Abstract
Gas chromatography ion mobility spectrometry (GC-IMS) was used to detect the volatile organic compounds (VOCs) of Zheng5–5 sweet cherry fruits cultivar under three cultivation patterns [arched cover (PN), umbrella cover (SX), and open field (LD)]. VOCs were analyzed and compared using three-dimensional and two-dimensional top view visualization, fingerprint analysis, and principal component analysis (PCA). A total of 24 VOCs (including monomers and dimers) were detected in PN, SX, and LD, and 19 of them were finally identified, mainly alcohols, aldehydes, acids, esters, and ketones. The VOCs of PN, SX, and LD were similar but significantly different in content. The three compounds with the highest relative content were 2-hexen-1-olD, ethanol, and hexanalD, with ranges of 13.71% (LD) to 22.31% (PN), 13.02% (SX) to 21.27% (LD), and 8.22% (LD) to 16.66% (PN), respectively. Esters are the main components that form the sweet cherry fruit aroma, with a relative content of LD>PN>SX. According to the PCA, fruit samples of PN, SX, and LD can be clearly distinguished, indicating significant differences in VOCs under different cultivation modes. The GC-IMS visual plots of PN, SX, and LD agreed with the PCA results, and their combination was suitable for characterizing the VOCs of sweet cherry fruits under different cultivation patterns. This study can provide a reference for evaluating the flavor characteristics of sweet cherry fruits with different cultivation patterns.
Flavor substances are an important part of the metabolism of organic matter in fruit (Gao et al. 2022). Because of their important effects on the aroma, taste, and quality of fruits, they have attracted extensive attention from scholars in the fields of agriculture and biology recently (Ahiakpa et al. 2021; Wang et al. 2020a). Aroma is one of the most important fruit characteristics that determines the consumer’s acceptance of the product (El Hadi et al. 2013). It is the result of the combined action of compounds such as esters, alcohols, aldehydes, organic acids, ketones, and terpenes (Hayaloglu and Demir 2015). Extraction/separation techniques of aroma components include simultaneous distillation extraction, supercritical fluid extraction, microwave-assisted hydrodistillation, and headspace solid-phase microextraction (HS-SPME) (Malaman et al. 2011; Mehdi and Majid 2016; Ning et al. 2011). With the rapid development of analytical instruments and sample preparation technology, research of fruit aroma has gradually deepened. SPME coupled with gas chromatography–mass spectrometry (GC-MS) is a simple, efficient, and convenient routine analysis method for identifying fruit aromatic components (Hung et al. 2014). Many studies have qualitatively and quantitatively assessed the aroma components of a large number of common fruits and vegetables through analyses via HS-SPME with GC-MS (HS-SPME–GC-MS) (Hou et al. 2020; Rajkumar et al. 2020; Tripodi et al. 2020). Zhang et al. (2022) found that there are quality differences between different species of cherries, and differences in pulp texture characteristics, color, and aroma components are important indicators that distinguish different varieties of cherry fruits. Legua et al. (2017) studied the bioactive and volatile compounds of sweet cherry (Prunus avium L.) fruit. However, there is no relevant research of the effects of different cultivation patterns on aromatic volatiles of sweet cherry fruits. Traditional HS-SPME–GC-MS has certain requirements for the volatilization of the detected aroma substances (Li et al. 2021). However, the concentration of volatile odorants in fruits and vegetables is usually low, and the content of most flavor substances is at the ppb level (Vautz et al. 2014). As a result, the trace aroma components of many fruits and vegetables cannot be detected. In addition, current detection technologies such as GC-MS require solid-phase microextraction (HS) for sample pretreatment. The flavor components of heat-sensitive samples will change after heating, and the results detected by the instrument are not the original smell of the samples (Guo et al. 2018). The FlavourSpec® Flavor Analyzer combines the high resolution of GC with the high sensitivity of ion mobility spectrometry (IMS) without sample preparation and directly injects and analyzes the headspace components of solid or liquid samples with detection limits up to the ppb level (Maria et al. 2019). This instrument enables qualitative and quantitative analyses of single compounds/markers, as well as fast and result-oriented analyses of volatile organic compounds (VOCs) in samples, thus allowing data visualization and visualization of flavor differences. GC-IMS is currently widely used for flavor evaluations during environmental odor monitoring (Gao et al. 2021), human respiratory diseases (Allers et al. 2016), the preparation of green tea, coffee, liquor, and other beverages (Lolli et al. 2020; Wang et al. 2020b), and VOC detection in biomass materials (Giosuè et al. 2016), fruits, and vegetables (Leng et al. 2021); however, there is no report of the identification and analysis of sweet cherry fruit VOCs with different cultivation patterns. Sweet cherry is a member of the Rosaceae family and a fruit crop with growing agronomic and economic importance. Aroma is one of the fruit characteristics that attracts the greatest attention and is usually composed of volatile flavor compounds that determine consumer acceptance of the product. Volatiles can be detected and quantified by GC-IMS. From a food flavor perspective, not all instrument-detected VOCs are equally important, and GC-IMS has important practical significance for the in-depth understanding of VOCs during the cultivation, processing, and storage of fruits and vegetables, as well as the changes in their flavor during extraction and separation.
Materials and Methods
Fruit sample preparation.
The fruit of Zheng5–5 (Prunus avium L.) sweet cherry variety with high-yield was collected from the fruit tree test base of Baiyi Town, Wudang District, Guiyang City, Guizhou Academy of Agricultural Sciences, Institute of Fruit Tree Science (27°03′3.89″N, 106°25′47.23″E), in May 2021. The two types of rain shelters are permanently installed, four-span, arched, multispan rain shelters (completed in Apr 2014) and umbrellas covered with colorless polyvinyl chloride (PVC) antiaging plastic films. The length, width, and height of the vaulted shed are 30 m, 8 m, and 5.3 m (aboveground), respectively. The radius and height of the umbrellas are 1.9 m and 3 m, respectively (aboveground), and one umbrella covers one tree. The rootstock is Gisela 6, the plant-row spacing is 2.0 m × 4.0 m, and the tree shape is spindle-shaped. The fruit samples were picked separately from sweet cherry trees with three cultivation patterns [arched cover (PN), umbrella cover (SX), and open field (LD)]. During the commercial harvest period, according to the subjective evaluation of fruit color, 27 commercial, mature, and healthy fruits were picked from PN, SX, and LD, immediately placed in an ice box, cooled, and transported to the laboratory for the determination of their VOCs. The quality parameter information of PN, SX, and LD are shown in Table 1. The single fruit weights of PN, SX, and LD were 8.09, 7.96, and 7.28 g, and the soluble solid contents were 14.87%, 14.53%, and 12.60%, respectively. The soluble sugar contents of PN, SX, and LD were 106.24, 103.52, and 96.89 mg⋅g−1, and the titratable acidity contents were 0.32%, 0.31%, and 0.35%, respectively.
Quality information of sweet cherry fruits with three cultivation modes.
Instruments and conditions.
A FlavourSpec® Flavor Analyzer (G.A.S. Company, Dortmund, Germany) and autosampler (CTC Analytics AG, Zwingen, Switzerland) were used. The overall process of this study is shown in Fig. 1. This process can quickly detect trace VOCs in samples without any special sample preparation. The GC conditions were as follows: column temperature, 60 °C; running time, 30 min; and carrier gas, high-purity N2. The carrier gas flow rate was 2 mL⋅min−1 for 0 to 2 min, linearly increased to 10 mL⋅min−1 from 2 to 10 min, linearly increased to 100 mL⋅min−1 from 10 to 20 min, and linearly increased to 150 mL⋅min−1 from 20 to 30 min. The positive ion mode was used for detection. High-purity N2 was used as the drift gas. The flow rate was 150 mL⋅min−1. The specific analysis parameters are shown in Table 2.
Overall flow chart of the gas chromatography ion mobility spectrometry (GC-IMS) method.
Citation: HortScience 58, 6; 10.21273/HORTSCI17171-23
Instrument analysis parameters.
Processing method.
The PN, SX, and LD samples were mashed, and 5-g samples were weighed and placed into three extraction bottles that were quickly sealed after leaving a space of ∼2 cm in the upper part. A 500-μL headspace sample was collected and injected into the GC-IMS instrument for analysis. All analyses were performed in triplicate.
Statistical analyses.
The statistical analysis was performed using SPSS Statistics version 21.0 software (Chicago, IL, USA). Duncan’s multiple comparisons test (P < 0.05) was used to assess statistically significant differences between the means of three replicates. The GC-IMS analysis software includes three plug-ins, such as VOCal, that analyze samples from different aspects. The VOCal plug-in is used to view analytical spectra and qualitative and quantitative data. The National Institute of Standards and Technology database and IMS database built into the application software can perform qualitative analyses of substances. The Dynamic principal component analysis (PCA) plug-in performs clustering and similarity analyses of samples. The Gallery Plot plug-in compares the fingerprints of VOCs between different samples.
Results and Discussion
VOC differences in sweet cherry fruits with three cultivation patterns.
Figure 2 is a three-dimensional (3D) spectrum of the collected samples. The ‘Reporter’ plug-in program in the multivariate data analysis software LAV was used to further analyze the samples, and a 3D comparison chart of VOCs of sweet cherry fruit samples of PN, SX, and LD was generated. The VOCs are displayed in the form of fingerprint spectra, and the flavor analysis of the sweet cherries was visualized through a 3D spectrum that showed the differences between samples (Cavanna et al. 2019). Figure 2 shows that GC-IMS can well-separate the volatile components of sweet cherry fruit, and the contents of VOCs in the sweet cherry fruit samples of PN, SX, and LD were different.
Three-dimensional (3D) spectra of gas chromatography ion mobility spectrometry (GC-IMS) of sweet cherry fruits with different cultivation patterns: (A) arched cover; (B) open field; and (C) umbrella cover.
Citation: HortScience 58, 6; 10.21273/HORTSCI17171-23
Figure 3 shows the two-dimensional GC-IMS spectra of sweet cherry fruits with the three cultivation patterns. Because two-dimensional spectra are more intuitive and easy to read than 3D spectra, they can accurately provide comprehensive images of the informative characteristics and intensities of VOCs, which are very useful for in-depth statistical analyses. The red vertical line on the left side of the abscissa in Fig. 3A–C is the reactive ion peak (normalized). According to the presence or absence of color points, the depth of the color and the size of the area, composition, and concentration differences between the three samples can be readily visualized (Chen et al. 2018). Figure 3 shows that the VOCs of the sweet cherry fruit samples with the three cultivation patterns can be well-separated and detected by GC-IMS technology. The VOCs in the red area are more abundant in SX samples, and the VOCs in the yellow area are relatively high in LD.
Ion migration spectra of gas chromatography ion mobility spectrometry (GC-IMS) of sweet cherry fruits with different cultivation patterns: (A) arched cover; (B) open field; and (C) umbrella cover. The ordinate represents the retention time of GC, and the abscissa represents the ion drift time. The dots represent one type of volatile organic compound (VOC). White indicates lower density. Red indicates higher density. Darker color indicates greater density.
Citation: HortScience 58, 6; 10.21273/HORTSCI17171-23
To observe this difference more clearly, the difference contrast mode was used, as shown in Fig. 4. Furthermore, Fig. 4A–B show the spectra of sweet cherry fruit samples of PN and LD, respectively, as a reference, and the spectra of the other two samples were deducted for reference. If two VOCs are consistent, then the deducted background is white; however, red indicates that the concentration of the substance is higher than that of the reference, and blue indicates that the concentration of the substance is lower than that of the reference. Using the difference map, it is easy to see the differences in VOCs of sweet cherries grown in different rain shelter cultivation patterns, among which the VOCs of sweet cherries of LD and PN are relatively similar.
Ion migration spectra of gas chromatography ion mobility spectrometry (GC-IMS) of sweet cherry fruits with different cultivation patterns and its differences: (A) the arched-cover sample spectra as a reference; (B) the open-field sample spectra as a reference.
Citation: HortScience 58, 6; 10.21273/HORTSCI17171-23
VOC odor fingerprint spectra of sweet cherry fruits with three cultivation patterns.
To comprehensively and intuitively analyze the differences in the composition of VOCs of the three samples of PN, SX, and LD, all VOCs in the spectra were selected using the Gallery Plot plug-in of the GC-IMS software to form a fingerprint spectrum. Because the chemically active components contained in the fruit are very complex, the fingerprint spectrum plays an important role in the identification of VOCs of sweet cherry fruits and can identify and evaluate the quality of the fruit flavor. In Fig. 5, the complete VOC information of the sweet cherry fruits grown with three cultivation patterns and the differences between the samples can be seen intuitively. The VOC species of the sweet cherry fruit samples of SX are relatively rich, and their content is significantly higher than that of the other two kinds of sweet cherry fruit samples. For example, benzaldehydeD only exists in SX, whereas the relative contents of benzaldehyde M, 3-pentanoneD, 2-butanone, and 3-methylbutanalD of the sweet cherries are SX>LD>PN. Hexanal and 2-hexen-1-ol were detected at higher concentrations in PN and SX. The highest relative contents of benzaldehyde, 3-methylbutanal, 2-methylpropanal, butanal, ethyl acetate, 2-butanone, and 3-pentanone were in SX.
The fingerprint of volatile organic compounds (VOCs) of sweet cherry fruits with different cultivation patterns [arched cover (PN), open field (LD), umbrella cover (SX)]. Each column represents the signal peak of the same VOCs of different samples. Each row represents all signal peaks selected in a sample. The numbers on the abscissa represent undetermined substances in the migration spectrum library and are replaced by numbers.
Citation: HortScience 58, 6; 10.21273/HORTSCI17171-23
Types and contents of VOCs of sweet cherry fruits with three cultivation patterns.
GC-IMS was used to analyze the VOCs of sweet cherry fruits with three cultivation patterns (PN, SX, and LD). As shown in Table 3, a total of 24 peaks to be analyzed were detected from the three samples. Using the built-in National Institute of Standards and Technology and IMS databases of the instrument, a total of 19 VOCs (including monomers and dimers) were identified. The three compounds with the highest relative contents were 2-hexen-1-olD, ethanol, and hexanalD, with ranges of 13.71% (LD) to 22.31% (PN), 13.02% (SX) to 21.27% (LD), and 8.22% (LD) to 16.66% (PN), respectively. The PN sample included eight types of aldehydes (relative content, 33.80%), three types of alcohols (47.03%), three types of ketones (1.69%), three types of esters (2.59%), and one type of acid (2.85%). The SX sample included nine aldehydes (41.08%), three alcohols (38.27%), three ketones (4.49%), three esters (2.26%), and one acid (2.17%). The LD sample included eight aldehydes (35.91%), three alcohols (45.28%), three ketones (2.98%), three esters (2.74%), and one acid (2.54%). The VOCs of sweet cherry fruits include monomers and dimers. The chemical formula and Chemical Abstracts Service (CAS) number of the identified dimers were the same; only the morphology was different. Five other substances were not identified. The VOCs in Table 3 and Fig. 5 correspond to each other. Except for benzaldehyde D, which was found only in the SX sample, all other substances were distributed in the sweet cherries grown with the three cultivation patterns, but the contents of some VOCs were significantly different. All identified compounds have been reported for fresh sweet cherries (Goncalves et al. 2022). The types of volatile components of PN, SX, and LD are approximately the same, but the relative content of most components is significantly different (P < 0.05). This result may be because of differences in cultivation types, similar to the results of Selli et al. (2012). The VOCs of sweet cherries is affected by cultivar, harvest date, cultivation conditions, and analytical methods (El Hadi et al. 2013; Papapetros et al. 2019). As far as we know, this is the first report of GC-IMS to analyze the VOCs of sweet cherries with different cultivation modes.
Identification of volatile compounds of sweet cherry fruits with different cultivation modes based on gas chromatography ion mobility spectrometry.
The total contents of alcohols and aldehydes in sweet cherries with different cultivation modes were highest and are the main VOCs of Zheng5–5 sweet cherry cultivar. Among them, the contents of hexanal, benzaldehyde, 3-methylbutanal, ethanol, and 2-hexen-1-ol were higher than those of other compounds, with ranges of 16.18% (LD) to 24.77% (PN), 0.26% (PN) to 3.32% (SX), 5.25% (PN) to 14.85% (SX), 13.02% (SX) to 21.27% (LD), and 24.01% (LD) to 32.08% (PN), respectively. Hexanal, benzaldehyde, 3-methylbutanal, and octanol in sweet cherry fruits with different cultivation modes were the main components of aldehyde compounds, accounting for 91.45% (LD) to 95.74% (PN). The contents of hexanal in PN and SX were 24.77% and 19.40%, respectively, higher than that of LD (16.18%). The contents of benzaldehyde and 3-methylbutal are highest in SX but lowest in PN. The content of octanal is the highest in PN, followed by LD and SX. The two main alcohol compounds detected in the sweet cherries with three cultivation modes were ethanol and 2-hexen-1-ol. In PN and SX, the ethanol content is lower than that in LD, whereas the content of 2-Hexen-1-ol is higher than that in LD. Among them, hexanal is a natural antibacterial molecule with a fresh, fruity aroma (Musetti and Fava 2012), whereas benzaldehyde has an aroma similar to bitter almonds (Sánchez-Pérez et al. 2010). Furthermore, 2-hexen-1-ol had a strong fruit smell that can be used to prepare apple and other fruit-type essences. It is found not only in sweet cherries but also in tea leaves (Aprea et al. 2015; Jaeger et al. 2012). With the increasing drying time, the content of 2-hexen-1-ol in tea increased and then decreased with increasing fermentation (Xiao et al. 2018).
After fruit is ripe, it will produce various aromatic substances, mainly ester compounds produced by the esterification of alcohols and fatty acids (Barroso et al. 2016; Bender et al. 2000). These aroma substances provide the unique aroma quality of sweet cherry fruits and have important scientific research value. Esters are the main components that constitute fruit aroma. Sweet cherry fruits contains ethyl acetate, propyl acetate, and other aromatic esters (Xu et al. 2019). Ethyl acetate has a fruity aroma, can be used as a food flavoring, and is widely used for the preparation of sweet cherry, peach, apricot, and other fruit flavors, as well as the preparation of brandy and wine flavors (Niu et al. 2019; Zhao et al. 2021). n-Propyl acetate is naturally present in strawberries, bananas, tomatoes, and sweet cherries, and it has a special fruity aroma. The relative content of esters in sweet cherry fruits with three cultivation modes was as follows: LD>PN>SX.
Principal component analysis comparison of VOCs of sweet cherry fruits with three cultivation patterns.
Using the PCA method to reduce the dimensionality of the processed data, the similarity between samples and the difference in VOCs can be visually compared (Garrido-Delgado et al. 2015). Each sample was well-separated without overlapping, which proved that GC-IMS can effectively distinguish VOCs in sweet cherries grown in the three cultivation patterns (Fig. 6). In Fig. 6, the contributions of PC1 and PC2 explain 90% of the total variation. SX samples are on the right side of the graph, PN samples are on the bottom left of the graph, LD samples are on the top left of the graph, and PN and LD are relatively close on the graph, indicating that their VOC species have high similarity. PN, LD, and SX can be clearly distinguished, which proves that their VOCs have obvious differences. It can also be seen from Table 4 that the distance between different samples is significantly larger than the distance between parallel samples. According to the PCA (Fig. 6), the nearest neighbor graph (Fig. 7), and the Euclidean distance (Table 4) (Sun et al. 2019), the VOCs of the LD and PN samples were more similar than those of SX. In general, PCA was an effective method of distinguishing sweet cherries with different cultivation modes based on their volatile profiles, and characteristic VOCs of sweet cherries with different cultivation modes could be characterized as well.
Principal component analysis (PCA) graphs of sweet cherry fruits with different cultivation patterns.
Citation: HortScience 58, 6; 10.21273/HORTSCI17171-23
The nearest neighbor graph of sweet cherry fruits with different cultivation patterns [arched-cover (PN), open-field (LD), umbrella-cover (SX)].
Citation: HortScience 58, 6; 10.21273/HORTSCI17171-23
The Euclidean distance among samples corresponding to the nearest neighbor.
Conclusions
Using the VOCs of sweet cherries with three cultivation patterns as the research object, odor fingerprints were collected by GC-IMS, and the PCA was used to obtain the odor fingerprints. The differences in the VOCs of different samples were analyzed, and the differences in the types and contents of VOCs of different samples were finally displayed in a visual form. A total of 19 organic compounds (including monomers and dimers) were identified, mainly alcohols, aldehydes, acids, esters, and ketones. Except for benzaldehydeD, which was found only in the fruits from sweet cherry with SX cultivation, all other substances were distributed in the three cultivated sweet cherry samples; however, the contents of some substances were significantly different. The relative content of esters in the LD sweet cherry fruit was the highest, and the aroma was the most intense. In addition, GC-IMS combined with PCA effectively distinguished sweet cherries with different cultivation modes based on their volatile profiles, and characteristic VOCs of sweet cherries with different cultivation modes could be characterized as well.
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