Introduction

Rice (Oryza sativa L) is the staple food for approximately 3.5 billion people worldwide with an estimated production of 480 million tons annually1. Rice provides up to 50% of the dietarycaloric supply and a substantial part of the protein intake for about 520 million people living in poverty in Asia2. The market value of rice is primarily determined by the grain quality, which in turn depends on the genetic background, agronomic management, geographic factors and postharvest factors3,4. Although the grain quality and thus the price for rice of different geographic origins could differ vastly, their appearance may be very alike. Thus, deliberate mislabeling and adulteration represent a serious issue, which not only threatens the credit of the traders, but also infringes the right of consumers5. To prevent such actions, a high-throughput, sensitive and precise method is urgently needed to discriminate rice of different geographic origins. The key to determining the geographic origin was to identify specific biomarkers for a specific rice variety. Previous studies had used a wide range of properties such as stable isotope, mineral element content that are associated with geographic features to track the origin of rice6,7. Notably, multiple parameters can be used together as they may provide complementary information. For instance, the isotope composition of δ13C, δ15N, δ2H, δ18O had been employed in junction with the multi-elemental concentrations analysis to determine the origin of different rice varieties8. For a more comprehensive comparison of the components among various rice cultivars, spectroscopy approaches such as near-infrared reflectance spectroscopy (NIR), nuclear magnetic resonance spectroscopy (NMR), Raman spectroscopy (RS) had also been used9,10,11. These methods requires large amount of input for data collection and has no direct relationship with the quality of rice.

Volatile organic compounds (VOCs) are the main source of aroma in rice. Although difficult to describe by words, aroma differ greatly among varieties due to a different composition in VOCs. Indeed, a previous study has reported the geographical discrimination of rice based on VOCs12. Headspace solid phase microextraction (HS-SPME)was applied in volatile substance concentrate to improve the analytes placed on column13. Due to its simplicity, high sensitivity and reproducibility, SPME is particularly suitable for the analysis of volatiles in food14,15. Coupled with GC–MS, the aroma compounds can be identified precisely.

Different rice varieties have different aromatic characteristics and volatiles of rice can be considered to be biomarker candidates of geographical varieties determination. Rice considered to be has high quality because of the attractive aroma and good taste16. So, to characterize the aroma profile of fragrant rice is meaningful not only on adulteration but also good for breeding. Wuchang rice, as its name suggests, grows in Wuchang county in Heilongjiang province of northeast China17. It is known for its intense aroma and enlisted as a National Geographical Indication Product of China18. Wuyoudao 4 is the dominant variety in this area since 1990s. Despite big differences in composition and the grain quality between WuChang rice and other varieties, it is still challenging to distinguish them due to a lack of robust and sensitive method19,20,21.

In this study, we aimed to address this challenge by profiling Wuchang rice VOCs with HS-SPME extraction and GC–MS detection. First, an untargeted metabolomic approach was used to profile the VOCs in both WuChang and non-WuChang rice varieties. Subsequent multivariate analysis showed an unambiguous classification of the samples according to their geographic origins. In addition, our data led to the identification of eight VOCs that can be used as biomarkers in variety determination. The GCMS approach described is readily applicable to determine the geographic origin of other premium rice.

Materials and methods

Material

Twenty rice samples grown in 2018 were purchased from either Wuchang or other regions (see Table 1 for details). It was confirmed that all methods were performed in accordance with the relevant legislation. For each sample group, three biological replicates were obtained. All samples were stored at – 80 °C until analysis. Headspace vials (20 ml in volume) were purchased from Agilent, each with a silver aluminum cap and a polytetrafluoroethylene (PTFE)/silicone rubber septum. Supplies for solid phase microextraction (SPME) including a manual injection handle and a 75 μm carboxen/polydimethylsiloxane (CAR/PDMS) extraction head were purchased from SUPELCO (St. Louis, USA)22.

Table 1 The origins of the 20 rice samples.
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Extraction of volatiles by HS-SPME

Four grams of rice grain were stored in a 20 mL headspace vial. The headspace bottle was heated at 80 °C for 30 min in a water bath. Subsequently, a SPME fiber was inserted into the headspace portion of the vial and then incubated for 60 min to absorb VOCs from the rice grain23.

GC–MS analysis

GC–MS analysis was performed using a TRACE GC ULTRA (Thermo) coupled with a SQ QUANTUM XLS (Thermo). The SPME fiber was inserted into the inlet of the GC–MS with the fiber head pushed out, and VOCs were desorbed at 250 °C for 5 min. Helium was used as the carrier gas with a flow rate of 1 mL/min and a spitless injection was used. A DB-5 capillary column (30 m × 0.25 mm × 0.25 μm) was used for separation with the following temperature gradient: an initial temperature of 40 °C for 3 min; a linear increase to 100 °C at 5 °C/min and hold for 3 min; and ramping to 250 °C at 10 °C/min and hold for 4 min. Eluted compounds are ionized by electron ionization with an electron energy of 70 eV and an ion source temperature of 230 °C. Full MS scans were performed at the mass range of 40–300 m/z24.

Chromatographic analyses

The obtained MS spectra were matched to the National Institute of Standards and Technology reference spectra (NIST 08 and Wiley 7). The retention index (RI) of putative compounds is further compared to previous reports (Table S2). The normalized peak area was used for calculating the compound concentration. Data from three biological replicates were reported (Table S3).

Clustering analysis

Prior to statistical analysis, the raw MS intensities were first subjected to log transformation and Pareto scaling. Feature selection was performed using standard methods such as fold change (FC), volcano plot, t-test and empirical Bayesian analysis of microarray (EBAM). Features with a relative standard deviations (RSD) > 30% were removed from further analysis. A feature was considered to be differentially expressed with the following criteria: (1) FC < 0.8 or FC > 1.2; (2) p-value < 0.05) and (3) false discovery rate (FDR) < 0.1.

Euclidean distance-based hierarchical cluster analysis (HCA) was used to explore the variance distribution and classification patterns among samples with the Ward method25. Discriminant analysis of the rice samples was performed with principal component analysis (PCA), partial least square-differential analysis (PLS-DA), cross validation and Heatmap. Further evaluation of the accuracy of these predictions were performed by random forest analysis26. Finally, putative biomarker candidates to discriminate Wuchang rice from other varieties were chosen based on (1) a variable importance in the projection (VIP) score ≥ 0.8; and (2) differentially expressed in the univariate analysis27. All the data were analyzed were conducted by R 4.2.2.

Results and discussion

The shape and VOCs profile of the rice grain

The morphology of rice showed in Fig. 1. Some of the rice have different shapes with Wuyoudao4, but some cultivar has similar length and shape such as JSJ. Although Wuyoudao4 have the characteristics with long grains, but it is also hard to tell whether it is Wuyoudao4 only depend on the shapes by naked eye. To prevent mislabeling and adulteration, we developed a method to profile VOCs from Wuchang rice and non-Wuchang rice. The representative total ion chromatography was shown Fig. 2 with the peaks annotated. In total, 22 VOCs were identified from our samples. These VOCs covered compounds with a diverse range of chemical compositions including eight aldehydes, five alcohols, two ketones, two heterocyclic compounds, and five hydrocarbon compounds (Table 2). In addition to VOCs, siloxane derivatives were also observed due to the presence of PDMS in the SPME fibers (Table S2), which is consistency with the previous report28,29.

Figure 1
figure 1

The morphological characteristics of difference rice grains. (a) The wuyoudao4 growed in 11 sites of Wuchang (b) The cultivars from Non-wuchang origins.

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Figure 2
figure 2

VOCs profiling of Wu Chang rice obtained by GC–MS using CAR/PDMS SPME.

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Table 2 8 typical biomarkers characteristics of Wuchang rice.
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Chemometric analysis of biomarkers for rice screening

To identify putative biomarker in determining the geographic origin of rice, we performed both single factor and multivariate analyses on the VOC dataset. First, differential analysis revealed that the concentration of eight features were significantly different among samples (p < 0.05, FDR < 0.1, and FC < 0.8 or FC > 1.2) showed in Venn diagram (Fig. 2). This indicates that the profile of VOCs could be used to distinct rice varieties.

The eight features showing differential concentration between Wuchang and non-Wuchang rice were further evaluated by the variable importance in the projection (VIP) score. All of them passed the 0.8 cutoff and were thus considered as putative biomarkers. They consisted of three aldehydes (heptanal, octanal, (E)-2-decenal), 3 alcohols (1-heptanol, (E)-2-decen-1-ol, 3,7,11-Trimethyl-3-dodecanol), one ketone (3-octene-2-one), and one heterocyclic compound (2-acetyl-1-pyrroline, or 2-AP). Details of the these compounds were summarized in Table S1. Compared to non-Wuchang rice, Wuchang rice showed a significantly lower level of 1-heptanol and 3-octene-2-one (P < 0.05), and a much higher level for the remaining six putative biomarkers (Fig. 3a). Among them, 2-AP has been reported as an important chemical trait to differentiate fragrant rice from non-fragrant rice. Other non-wuchang rice have a relative lower amount of 2-AP amount except TG(Jasmine 105). The identification of 2-AP (Fig. 3b) wast validate which the robustness of our method, but also aligns aligned well with previous findings.

Figure 3
figure 3

Box plots and 2-AP analysis of eight chemical biomarkers in rice samples. (a) Box diagram of eight typical biomarkers for rice samples from WuChang and other regions; (b) 2-AP ion map; (c) Correlation analysis of 2-AP with other volatile compounds.

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Despite we observed a significant difference in the 2-AP concentration between Wuchang and non-Wuchang rice, we next sought to see whether other volatiles show a similar pattern. Thus, we examined the correlations between 2-AP and other compounds. We observed a negative correlation for (E)-2-octenal, (Z)-heptenal, 1-octene-3-ol, dodecane, and heptadecane, and a positive correlation for the rest of 22 VOCs (Fig. 3c).

Evaluation of biomarker efficiency

Previous studies reported the use of 2-AP in determining fragrant rice and non-fragrant rice30. However, the usefulness of other biomarkers remain unclear. To this end, we assessed the discrimination efficiency of putative markers identified here using several multivariate analysis techniques. Our results showed that a clear separation of rice samples by the VOC data. Finally, random forest (RF) analysis further revealed a high accuracy of these markers in distinguishing rice samples from different sources.

Clustering and heat map analysis

HCA clustering classified the samples into two groups neatly with respective to their geographic origins: Wuchang rice and non-Wuchang (Fig. 4a). A large distance between the two groups was also observed (Euclidean distance > 20), supporting the significant difference in grain quality between them. By contrast, the Euclidean distances among the 8 Wuchang samples are less than 5, suggesting that subtle variations exist for rice grown in the same area.

Figure 4
figure 4

Clusting analysis of rice from different regions using eight VOC typical biomarkers. (a) Dendrogram (b) heatmap, weak blue and white represent weak correlation, pink and brown represent strong correlation.

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Next, heatmap analysis was performed to visualize the correlation of eight putative VOCs (Fig. 4b). The 20 samples were separated into two groups. A high degree of correlation was found for the first group consisted of 9 samples, including all 8 varieties from Wuchang. Notably, samples in this group were also high in 2-AP, contribution to a better rice flavor. By contrast, a lower level of correlation in term of VOC content was found for the second group of 11 samples.

Unsupervised PCA was used to process the original data into orthogonal components. The results showed a percentage of variance of 33.9%, 26.8% and 11.1% for the first three PCs respectively (Fig. 5a). Consistent with the clustering analysis, a clear separation of Wuchang rice from other varieties was also observed using the first three PCs. It is notable that nine samples of Wuchang rice concentrated in the three-dimensional PCA plot, supporting that no statistical significant difference were found among them (p > 0.05). Conversely, a wide distribution was observed for the 11 other rice samples, reflecting the fact that they were grown in a diverse range of geographic locations.

Figure 5
figure 5

Different statistical analyses of the chemical biomarkers. (a) 3D score plot between the selected PCs in PCA. (b) PLS-DA models (c) Cumulative error rates by Random Forest classification.

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Similar to clustering and PCA, the PLS-DA analysis showed a clear aggregation among Wuchang varieties (Fig. 5b), indicating that the composition and content of these nine samples were similar. By contrast, disperse of the other 11 samples suggested a large difference in composition and content among them. Significantly, the PLS-DA also revealed the discrimination capacity of the eight biomarkers with a fitness R2 of 0.90, prediction goodness Q2 of 0.85, and displacement test p value of 0.01.

To further evaluate the ability of the eight putative biomarkers in rice classification, we built a model based on the random forest algorithm (RF). RF is not only suitable for feature selection, but also provides useful information such as OOB (out-of-bag) error, variable importance measurement, and outlier measurement31. We found an excellent classification ability of the eight putative biomarkers, indicated by a classification error of essentially 0 (Fig. 5c).

Our study has demonstrated the feasibility of using HS-SPME/GC-MS to profile the VOCs in rice grains. In addition, we found that Wuchang rice can be unambiguously distinguished from non-Wuchang rice by eight putative biomarkers. Thus, this work represents an important contribution to the field of non-destructive geographical authentication of rice. Application of the method in industrial settings would bring a broad impact on the production and management of Wuchang rice, commercial rice trading and consumer's satisfaction. Putative biomarkers include 2AP, consistent with its contribution to rice aroma and previous findings that 2AP can serve as a biomarker to distinguish fragrant rice from non-fragrant ones. More importantly, our untargeted metabolomic approach also identified other putative biomarkers of diverse chemical properties. In the following section, we discuss the relevance of these compound in distinguishing rice verities.

Among the eight putative biomarkers, 2-AP is the most important source of flavor in rice, followed by aldols and ketones. As the most important aroma compound in fragrant rice, 2-AP promotes appetite and improves human metabolim32,33,34. The odor of 2-AP at 0.05 ppm aroma was described as popcorn, which is positively correlated with “butter” and “corn. The odor threshold for 2-AP in water and air had been determined to be 0.1 nL/L, and 0.02 ng/L, respectively35. The extremely low threshold makes 2-AP an important source of food aroma. In rice, 2-AP is mostly produced by the plants, although it was originally thought as a product of the Maillard reaction during rice cooking36,37. In line with this, we detected 2-AP by GCMS in the rice grain with the highest concentration observed in the Wuchang samples. These results are also in consistent with previous reports that different levels of 2-AP are detected in distinct rice varieties38,39. For instance, a 10 times lower level of 2-AP was found in non-fragrant rice compared to that of fragrant rice. Together with other compounds such as hexanal, octanal, (E,E)-2,4-decanedialdehyde, (E)-2-nonanedialdehyde, 4-vinyl-2-methoxy -phenol and hydrazine, 2-AP has been identified as a common aromatic compound among three fragrant rice varieties40. Thus, the high level of 2-AP in Wuchang rice suggests that 2-AP is a major factor in determining the pleasant flavor of Wuchang rice.

Aldehydes were odorous compounds found in many plants and foods, especially in fragrant rice. They are generated either by the oxidation of free fatty acids or the decomposition of linoleic acid41. We found three aldehydes that show differential levels between Wuchang and non-Wuchang rice: heptanal, octanal, and (E)-2-decenal. Previous studies have shown that heptanal, among other saturated aldehydes such as valeraldehyde, hexanal, heptaldehyde, octanal, and furfural, are odor-generating compounds in rice. Interestingly, heptanal and octanal give rice a pleasant fresh grassy scent and a light fruit scent at low concentration, while it produces a disgusting rancid taste if the concentration is too high. In addition, (E)-2-nonenal have a pleasant orange aroma at an extremely low concentration. It will be of interest to explore the contribution of these compounds, either alone or combined with other compounds, in rice flavor.

Three alcohols, 1-heptanol, (E)-2-decen-1-ol, 3,7,11-Trimethyl-3-dodecanol, were identified in our samples. These volatile alcohols produce a milder odor, e.g., the turf taste of 1-heptanol. Most alcohol compounds have higher thresholds, and only higher contents or a non-saturated alcohol such as (E)-2-nonenol and 3,7,11-trimethyl-3-dodecyl alcohol will have a great influence on the flavor.

Ketones can be generated from a variety of pathways in plants, including oxidative or thermal degradation of polyunsaturated fatty acids, amino acid degradation or microbial oxidation42. Ketones give rice a pleasant aroma. Daygon et al. reported that compounds such as 2-heptanone, 2-hexanone, and 3-octene-2-one give fruity/floral aroma in rice, contributing to rice flavor43. We observed a narrow distribution of 3-octene-2-one content in Wuchang rice (Fig. 3a), indicating a potential of 3-octene-2-one in determining the geographic origin of rice. Interestingly, 3-octene-2-one is considered to be the most active ketone in rice, with a rose aroma and excellent long-lasting flavor, leading to the most intense flavor of rice.

Conclusion

A total of 22 volatile compounds were identified by HS–SPME–GC–MS. Among the identified compounds, aldehydes, alcohols, ketones, hydrocarbon were observed to be predominance coumpounds. Among them, heptanal, octanal, (E)-2-decenal, 1-heptanol, (E)-2-decen-1-ol, 3,7,11-Trimethyl-3-dodecanol, 3-octene-2-one, and 2-acetyl-1-pyrroline was used to differentiate Wuchang rice from the others using PCA analysis. The amount of 2-acetyl-1-pyrroline was significant higher than the others. 2-AP together with the other 7 compouds constitute the flavor characteristics of Wuchang rice. The methods can be considered to analyze the rice flavor trait of different cultivars.