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Publicly Available Published by De Gruyter March 9, 2020

Towards a green and sustainable fruit waste valorisation model in Brazil: optimisation of homogenizer-assisted extraction of bioactive compounds from mango waste using a response surface methodology

  • Vânia G. Zuin EMAIL logo , Mateus L. Segatto and Karine Zanotti


Food waste valorisation is currently at the core of discussions and development of future economic models which, allied to the application of green and sustainable technologies, offers a viable alternative to shift industrial practices towards a circular bioeconomy. The feasibility and technological possibilities based on an integrated mango waste biorefinery concept, focusing on the extraction of bioactive compounds, are discussed in this paper. Additionally, a statistically robust methodology is presented as a green approach to optimise the variables of a sustainable, low time and energy consumption extraction technique (homogenizer-assisted extraction). Maximum concentrations of the bioactive compounds were obtained in similar values of parameters ethanol/water concentration (67.73 and 70.11 %), sample/solvent ratio (29.33 and 28.17 %) and time (4.47 and 5.00 min) for mangiferin (354.4 mg/kg DW) and hyperoside (258.7 mg/kg DW), respectively. These results demonstrated the efficiency of the proposed green and sustainable method to obtain bioactive compounds from a very common and significant tropical fruit waste in Brazil, based on an integrated mango biorefinery concept.


According to the Strategic Framework for the Food and Agriculture Organisation (FAO) of the United Nations, several studies have shown that population growth is one of the key challenges to tackle sustainable development globally. World population should be around 9.73 billion people in 2050, and 11.2 billion in 2100, with more than half of this growth concentrated in developing countries. As a result, higher demands for food, feed, chemicals and all types of materials and energy have been affecting the utilisation of natural resources, biodiversity and the greenhouse gas emissions in times of climate change and global warming. Beyond quantity, the current and future agro-industrial production should ensure quality not only for the aimed products, but also for the processes to obtain them, which should be as green and sustainable as possible. Thus, for food, beverages and related bioactive products, safe and nutritious food manufacturing associated to waste prevention are mandatory approaches in all steps of the production chain [1], [2].

More recently, the United Nation’s report “Global Chemical Outlook II” brought out a roadmap to support strategies to locate Chemistry in global challenges by means of the 17 Sustainable Development Goals (SDGs), highlighting economic, political, social and technological factors to handle chemicals and waste generation in global-scale processes. Food loss and waste is a major global issue approached by the SDGs, with the generation of roughly 1.3 billion tons of residues per year, part of which is unavoidably generated despite efforts in food waste education and transport/storage loss prevention [3]. The unavoidable part of Food Supply Chain (FSC) waste, consisting basically of parts of fruits, vegetables and other raw materials that are not consumed in the food industry, can be used as feedstocks to produce novel products in chemical and biochemical platforms, biorefineries, aggregating value to a material that was considered a residue [4].

Other than structural materials that can be recovered from FSC waste (e.g. cellulosic fractions, pectin and starch), this new feedstock can be a mine of high-valued smaller molecules called secondary metabolites. Naturally produced in plants and often related to their defence mechanism against natural forces, these phytochemicals present important biological activities, which could be used to increase nutritional values in food and for human health, as nutraceuticals and pharmaceutical products [5]. Novel alternative extraction techniques for the isolation of phytochemical-rich extracts from plant FSC residues are important tools to develop low-impact processes that can be used in biorefinery schemes [6]. This approach can transform the food industry into a biorefinery chemical platform that, using Green and Sustainable Chemistry techniques, helps to close the loop of a bio-based circular economy that has the potential to support reaching sustainable goals on several fronts [7].

Case study: mango biorefinery

As a developing country with an agricultural based economy, Brazil’s biggest share of food losses and waste is concentrated on harvest, transport and processing FSC steps [8]. Therefore, using plant residues generated in these steps appears as an opportunity to reduce waste generation and create value for the FSC, as they can contain functional materials and other substances with useful activities, such as bioactive compounds [9]. Brazil is the third largest fruit producer in the world, where citrus and tropical fruits are predominant; nearly half of fruit production is processed into pulp and other products, generating a residue consisting of its peel, seed, leaves and other parts of the plant [10]. As part of the native tropical plants, mango (Mangiferina indica L.) is one the most produced fruits in the country, accounting for more than 13% of the world’s production that, with India in the forefront, exceeded 50 million tons of mangoes in 2017, according to FAO. When processed, it produces a Mango Processing Waste (MPW), basically consisting of its peel and seed (husk and internal kernel), which accounts for 40% of the fruit’s weight, depending on the variety [11].

A high production volume and processing rate, together with a large amount of waste generated, have made the mango biorefinery case study one of the most prominent subjects on the generation of value in the food supply chain by means of residue valorisation. A techno-economic analysis of a mango biorefinery applied to the local Indian industrial landscape has been studied by Arora and collaborators [12], considering only pectin from the peel, pectin and seed oil, and the full biorefinery scenario. According to this study, pectin and seed oil recovery was the most profitable scheme, which considered the seasonality of mango production and the possible fluctuations of pectin prices to show the feasibility of a mango biorefinery in India.

As summarised in Fig. 1, there are several possibilities of product recovery in an integrated mango biorefinery scheme, and financial viability may depend on developing technical processes and new consumer markets that can arise from waste valorisation and modern food and health consumption patterns. In a regular mango processing unit, after the pulp is separated from non-edible mango parts, it is transformed into food products such as juices, jams, and jellies, as well as parts of other processed aliments. Part of the MPW, mango pits can be separated between husks (the outer shell) and kernels (the oily core), to give different products such as cellulose from husks and mango seed oil and starch from the kernels. Mango peel can be subjected to different chemical transformations (solid-liquid extractions) to isolate bioactive compounds in a liquid solution (extract). The remaining solid can be separated from the bioactive extract to recover pectin, a functional carbohydrate used in food and pharmaceutical industries. All of these transformations will be discussed in the next sections, showing central studies regarding each part of the mango residues and the state-of-the-art of technologies used in MPW valorisation.

Fig. 1: Integrated mango biorefinery scheme.
Fig. 1:

Integrated mango biorefinery scheme.

Mango peel: bioactive extract

Mango peel has been reported to be used as food ingredients in the form of powder, not only for their structural properties (as a thickener or texturiser), but also to add nutritional value and increase shelf life in industrialised products [13]. Due to the high presence of secondary metabolites, mango peel has been found to have therapeutic and preservative properties, such as UV-light protection, antioxidant effects and microorganism inhibition, as tested for several microbes [14]. The main groups of secondary metabolites in mango peel (Table 1) are the small phenolic compounds, consisting of xanthonoids, flavonoids and anthocyanins (usually referred to as phenolic or polyphenolic compounds, and anthocyanins as a separated group). Carotenoids are long molecules that also have interesting antioxidant activities and are found in high concentrations in mango peel [15].

Table 1:

Concentrations of the main bioactive compounds in mango peel.

Group Compound Concentration Unit (DWa)
Xanthonoidsb Mangiferin 1690.4 mg/kg
Mangiferin gallate 321.9
Flavonoidsb Quercetin 3-O-galactoside 651.2 mg/kg
Quercetin 3-O-glucoside 557.7
Quercetin 3-O-xyloside 207.3
Anthocyaninsc Cyanidin 3-O-galactoside 234 μg/kg
Anthocyanidin hexoside 3458
Carotenoidsd β-cryptoxanthin 0.37 mg/g
Lutein 3.47
β-carotene 2.07
  1. Data from references (mango variation): aDW, dry weight. bBerardini et al. (16) and cBerardini et al. (17) (Tommy Atkins); dMercado-Mercado et al. (15) (Ataulfo).

Mangiferin and hyperoside (quercetin 3-O-galactoside) are usually reported as the most concentrated phenolic compounds in mango peel (Fig. 2), detected in scales of up to 2.35 g/kg of dry weight [16], [17]. They are also identified in kernels, bark and leaves [18], possessing biological activities that range from antioxidant to antimicrobial effects, which could be helpful for its application in food, nutraceutical and pharmaceutical industries [19].

Fig. 2: Mangiferin and Hyperoside (Quercetin-3-O-galactoside).
Fig. 2:

Mangiferin and Hyperoside (Quercetin-3-O-galactoside).

Considering a biorefinery scheme, it is important to study the sequential recovery of valuable products as a way of fully using the material’s potential, as explored with the isolation of phenolic compounds and pectin using ultrasound-assisted methodology [20]; anthocyanins were also target compounds using this sequential procedure [21]. Alternative extraction techniques such as ultrasound have been explored as greener and efficient methodologies to isolate carotenoids [15] and polyphenols from mango peel compared to conventional maceration techniques [22]. Pulsed electric fields (PEF) were also tested as an unconventional extraction tool for polyphenolic compounds [23]. The efficiency of supercritical CO2 as an extraction medium was assessed by means of the antioxidant activity and the isolation of carotenoids, phenolics and flavonoids in the resulting extracts [24]. Most of the studies involved methanolic or ethanolic solvents as extraction medium, the latter highlighting the possibility of using biorenewable sugarcane ethanol. This solvent is produced on industrial scales in Brazil, building a more robust case for biorefinery models that use bioactive compound extractions in this country.

Mango peel: pectin

As discussed in the last section, mango peel can be subjected to the recovery of pectin after the solid-liquid extraction of nutritional-valued compounds. Pectin is a structural polysaccharide, often found in non-woody plant materials, considered a commodity in the food and cosmetic industry, and used as a thickener, stabilising and gelling agent [25]. Thus, pectin recovery has the potential of enhancing the impact of a mango biorefinery to generate value within the food supply chain, supporting the development of integrated food processing-biorefinery industrial parks. Conventional pectin recovery involves precipitation with alcohol (usually ethanol) and heat assisted acid hydrolysis, using mineral acids (pH between 1 and 3) in medium-high temperatures (up to 100°C) for 1–3 h, as recent studies indicate [26]. Faster and greener pectin recoveries were achieved using ultrasound or microwave energy, either with traditional acidic solutions [27], [28], [29] or acid-free procedures [30]. Acid-free pectin extraction was also achieved with supercritical water [25]. The substitution of mineral acids for natural acids was subject to studies in mango peel pectin extraction, adopting lemon juice as the extraction medium combined with ultrasound energy [31] and citric acid in a conventional procedure [32].

Mango kernel: bioactive extract and kernel oil

The oily inner mango seed, commonly called kernel, has been studied for its biological activity, either extracted using aqueous solutions with organic solvents to obtain a bioactive extract or incorporated in its useful oil fraction, which depends on the solubility of the compounds in oil. As in the extract obtained from the peel, the main compounds responsible for the antioxidant, anti-inflammatory and other biological effects are phenolics, with a higher presence of phenolic acids and gallotannins [33]. Optimisation of conventional ethanolic extraction techniques was reported [34], [35], as well as the use of chemometrics to optimise microwave-assisted extractions, assessing antioxidant effects [36]. A evaluation of the use of ethanolic seed extracts in fresh-cut fruits showed enhanced food preservation and important data on consumer acceptability towards using plant extracts as preservatives in food products [37].

Mango Kernel Oil (MKO) has been mainly studied as a substitute to cocoa butter [38] and in the cosmetic industry [39]. Interesting features of MKO, such as the presence of bioactive compounds [40], has brought attention to its use as an edible oil in the food industry [41]. Regarding the use of green and sustainable techniques to extract MKO from mango seeds, we highlight the use of supercritical carbon dioxide as the extraction medium [42], [43].

Mango kernel: starch

Just as pectin, starch is another commodity for the food and pharmaceutical industries and is a relevant natural thickener and stabiliser. Starch derived from mango kernels has good functional properties and can be applied as a food additive [33], which can lower the demand for starch derived from primary food-related feedstock, its main commercial source [44]. A South African/Ethiopian group led by Tesfaye et al. [45] has studied the economic performance of a mango seed biorefinery through starch recovery, reaching financial feasibility parameters and adding a new strategy to help develop the Ethiopian industry through waste valorisation. Recent studies explored the characterisation of starch from mango kernels, focusing on the development of biodegradable materials [46] and derivatisation by reaction with other compounds [47]. Incorporation of mango kernel starch on industrial soup mixes was tested by a group from India, using it as replacement of corn starch with minor differences on sensory properties and shelf life [44].

Mango husk: cellulose

Mango seed outer shell, or husk, is a very fibrous part of the mango seed, consisting mainly of cellulose and hemicellulose, which can act as a naturally-derived carbon source for activated carbon, a adsorbent material used in several applications [48]. In a biorefinery scheme, this section of the fruit can be burnt to generate electricity or heat as way of allowing industrial feasibility [12], although it is preferable to enhance value generation across all fractions of mango using more efficient energy sources, guaranteeing viability through technology development and innovative products. Thus, mango husks can be a powerful source of cellulose and derivatives, such as cellulose nanocrystals [49] and nanowhiskers [46], adding fine valuable biodegradable materials to the list of products derived from MPW.

Homogenizer-assisted extraction of MPW bioactive compounds: optimisation through chemometrics

From a holistic point of view, it is inseparable to promote a circular economy by using waste in a biorefinery strategy without also applying green thinking in developing and optimising environmentally friendly processes that could be used inside the industrial platforms. Therefore, it is important to promote Green and Sustainable extraction techniques, which benefits both sample preparation steps on laboratory scales for analytical methodologies and the development of industrial extraction operations [50]. Homogenizer-assisted extraction (HAE), also known as turbolysis, has often been used as a simple, effective and low-cost sample preparation method, especially for natural products [51]. This solid-liquid extraction procedure is based on homogenisation in a high rotation speed, consequently promoting high shear rates between the sample matrix and the solvent; thus, the rupture of the cell walls occurs in low time and without any external source of heating [52]. As it has a low energy consumption and can be performed in up to 5 min for each extraction, allied to adopting green solvents, HAE can be considered a green extraction technique for natural matrices. In addition, with the possibility of industrial scaling of HAE by using batch dispersers that can process up to 3500 L of solid-liquid mixtures, this technique appears as a low cost and efficient option for the extraction of bioactive compounds in the development of industrial biorefineries.

Chemometric routines such as response surface methodology (RSM) and experimental design are undeniable tools to promote a multivariate optimisation of processes and products, and can be considered green devices as it guarantees statistically robust results with minimum experiment time, cost and energy and material consumption [53]. In this study, such tools were used to optimise the conditions involved in the extraction of mangiferin and hyperoside from MPW using HAE, considering solvent concentration, sample/solvent ratio and extraction time. A Box-Behnken experimental design was used to calculate the effect of the three variables on the extraction efficiency of both compounds, as well as the determination of a second-order polynomial model in order to obtain a response surface and establish maximum extraction conditions for the selected parameters.

Materials and methods

Chemicals and reagents

Mangiferin standard was purchased from Sigma-Aldrich (assay ≥98.0%) and Hyperoside from the HWI group (assay ≥88.5%). HPLC-grade ethanol was purchased from Sigma-Aldrich and HPLC-grade methanol from TEDIA. Standard stock solutions of 800 and 1600 mg/L of mangiferin and hyperoside, respectively, were prepared by accurately weighing the proper mass in 65% ethanol/water solvent.

Calibration curve and analytical validation

Each stock solution was properly diluted in a MPW extract to give a mixed solution of 400, 200, 100, 50 and 5 mg/L of each compound to obtain the analytical curve. Therefore, the concentration of any sample could be calculated from the area of the peak related to each compound, as obtained by liquid chromatography. The validation of the analytical methodology was evaluated according to the International Conference of Harmonization guidelines [54], assessing the specificity, linearity, accuracy (recovery), precision (intra- and inter-day error), detection limit (LOD) and quantification limit (LOQ).

Recovery (or fortification) essay was performed by adding known amounts of the standard stock solutions to the MPW samples in four levels for each compound (30, 50, 100 and 150 mg/L), followed by extraction. Fortified extracts were analysed by liquid chromatography to calculate final concentrations (discounting the area of the blank extract) and recovery was predicted as a percentage of the experimental concentration compared to the initial added concentration. Inter-day error was calculated by injecting the fortification extracts three times in a single day and intra-day error was estimated by injecting the same extracts in three different days. Inter- and intra-day errors were presented as the percentage coefficient of variation between the injections (standard deviation/mean).

MPW sample

Organic mango processing waste (var. Palmer) was obtained from a local processing unit in Itirapina (São Paulo) as a mixture of mango peels, puree and seeds. Samples were refrigerated on site and transported to the laboratory, where they were stocked in −20°C until being properly processed. Frozen samples were dried until constant mass, homogenized, blended and sieved, obtaining a powder with particle size <500 μm, which was stored protected from light and humidity until extraction.

Experimental design, statistical analysis and RSM

A Box-Behnken experimental design (BBD) was used to evaluate the influence of variables in the concentration of the two substances, which consisted of 15 randomised experiments with three replicates at the central point. BBD is defined as a balanced incomplete block design, with two variables paired together while the third variable is fixed at the central point. This is repeated for the two other possible pairs, drawing a spherical design that covers all edge points but does not approach extreme points (e.g. all parameters in the minimum level) [53]. The three variables selected were the concentration of ethanol in water (X1; 30–100% v/v), sample/solvent ratio (X2; 5–50% w/v) and extraction time (X3; 0.5–5 min). The parameters were coded between −1 and 1, as can be seen in Table 2.

Table 2:

Variables and coded levels used in the experimental design.

Symbol Real variables Coded variables
Min (−1) CP (0) Max (+1)
X1 % Ethanol/Water (%v/v) 30 55 80
X2 % Sample/Solvent (%w/v) 15% 32.5% 50%
X3 Time (min) 0.5 2.75 5
  1. CP, central point.

The responses obtained from the experimental design were fitted in a second-order polynomial model (Eq. 1), of which the calculated coefficients could be used to describe the influence of the determined variables, and therefore calculate optimum conditions and determine RSM plots:

(1) Y=β0+j=1kβjXj+j=1kβjjXj2+i<j=2kβijXiXj

where Y is the response, β represents the regression coefficients and X represents the independent variables.

Statistical analysis of variable influence, second-order polynomial model calculation and analysis of variance (ANOVA) were performed using GNU Octave software. Final response surface plots were generated with the OriginPro 9.0 software (OriginLab). A validation of the model was performed by selecting five points, near and including the point of maximum response, and calculating the percentile variation (v) between the experimental concentration (Ce) compared to the predicted concentration (Cp) (Eq. 2).

(2) v=100%(CeCp/Cp).

HAE process

For the extraction step, samples were accurately weighed accordingly to the sample/solvent ratio of each run and transferred to a 15 mL plastic tube containing 5 mL of the ethanol/water solvent, using the respective concentration defined by the experimental design. Extraction was performed using IKA’s T10 Basic ULTRA-TURRAX® at 20 500 rpm. The extraction medium was then centrifuged at 10°C and 12 000 rpm for 10 min; the supernatant was collected and filtered using a 0.45 μm PTFE filter and the resulting extract was further analysed by liquid chromatography in triplicate. The results are expressed as the concentration mean of the three injections, in mg/kg of MPW (dry weight).

Liquid chromatography

Liquid chromatography was performed using a UHPLC (Ultra-High-Performance Liquid Chromatography) system Waters ACQUITY H-class UPLC® coupled with Photodiode Array UV (PDA) and QDa mass spectrometer detectors, which allowed the detection of the analytes in the UV-Vis range, the UV-Vis profile and the relative mass for each peak. The separation was achieved with ACQUITY HSS C18 column (Waters, 1.8 μm; 2.1×100 mm), using water/acetonitrile mobile phase at 0.4 mL/min, injection volume of 1 μL, column temperature of 35°C and the selected wavelength of 350 nm. The gradient started with the percentage of acetonitrile in 12% and raised through the chromatographic run as follows: 0 min, 12%; 5 min, 13%; 7 min, 14%; 15.5 min, 14.5%; 18.5 min, 100%.

Results and discussion

Calibration curve and analytical validation

The analytical methodology for the quantification of mangiferin and hyperoside from MPW using HAE and liquid-chromatography analysis presented appropriate results regarding the validation parameters tested in this work. UHPLC analysis with both UV and mass detectors showed good specificity for both compounds, with appropriate peak separation as determined by the chromatograms, the mass prediction for each peak corresponding to the analytical standards and the UV profile having consistency with the standards in three different peak positions (Supplementary Material A). Table 3 shows the calculated parameters of linearity (linear regression equation and coefficient of determination, R2), detection limits (LOD and LOQ), accuracy (recovery) and precision (intra- and inter-day errors). A strong linear correlation was found for both compounds, as well as sufficient values of LOD and LOQ, given that the experimental runs showed concentrations in the range of 32.84–161.86 and 22.26–111.60 mg/L for mangiferin and hyperoside, respectively. The accuracy assay showed recovery percentages in the range of 80–120%, which indicates a robust analysis, according to the ICH guidelines. Intra- and inter-day precision did not surpass 5% of error, indicating low variance of peak area values between different injections.

Table 3:

Calibration curve and validation parameters.

Compound Equation R2 LOD (mg/L) LOQ (mg/L) Recovery (%) Intra-day error (%) Inter-day error (%)
Mangiferin y=1887.40x −1712.93 0.99985 6.11 18.51 80.4–114.3 1.0–4.4 0.4–4.7
Hyperoside y=2126.70x +247.63 0.99984 6.38 19.34 89.3–109.1 0.9–4.8 0.9–2.2

HAE extraction

The extraction experiments were carried according to the BBD, as seen in Table 4, with responses by the means of the concentrations of mangiferin and hyperoside, calculated as mg/kg of MPW in dry weight. The Box-Behnken design allowed a multivariate analysis of the extraction parameters within the selected range, showing that the main variable affecting the final concentration of both compounds in the extract was the ethanol/water ratio (effect of 68.67 for mangiferin and 60.93 for hyperoside, in absolute mg/kg DW values). It can be inferred in Table 4 that the concentration of both compounds followed similar trends, which can be explained by the similar chemical structure, molecular size and polarity, properties that directly affect the solubility of such compounds in ethanol-water mixtures. Therefore, solubility has shown to be a major factor on the HAE extraction of the selected compounds, and optimum ethanol-water concentration is an important parameter to determine the best conditions for this methodology.

Table 4:

Experimental BBD and extraction responses for all experiments.

Run Ethanol/Water (X1)
Sample/Solvent (X2)
Time (X3)
% v/v
% w/v
mg/kg dry weight
Coded Real Coded Real Coded Real Mangiferin Hyperoside
01 −1 30 −1 15 0 2.75 218.96 148.41
02 1 80 −1 15 0 2.75 332.34 218.63
03 −1 30 1 50 0 2.75 214.26 117.23
04 1 80 1 50 0 2.75 319.23 223.21
05 −1 30 0 32.5 −1 0.5 238.20 148.44
06 1 80 0 32.5 −1 0.5 329.16 234.19
07 −1 30 0 32.5 1 5 235.05 138.06
08 1 80 0 32.5 1 5 337.77 241.69
09 0 55 −1 15 −1 0.5 317.34 221.47
10 0 55 1 50 −1 0.5 323.72 203.42
11 0 55 −1 15 1 5 326.94 235.74
12 0 55 1 50 1 5 320.22 206.37
13 0 55 0 32.5 0 2.75 340.12 230.27
14 0 55 0 32.5 0 2.75 338.99 227.97
15 0 55 0 32.5 0 2.75 342.45 231.87

Sample/solvent ratio (negative effect of 3.03 and 12.34 mg/kg) and time (positive effect of 1.93 and 2.39 mg/kg) had a low effect on final responses of mangiferin and hyperoside extraction rates (respectively). It is important to notice that variable X2 had a major effect on the detected concentration of the analytes in mg/L, as more mass of the MPW samples resulted in higher concentrations, but when the mass of the analytes per kg of sample was calculated, little effect was observed. This can be considered a positive result, as when scaling up the process a minimum solvent volume can be used with minor effect on the extraction efficiency, yielding very concentrated extracts. In addition, the low effect of variable X3 allows viable extraction times as low as 30 s with a minor impact on the final concentration of the isolated substances.

Response surface methodology

The regression coefficients were obtained by multiple regressions to fit a secondary polynomial model, as described in the methodology section. The effects of the variables are described by the following equations 3 and 4:

(3) Ymangiferin=340.52+51.5X12.25X2+1.45X353.17X1216.16X222.31X322.10X1X2+2.94X1X33.28X2X3
(4) Yhyperoside=230.04+45.7X19.25X2+1.79X339.66X1213.51X220.22X328.94X1X2+4.47X1X32.83X2X3

The calculated model for both responses showed a reliable representation of data, with good coefficients of determination (R2=0.996 and 0.994), which means that 99.6 and 99.4% of the data are explained by the equations for mangiferin and hyperoside, respectively. The models had shown to be statistically valid, as hypothesis testing described significant regression for the fitted model and not a significant lack of fit, according to the ANOVA table (Supplementary Data B).

The visualisation of the data regarding the effects of the variables on final extraction concentration values is presented by the response surface of paired variables in Fig. 3. From the visual representation, maximum regions can be observed in similar values for both compounds in all combinations. Bigger curvatures on the surface response show an enhanced effect of the related variable on the concentrations, as can be observed for the variable X1 (first and second rows of Fig. 3). Flat or low curvatures are observed for the other two variables, showing smaller effects and confirming the data discussed in the last section. The parameters that represented the maximum responses according to the fitted models were calculated using Solver add-in from Excel software, resulting in the following values: X1=67.73%, X2=29.33% and X3=4.47 min, for mangiferin; X1=70.11%, X2=28.17% and X3=5 min, for hyperoside.

Fig. 3: Response surface methodology for the extraction of mangiferin (left) and hyperoside (right) from MPW. Black dots are the experimental BBD points.
Fig. 3:

Response surface methodology for the extraction of mangiferin (left) and hyperoside (right) from MPW. Black dots are the experimental BBD points.

Validation of the mathematical model

The variable levels selected for the model validation essay, listed in Table 5, can be visualised by the contour plots of the mangiferin and hyperoside concentrations, ruled by the variables X1 and X2 (ethanol/water ratio and sample/solvent ratio, respectively), as can be seen in Fig. 4. Five validation runs were performed using points in the maximum region for both compounds (70% ethanol/water, 30% sample/solvent, 5 min) and four other points in different regions around the one described (black dots in Fig. 4). Table 5 also shows the data acquired from the validation runs, comparing the experimental concentration with the concentration predicted by the mathematical model. Variation (v) data showed a good correlation between the mathematical model and the experimental runs in the maximum region, varying between −3.1 and 7.9% of variation. It is important to notice that the maximum values were found on the predicted maximum regions, with concentrations of 366.64 and 367.12 mg/kg DW for mangiferin, and 264.20 and 263.37 mg/kg DW for hyperoside, both in runs 1 and 2.

Table 5:

Validation parameters and variation.

Compound Run Variables (coded)
Experimental Concentration
Predicted concentration
Variation (v)
X1 (%) X2 (%) X3 (min) mg/kg DW mg/kg DW %
Mangiferin 1 70 (0.6) 30 (−0.1) 5 (1) 366.64 353.83 3.5
2 70 (0.6) 40 (0.4) 5 (1) 367.12 347.30 5.4
3 70 (0.6) 20 (−0.7) 5 (1) 363.77 349.80 3.8
4 50 (−0.2) 30 (−0.1) 5 (1) 335.86 327.04 2.6
5 80 (1) 30 (−0.1) 5 (1) 331.48 341.70 −3.1
Hyperoside 1 70 (0.6) 30 (−0.1) 5 (1) 264.20 248.56 5.9
2 70 (0.6) 40 (0.4) 5 (1) 263.37 242.51 7.9
3 70 (0.6) 20 (−0.7) 5 (1) 244.10 245.78 −0.7
4 50 (−0.2) 30 (−0.1) 5 (1) 215.65 222.13 −3.0
5 80 (1) 30 (−0.1) 5 (1) 250.36 242.73 3.0
Fig. 4: Contour plot for mangiferin (red) and hyperoside (blue) concentrations (values in mg/kg DW), according to variables X1 and X2. Black dots represent the selected validation points.
Fig. 4:

Contour plot for mangiferin (red) and hyperoside (blue) concentrations (values in mg/kg DW), according to variables X1 and X2. Black dots represent the selected validation points.


The green and sustainable extraction of bioactive compounds from FSC waste, and its optimisation, plays an important role on the development of integrated mango waste biorefineries, pushing the viability of such an agro-industrial platform. This paper showed that is possible to acquire optimum conditions for a fast extraction, which can be potentially scaled up to industrial levels, by using a set of chemometric tools. Thus, this approach can promote additional value to waste valorisation processes, offering a more efficient, cheaper and cleaner way to design, develop and apply them to many agro-industrial waste cases all over the world. Therefore, a statistically robust analytical method can be one of the triggers to create a plus green value within the food supply chain and develop enhanced and sustainable industrial practices through green chemistry and bio-circular economy [55], especially important to tackle the increasing global challenges and reach the UN SDGs.

Article note

A collection of invited papers based on presentations at the 8th IUPAC International Conference on Green Chemistry (ICGC-8), Bangkok, Thailand, 9–14 September 2018.

Award Identifier / Grant number: PIBIC 2019/UFSCar

Award Identifier / Grant number: 14/50827-1

Award Identifier / Grant number: 2017/25015-1

Award Identifier / Grant number: 2018/11409-0

Award Identifier / Grant number: 2019/08389-0

Funding statement: The authors would like to thank FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico, Funder Id:, Grant Number: PIBIC 2019/UFSCar) for the financial support (Funder Id:, FAPESP process numbers: 14/50827-1; 2017/25015-1; 2018/11409-0; 2019/08389-0).


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Published Online: 2020-03-09
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