1. Introduction
According to FAO, it is estimated that the world production of pineapple (
Ananas comosus (L.) Merrill) can grow 2.3% per year, up to 33 million tons in 2029 with Asian countries and America as the main producers. In recent years the pineapple market has grown significantly, reporting a clear increase in exports from 3 to 4M tons from 2016 to 2019 [
1]. This increase could be due to both its high nutritional value and the competitive sales prices to the public [
2]. Pineapple is one of the most appreciated tropical fruits in the world due to its nutritional and organoleptic properties. The pineapple cultivar, level of maturity, climatic conditions, and postharvest handling are factors that significantly impact the chemical and biochemical properties of pineapple [
3]. On a nutritional level, pineapple contains mainly carbohydrates and water, followed by dietary fiber, sugars, organic acids, vitamins (ascorbic acid, niacin, and thiamine), and minerals (mainly magnesium, manganese, and copper) Moreover, pineapple residues also contain significant quantities of antioxidant compounds which are known to have a beneficial effect on human health when fed. A recent study has proved that the ingestion of pineapple in rats lowered the hypercholesterolemia-induced cardiac lipid peroxidation risk and inflammation [
4].
On the other hand, volatile compounds present in the pineapple aroma are key substances that determine the final attributes of fresh and processed pineapples [
5]. Regarding the volatile profile, previous works reported esters as main components, contributing 50–80% of the total volatile compounds identified and being related to the quality of the flavor of different pineapple parts [
6]. Apart from esters, other volatile compounds present in pineapple are terpenes (2–30%), alcohols (16%), acids (7–14%), aldehydes (10–13%), lactones (2–13%), phenolic compounds (6–12%), and ketones (7–10%) [
7,
8].
This fruit can be consumed fresh, processed into juice, or packaged in different formats such as pineapple in its juice, slices, natural, etc. [
5]. In 2016, 1.45 million tons of pineapple were imported into Europe, of which 50% was treated [
1]. During the processing steps, around 60 wt.% of by-products (435,000 tons) such as the crown, peeled skin, and core were generated, which represented around EUR 360,000,000 of economic losses. Traditionally, trying to avoid a negative impact of residues on the environment, these pineapple by-products are usually used for animal feed, disposed of as waste in landfills, or burned for energy production [
9]. Nonetheless, the mentioned by-products constitute a potential source of high-added valuable substances, such as volatile compounds, antioxidants, organic acids, sugars, bromelain, and phenolic compounds [
5]. However, most of the research related to their revalorization has been focused on the reuse of proteolytic enzymes such as bromelain [
10], the extraction of pectin from the peel [
11], or the use of juice to produce vinegar [
12]. One additional promising possibility is the extraction of the antioxidant compounds from the pineapple by-products to use in the pharmaceutical industry as natural sources of bioactive substances. The potential source of antioxidants and alfa-glucosidase inhibitors in pineapple subproducts was recently verified by Azizan and coworkers in ethanolic extracts [
13].
To characterize the volatiles, present in pineapple by-products, Headspace Solid Phase Microextraction (SPME) coupled with Gas Chromatography–Mass Spectrometry (GC-MS) is a relatively inexpensive, easy-to-use analytical technique that is widely applied to volatile compound profile analysis. This technique has also been used to characterize the aroma of pineapples combining extraction and preconcentration in a single step [
6,
7,
8]. Some parameters, such as the extraction temperature and time, salinity of the medium, pH, amount of solvent, and the sample amount and/or volume, among others, directly influence the extraction process using HS-SPME [
14]. In this sense, previous studies have described the effect of the addition of a saline solution on the efficiency of the extraction of volatile aromatic compounds in pineapple at different concentration levels [
15]. Regarding the extraction temperature in pineapple samples, the reported values of this parameter in studies carried out are between 25–40 °C, while the most suitable extraction time is around 40 and 60 min, depending on the study [
6,
7,
8]. However, optimal operating conditions related to the extraction process of volatile compounds can be obtained using more complex experimental designs, such as the Doehlert matrix (DM), the central compound design (CCD), and three-level designs, such as the Box–Behnken (BBD) design. Focusing on the BBD-type experimental design, it has been used in the extraction of volatile compounds present in fruits such as raspberry [
16] or pineapple [
17], among others. However, no studies have been found in the literature in which this type of design has been used to optimize the extraction process of volatile compounds present in pineapple by-products, as is shown in this work.
Total Phenolic Content (TPC) can be used as a preliminary screening test of the antioxidant potential of a fruit subproduct. The profile of phenolic compounds and their concentration depends on a diversity of factors such as fruit variety, ripeness, agronomical growing conditions, and so on. Additionally, as the phenolic compounds and other antioxidants compounds must be extracted previously to their determination, the recovery from the products will depend on the solubility in the solvent employed [
18]. Considering all these variables it is not strange to find a great variability in results in the literature concerning TPC and antioxidant capacity. Nevertheless, this methodology is widely employed as it is based on colorimetric methods such as the Folin–Ciocalteu method that are very common and easy to use to compare sample processes under the same experimental conditions [
19].
Related to pineapple samples, extraction procedures have been carried out by using different solvents. The results showed that the polyphenol content of the extracts was higher when carrying out the extraction in methanol, followed using ethyl acetate and the aqueous extract [
20,
21]. Other studies have analyzed the content of polyphenols present in the total pineapple by-products [
22], while, in the specific case of pineapple peel, the value obtained was around 150 mg GAE 100 g
−1 of by-product in fresh weight [
21].
There are a great variety of antioxidant capacity determination methods in food samples such as 2,2-diphenyl-1-picrylhydrazyl (DPPH), the antioxidant capacity to reduce the ferric ion (FRAP), and the method that uses 2,2’-azinobis (3-ethylbenzothiazoline-6-sulfonate) (ABTS). Studies carried out on pineapple by-products have been obtained for each 0.1 mg mL
−1 of extract analyzed, an inhibition between 20–70% using the DPPH method [
21,
22]. On the other hand, by using the FRAP methodology, freshly cut pineapple without treatment presented a value of 7.91 mmol kg
−1 while the samples treated with chitosan and procydianine showed slightly higher FRAP values of 8.49 and 8.97 mmol kg
−1, respectively, due to the production of antioxidant coatings on the surface of the sample [
20,
21]. Finally, values between 63.66–64.02 mM TROLOX g
−1 of fresh weight were obtained after the application of the ABTS method for the analysis of different pineapple samples treated with different ultrasound power [
23].
Based on this background, the aim of this work is the extraction and characterization of the volatile compounds present in two different pineapple by-products (core and peel) and the subsequent evaluation of their antioxidant capacity. For this, the evaluation of the antioxidant content in the two pineapple wastes has been performed employing different methods, analysis of the total phenolic content (TPC) in addition to analysis of the antioxidant capacity by using the antioxidant capacity to reduce the ferric ion (FRAP), the 2,2-diphenyl-1-picrylhydrazyl (DPPH) procedure and the method that uses 2,2’-azinobis (3-ethylbenzothiazoline-6-sulfonate) (ABTS). Additionally, the volatile profile analysis of both by-products has been carried out through the headspace solid-phase microextraction technique coupled to gas chromatography with a mass spectrometry detector (HS-SPME-GC-MS). The optimization of the extraction conditions of volatile compounds has been validated using a Box–Behnken (BBD) experimental design. In addition, a quantitative analysis has been carried out to determine the content of ethyl acetate and isopentyl acetate, as characteristic compounds of pineapple, in both by-products.
2. Materials and Methods
2.1. Reagents
Methanol (HPLC grade), n-hexane (99%, GC grade), sodium carbonate, sodium chloride, glacial acetic acid, ferric chloride, and potassium persulphate of analytical grade were obtained from Panreac (Barcelona, Spain). Gallic acid monohydrate ACS > 99% (CAS 5995-86-8), phenolic reagent of Folin and Ciocalteu, (±)-6-hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid approx. 90% (Trolox) (CAS 238813), 2,2-diphenyl-1-picrylhydrazyl (DPPH) (CAS 1898-66-4), 2,4,6-tris(2-pyridyl)-s-triazine ACS > 99% (TPTZ) (CAS 3682-35-7), 2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt ACS > 98% (ABTS) (CAS 30931-67-0), ethyl acetate, isopentyl acetate and 2-methyl-1-pentanol were purchased from Sigma-Aldrich Inc. (St. Louis, MO, USA).
2.2. Pineapple Samples
Two by-products of pineapple samples, the core (Core S1), and the peel (Peel S1), from Anecoop S. Coop (Murcia, Spain) and two more core (Core S2, Core S3) and peel (Peel S2, Peel S3) samples from two different supermarkets were included in the study (
Figure 1a). After receiving the samples, they were immediately vacuum-packed and frozen until their analysis. Before the analysis, samples were firstly crushed with a domestic blender (
Figure 1b) for 20 s to homogenize them and reduce their size (
Figure 1c).
The crushed samples were used directly for the analysis by HS-SPME-GC-MS. For the study of the antioxidant capacity, it was necessary to extract them in triplicate using a mixture of methanol: deionized water: HCl 1% (70:28:2) according to a methodology previously used by Valdés et al., 2020 [
16]. The extracts were stored in the fridge until the analysis was complete.
2.3. Antioxidant Capacity Assays In Vitro
Once extracted, samples were subjected to a variety of tests to determine the antioxidant capacity. The methods applied were Folin and Ciocalteu reducing capacity (FRC), the ferric reducing antioxidant power (FRAP), radical scavenging activity by DPPH assay and ABTS cation radical all based on the electron transfer mechanism. The ABTS+ discoloration assay was employed to obtain the Trolox equivalent antioxidant capacity (TEAC). The TEAC assay was previously carried out by Pellegrini et al., 1999 and it was slightly amended for a previous work [
24,
25]. Then, 200 µL of the extracts were combined with 3 mL of the diluted ABTS solution in a polystyrene disposable cuvette with a lid and then after that it was homogenized in a vortex for 5 s approximately. The reaction mixture was incubated at 25 ± 2 °C for 30 min and afterwards the absorbance was measured at 734 nm.
The employed FRAP assay was based on the methodology developed previously by Benzie and Strain (1996) [
26] but introducing slight modifications that were optimized in a previous work [
25]. An extract volume of 200 µL was mixed with 3 mL of FRAP reagent in a polystyrene disposable cuvette and incubated for 40 min sheltered from the light at 25 ± 2 °C. Measurements were conducted with a spectrophotometer at 593 nm.
The DPPH methodology used was adapted from a previous study by Beltran et al., 2019 [
25]. An aliquot of 200 µL of the pineapple peel or core extract was added to 2.5 mL of 24 mg a methanol solution of DPPH in a polystyrene cuvette and the kinetics of the reaction was followed monitoring the absorbance spectrophotometrically at 517 nm until the signal reached a stable value. For these samples a stable reaction time of 60 min was selected. Thereafter, all samples were measured in the spectrophotometer at the same wavelength after 60 min of incubation in the dark at ambient temperature. A standard curve was obtained similar to the one obtained in the ABTS, FRAP assays. The results of FRAP, DPPH, and ABTS were expressed as TROLOX micromoles equivalents (TE) per 100 g of pineapple fresh weight (FW).
The FCR assay was carried out based on previous work with some modifications [
27]. 300 µL of the methanolic extract was mixed with 100 µL of Folin and Ciocalteu phenol reagent (2 N) and 500 µL of a 7% sodium carbonate solution. The mixture was homogenized with a vortex stirrer for 10 s followed by an incubation period at room temperature for 90 min. Afterward, 5 mL of distilled water was added to each tube and the absorbance of each sample or standard solution was measured at 760 nm in a spectrophotometer using deionized water as blank. Results were expressed as mg gallic acid equivalents (GAE) per 100 g of 100 g of pineapple FW. All antioxidant results obtained were presented in the form of an average of three different extracts for each sample.
2.4. Optimisation of HS-SPME Procedure
To optimize the extraction of volatile compounds from pineapple by-products by the HS-SPME methodology, a Box–Behnken design (BBD) was used with three factors on three levels, and each independent variable was coded between +1, 0, and −1, corresponding to a low, medium, and high level, respectively (
Table 1). The experiment selected ranges for the independent variables were extraction temperature (30–70 °C), extraction time (10–60 min), and NaCl concentration (0–4 M). In this work, the proposed BBD consisted of 17 experiments carried out in randomized order, including five central points. The core pineapple sample was selected for the optimization of HS-SPME procedure. The variables were evaluated in a selected ranges on the basis of results obtained in previous analysis and the previous references found [
7,
8].
The relationship between the response (Y) and the parameters of independent variables was used to monitor the optimization process. The response (Y) was related to the independent variables (X
1, X
2, …, X
k) by using a second-order polynomial model, as can be seen in Equation (1) [
28].
where Y is the predicted response, X indicates the variables of the process, i and j are design variables, β
0 is a constant, β
i is the linear coefficient, β
ii is the quadratic coefficient, and β
ij is the interaction coefficient of variables i and j.
The response obtained from the BBD design was evaluated based on the sum of areas obtained for 11 selected volatile compounds: 4 esters (hexanoic acid, methyl ester; 3-(methylthio) propanoic acid methyl ester; 1-butanol-3-methyl acetate; ethyl acetate), 3 terpenes (limonene; α-muurolene; α-copaene), 3 aldehydes (nonanal; decanal; dodecanal) and 1 alcohol (phenylethyl alcohol). All of them have been identified as common and characteristic compounds of the pineapple core in all runs [
29].
The satisfactoriness of the fitted model was evaluated by the use of the lack of fit value, the F test, and the coefficient of determination (R
2) obtained from the analysis of variance [
30]. Statistical significance of model parameters was determined at α = 0.05. Additional confirmation experiments (in triplicate) were conducted under the optimal conditions to verify the model validation.
2.5. HS-SPME-GC-MS Procedure
Next, 1.0 ± 0.1 g of the sample was weighed into a glass vial (20 mL). Then, 5 µL of internal standard 2-methyl-1-pentanol (560 mg Kg
−1) was added into the vial, followed by the addition of 2 mL of distilled water (with or without NaCl addition). A polytetrafluoroethylene (PTFE) stirring rod was added to ensure homogeneous stirring of the sample. The fiber used for the extraction of the volatiles was a DVB/CAR/PDMS (divinylbenzene/carboxen/polydimethylsiloxane) 50/30 mm, StableFlex, 1 cm long, mounted to an SPME manual holder assembly (Supelco, Bellefonte, PA, USA) and the procedure was carried out by using the auto-sampler of the equipment. This fiber has been previously used to extract volatile compounds from pineapple samples such as wine [
31], juices [
32], and pulps from tropical fruits [
33].
After the extraction process of volatile compounds, the fiber was immediately desorbed in the spitless mode for 10 min into the injection port of the GC-MS equipment. The equipment used in the analysis was a gas chromatograph (Agilent 7890B) coupled to a quadrupole mass spectrometer (Agilent 5977B). A Gerstel Multipurpose Sampler (MPS) robot was used as the sample introduction system to the chromatograph. The chromatographic column used was an Agilent DB624. The sample was subjected to the following temperature program using helium as carrier gas with a flow rate of 1 mL min−1: initial temperature of 40 °C, maintained for 2 min and then an increase in temperature at a rate of 5 °C min−1 up to 250 °C, where it was maintained for 10 min. The energy of the ionization source used was 70 eV. The temperature values of the ion source and the transfer line were 230 and 150 °C, respectively. The mass detector was operated in scan mode at a mass-to-charge ratio range (m/z) of 50–230. In order to verify the absence of contaminants, blank runs were carried out between samples
To identify unknown compounds, the comparison of their mass spectrum data (full scan mode (m/z 30–550)) with the ones found in the NIST library was carried out. A % of similarity equal or higher than 80% was fixed. In this study, two main pineapple volatile markers were selected: ethyl acetate and isopentyl acetate. Both were quantified in all the studied samples using calibration curves at six concentration levels prepared in deionized water. All determinations were carried out in triplicate.
2.6. Statistical Analysis
The study of the fitted model was carried out by using StatGraphics Centurion XV software (Statistical Graphics Corporation, Rockville, MD, USA). SPSS commercial software, ver. 15.0 (Chicago, IL, USA), was used for ANOVA and Tukey’s test at a p ≤ 0.05 significance level to obtain differences between values.