative approach is to incorporate plant extracts containing bioactive compounds with potent antidiabetic properties into snack foods (Olagunju et al., 2018; Indiarto et al., 2023). Other studies have tried to successfully incorporate plant extracts into crackers to influence α-glucosidase and α-amylase activities, including extracts from species such as
MATERIALS AND METHODS
Materials
Enzymes (i.e., α-glucosidase, α-amylase Type IV-B, and lipase Type II sourced from porcine pancreas), p-nitrophenyl-α-D-glucopyranoside (p-NPG), acarbose, and 4-methylumbelliferyl oleate (4MUO) were purchased from Sigma-Aldrich. DPPH was obtained from Thermo Fisher Scientific, and 2,4,6-tri(2-pyridyl)-s-triazine, gallic acid monohydrate, ethylenediaminetetraacetic acid (EDTA), 3-(2-pyridyl)-5,6-diphenyl-1,2,4-triazine-p,p-disulfonic acid monosodium salt hydrate (Ferrozine), L-ascorbic acid, and Folin-Ciocalteu reagent were purchased from Acros Organics. All chemicals employed were of analytical quality. Ten kilogram each of fresh GLVs, including spring onions (
Preparation of GLV powder
GLV powder was prepared using a method described by Maser et al. (2023b). Briefly, GLVs were first dehydrated in a WRH-100 drier (IKE Industrial Co., Ltd.) at 45°C until they reached a constant weight. The dried GLVs were then blended in a Philips HR2222 blender.
Preparation of extracts by conventional and UAE processes
Three types of GLV powder (100 g each) were mixed in equal proportion (1:1:1; w:w:w) then mixed with 0, 40, or 80% ethanol (1:10 w/v ratio). Samples were then homogenized at 4,000
The UAE process was optimized using a BBD with three factors (Table 1). Briefly, equal proportions (i.e., 100 g each) of powdered samples from spring onions, bunching onions, and celery were first combined (1:1:1; w:w:w) and mixed with 200 mL of solvent containing 0%, 40%, or 80% ethanol at a sonication amplitude of 40%, 60%, or 80%. Samples were then sonicated for 10, 20, or 30 min in an inert atmosphere using an ultrasound processor (Sonics & Material Vibra-Cell model), equipped with a 13-mm tip probe. Ultrasonic sonication proceeded at a power of 750 W and a frequency of 20 kHz, at 35°C±5°C; the pulsing mode used was 10 s on and 5 s off. After extraction, sample mixtures were centrifuged, filtered, concentrated, and dried as described above. The dependent variables measured to evaluate the UAE and conventional extraction processes include yield (%) and α-glucosidase inhibitory (AGI) activity [mmol acarbose equivalent (ACE)/g extract].
-
Table 1 . Box-Behnken design parameters for ultrasound-assisted extraction of green leafy vegetable using response surface methodology.
Run Standard Independent variable Dependent variable Factor X1 Ethanol concentration (%)Factor X2 Amplitude (%)Factor X3 Sonication time (min)Yield (%) α-Glucosidase inhibitory activity (mmol ACE/g extract) 1 2 80 40 20 20.01±0.18d 1,161.74±27.70b 2 1 0 40 20 25.20±2.44abc 1,070.39±60.08bcd 3 10 40 80 10 27.99±2.42a 1,045.24±39.03d 4 12 40 80 30 25.70±2.15abc 1,460.96±16.17a 5 8 80 60 30 17.45±1.28d 1,432.46±76.72a 6 14 40 60 20 25.50±1.70abc 964.46±59.73de 7 15 40 60 20 26.49±1.34abc 919.42±63.20e 8 4 80 80 20 19.07±2.43d 1,455.93±80.55a 9 6 80 60 10 18.03±0.72d 1,053.10±53.71cd 10 5 0 60 10 27.90±2.20ab 974.00±26.41de 11 3 0 80 20 24.46±2.40abc 1,059.49±53.77cd 12 11 40 40 30 26.37±1.41abc 1,150.01±66.64bc 13 9 40 40 10 23.89±1.16c 998.31±57.90de 14 7 0 60 30 24.36±2.35bc 989.66±49.17de 15 13 40 60 20 25.22±1.38abc 969.72±56.06de Values are presented as mean±SD of three technical replicates (i.e., n=3)..
Different superscripts in the same column (a-e) indicate statistically significant differences (
P <0.05)..ACE, acarbose equivalent..
RSM
Next, RSM was used to analyze and optimize extraction. RSM was performed using Design-Expert version 7.0.0 (Stat-Ease). Specifically, we used an ANOVA to determine the coefficients of regression,
Here
All data were then subjected to multiple regression analysis using Design-Expert version 7.0.0 to develop another polynomial model. This model described the relationship between the independent experimental conditions and response variables (e.g., extraction yield and AGI activity) and was represented using the Equations as follows:
To optimize the process, a desirability function (
Here,
Cracker preparation
Next, we prepared crackers using the obtained extracts. For all tests, acarbose (0.1% w/w) was used as a control. We tested different percentages of combination extracts (i.e., 0.625%, 1.25%, and 2.5% w/w; Table 2) during optimization testing. A kneading machine was then used to combine the ingredients, and the resulting dough was allowed to rest for 30 min at 4°C. After resting, the dough was then rolled into a 2 mm layer, cut into 35-mm disks, then baked for 15 min at one of the following temperatures: 140°C, 150°C, or 160°C. The crackers were then removed from the oven, allowed to cool to room temperature, and vacuum sealed in flexible polylaminate pouches for storage. Crackers were stored in the dark until further analysis.
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Table 2 . Ingredients of crackers enriched with green leafy vegetable extracts.
Ingredient (% w/w) Control 0.1% acarbose 0.625% extract 1.25% extract 2.5% extract Egg 38.36 38.36 38.36 38.36 38.36 Soybean oil 8.70 8.70 8.70 8.70 8.70 Wheat flour 52.23 52.17 51.90 51.57 50.92 Combination extract 0.00 0.05 0.33 0.65 1.31 NaCl 0.30 0.30 0.30 0.30 0.30 Baking powder 0.40 0.40 0.40 0.40 0.40
Analysis of the combination extract
Extraction yield (%)=(
Here,
Cracker analysis
Moisture content (%)=[(
Percentage inhibition (%)=[(
Here,
Statistical analyses
All measurement results were presented as a mean plus or minus standard deviation. ANOVAs were then performed on the data, and significance levels were determined using Duncan Multiple Comparison tests. Here
RESULTS AND DISCUSSION
GLV extraction using UAE
Regarding the BBD experiment, 15 treatments were performed using three independent variables: ethanol concentration (
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Table 3 . ANOVA to evaluate fitted linear and quadratic polynomial models with respect to parameter optimization and desirability value.
Source Degrees of freedom Sum of squares Mean square F -valueP -valueYield (%) Model 9 158.46 17.61 7.78 0.0180s Lack of fit 3 10.42 3.47 7.79 0.1159ns Pure error 2 0.89 0.45 Total error 14 169.77 R 20.9334 adj- R 20.8134 CV (%) 6.31 AGI activity (mmol ACE/g extract) Model 9 478,996.67 53,221.85 43.74 0.0003s Lack of fit 3 4,556.11 1,518.70 1.99 0.3520ns Pure error 2 1,528.45 764.22 Total error 14 485,081.23 R 20.9875 adj- R 20.9649 CV (%) 3.13 Desirability value1) Ethanol concentration Amplitude Time Yield AGI activity Desirability 44.08 80.00 30.00 24.21 1,460.96 0.801 43.65 80.00 30.00 24.24 1,457.60 0.800 43.31 80.00 30.00 24.27 1,454.95 0.800 44.42 80.00 29.92 24.19 1,460.96 0.800 44.38 79.89 30.00 24.18 1,460.96 0.799 41.72 80.00 30.00 24.40 1,442.85 0.798 44.95 80.00 29.80 24.16 1,460.96 0.798 44.76 79.76 30.00 24.15 1,460.96 0.797 45.40 80.00 29.69 24.14 1,460.96 0.796 45.38 79.53 30.00 24.10 1,460.95 0.794 sSignificant. nsNot significant..
1)Only the 10 highest of 43 values are shown..
adj-
R 2, the coefficient of adjusted determination; CV, coefficient of variance; AGI, α-glucosidase inhibitory; ACE, acarbose equivalent..
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Table 4 . Yield and α-glucosidase inhibitory activity of green leafy vegetable extracts produced using conventional processes at different ethanol concentrations.
Ethanol concentration (%) Extraction yield (%) α-Glucosidase inhibitory activity (mmol ACE/g extract) 0 23.89±1.16a 794.27±36.84b 40 22.83±1.56a 869.19±72.51b 80 17.21±0.08b 974.46±81.57a Values are presented as mean±SD of three technical replicates..
Different superscripts in the same column (a,b) indicate statistically significant differences (
P <0.05)..ACE, acarbose equivalent..
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Figure 1. Response surface plots indicate the effect of ethanol concentration, amplitude, and sonication time on green leafy vegetable extraction yield using ultrasound-assisted extraction.
The polynomial model was determined to not be significant (
Overall, our results demonstrated that lower ethanol concentrations resulted in AGI activity (Fig. 1). This finding confirmed the finding that ethanol concentration can have different effects on yield and inhibitory activity. This effect was observed in
We observed the maximum yield (27.99%) at an amplitude of 80%, an ethanol concentration of 40%, and a sonication time of 10 min. Moreover, our findings suggested that an increase in amplitude resulted in higher extraction yield. This finding is consistent with Calliari et al. (2020), who optimized
We further found that the extraction yield increased with sonication time at low amplitudes. However, increasing sonication time decreased the yield at high amplitudes. In general, cavitation is pivotal in disrupting cell walls and accelerating the extraction process (Ali et al., 2019). For example, Petcharat et al. (2021) reported that UAE under suitable conditions could enhance the yield when extraction was performed at 80% amplitude for 10 min. Moreover, extended exposure may result in the deterioration and impairment of the structural characteristics of the extracted compounds (Ali et al., 2019). Moreover, the strong molecular association between metabolites and the cell wall can hinder solvent penetration, resulting in incomplete extraction and reduced efficiency (Chotphruethipong et al., 2019).
Our results observed that the ultrasound-induced cavitation effect was the primarily regulator of the extraction of compounds from GLV cells. Intense cavitation waves have been shown to promote solvent infiltration into the tissue matrix, aiding in mass transfer (Ali et al., 2019). In addition, we also found that the yield was higher under the UAE treatment than the conventional method. High-intensity ultrasound appeared to effectively disrupt cell membranes and cause the release of metabolites from complex tissues, which also led to relatively high efficiency (Table 1 and 4).
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Figure 2. Response surface plots indicating the effect of ethanol concentration, amplitude, and sonication time on α-glucosidase inhibitory (AGI) activity of green leafy vegetable extracts obtained using ultrasound-assisted extraction.
Next, the reliability of the model in predicting responses was evaluated by examining the lack of fit value, which was determined to be insignificant (
Our findings also indicated that higher ethanol concentrations can result in increased AGI activity, as illustrated in Fig. 2. In addition, the combined effect of ethanol concentration, sonication time, and amplitude was also found to contribute to AGI activity. Interestingly, cavitation led to higher AGI activity at an ethanol concentration of 40%, which was higher than the activity observed at other concentrations (Table 1). Due to the principles of phase solubility and similarity, the release of compounds from the cell wall is enhanced when the solute and solvent have similar polarities (Li et al., 2022). Moreover, UAE influences the level of surface contact between the solvent and solute, thereby facilitating the general diffusion of target compounds (Li et al., 2022). UAE also promotes improved extraction, resulting in the optimal production of desired AGI-active compounds at a concentration of 40% ethanol. Similarly, Liu et al. (2022) reported that in a pomegranate peel system combined with UAE, the use of 40%∼50% ethanol enhanced the yield of compounds responsible for AGI activity.
We found that the highest level of AGI activity (i.e., 1,460.96 mmol ACE/g extract) was achieved at an amplitude of 80% using an ethanol concentration of 40% and a sonication time of 30 min. These findings indicated that increasing the amplitude resulted in an increase in AGI activity. Likewise, Gulzar and Benjakul (2019) reported the use of UAE at an ultrasonic amplitude of 80% to obtain extracts from
In general, we found that AGI activity increased as the sonication time increased. These findings are consistent with those of a study conducted by Wang et al. (2018), who reported that the extraction of metabolites from apple pomace peaked following being subjected to a sonication treatment for 30 min. Furthermore, Ma et al. (2022) reported that the AGI activity of glycosylated α-lactalbumin and α-lactalbumin digestive products in the intestine and stomach was significantly enhanced (
Conventional extraction yields of green vegetable combinations
The extraction yields of combined GLV samples at different concentrations of ethanol (Table 4) suggest that the polarity of the solvent plays a pivotal role in determining extraction yield, with more polar solvents resulting in higher yields. This finding indicates that water was the most effective solvent for extracting the desired yield. Similarly, previous studies have also reported that higher ethanol concentrations decrease yield (Javadi et al., 2014; Easmin et al., 2017). In addition, the AGI activity was found to be higher at higher ethanol concentrations (Table 4), which was consistent with the findings of Javadi et al. (2014) and Easmin et al. (2017). Since ethanol has a lower polarity than water, lipophilic compounds can be more easily extracted in ethanol than in water (Easmin et al., 2017). The highest activity was observed in the 80% ethanol extract, thereby suggesting that the presence of more lipophilic compounds in GLV samples may have contributed to the presence of inhibition.
Properties of cracker enriched in GLV extract
The results of our baking experiments revealed that crackers with higher amounts of GLV extract showed a significantly greener color relative to those with lower extract content (Fig. 3). Moreover, as the baking temperature increased, cracker color was darker (Fig. 3). Furthermore, our color analysis of crackers produced at different baking temperatures was performed using the following parameters:
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Table 5 . Properties of green leafy vegetable extract-enriched crackers.
No. Formulation Baking temperature (°C) Color Hardness (g) Crispiness (mm) L* a* b* 1 Control 140 70.39±0.44a 3.65±0.24d 34.43±0.93hi 4,542.75±118.90c 0.48±0.10de 150 68.43±0.75b 4.56±0.18bc 34.57±1.46ghi 2,664.70±265.08f 1.35±0.30abc 160 65.47±0.36e 6.53±0.65a 35.73±0.59defg 1,409.91±364.03h 1.64±0.09a 2 0.1% acarbose 140 70.95±0.51a 3.34±0.14d 33.45±0.28i 4,561.14±178.49c 0.30±0.25def 150 67.04±0.63cd 4.93±0.36b 35.32±0.89fgh 2,765.63±182.85f 1.30±0.06abc 160 66.06±0.97de 6.63±0.65a 36.27±0.18cdef 1,467.14±264.07gh 1.59±0.34a 3 0.625% extract 140 67.48±0.96bc 1.32±0.30e 38.26±1.00a 4,808.20±239.32bc 0.22±0.06efg 150 61.69±0.85f 3.38±0.14d 37.25±0.39abc 3,229.86±185.40e 1.10±0.30bc 160 59.90±0.60g 4.01±0.26cd 36.87±0.18bcde 1,725.92±42.05gh 1.48±0.10a 4 1.25% extract 140 61.57±1.18f —1.41±0.62g 38.02±0.16ab 5,119.05±204.98b 0.09±0.04fg 150 59.19±0.89g —0.01±0.52f 36.05±0.59cdef 3,295.08±206.15e 1.03±0.25c 160 56.90±0.33h 0.60±0.38f 36.02±0.37cdef 1,830.40±97.04g 1.40±0.09ab 5 2.5% extract 140 59.02±0.57g —3.06±0.42h 36.95±0.45bcd 5,606.44±359.02a 0.02±0.09g 150 57.47±0.11h —1.95±0.35g 35.65±0.70efg 4,005.99±282.98d 0.62±0.07d 160 54.80±0.44i 0.18±0.08f 33.71±0.39i 2,764.07±58.80f 1.35±0.12abc Mean±SD of three technical replicates..
Different superscript letters in the same column (a-i) indicate statistically significant differences (
P <0.05)..
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Figure 3. Green leafy vegetable (GLV) extract-enriched crackers produced at different baking temperatures.
Higher baking temperatures generally resulted in darker crackers (Table 5). A darker hue is common in baked biscuits (Al-Ansi et al., 2019). This is because the nonenzymatic Maillard reaction occurs between amino acids and reducing sugars during baking, leading to a brownish effect (Nabil et al., 2020). Moreover, at higher temperatures the green color of high-GLV crackers (Table 5) further because of the degradation of chlorophyll pigments. This agrees with the results of Galla et al. (2017) who reported that chlorophyll levels decline during cooking. In addition, Zheng et al. (2023) reported that elevated temperatures resulted in the increased chlorophyll release, which then undergoes conversion into a brown substance known as pheophytin.
Table 5 illustrates the hardness and crispiness values of crackers produced at different baking temperatures. The findings of this study differ slightly from those of Dhal et al. (2023), who showed a hardness level of approximately 5,872 g and crispiness of about 0.6 mm for their control crackers. These differences may be attributed to differences in constitutive ingredients. Furthermore, cracker hardness also increased with increased extract levels (
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Figure 4. Total phenolic content of green leafy vegetable extract-enriched crackers produced at different baking temperatures. Bars represent standard deviation (n=3). Different lowercase letters (a-h) indicate statistically significant differences (
P <0.05).
Higher baking temperature resulted in reduced hardness and an enhancement in the crispiness of crackers (Table 5). These results are consistent with those of Sazesh and Goli (2020), who reported that cracker hardness decreased when the baking temperature was lowered from 160°C to 185°C. This was thought to occur due to the protein network coagulating more rapidly as well as an increase in carbon dioxide gas entrapment within the cracker at higher baking temperatures, two processes that resulted in increased porosity and decreased cracker density (Sazesh and Goli, 2020). Here, these factors likely also affected the crispiness of the crackers. Furthermore, the low moisture content of the high-baking-temperature crackers also contributed to their increased crunchiness, as depicted in Fig. 5. Water plays a crucial role in many manufacturer foods, since it significantly influences the overall texture, appearance, and flavor (Setyaningsih et al., 2019).
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Figure 5. Moisture contents of green leafy vegetable extract-enriched crackers produced at different baking temperatures. Bars represent SD (n=3). Different lowercase letters (a-h) indicate statistically significant differences (
P <0.05).
The moisture content of crackers at various baking temperatures is illustrated in Fig. 5. Generally, an increase in the amount of extract used led to a rise in moisture content. In addition, higher moisture content is known to be related to hydrophilic content (Bolarinwa et al., 2019). Here, the use of the GLV extract may cause crackers to contain a higher level of hydrophilic compounds, including polyphenols and polyol (Maser et al., 2023a), thereby resulting in a greater ability to retain water (Al-Ansi et al., 2019). These moisture content results align with those reported by Jiang et al. (2022), who found that crackers supplemented with papaya seed and peel had moisture contents ranging from 7.83% to 15.42%. However, when the baking temperature increased, the moisture content of the crackers decreased (Fig. 5). During the baking process, the moisture within the dough vaporizes from the surface of the cracker, causing moisture deep within the cracker to migrate to the surface, after which it to vaporizes (Setyaningsih et al., 2019). This leads to a steep reduction in moisture content that is proportional to the temperature increase (Ranjbar et al., 2014).
Strongly correlated with moisture content was the water content of crackers, which also increased as the amount of the GLV extract used rose (Fig. 6). Similarly, as the baking temperature increased, we observed a corresponding decline in water activity. It is likely that reduced water activity is connected to the reduction in moisture content (Renshaw et al., 2019). Taken together, these findings align with previously reported results for olive leaf extract crackers, in which crackers with a moisture content of approximately 3.73 had a water activity of approximately 0.3 (Paciulli et al., 2023).
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Figure 6. Water activity (aw) of green leafy vegetable extract-enriched crackers produced at different baking temperatures. Bars represent standard deviation (n=3). Different lowercase letters (a-j) indicate statistically significant differences (
P <0.05).
Antioxidant activities of crackers enriched with GLV extract
Fig. 4 illustrates the TPC of crackers enriched in GLV extract at various baking temperatures. In general, a higher amount of GLV extracts corresponded to higher TPC values of the crackers. Moreover, the TPC results recorded here were slightly lower than those found in a prior study where wheat cookies exhibited a TPC of 19.23 mg GAE/100 g (Sharma et al., 2016). The observed differences in phenolic acid content can be accounted for by diverse factors, including variation in geographical conditions, species, and other environmental influences (Nabil et al., 2020). Furthermore, higher baking temperatures led reduced TPC content across all cracker batches. Similarly, Nabil et al. (2020) reported that baking Moroccan cladode flour biscuits at 160°C for a few minutes resulted in minimal phenolic compound (e.g., ferulic acid) content. This may be due to structural alterations in phenolics caused by heating, and the degree of polyphenol degradation is contingent on the material composition and processing conditions (Nabil et al., 2020).
Next, the DPPH activity of GLV extract-enriched crackers is presented in Table 6. Overall, we found that the DPPH activity of the crackers increased as the amount of extract increased. Similarly, Paciulli et al. (2023) noted that adding olive leaf extract significantly boosted DPPH activity relative to an unenriched control group. Next, a direct link between TPC (Fig. 4) and DPPH (Table 6) was established, which confirmed the antioxidative potential of the polyphenols present in the GLV extract. However, higher baking temperatures also decreased the DPPH activity of crackers. In one paper, Zheng et al. (2023) reported that the loss of antioxidant activity occurs due to the poor thermal stability of certain antioxidant compounds under prolonged exposure to heat. Changes in heat-sensitive antioxidants therefore led to an overall decline in antioxidant activity.
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Table 6 . Antioxidant and antidiabetic activities of green leafy vegetable extract-enriched crackers.
No. Formulation Baking temperature (°C) DPPH (mg AEAC/100 g) Metal chelating (mg EECC/100 g) FRAP (mg AEAC/100 g) AAI (mmol ACE/100 g) AGI (mmol ACE/100 g) LPI (% inhibition) 1 Control 140 11.76±0.06c 0.79±0.08f 10.77±0.51d 40.07±3.38c 134.68±11.70de 22.26±0.97bcd 150 10.16±0.04e 0.40±0.03h 8.73±0.11f 35.47±2.38de 127.00±12.69e 19.61±1.27fgh 160 9.92±0.22e 0.24±0.02i 8.54±0.21f 29.79±2.20f 77.67±7.11f 17.73±1.24h 2 0.1% acarbose 140 12.28±0.16b 0.80±0.05f 11.06±0.49d 40.69±2.26bc 209.94±11.28a 22.32±0.56bcd 150 10.24±0.36e 0.42±0.04h 10.04±0.29e 37.43±2.64cd 152.25±9.58cd 19.69±1.62fgh 160 9.87±0.07e 0.21±0.03i 8.61±0.11f 30.67±0.71f 83.13±6.95f 19.13±1.08gh 3 0.625% extract 140 12.42±0.84b 1.45±0.06c 13.04±0.35b 41.25±1.64bc 225.30±15.21a 22.84±1.97bc 150 11.03±0.26d 0.97±0.10e 12.09±0.41c 39.81±1.98c 170.69±14.14bc 20.20±1.04def 160 9.98±0.21e 0.67±0.01g 11.23±0.42d 31.70±1.71ef 91.15±6.60f 19.19±1.37gh 4 1.25% extract 140 13.04±0.13a 1.59±0.01b 14.62±0.32a 44.45±4.19ab 226.84±19.76a 23.31±1.26b 150 11.11±0.22d 1.08±0.03d 12.14±0.43c 40.07±1.73c 183.83±17.66b 20.58±0.95cdef 160 10.16±0.04e 0.74±0.05fg 11.23±0.52d 32.11±1.17ef 98.83±4.11f 19.28±1.30gh 5 2.5% extract 140 13.38±0.05a 1.86±0.08a 14.95±0.17a 47.76±0.63a 227.35±12.29a 26.70±0.75a 150 11.29±0.20cd 1.10±0.02d 14.72±0.46a 45.59±2.06ab 189.46±12.33b 21.94±0.70bcde 160 10.94±0.40d 0.83±0.07f 13.69±0.86b 34.85±1.48de 142.70±9.97de 19.45±1.91gh Values are presented as mean±SD of three technical replicates..
Different superscript letters in the same column (a-i) indicate statistically significant differences (
P <0.05)..DPPH, 2,2-diphenyl-1-picrylhydrazyl; AEAC, L-ascorbic acid equivalent antioxidant capacity; EECC, ethylenediaminetetraacetic acid equivalent chelating capacity; FRAP, ferric reducing antioxidant power; AAI, α-amylase inhibitory; ACE, acarbose equivalent; AGI, α-glucosidase inhibitory; LPI, lipase inhibitory..
Like DPPH activity, the metal chelating activity of the crackers was found to increase with increasing GLV extract but decreased with higher baking temperature (Table 6). This occurrence may be associated to the presence of phytochemical antioxidants within the GLV extract. We also observed that the metal chelating activity correlated with cracker TPC content (Fig. 4). In one recent study, Maser et al. (2023b) also reported a positive correlation in GLV extracts between metal chelating activity and TPC (
Next, Table 6 shows the FRAP activity of crackers enriched GLV extract baked at different temperatures. In general, higher GLV content correlated with higher FRAP activity, but higher baking temperatures were associated with lower FRAP activity. In this study, we identified a connection between TPC and FRAP activity; this is similar to the results of a prior investigation, which reported a linear correlation (
Antidiabetic activities of GLV-enriched crackers enriched with the combination extract
Table 6 presents the AAI activity of crackers enriched with GLV combination extracts. The control cracker demonstrated a relatively favorable AAI activity of 40.07 mmol ACE/100 g cracker. Similarly, a study by Olagunju et al. (2018) reported that their control (100% wheat) cracker exhibited an AAI activity of approximately 54.22% inhibition. Furthermore, we also found that AAI activity was contingent on the concentration of the combination extract. For example, incorporation of 0.1% acarbose displayed an inhibitory efficacy equivalent to the use of 0.625% GLV extract (
Next, we measured the inhibition of α-glucosidase in crackers enriched with GLV extracts at various baking temperatures; these results are presented in Table 6. The control crackers displayed a moderate AGI activity of 134.68 mmol ACE/100 g. This result slightly exceeds that reported by Olagunju et al. (2018), who documented 15.56% AGI activity in 100% wheat crackers. This difference may be attributed to variation in ingredients used, including the presence of soybean oil, which is known for its high oleic and linoleic acid contents and is widely recognized as increasing AGI activity (Su et al., 2013). Moreover, we also observed that the addition of 0.1% acarbose resulted in a significant improvement relative to control crackers (
The addition of various concentrations of GLV extract was associated with different increases in AGI activity, although this effect was not statistically significantly different from the addition of 0.1% acarbose (
Table 6 presents the LPI activity of crackers enriched with GLV extract at various baking temperatures. Here, adding 0.1% acarbose did not yield a significant difference in LPI activity compared to control crackers (
Proximate composition of crackers
Next, we selected the cracker formulation featuring the most potent antidiabetic, antiobesity, and antioxidant properties and determined their proximate composition. First, all crackers baked at 140°C were selected for proximate composition analysis (Table 7). The moisture content of these crackers was found to increase following supplementation with 0.1% acarbose and GLV extract (
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Table 7 . Proximate composition of green leafy vegetable extract-enriched crackers produced at a baking temperature of 140°C.
No. Formulation Moisture (%) Ash (%) Crude protein (%) Fat (%) Carbohydrate (%) 1 Control 11.80±0.12d 1.41±0.03c 18.12±0.62a 17.75±0.62a 50.92±0.47a 2 0.1% acarbose 12.97±0.19c 1.43±0.02c 17.80±0.79a 17.74±0.25a 50.06±0.42a 3 0.625% extract 13.57±0.16b 1.53±0.01b 17.52±0.14a 17.64±0.70a 49.74±0.34ab 4 1.25% extract 15.28±0.37a 1.54±0.01b 17.32±0.59a 17.46±0.85a 48.40±0.61b 5 2.5% extract 15.51±0.12a 1.69±0.00a 17.22±0.06a 17.28±0.62a 48.30±0.27b Values are presented as mean±SD of three technical replicates..
Different superscript letters in the same column (a-d) indicate statistically significant differences (
P <0.05)..
Unlike moisture content, we found no significant differences in crude protein and fat content among cracker types (
In summary, in this study we report an optimized ultrasound-assisted process for extracting antidiabetic metabolites from GLVs. Overall, this method was more effective than conventional extraction methods in extracting these metabolites. The optimal extraction conditions for samples tested here were 44.08% ethanol concentration, 80% amplitude, and 30 min sonication time. These conditions resulted in a 24.16% increase in extraction yield compared to a conventional extraction method and an AGI activity of 1,449.73 mmol ACE/g extract. In addition, sonication improved yield while reducing solvent consumption and showed no detrimental effects on AGI activity. Next, when the GLV extract was used for the production of crackers at different baking temperatures, we observed a general increase in the amount of total phenolic compounds and their associated bioactivities, including antioxidant capacity and inhibitory effects on enzymes such as α-glucosidase, α-amylase, and lipase. However, higher baking temperatures (e.g., 160°C) reduced the amount of total phenolic compounds present as well as their bioactivity, and therefore lower baking temperatures such as 140°C or 150°C are recommended. Further research is recommended to examine the textural and sensory evaluations of GLV-supplemented crackers as well as to evaluate food safety and consumer acceptance.
FUNDING
This work was supported by King Mongkut’s Institute of Technology Ladkrabang Research Fund under the KMITL Doctoral Scholarship [KDS2020/031].
AUTHOR DISCLOSURE STATEMENT
The authors declare no conflict of interest.
AUTHOR CONTRIBUTIONS
Concept and design: AMMA, SCBB. Analysis and interpretation: WHM, NM, NH. Data collection: WHM, NM, SK. Writing the article: WHM, SK, PN. Critical revision of the article: PN, AKT, NH, AMMA, SCBB. Final approval of the article: all authors. Statistical analysis: WHM, NM. Obtained funding: WHM, AMMA, SCBB. Overall responsibility: PN, AMMA, SCBB.
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Table 1 . Box-Behnken design parameters for ultrasound-assisted extraction of green leafy vegetable using response surface methodology
Run Standard Independent variable Dependent variable Factor X1 Ethanol concentration (%)Factor X2 Amplitude (%)Factor X3 Sonication time (min)Yield (%) α-Glucosidase inhibitory activity (mmol ACE/g extract) 1 2 80 40 20 20.01±0.18d 1,161.74±27.70b 2 1 0 40 20 25.20±2.44abc 1,070.39±60.08bcd 3 10 40 80 10 27.99±2.42a 1,045.24±39.03d 4 12 40 80 30 25.70±2.15abc 1,460.96±16.17a 5 8 80 60 30 17.45±1.28d 1,432.46±76.72a 6 14 40 60 20 25.50±1.70abc 964.46±59.73de 7 15 40 60 20 26.49±1.34abc 919.42±63.20e 8 4 80 80 20 19.07±2.43d 1,455.93±80.55a 9 6 80 60 10 18.03±0.72d 1,053.10±53.71cd 10 5 0 60 10 27.90±2.20ab 974.00±26.41de 11 3 0 80 20 24.46±2.40abc 1,059.49±53.77cd 12 11 40 40 30 26.37±1.41abc 1,150.01±66.64bc 13 9 40 40 10 23.89±1.16c 998.31±57.90de 14 7 0 60 30 24.36±2.35bc 989.66±49.17de 15 13 40 60 20 25.22±1.38abc 969.72±56.06de Values are presented as mean±SD of three technical replicates (i.e., n=3).
Different superscripts in the same column (a-e) indicate statistically significant differences (
P <0.05).ACE, acarbose equivalent.
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Table 2 . Ingredients of crackers enriched with green leafy vegetable extracts
Ingredient (% w/w) Control 0.1% acarbose 0.625% extract 1.25% extract 2.5% extract Egg 38.36 38.36 38.36 38.36 38.36 Soybean oil 8.70 8.70 8.70 8.70 8.70 Wheat flour 52.23 52.17 51.90 51.57 50.92 Combination extract 0.00 0.05 0.33 0.65 1.31 NaCl 0.30 0.30 0.30 0.30 0.30 Baking powder 0.40 0.40 0.40 0.40 0.40
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Table 3 . ANOVA to evaluate fitted linear and quadratic polynomial models with respect to parameter optimization and desirability value
Source Degrees of freedom Sum of squares Mean square F -valueP -valueYield (%) Model 9 158.46 17.61 7.78 0.0180s Lack of fit 3 10.42 3.47 7.79 0.1159ns Pure error 2 0.89 0.45 Total error 14 169.77 R 20.9334 adj- R 20.8134 CV (%) 6.31 AGI activity (mmol ACE/g extract) Model 9 478,996.67 53,221.85 43.74 0.0003s Lack of fit 3 4,556.11 1,518.70 1.99 0.3520ns Pure error 2 1,528.45 764.22 Total error 14 485,081.23 R 20.9875 adj- R 20.9649 CV (%) 3.13 Desirability value1) Ethanol concentration Amplitude Time Yield AGI activity Desirability 44.08 80.00 30.00 24.21 1,460.96 0.801 43.65 80.00 30.00 24.24 1,457.60 0.800 43.31 80.00 30.00 24.27 1,454.95 0.800 44.42 80.00 29.92 24.19 1,460.96 0.800 44.38 79.89 30.00 24.18 1,460.96 0.799 41.72 80.00 30.00 24.40 1,442.85 0.798 44.95 80.00 29.80 24.16 1,460.96 0.798 44.76 79.76 30.00 24.15 1,460.96 0.797 45.40 80.00 29.69 24.14 1,460.96 0.796 45.38 79.53 30.00 24.10 1,460.95 0.794 sSignificant. nsNot significant.
1)Only the 10 highest of 43 values are shown.
adj-
R 2, the coefficient of adjusted determination; CV, coefficient of variance; AGI, α-glucosidase inhibitory; ACE, acarbose equivalent.
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Table 4 . Yield and α-glucosidase inhibitory activity of green leafy vegetable extracts produced using conventional processes at different ethanol concentrations
Ethanol concentration (%) Extraction yield (%) α-Glucosidase inhibitory activity (mmol ACE/g extract) 0 23.89±1.16a 794.27±36.84b 40 22.83±1.56a 869.19±72.51b 80 17.21±0.08b 974.46±81.57a Values are presented as mean±SD of three technical replicates.
Different superscripts in the same column (a,b) indicate statistically significant differences (
P <0.05).ACE, acarbose equivalent.
-
Table 5 . Properties of green leafy vegetable extract-enriched crackers
No. Formulation Baking temperature (°C) Color Hardness (g) Crispiness (mm) L* a* b* 1 Control 140 70.39±0.44a 3.65±0.24d 34.43±0.93hi 4,542.75±118.90c 0.48±0.10de 150 68.43±0.75b 4.56±0.18bc 34.57±1.46ghi 2,664.70±265.08f 1.35±0.30abc 160 65.47±0.36e 6.53±0.65a 35.73±0.59defg 1,409.91±364.03h 1.64±0.09a 2 0.1% acarbose 140 70.95±0.51a 3.34±0.14d 33.45±0.28i 4,561.14±178.49c 0.30±0.25def 150 67.04±0.63cd 4.93±0.36b 35.32±0.89fgh 2,765.63±182.85f 1.30±0.06abc 160 66.06±0.97de 6.63±0.65a 36.27±0.18cdef 1,467.14±264.07gh 1.59±0.34a 3 0.625% extract 140 67.48±0.96bc 1.32±0.30e 38.26±1.00a 4,808.20±239.32bc 0.22±0.06efg 150 61.69±0.85f 3.38±0.14d 37.25±0.39abc 3,229.86±185.40e 1.10±0.30bc 160 59.90±0.60g 4.01±0.26cd 36.87±0.18bcde 1,725.92±42.05gh 1.48±0.10a 4 1.25% extract 140 61.57±1.18f —1.41±0.62g 38.02±0.16ab 5,119.05±204.98b 0.09±0.04fg 150 59.19±0.89g —0.01±0.52f 36.05±0.59cdef 3,295.08±206.15e 1.03±0.25c 160 56.90±0.33h 0.60±0.38f 36.02±0.37cdef 1,830.40±97.04g 1.40±0.09ab 5 2.5% extract 140 59.02±0.57g —3.06±0.42h 36.95±0.45bcd 5,606.44±359.02a 0.02±0.09g 150 57.47±0.11h —1.95±0.35g 35.65±0.70efg 4,005.99±282.98d 0.62±0.07d 160 54.80±0.44i 0.18±0.08f 33.71±0.39i 2,764.07±58.80f 1.35±0.12abc Mean±SD of three technical replicates.
Different superscript letters in the same column (a-i) indicate statistically significant differences (
P <0.05).
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Table 6 . Antioxidant and antidiabetic activities of green leafy vegetable extract-enriched crackers
No. Formulation Baking temperature (°C) DPPH (mg AEAC/100 g) Metal chelating (mg EECC/100 g) FRAP (mg AEAC/100 g) AAI (mmol ACE/100 g) AGI (mmol ACE/100 g) LPI (% inhibition) 1 Control 140 11.76±0.06c 0.79±0.08f 10.77±0.51d 40.07±3.38c 134.68±11.70de 22.26±0.97bcd 150 10.16±0.04e 0.40±0.03h 8.73±0.11f 35.47±2.38de 127.00±12.69e 19.61±1.27fgh 160 9.92±0.22e 0.24±0.02i 8.54±0.21f 29.79±2.20f 77.67±7.11f 17.73±1.24h 2 0.1% acarbose 140 12.28±0.16b 0.80±0.05f 11.06±0.49d 40.69±2.26bc 209.94±11.28a 22.32±0.56bcd 150 10.24±0.36e 0.42±0.04h 10.04±0.29e 37.43±2.64cd 152.25±9.58cd 19.69±1.62fgh 160 9.87±0.07e 0.21±0.03i 8.61±0.11f 30.67±0.71f 83.13±6.95f 19.13±1.08gh 3 0.625% extract 140 12.42±0.84b 1.45±0.06c 13.04±0.35b 41.25±1.64bc 225.30±15.21a 22.84±1.97bc 150 11.03±0.26d 0.97±0.10e 12.09±0.41c 39.81±1.98c 170.69±14.14bc 20.20±1.04def 160 9.98±0.21e 0.67±0.01g 11.23±0.42d 31.70±1.71ef 91.15±6.60f 19.19±1.37gh 4 1.25% extract 140 13.04±0.13a 1.59±0.01b 14.62±0.32a 44.45±4.19ab 226.84±19.76a 23.31±1.26b 150 11.11±0.22d 1.08±0.03d 12.14±0.43c 40.07±1.73c 183.83±17.66b 20.58±0.95cdef 160 10.16±0.04e 0.74±0.05fg 11.23±0.52d 32.11±1.17ef 98.83±4.11f 19.28±1.30gh 5 2.5% extract 140 13.38±0.05a 1.86±0.08a 14.95±0.17a 47.76±0.63a 227.35±12.29a 26.70±0.75a 150 11.29±0.20cd 1.10±0.02d 14.72±0.46a 45.59±2.06ab 189.46±12.33b 21.94±0.70bcde 160 10.94±0.40d 0.83±0.07f 13.69±0.86b 34.85±1.48de 142.70±9.97de 19.45±1.91gh Values are presented as mean±SD of three technical replicates.
Different superscript letters in the same column (a-i) indicate statistically significant differences (
P <0.05).DPPH, 2,2-diphenyl-1-picrylhydrazyl; AEAC, L-ascorbic acid equivalent antioxidant capacity; EECC, ethylenediaminetetraacetic acid equivalent chelating capacity; FRAP, ferric reducing antioxidant power; AAI, α-amylase inhibitory; ACE, acarbose equivalent; AGI, α-glucosidase inhibitory; LPI, lipase inhibitory.
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Table 7 . Proximate composition of green leafy vegetable extract-enriched crackers produced at a baking temperature of 140°C
No. Formulation Moisture (%) Ash (%) Crude protein (%) Fat (%) Carbohydrate (%) 1 Control 11.80±0.12d 1.41±0.03c 18.12±0.62a 17.75±0.62a 50.92±0.47a 2 0.1% acarbose 12.97±0.19c 1.43±0.02c 17.80±0.79a 17.74±0.25a 50.06±0.42a 3 0.625% extract 13.57±0.16b 1.53±0.01b 17.52±0.14a 17.64±0.70a 49.74±0.34ab 4 1.25% extract 15.28±0.37a 1.54±0.01b 17.32±0.59a 17.46±0.85a 48.40±0.61b 5 2.5% extract 15.51±0.12a 1.69±0.00a 17.22±0.06a 17.28±0.62a 48.30±0.27b Values are presented as mean±SD of three technical replicates.
Different superscript letters in the same column (a-d) indicate statistically significant differences (
P <0.05).
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