Development of molecular diagnostic methods to distinguish Acerola species for quality assurance of food, dietary supplements and natural health products

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The fruits of Malpighia glabra , and M. emarginata are utilized in food products, dietary supplements and natural health products. However, there are differences among the fruit of Malpighia species with respect to phytochemicals, nutrient value and clinical research. Furthermore, there is evidence of adulteration with other fruit such as cherries ( Prunus spp.). Unfortunately, conventional morphological examination does not distinguish acerola fruit species. Furthermore, no published methods are available to distinguish the fruits of these species including chemical and DNA based techniques. This risk to quality assurance (QA) is increased when considering processed berries into juice or powdered ingredients of which are the most common source for manufactures. This lack of QA methods also increases the risk of adulteration with cheaper fruit from other species. The goal of this research is to provide orthogonal molecular methods to authenticate Acerola fruit ingredients and discuss the benefits and constraints of these two different methods. This research supports quality assurance (QA) programs with fit-for-purpose methods for verifying the authenticity of acerola species ingredients from suppliers. Biological sciences/Biological techniques Biological sciences/Chemical biology Biological sciences/Molecular biology Barbados cherry DNA identification NMR fingerprints metabolite spectra adulteration food security Figures Figure 1 Figure 2 Figure 3 Introduction The superfruit market has had significant growth in the marketplace putting demand on suppliers. Consumer demand for superfoods such as superfruit is increasing and attracting the attention of multiple industry sectors including food products, dietary supplements and natural health products 1 . Industry has responded to this demand with marketing strategies for superfood ingredients in their products that promote considerable health benefits within the human body and play an important role in the progression of degenerative diseases 2 , 3 . The superfruit market alone was valued at 134.8 billion USD in 2024 and is expected to grow over 200 billion USD in the next decade (FMI 2025). This is partly driven by the demand from contemporary consumers that value a healthier and environmentally friendly source of nutrition of which superfoods are highly nutritional with bioavailable nutrients with documented bioactivity within the body due to the concentration of nutrients and bioactive ingredients 4 . Few fruits meet the criteria of high nutrient value with notable nutrients such as vitamin C and can be sourced at a reasonable cost by large manufactures that focus on global markets. Acerola berries are designated as a superfruit that can be sustainably grown by producers and sourced in large quantities in the marketplace 5 . Acerola berries are also known as Barbados cherry and West Indian cherry and are grown commercially as small trees or shrubs. Taxonomically there are two species ( Malpighia glabra L.; Malpighia emarginata DC.) from the family Malpighiaceae that contains about 45 species 6 , 7 . There is mention in the literature of another species Malpighia punicifolia L. which is a synonym for Malpighia glabra. The fruit of these two species is undistinguishable as a red fleshy drupe that produces a juicy acidic pulp. The common names are used inconsistently for the respective species causing some confusion when sourcing acerola ingredients from the global supply chain 8 . Malpighia glabra is native to the Americas, including Mexico, Central America, South America, and the Caribbean with more recent introduction and cultivation in USA (Florida, California, Texas), Cuba, Jamaica, and Puerto Rico. Malpighia emarginata is originally from Mexico in the Yucatán peninsula, but is now cultivated in Central America, the Caribbean, and South America as far south as Peru 9 , 10 Brazil is the world’s largest producer of acerola berries with most of the production in the northeast states of Pernambuco, Paraíba, Bahia, and Ceará 5 , 11 . Both species have been introduced for cultivation in Southeast Asia and southern India. In India, cultivation is reported in backyard gardens across the states of Tamil Nadu, Karnataka, Kerala and Maharashtra. More recently production has been recorded in the Andaman and Nicobar Islands 12 . Production is relatively small in the southern USA. The largest markets for acerola products include United States, Germany, France, and Japan. Acerola fruit has considerable nutritional and health benefits. There is a plethora of research on acerola to support pharmacological, medicinal and nutritional claims of which have been well documented in several scientific reviews 5 , 13 , 14 . Acerola health benefits include high antioxidant capacity 6 , 15 , 16 , antitumor 17 , antimutagenic 18 – 23 , antidiabetic 24 , hepatoprotective 25 and functional properties like skin anti-aging 26 , skin whitening, and multidrug resistant reversal activity 11 , 27 . This body of research is supported by many biochemistry studies that have recorded significant phytonutrients such as flavonoids, anthocyanins, carotenoids, phenolics, benzoic acid derivatives and phenylpropanoids within comprehensive scientific reviews 28 , 29 . The presence of these bioactive compounds provides multiple hypothetical mechanisms to support the numerous health claims 27 , 28 . This includes various biological activities using in vitro and in vivo models in which probable mechanisms have been determined 13 . One of the most studied areas of research underpins the claim that acerola is one of the richest natural sources of ascorbic acid up to 100 times more than that of oranges and lemons 13 , 30 – 32 . It has been reported that the vitamin C of acerola is more easily absorbed than other forms including synthetic ascorbic acid 27 , 33 . Acerola berries are consumed and prepared as a nutritional drink and traditional remedy in Brazil. In Europe (e.g., France, Germany, and Hungary) the fruit is utilized as juice, whilst in multiple forms within the in the United States where it is consumed as a rich source of ascorbic acid for vitamin C within supplements and natural health products 27 . There is a lack of published research on quality assurance tools in the acerola industry. These QA tools are needed to ensure species ingredient authenticity and prevent adulteration with other cheaper fruit species. Morphological techniques are inadequate because they cannot differentiate among the species of Malpighia. DNA-based markers have become a popular method for identifying and verifying botanical ingredients. This is because the genetic makeup of each species is unique, regardless of factors such as sample age, physiological condition, environmental growth conditions, harvesting methods, storage, and processing 34 . The DNA extracted from the fruit, leaves, stems or roots of plants all carry the same genetic sequences of which can be stored for long periods of time as they are stable 35 . Multiple DNA regions have been utilized to develop specific markers for identifying and authenticating botanical ingredients 36 , 37 . Several recent reviews provide the benefits and challengers of using DNA-based methods for quality assurance of botanical ingredients 38 – 41 . The use of chemical authentication has been used extensively for quality assurance of botanical ingredients 42 . Traditional analytical chemistry methods are well established and the advantages and limitations are discussed in numerous publications 43 – 45 . More advanced methods have been utilized providing rigorous approach to quality assurance of botanical ingredients that overcomes the challenges of traditional analytical methods 46 – 48 . The development of orthogonal molecular methods for specific species ingredients has eliminated the challenges of DNA methods (e.g., degraded DNA in processed samples) and presented alternative metabolomic methods such as nuclear magnetic resonance (NMR) 49 – 54 . The use of phytochemical analysis and metabolomics methods such as chemical profiling by NMR are the fit-for-purpose in identifying the active ingredients labelled on herbal products 55 , 56 . Analytical chemistry and DNA methods are not fit-for-purpose when evaluating complex samples, such as herbal dietary supplements that can include a mixture of several plant species in one product 36 , 54 , 57 . NMR methods overcome the admixtures barrier and have a wide range of applications in food and botanical industry, as ingredients authentication and quantification, including active ingredient quantification and differentiating the geographic origins ingredients 58 – 65 . These molecular methods need to be assessed in the context of specific species ingredients to determine fit-for-purpose in the quality assessment of sourced botanical ingredients. The objective of this study is to develop of Nuclear Magnetic Resonance Fingerprints and DNA sequence methods to distinguish Acerola species ( Malpighia glabra, M. emarginata ) for quality assurance of Food, dietary supplements and natural health products. More specifically we used two methods including, 1) DNA sequencing the ITS nuclear region for 16 samples and, 2) 1H-NMR metabolite fingerprinting to analyze 16 samples consisting of 10 samples of two Acerola species ( Malpighia glabra, M. emarginata ) and 6 samples of common adulterant cherry ( Prunus spp. ) species. The validation of genomics and metabolomics approaches in this study will ensure quality assurance for both product identity and purity. Materials and Methods Botanical Samples This study develop two separate orthogonal methods using 32 Samples including, 1) DNA sequencing of 16 samples representing two acerola species ( Malpighia glabra, M. emarginata ) of which 13 were leaf samples and 3 were berry samples (Table S1 ), and 2) NMR metabolite fingerprinting of 16 samples representing 10 berry samples of two acerola species ( Malpighia glabra, M. emarginata ) and 6 berry samples of cherry representing two species ( Prunus cerasus L.; Prunus avium (L.) L.) (Table S2). Only berry samples were used for NMR metabolite fingerprinting representing the form of acerola product in the supply chain because NMR fingerprints are known to be different among leaves and fruit 66 , 67 . It is known that DNA sequences for specific regions such as ITS do not change for different tissues such as leaves and fruit. Therefore, we used mostly leaves in this study for DNA sequencing. However, we did sequence five vouchers (e.g., leaves and berries) from the NMR study including samples for each Malpighia species to verify that the berries used for NMR metabolite fingerprinting were the correct species (Table S1 ). We did not attempt to sequence the cherry samples due to the known challenges of barcoding cherry ( Prunus spp.) in the published literature including ITS and other regions 68 – 70 . The identification of the herbarium voucher samples was confirmed by qualified taxonomist on staff at the University of Guelph. All samples are housed at the Natural Health Products Research Alliance, University of Guelph. Genomic DNA extraction Genomic DNA from the samples were extracted using the Nucleospin Plant II kit (Macherey- Nagel GmbH & Co. KG, Düren, Germany) to get high-quality DNA. DNA extractions were conducted using 100 mg of each sample, following the manufacturer's instructions. DNA quantification was carried out with the QubitTM 3.0 Fluorometer (Invitrogen, Carlsbad, CA). DNA Amplification of ITS The ITS region was used because of its ability to discriminate con generic species 3 , 71 – 73 . PCR was performed using species-specific ITS primer pairs as described by Fazekas et al. (2012) 74 . The reaction mixtures (20 µL) contained 1 U AmpliTaq Gold Polymerase, GeneAmp buffer II (100 mM Tris-HCl pH 8.3 and 500 mM KCl), 2.5 mM MgCl2, 0.2 mM dNTPs, 0.1 mM of each primer, and 20 ng of template DNA. DNA sequencing of ITS region The ITS amplified products were sequenced in both directions following the protocols established at the University of Guelph Genomics Facility ( www.uoguelph.ca/~genomics ). The products from each specimen were purified using Sephadex columns and analyzed on a ABI 3730 sequencer (Applied Biosystems). Bidirectional sequence reads were acquired for all the PCR products. The sequences were assembled using CodonCode Aligner version 11.0.1 (CodonCode Corp) and manually aligned with BioEdit version 7.0.9. Subsequently, the aligned sequences were processed using Clustal W 75 . The genetic distances were calculated using the Kimura2Parameter (K2P) model in Mega11 76 . 18 DNA sequences from GenBank were used to assess the specificity of the ITS region and compare interspecific variation among the two species of Malpighia including, M. glabra , M. emarginata . These 18 sequences were used in a BLAST analysis within GenBank to assess the specificity of these sequences to other Malpighia species and that of any potential adulterants such as Prunus species. NMR Sample Preparation Samples for NMR analysis were prepared by weighing 300 mg of finely ground plant tissue (Table S2). To ensure complete homogenization, the plant material was ground in liquid nitrogen using a mortar and pestle, then dissolved in a solvent mixture of 90% regular methanol and 10% deuterated methanol (CD₃OD) for its broad solubility range, which aids in NMR acquisition 77 , 78 . Each sample was prepared in triplicate for consistency, sonicated in a water bath at room temperature for 10 minutes to enhance extraction, and centrifuged at 6000 rpm for 5 minutes. Finally, 650 µL of the clear supernatant was transferred into a 5 mm Wilmad® NMR tube for spectral acquisition. NMR Spectral Acquisition The proton (¹H) NMR spectra were recorded on a Bruker Avance III 400 MHz spectrometer, which features a 5 mm Broadband Inverse (BBI) probe designed for room temperature use. We used a proton NOESY (Nuclear Overhauser Effect Spectroscopy) pulse sequence with pre-saturation to improve the results. This method included dual solvent suppression for both water and methanol, helping to reduce any interference from the solvent signals. The key acquisition parameters included: Spectrometer frequency : 400.3 MHz; Number of scans : 64; Acquisition time : 2.27 seconds; Relaxation delay : 12.73 seconds; Spectral width : 8223.68 Hz. The use of dual solvent suppression was utilized to improve the spectral quality by reducing peak overlap from residual solvent signals, enhancing metabolite detection in complex biological matrices 79 . Temperature stabilization was maintained at 300 K throughout data acquisition. NMR Data Processing and Analysis In this study, NMR spectral data were processed with TopSpin 3.6.3 for consistency and accuracy, using automated phase and baseline corrections and referencing the tetramethylsilane (TMS) peak at 0.00 ppm for calibration. A rectangular binning approach with a bin width of 0.01 ppm was utilized over a chemical shift range from − 1 to 12 ppm, while residual solvent peaks corresponding to water (4.75–5.06 ppm) and methanol (3.16–3.45 ppm) were excluded to minimize spectral distortion. Each spectrum was normalized via a scaling method wherein values below the mean intensity were set to zero, and intensities above the mean were scaled to fit within a range of 1 to 100. For statistical analysis, we performed multivariate analyses, including Hierarchical Clustering Analysis (HCA) and Hierarchical Clustering on Principal Components (HCPC), based on an Euclidean dissimilarity matrix while employing Ward's clustering method in R 80 . We converted spectral intensities into chemical fingerprints, which allowed us to use hierarchical clustering to distinguish between different botanical species. This NMR-based metabolomics approach provides reliable differentiation and ensures high reproducibility for future analyses. Results DNA Extraction and Sequencing. The DNA extraction protocols yielded good quality, high molecular weight genomic DNA from the dried berry and leaf samples of M. glabra and M. emarginata. The procedure yielded 40–60ng of DNA per ng/ul of leaf tissue and for a whole dried berries and powders yielded (2 to 4.5 ng/ul). The amplification of the complete ITS region (comprising ITS1, the 5.8S rRNA gene, and ITS2) was successfully achieved using the universal primers ITS5 (forward) and ITS4 (reverse). This process generated an amplicon of approximately 700 bp for all three species investigated. Direct sequencing of amplicon yielded a ~ 700bp ITS sequence for M. glabra and M. emarginata . GenBank accession numbers are recorded (Table S1 ). Searches and BLAST analysis in GenBank indicated that the sequences of M. emarginata matched that of those in GenBank and that those sequences for M. glabra were novel and added to the GenBank library. Alignment of all the sequences revealed that there was enough interspecific variation to distinguish all the samples of M. glabra from M. emarginata. Interspecific among the two species was 1% including seven species specific single nucleotide polymorphisms (SNPs) within the 700 base pair nucleotide sequence. Sequence variation indicated that the ITS1, 5.8S rRNA gene and ITS2 regions of each respective species were unique. BLAST analysis revealed that all the acerola species sequences did not match any other potential adulterant species including cherry ( Prunus spp.). NMR Fingerprinting Metabolite diversity among the NMR fingerprints was considerable. Hierarchical clustering analysis (HCA) of the ¹H NMR spectral data was used to assess metabolite diversity within a heatmap of metabolite diversity (Figure: 1). The resulting dendrogram clearly distinguishes the samples of M. glabra and M. emarginata highlighting their distinct metabolite profiles. However , M. glabra exhibits closer metabolic resemblance to Prunus spp. compared to M. emarginata , suggesting a greater risk of potential adulteration. The hierarchical clustering of cherry samples groups respective Prunus species from acerola species based on their metabolic composition. Clusters labeled A and D correspond to M. glabra and M. emarginata , respectively, while clusters B and C include Prunus spp. The distinct clustering of M. emarginata underscores its unique metabolite profile, which is markedly different from M. glabra and Prunus species. This separation suggests that while M. glabra may share some chemical characteristics with Prunus , M. emarginata remains phytochemically distinct. Comparative ¹H NMR Spectral Analysis : Prunus spp. vs. Malpighia spp. ¹H NMR spectra of M. emarginata, Prunus cerasus , and Prunus avium demonstrate clear differences in metabolite distribution (Figure: S1). Although some spectral overlaps exist, key variations are observed in regions associated with carbohydrates (3.0–5.5 ppm), organic acids (2.0–3.0 ppm), and aromatic compounds (6.0–8.0 ppm). The most notable differences include: The prominence of organic acids such as malic acid (2.4–3.0 ppm) in M. emarginata , which is significantly reduced or absent in Prunus spp. Higher concentrations of ascorbic acid (4.0–4.3 ppm) in Acerola, confirming its known vitamin C content (de Souza et al., 2002). The presence of ferulic acid (6.5–7.5 ppm) in M. emarginata , a unique authentication marker absent in Prunus spp. These spectral differences validate the use of ¹H NMR fingerprinting as a reliable method for species authentication, ensuring that Malpighia species can be accurately distinguished from potential adulterants such as cherry ( Prunus spp.). Metabolite Assignments and Authentication Markers Elucidation of specific metabolites identifies differences among the key metabolite assignments for M. glabra and M. emarginata , respectively (Figure: 2 & 3) . The assigned peaks correspond to major bioactive compounds that play a role in species differentiation (Figure: 2 & 3). The presence of ferulic acid and amino acids in M. emarginata sets it apart from M. glabra and Prunus spp. (Figure: 2 & 3). The metabolites identified in M. glabra include α-D-glucose (5.2–5.4 ppm), β-D-glucose (4.6–4.8 ppm), fructose (4.0–4.5 ppm), ascorbic acid (4.0–4.3 ppm), and malic acid (2.4–3.0 ppm). In comparison, M. emarginata metabolites encompass ferulic acid (6.5–7.5 ppm), notably absent in Prunus spp., along with α-glucose (5.2–5.4 ppm), β-glucose (4.6–4.8 ppm), fructose (4.0–4.5 ppm), and malic acid (2.4–3.0 ppm), the latter serving as a distinguishing marker. Additionally, amino acids such as valine, leucine, and isoleucine (0.8–1.5 ppm) are specifically identified in M. emarginata. Discussion One of the impediments in the acceptance of herbal formulations in the medical and pharmaceutical community is the lack of standardization and quality control. This is due to unacceptable risks to human health and unjustified health claims. It is challenging to develop robust quality control parameters using analytical chemical methods because of the complex nature and inherent variability of the chemical ingredients and molecular constituents used in supplements and natural health products, (World Health Organization 2000). These challenges including that of other conventional pharmacognosy methods such as morphology, microscopy, DNA-based and phytochemical analysis have led to the demand for more robust, fit-for-purpose methods of authentication of botanical species ingredients 3 , 81 – 83 . This is driven by consumer demand that seek natural remedies and nutrition that support health lifestyles without the use of drugs and synthetic health supplements 84 . There are considerable challenges in authentication of acerola species ingredients from the commercial supply chain. Our experience and collaboration with industry members working directly with procuring M. glabra and M. emarginata materials indicates that these species cannot be distinguished based on their morphology or histology. Conventional analytical chemistry methods are often providing inconclusive reports. For example, high performance thin layer chromatography (HPTLC) analysis of acerola berries of M. glabra and M. emarginata often have identical or closely overlapping profiles with similar or highly variable acerolin content depending on product processing used by different suppliers (NHPRA members pers. Comm.). More recently the industry has moved to trading fruit as dried extracts of which there is a lack of standard methods for quality assurance protocols such as reference standards and product species verification. This problem is intensified when considering that acerola is considered a superfruit in high demand due to its high vitamin C content of which is highly perishable in transit and storage 85 , 86 . Dehydrating acerola juice using a spray dryer has become a common solution in the supply industry to extend the product's shelf life and subsequent profit margins 87 , 88 . The NHP community has repeatedly voice there is a gap in acerola quality assurance methods and need for research on the development of new methods. This study provides two orthogonal molecular methods for the authentication of acerola species ingredients procured in the industry supply chain. The first method utilized common DNA sequencing. Several studies have used ITS sequences as genetic markers for many botanical species 3 , 71 – 73 , 89 . The sequence variation of ribosomal RNA gene repeats is believed to rapidly turn over thus providing considerable interspecific variation among congeneric species 90 . Universal PCR primers designed from highly conserved regions flanking the ITS region are available and are relatively small in size (600–700 bp) with high copy number provide relative ease of amplification of the ITS region. In our study we had successful sequencing and found sufficient variation to distinguish the two commercial acerola species. However, the materials we used contained considerable amounts of DNA unlike that of highly processed extracts, which have considerably less DNA presenting challenges for PCR and sequencing 34 , 91 . Another consideration for extract materials is the presence of PCR amplification inhibiters such as concentrated phenolic compounds, acidic polysaccharides and pigments, which can be overcome by choosing appropriate DNA extraction methods that can reduce or eliminate PCR inhibitors 35 . Further research is needed to develop species specific probes based on unique SNPs for M. glabra and M. emarginata that could be used within specific QPCR methods. This DNA approach has been successfully used for species specific verification of highly processed supplements in the form of leaf or berry extracts have reported mini sequence-based authentication of several botanical species worked well in botanical extracts 50 , 53 . ITS sequences were unique to commercial acerola species and not potential adulterants such as cherry species. However, a fit-for-purpose standard operating aimed at authenticating target species ingredients and preventing adulteration would require full ITS sequencing, which requires considerable resources (e.g., time, cost). If the materials are highly processed extracts, then targeted QPCR would be required including specific QPCR assays for all the potential adulterants of which resource intensive (e.g., time costs). In this study, ¹H Nuclear Magnetic Resonance (NMR) metabolomic fingerprinting combined with chemometric clustering distinguished highly all samples of two Acerola species, M. glabra and M. emarginata , from potential adulterants belonging to the Prunus genus ( Prunus cerasus and Prunus avium ). The results provide a robust metabolic fingerprint that can serve as a scientific authentication tool based on primary and secondary metabolite composition. ¹H NMR fingerprinting, coupled with multivariate chemometric analysis, provides a powerful authentication tool for differentiating botanical species. Unlike chromatographic techniques, which can be manipulated by introducing synthetic analogs, NMR-based authentication relies on the holistic metabolite spectrum, making it more resistant to adulteration 79 . The authentication of commercial acerola is particularly significant due to its high economic value and susceptibility to adulteration with cherry derivatives. The hierarchical clustering of metabolites indicates that while M. glabra exhibits some spectral resemblance to Prunus spp., M. emarginata remains chemically distinct. By integrating metabolite-specific peak ratios, particularly malic acid and ascorbic acid content, a more rigorous authentication framework is established. This approach of provides both a species ingredient identification tools while providing verification of specific bioactive metabolites that are of value to health minded consumers. The elucidation of specific bioactive metabolites is particularly valuable for product claims and specific ingredients on product labels. Conclusion Two methods provide novel tools for the quality assurance of acerola species procured in the industry supply chain. DNA methods have several limitations for berry extracts and may be cost prohibitive if the goal is to detect species adulteration. NMR fingerprinting can be used for berry extracts and has the benefit of authenticating acerola species ingredients whilst detecting any adulterants in a single analysis. The resulting NMR spectra also provide quantitative estimates of bioactive phytochemicals negating the need for further analytical chemistry methods. This study highlights the application of NMR fingerprinting as a critical quality control measure in the natural health product and food industry. Declarations Acknowledgements We thank Natural health product research alliance (NHPRA), University of Guelph for supporting this study. We would like to thank the Genomics facility, University of Guelph for their help in carrying out experiments in their lab and also for their timely help and assistance whenever needed. Thomas Henry is greatly acknowledged for his help in the wet lab. Data availability statement All data supporting the findings of this study are included in the article and supplementary material. Any additional inquiries can be directed to the corresponding author. Funding source Funding for this research was provided by the Natural Health Product Research Alliance, University of Guelph, grant number 053312. Author contributions: Sub.R. and S.G.N conceived the project and experiments; Sub.R and Sne. R. carried out the DNA molecular work and analysis; V.V. Sne. R. and A.T. carried out the NMR metabolite lab work and analysis; Sub.R. led the manuscript writing, and all other authors contributed to writing, editing, reading and accepting the final version of the manuscript. Competing Interests: The authors declare no competing interests. Additional Information: The authors confirm that Dr Ragupathy is the trained taxonomist who identified all plants. All the vouchers are recorded within Table S1 and the specimens were deposited at the Natural Health Products Research Alliance, the University of Guelph. The plants used in this study are common, commercially available species that do not require any permits/permissions/licenses. References Laurindo, L. F. et al. Health benefits of acerola (Malpighia spp) and its by-products: A comprehensive review of nutrient-rich composition, pharmacological potential, and industrial applications. 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Chapter 1 - Quality Related Safety Issue-Evidence-Based Validation of Herbal Medicine Farm to Pharma in 1–28 (Elsevier Inc, 2015). 10.1016/B978-0-12-800874-4.00001-5 Govindaraghavan, S. & Sucher, N. J. Quality assessment of medicinal herbs and their extracts: Criteria and prerequisites for consistent safety and efficacy of herbal medicines. Epilepsy Behav. 52 , 363–371 (2015). Dubey, N. K., Kumar, R. & Tripathi, P. Global promotion of herbal medicine: India’s opportunity. Curr. Sci. 86 , (2003). de Medeiros, F. G. M., Pereira, G. B. C., Pedrini, M. R. S., Hoskin, R. T. & Nunes, A. O. Evaluation of the environmental performance of the production of polyphenol-rich fruit powders: A case study on acerola. J. Food Eng. 372 , (2024). Gomes, B. T. et al. Acerola byproducts microencapsulated by spray and freeze-drying: The effect of carrier agent and drying method on the production of bioactive powder. Int. J. Food Eng. 20 , 347–356 (2024). Fonseca, M. T. et al. 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Newmaster","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Steven","middleName":"G.","lastName":"Newmaster","suffix":""}],"badges":[],"createdAt":"2025-04-04 00:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6372499/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6372499/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-12408-6","type":"published","date":"2025-08-04T15:57:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82825872,"identity":"efa95fca-a07e-4252-9c32-bf640222c626","added_by":"auto","created_at":"2025-05-15 16:06:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":322561,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHierarchically clustering of NMR fingerprints.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6372499/v1/fe512f79af90e6dcfeb8ab62.png"},{"id":82825878,"identity":"6cbd896d-43f3-4c22-9ae5-34306d2d088f","added_by":"auto","created_at":"2025-05-15 16:06:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":179664,"visible":true,"origin":"","legend":"\u003cp\u003eBioactive molecule elucidation of M. glabra.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6372499/v1/7877be569d59a88814ea048f.png"},{"id":82825874,"identity":"37374601-d643-4850-abf0-d1f6b8453a8d","added_by":"auto","created_at":"2025-05-15 16:06:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":162058,"visible":true,"origin":"","legend":"\u003cp\u003eBioactive molecule elucidation of M. emarginata.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6372499/v1/fc320ed4b1e237ccf8aa54f6.png"},{"id":88814131,"identity":"a28efd46-86e7-4d18-aa05-f8f0d51e491e","added_by":"auto","created_at":"2025-08-11 16:07:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2173771,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6372499/v1/6453bafd-b8ca-4331-947f-9a6c2078f96a.pdf"},{"id":82826924,"identity":"22630437-14e2-4536-8ae1-5513d576e678","added_by":"auto","created_at":"2025-05-15 16:14:11","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":171640,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-6372499/v1/cc025e1e2eb81491136f89f9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of molecular diagnostic methods to distinguish Acerola species for quality assurance of food, dietary supplements and natural health products","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe superfruit market has had significant growth in the marketplace putting demand on suppliers. Consumer demand for superfoods such as superfruit is increasing and attracting the attention of multiple industry sectors including food products, dietary supplements and natural health products \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Industry has responded to this demand with marketing strategies for superfood ingredients in their products that promote considerable health benefits within the human body and play an important role in the progression of degenerative diseases \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The superfruit market alone was valued at 134.8\u0026nbsp;billion USD in 2024 and is expected to grow over 200\u0026nbsp;billion USD in the next decade (FMI 2025). This is partly driven by the demand from contemporary consumers that value a healthier and environmentally friendly source of nutrition of which superfoods are highly nutritional with bioavailable nutrients with documented bioactivity within the body due to the concentration of nutrients and bioactive ingredients \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Few fruits meet the criteria of high nutrient value with notable nutrients such as vitamin C and can be sourced at a reasonable cost by large manufactures that focus on global markets.\u003c/p\u003e \u003cp\u003eAcerola berries are designated as a superfruit that can be sustainably grown by producers and sourced in large quantities in the marketplace \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Acerola berries are also known as Barbados cherry and West Indian cherry and are grown commercially as small trees or shrubs. Taxonomically there are two species (\u003cem\u003eMalpighia glabra\u003c/em\u003e L.; \u003cem\u003eMalpighia emarginata\u003c/em\u003e DC.) from the family Malpighiaceae that contains about 45 species \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. There is mention in the literature of another species \u003cem\u003eMalpighia punicifolia\u003c/em\u003e L. which is a synonym for \u003cem\u003eMalpighia glabra.\u003c/em\u003e The fruit of these two species is undistinguishable as a red fleshy drupe that produces a juicy acidic pulp. The common names are used inconsistently for the respective species causing some confusion when sourcing acerola ingredients from the global supply chain \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eMalpighia glabra\u003c/em\u003e is native to the Americas, including Mexico, Central America, South America, and the Caribbean with more recent introduction and cultivation in USA (Florida, California, Texas), Cuba, Jamaica, and Puerto Rico. \u003cem\u003eMalpighia emarginata\u003c/em\u003e is originally from Mexico in the Yucat\u0026aacute;n peninsula, but is now cultivated in Central America, the Caribbean, and South America as far south as Peru\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Brazil is the world\u0026rsquo;s largest producer of acerola berries with most of the production in the northeast states of Pernambuco, Para\u0026iacute;ba, Bahia, and Cear\u0026aacute; \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Both species have been introduced for cultivation in Southeast Asia and southern India. In India, cultivation is reported in backyard gardens across the states of Tamil Nadu, Karnataka, Kerala and Maharashtra. More recently production has been recorded in the Andaman and Nicobar Islands \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Production is relatively small in the southern USA. The largest markets for acerola products include United States, Germany, France, and Japan.\u003c/p\u003e \u003cp\u003eAcerola fruit has considerable nutritional and health benefits. There is a plethora of research on acerola to support pharmacological, medicinal and nutritional claims of which have been well documented in several scientific reviews \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Acerola health benefits include high antioxidant capacity \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, antitumor \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, antimutagenic \u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, antidiabetic \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, hepatoprotective\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and functional properties like skin anti-aging \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, skin whitening, and multidrug resistant reversal activity \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This body of research is supported by many biochemistry studies that have recorded significant phytonutrients such as flavonoids, anthocyanins, carotenoids, phenolics, benzoic acid derivatives and phenylpropanoids within comprehensive scientific reviews \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The presence of these bioactive compounds provides multiple hypothetical mechanisms to support the numerous health claims \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. This includes various biological activities using in vitro and in vivo models in which probable mechanisms have been determined \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. One of the most studied areas of research underpins the claim that acerola is one of the richest natural sources of ascorbic acid up to 100 times more than that of oranges and lemons \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. It has been reported that the vitamin C of acerola is more easily absorbed than other forms including synthetic ascorbic acid \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Acerola berries are consumed and prepared as a nutritional drink and traditional remedy in Brazil. In Europe (e.g., France, Germany, and Hungary) the fruit is utilized as juice, whilst in multiple forms within the in the United States where it is consumed as a rich source of ascorbic acid for vitamin C within supplements and natural health products \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere is a lack of published research on quality assurance tools in the acerola industry. These QA tools are needed to ensure species ingredient authenticity and prevent adulteration with other cheaper fruit species. Morphological techniques are inadequate because they cannot differentiate among the species of \u003cem\u003eMalpighia.\u003c/em\u003e DNA-based markers have become a popular method for identifying and verifying botanical ingredients. This is because the genetic makeup of each species is unique, regardless of factors such as sample age, physiological condition, environmental growth conditions, harvesting methods, storage, and processing \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The DNA extracted from the fruit, leaves, stems or roots of plants all carry the same genetic sequences of which can be stored for long periods of time as they are stable \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Multiple DNA regions have been utilized to develop specific markers for identifying and authenticating botanical ingredients \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Several recent reviews provide the benefits and challengers of using DNA-based methods for quality assurance of botanical ingredients \u003csup\u003e\u003cspan additionalcitationids=\"CR39 CR40\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. The use of chemical authentication has been used extensively for quality assurance of botanical ingredients \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Traditional analytical chemistry methods are well established and the advantages and limitations are discussed in numerous publications \u003csup\u003e\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. More advanced methods have been utilized providing rigorous approach to quality assurance of botanical ingredients that overcomes the challenges of traditional analytical methods \u003csup\u003e\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. The development of orthogonal molecular methods for specific species ingredients has eliminated the challenges of DNA methods (e.g., degraded DNA in processed samples) and presented alternative metabolomic methods such as nuclear magnetic resonance (NMR) \u003csup\u003e\u003cspan additionalcitationids=\"CR50 CR51 CR52 CR53\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The use of phytochemical analysis and metabolomics methods such as chemical profiling by NMR are the fit-for-purpose in identifying the active ingredients labelled on herbal products \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Analytical chemistry and DNA methods are not fit-for-purpose when evaluating complex samples, such as herbal dietary supplements that can include a mixture of several plant species in one product \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. NMR methods overcome the admixtures barrier and have a wide range of applications in food and botanical industry, as ingredients authentication and quantification, including active ingredient quantification and differentiating the geographic origins ingredients \u003csup\u003e\u003cspan additionalcitationids=\"CR59 CR60 CR61 CR62 CR63 CR64\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. These molecular methods need to be assessed in the context of specific species ingredients to determine fit-for-purpose in the quality assessment of sourced botanical ingredients.\u003c/p\u003e \u003cp\u003eThe objective of this study is to develop of Nuclear Magnetic Resonance Fingerprints and DNA sequence methods to distinguish Acerola species (\u003cem\u003eMalpighia glabra, M. emarginata\u003c/em\u003e) for quality assurance of Food, dietary supplements and natural health products. More specifically we used two methods including, 1) DNA sequencing the ITS nuclear region for 16 samples and, 2) 1H-NMR metabolite fingerprinting to analyze 16 samples consisting of 10 samples of two Acerola species (\u003cem\u003eMalpighia glabra, M. emarginata\u003c/em\u003e) and 6 samples of common adulterant cherry (\u003cem\u003ePrunus spp.\u003c/em\u003e) species. The validation of genomics and metabolomics approaches in this study will ensure quality assurance for both product identity and purity.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cb\u003eBotanical Samples\u003c/b\u003e This study develop two separate orthogonal methods using 32 Samples including, 1) DNA sequencing of 16 samples representing two acerola species (\u003cem\u003eMalpighia glabra, M. emarginata\u003c/em\u003e) of which 13 were leaf samples and 3 were berry samples (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), and 2) NMR metabolite fingerprinting of 16 samples representing 10 berry samples of two acerola species (\u003cem\u003eMalpighia glabra, M. emarginata\u003c/em\u003e) and 6 berry samples of cherry representing two species (\u003cem\u003ePrunus cerasus\u003c/em\u003e L.; \u003cem\u003ePrunus avium\u003c/em\u003e (L.) L.) (Table S2). Only berry samples were used for NMR metabolite fingerprinting representing the form of acerola product in the supply chain because NMR fingerprints are known to be different among leaves and fruit \u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. It is known that DNA sequences for specific regions such as ITS do not change for different tissues such as leaves and fruit. Therefore, we used mostly leaves in this study for DNA sequencing. However, we did sequence five vouchers (e.g., leaves and berries) from the NMR study including samples for each \u003cem\u003eMalpighia\u003c/em\u003e species to verify that the berries used for NMR metabolite fingerprinting were the correct species (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). We did not attempt to sequence the cherry samples due to the known challenges of barcoding cherry (\u003cem\u003ePrunus\u003c/em\u003e spp.) in the published literature including ITS and other regions \u003csup\u003e\u003cspan additionalcitationids=\"CR69\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. The identification of the herbarium voucher samples was confirmed by qualified taxonomist on staff at the University of Guelph. All samples are housed at the Natural Health Products Research Alliance, University of Guelph.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGenomic DNA extraction\u003c/b\u003e Genomic DNA from the samples were extracted using the Nucleospin Plant II kit (Macherey- Nagel GmbH \u0026amp; Co. KG, D\u0026uuml;ren, Germany) to get high-quality DNA. DNA extractions were conducted using 100 mg of each sample, following the manufacturer's instructions. DNA quantification was carried out with the QubitTM 3.0 Fluorometer (Invitrogen, Carlsbad, CA).\u003c/p\u003e \u003cp\u003e \u003cb\u003eDNA Amplification of ITS\u003c/b\u003e The ITS region was used because of its ability to discriminate con generic species \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR72\" citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. PCR was performed using species-specific ITS primer pairs as described by Fazekas et al. (2012)\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. The reaction mixtures (20 \u0026micro;L) contained 1 U AmpliTaq Gold Polymerase, GeneAmp buffer II (100 mM Tris-HCl pH 8.3 and 500 mM KCl), 2.5 mM MgCl2, 0.2 mM dNTPs, 0.1 mM of each primer, and 20 ng of template DNA.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDNA sequencing of ITS region\u003c/b\u003e The ITS amplified products were sequenced in both directions following the protocols established at the University of Guelph Genomics Facility (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.uoguelph.ca/~genomics\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.uoguelph.ca/~genomics\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The products from each specimen were purified using Sephadex columns and analyzed on a ABI 3730 sequencer (Applied Biosystems). Bidirectional sequence reads were acquired for all the PCR products. The sequences were assembled using CodonCode Aligner version 11.0.1 (CodonCode Corp) and manually aligned with BioEdit version 7.0.9. Subsequently, the aligned sequences were processed using Clustal W \u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. The genetic distances were calculated using the Kimura2Parameter (K2P) model in Mega11 \u003csup\u003e76\u003c/sup\u003e. 18 DNA sequences from GenBank were used to assess the specificity of the ITS region and compare interspecific variation among the two species of \u003cem\u003eMalpighia\u003c/em\u003e including, \u003cem\u003eM. glabra\u003c/em\u003e, \u003cem\u003eM. emarginata\u003c/em\u003e. These 18 sequences were used in a BLAST analysis within GenBank to assess the specificity of these sequences to other \u003cem\u003eMalpighia\u003c/em\u003e species and that of any potential adulterants such as \u003cem\u003ePrunus\u003c/em\u003e species.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNMR Sample Preparation\u003c/b\u003e Samples for NMR analysis were prepared by weighing 300 mg of finely ground plant tissue (Table S2). To ensure complete homogenization, the plant material was ground in liquid nitrogen using a mortar and pestle, then dissolved in a solvent mixture of 90% regular methanol and 10% deuterated methanol (CD₃OD) for its broad solubility range, which aids in NMR acquisition \u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e,\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. Each sample was prepared in triplicate for consistency, sonicated in a water bath at room temperature for 10 minutes to enhance extraction, and centrifuged at 6000 rpm for 5 minutes. Finally, 650 \u0026micro;L of the clear supernatant was transferred into a 5 mm Wilmad\u0026reg; NMR tube for spectral acquisition.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNMR Spectral Acquisition\u003c/b\u003e The proton (\u0026sup1;H) NMR spectra were recorded on a Bruker Avance III 400 MHz spectrometer, which features a 5 mm Broadband Inverse (BBI) probe designed for room temperature use. We used a proton NOESY (Nuclear Overhauser Effect Spectroscopy) pulse sequence with pre-saturation to improve the results. This method included dual solvent suppression for both water and methanol, helping to reduce any interference from the solvent signals. The key acquisition parameters included: \u003cb\u003eSpectrometer frequency\u003c/b\u003e: 400.3 MHz; \u003cb\u003eNumber of scans\u003c/b\u003e: 64; \u003cb\u003eAcquisition time\u003c/b\u003e: 2.27 seconds; \u003cb\u003eRelaxation delay\u003c/b\u003e: 12.73 seconds; \u003cb\u003eSpectral width\u003c/b\u003e: 8223.68 Hz. The use of dual solvent suppression was utilized to improve the spectral quality by reducing peak overlap from residual solvent signals, enhancing metabolite detection in complex biological matrices \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. Temperature stabilization was maintained at 300 K throughout data acquisition.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNMR Data Processing and Analysis\u003c/b\u003e In this study, NMR spectral data were processed with TopSpin 3.6.3 for consistency and accuracy, using automated phase and baseline corrections and referencing the tetramethylsilane (TMS) peak at 0.00 ppm for calibration. A rectangular binning approach with a bin width of 0.01 ppm was utilized over a chemical shift range from \u0026minus;\u0026thinsp;1 to 12 ppm, while residual solvent peaks corresponding to water (4.75\u0026ndash;5.06 ppm) and methanol (3.16\u0026ndash;3.45 ppm) were excluded to minimize spectral distortion. Each spectrum was normalized via a scaling method wherein values below the mean intensity were set to zero, and intensities above the mean were scaled to fit within a range of 1 to 100. For statistical analysis, we performed multivariate analyses, including Hierarchical Clustering Analysis (HCA) and Hierarchical Clustering on Principal Components (HCPC), based on an Euclidean dissimilarity matrix while employing Ward's clustering method in R \u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. We converted spectral intensities into chemical fingerprints, which allowed us to use hierarchical clustering to distinguish between different botanical species. This NMR-based metabolomics approach provides reliable differentiation and ensures high reproducibility for future analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eDNA Extraction and Sequencing.\u003c/b\u003e The DNA extraction protocols yielded good quality, high molecular weight genomic DNA from the dried berry and leaf samples of \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003eM. emarginata.\u003c/em\u003e The procedure yielded 40\u0026ndash;60ng of DNA per ng/ul of leaf tissue and for a whole dried berries and powders yielded (2 to 4.5 ng/ul). The amplification of the complete ITS region (comprising ITS1, the 5.8S rRNA gene, and ITS2) was successfully achieved using the universal primers ITS5 (forward) and ITS4 (reverse). This process generated an amplicon of approximately 700 bp for all three species investigated.\u003c/p\u003e \u003cp\u003eDirect sequencing of amplicon yielded a\u0026thinsp;~\u0026thinsp;700bp ITS sequence for \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003eM. emarginata\u003c/em\u003e. GenBank accession numbers are recorded (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Searches and BLAST analysis in GenBank indicated that the sequences of \u003cem\u003eM. emarginata\u003c/em\u003e matched that of those in GenBank and that those sequences for \u003cem\u003eM. glabra\u003c/em\u003e were novel and added to the GenBank library. Alignment of all the sequences revealed that there was enough interspecific variation to distinguish all the samples of \u003cem\u003eM. glabra\u003c/em\u003e from \u003cem\u003eM. emarginata.\u003c/em\u003e Interspecific among the two species was 1% including seven species specific single nucleotide polymorphisms (SNPs) within the 700 base pair nucleotide sequence. Sequence variation indicated that the ITS1, 5.8S rRNA gene and ITS2 regions of each respective species were unique. BLAST analysis revealed that all the acerola species sequences did not match any other potential adulterant species including cherry (\u003cem\u003ePrunus\u003c/em\u003e spp.).\u003c/p\u003e \u003cp\u003e \u003cb\u003eNMR Fingerprinting Metabolite diversity among the NMR fingerprints was considerable. Hierarchical clustering analysis (HCA)\u003c/b\u003e of the \u0026sup1;H NMR spectral data \u003cb\u003ewas used to assess metabolite diversity within a heatmap of metabolite diversity (Figure: 1). The resulting dendrogram clearly distinguishes the samples of\u003c/b\u003e \u003cb\u003eM. glabra\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eM. emarginata\u003c/b\u003e \u003cb\u003ehighlighting their distinct metabolite profiles. However\u003c/b\u003e, \u003cb\u003eM. glabra\u003c/b\u003e \u003cb\u003eexhibits closer metabolic resemblance to\u003c/b\u003e \u003cb\u003ePrunus\u003c/b\u003e \u003cb\u003espp. compared to\u003c/b\u003e \u003cb\u003eM. emarginata\u003c/b\u003e, \u003cb\u003esuggesting a greater risk of potential adulteration. The hierarchical clustering of cherry samples groups respective Prunus species from acerola species based on their metabolic composition. Clusters labeled A and D correspond to\u003c/b\u003e \u003cb\u003eM. glabra\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eM. emarginata\u003c/b\u003e, \u003cb\u003erespectively, while clusters B and C include\u003c/b\u003e \u003cb\u003ePrunus\u003c/b\u003e \u003cb\u003espp. The distinct clustering of\u003c/b\u003e \u003cb\u003eM. emarginata\u003c/b\u003e \u003cb\u003eunderscores its unique metabolite profile, which is markedly different from\u003c/b\u003e \u003cb\u003eM. glabra\u003c/b\u003e \u003cb\u003eand Prunus species. This separation suggests that while\u003c/b\u003e \u003cb\u003eM. glabra\u003c/b\u003e \u003cb\u003emay share some chemical characteristics with Prunus\u003c/b\u003e, \u003cb\u003eM. emarginata\u003c/b\u003e \u003cb\u003eremains phytochemically distinct.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eComparative \u0026sup1;H NMR Spectral Analysis\u003c/b\u003e: \u003cb\u003ePrunus\u003c/b\u003e \u003cb\u003espp. vs.\u003c/b\u003e \u003cb\u003eMalpighia\u003c/b\u003e \u003cb\u003espp. \u0026sup1;H NMR spectra of\u003c/b\u003e \u003cb\u003eM. emarginata, Prunus cerasus\u003c/b\u003e, \u003cb\u003eand\u003c/b\u003e \u003cb\u003ePrunus avium\u003c/b\u003e \u003cb\u003edemonstrate clear differences in metabolite distribution (Figure: S1). Although some spectral overlaps exist, key variations are observed in regions associated with carbohydrates (3.0\u0026ndash;5.5 ppm), organic acids (2.0\u0026ndash;3.0 ppm), and aromatic compounds (6.0\u0026ndash;8.0 ppm).\u003c/b\u003e The most notable differences include:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe prominence of organic acids such as \u003cb\u003emalic acid\u003c/b\u003e (2.4\u0026ndash;3.0 ppm) in \u003cem\u003eM. emarginata\u003c/em\u003e, which is significantly reduced or absent in \u003cem\u003ePrunus\u003c/em\u003e spp.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHigher concentrations of \u003cb\u003eascorbic acid\u003c/b\u003e (4.0\u0026ndash;4.3 ppm) in Acerola, confirming its known vitamin C content (de Souza et al., 2002).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe presence of \u003cb\u003eferulic acid\u003c/b\u003e (6.5\u0026ndash;7.5 ppm) in \u003cem\u003eM. emarginata\u003c/em\u003e, a unique authentication marker absent in \u003cem\u003ePrunus\u003c/em\u003e spp.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThese spectral differences validate the use of \u0026sup1;H NMR fingerprinting as a reliable method for species authentication, ensuring that \u003cem\u003eMalpighia\u003c/em\u003e species can be accurately distinguished from potential adulterants such as cherry (\u003cem\u003ePrunus\u003c/em\u003e spp.).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMetabolite Assignments and Authentication Markers Elucidation of specific metabolites identifies differences among\u003c/b\u003e the key metabolite assignments for \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003eM. emarginata\u003c/em\u003e, respectively \u003cb\u003e(Figure: 2 \u0026amp; 3)\u003c/b\u003e. The assigned peaks correspond to major bioactive compounds that play a role in species differentiation (Figure: 2 \u0026amp; 3). The presence of ferulic acid and amino acids in \u003cem\u003eM. emarginata\u003c/em\u003e sets it apart from \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003ePrunus\u003c/em\u003e spp. (Figure: 2 \u0026amp; 3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe metabolites identified in \u003cem\u003eM. glabra\u003c/em\u003e include α-D-glucose (5.2\u0026ndash;5.4 ppm), β-D-glucose (4.6\u0026ndash;4.8 ppm), fructose (4.0\u0026ndash;4.5 ppm), ascorbic acid (4.0\u0026ndash;4.3 ppm), and malic acid (2.4\u0026ndash;3.0 ppm). In comparison, \u003cem\u003eM. emarginata\u003c/em\u003e metabolites encompass ferulic acid (6.5\u0026ndash;7.5 ppm), notably absent in \u003cem\u003ePrunus\u003c/em\u003e spp., along with α-glucose (5.2\u0026ndash;5.4 ppm), β-glucose (4.6\u0026ndash;4.8 ppm), fructose (4.0\u0026ndash;4.5 ppm), and malic acid (2.4\u0026ndash;3.0 ppm), the latter serving as a distinguishing marker. Additionally, amino acids such as valine, leucine, and isoleucine (0.8\u0026ndash;1.5 ppm) are specifically identified in \u003cem\u003eM. emarginata.\u003c/em\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOne of the impediments in the acceptance of herbal formulations in the medical and pharmaceutical community is the lack of standardization and quality control. This is due to unacceptable risks to human health and unjustified health claims. It is challenging to develop robust quality control parameters using analytical chemical methods because of the complex nature and inherent variability of the chemical ingredients and molecular constituents used in supplements and natural health products, (World Health Organization 2000). These challenges including that of other conventional pharmacognosy methods such as morphology, microscopy, DNA-based and phytochemical analysis have led to the demand for more robust, fit-for-purpose methods of authentication of botanical species ingredients \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR82\" citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. This is driven by consumer demand that seek natural remedies and nutrition that support health lifestyles without the use of drugs and synthetic health supplements \u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere are considerable challenges in authentication of acerola species ingredients from the commercial supply chain. Our experience and collaboration with industry members working directly with procuring \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003eM. emarginata\u003c/em\u003e materials indicates that these species cannot be distinguished based on their morphology or histology. Conventional analytical chemistry methods are often providing inconclusive reports. For example, high performance thin layer chromatography (HPTLC) analysis of acerola berries of \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003eM. emarginata\u003c/em\u003e often have identical or closely overlapping profiles with similar or highly variable acerolin content depending on product processing used by different suppliers (NHPRA members pers. Comm.). More recently the industry has moved to trading fruit as dried extracts of which there is a lack of standard methods for quality assurance protocols such as reference standards and product species verification. This problem is intensified when considering that acerola is considered a superfruit in high demand due to its high vitamin C content of which is highly perishable in transit and storage \u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e,\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e. Dehydrating acerola juice using a spray dryer has become a common solution in the supply industry to extend the product's shelf life and subsequent profit margins \u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e,\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e. The NHP community has repeatedly voice there is a gap in acerola quality assurance methods and need for research on the development of new methods.\u003c/p\u003e \u003cp\u003eThis study provides two orthogonal molecular methods for the authentication of acerola species ingredients procured in the industry supply chain. The first method utilized common DNA sequencing. Several studies have used ITS sequences as genetic markers for many botanical species \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR72\" citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e. The sequence variation of ribosomal RNA gene repeats is believed to rapidly turn over thus providing considerable interspecific variation among congeneric species \u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e. Universal PCR primers designed from highly conserved regions flanking the ITS region are available and are relatively small in size (600\u0026ndash;700 bp) with high copy number provide relative ease of amplification of the ITS region. In our study we had successful sequencing and found sufficient variation to distinguish the two commercial acerola species. However, the materials we used contained considerable amounts of DNA unlike that of highly processed extracts, which have considerably less DNA presenting challenges for PCR and sequencing \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e. Another consideration for extract materials is the presence of PCR amplification inhibiters such as concentrated phenolic compounds, acidic polysaccharides and pigments, which can be overcome by choosing appropriate DNA extraction methods that can reduce or eliminate PCR inhibitors \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Further research is needed to develop species specific probes based on unique SNPs for \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003eM. emarginata\u003c/em\u003e that could be used within specific QPCR methods. This DNA approach has been successfully used for species specific verification of highly processed supplements in the form of leaf or berry extracts have reported mini sequence-based authentication of several botanical species worked well in botanical extracts \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. ITS sequences were unique to commercial acerola species and not potential adulterants such as cherry species. However, a fit-for-purpose standard operating aimed at authenticating target species ingredients and preventing adulteration would require full ITS sequencing, which requires considerable resources (e.g., time, cost). If the materials are highly processed extracts, then targeted QPCR would be required including specific QPCR assays for all the potential adulterants of which resource intensive (e.g., time costs).\u003c/p\u003e \u003cp\u003eIn this study, \u0026sup1;H Nuclear Magnetic Resonance (NMR) metabolomic fingerprinting combined with chemometric clustering distinguished highly all samples of two Acerola species, \u003cem\u003eM. glabra\u003c/em\u003e and \u003cem\u003eM. emarginata\u003c/em\u003e, from potential adulterants belonging to the \u003cem\u003ePrunus\u003c/em\u003e genus (\u003cem\u003ePrunus cerasus\u003c/em\u003e and \u003cem\u003ePrunus avium\u003c/em\u003e). The results provide a robust metabolic fingerprint that can serve as a scientific authentication tool based on primary and secondary metabolite composition. \u0026sup1;H NMR fingerprinting, coupled with multivariate chemometric analysis, provides a powerful authentication tool for differentiating botanical species. Unlike chromatographic techniques, which can be manipulated by introducing synthetic analogs, NMR-based authentication relies on the holistic metabolite spectrum, making it more resistant to adulteration \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. The authentication of commercial acerola is particularly significant due to its high economic value and susceptibility to adulteration with cherry derivatives. The hierarchical clustering of metabolites indicates that while \u003cem\u003eM. glabra\u003c/em\u003e exhibits some spectral resemblance to \u003cem\u003ePrunus\u003c/em\u003e spp., \u003cem\u003eM. emarginata\u003c/em\u003e remains chemically distinct. By integrating metabolite-specific peak ratios, particularly malic acid and ascorbic acid content, a more rigorous authentication framework is established. This approach of provides both a species ingredient identification tools while providing verification of specific bioactive metabolites that are of value to health minded consumers. The elucidation of specific bioactive metabolites is particularly valuable for product claims and specific ingredients on product labels.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTwo methods provide novel tools for the quality assurance of acerola species procured in the industry supply chain. DNA methods have several limitations for berry extracts and may be cost prohibitive if the goal is to detect species adulteration. NMR fingerprinting can be used for berry extracts and has the benefit of authenticating acerola species ingredients whilst detecting any adulterants in a single analysis. The resulting NMR spectra also provide quantitative estimates of bioactive phytochemicals negating the need for further analytical chemistry methods. This study highlights the application of NMR fingerprinting as a critical quality control measure in the natural health product and food industry.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Natural health product research alliance (NHPRA), University of Guelph for supporting this study. We would like to thank the Genomics facility, University of Guelph for their help in carrying out experiments in their lab and also for their timely help and assistance whenever needed. Thomas Henry is greatly acknowledged for his help in the wet lab.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings of this study are included in the article and supplementary material. Any additional inquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for this research was provided by the Natural Health Product Research Alliance,\u003c/p\u003e\n\u003cp\u003eUniversity of Guelph, grant number 053312.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSub.R. and S.G.N conceived the project and experiments; Sub.R and Sne. R. carried out the DNA molecular work and analysis; V.V. Sne. R. and A.T. carried out the NMR metabolite lab work and analysis; Sub.R. led the manuscript writing, and all other authors contributed to writing, editing, reading and accepting the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that Dr Ragupathy is the trained taxonomist who identified all plants. All the vouchers are recorded within Table S1 and the specimens were deposited at the Natural Health Products Research Alliance, the University of Guelph. The plants used in this study are common, commercially available species that do not require any permits/permissions/licenses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLaurindo, L. F. et al. 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AOAC Int.\u003c/em\u003e \u003cb\u003e102\u003c/b\u003e, 1798\u0026ndash;1807 (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Barbados cherry, DNA identification, NMR fingerprints, metabolite spectra, adulteration, food security","lastPublishedDoi":"10.21203/rs.3.rs-6372499/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6372499/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAcerola (Barbados cherries) has become a highly traded superfruit because it contains many phytonutrients and is a good source of vitamin C. The fruits of \u003cem\u003eMalpighia glabra\u003c/em\u003e, and \u003cem\u003eM. emarginata\u003c/em\u003e are utilized in food products, dietary supplements and natural health products. However, there are differences among the fruit of \u003cem\u003eMalpighia\u003c/em\u003e species with respect to phytochemicals, nutrient value and clinical research. Furthermore, there is evidence of adulteration with other fruit such as cherries (\u003cem\u003ePrunus\u003c/em\u003e spp.). Unfortunately, conventional morphological examination does not distinguish acerola fruit species. Furthermore, no published methods are available to distinguish the fruits of these species including chemical and DNA based techniques. This risk to quality assurance (QA) is increased when considering processed berries into juice or powdered ingredients of which are the most common source for manufactures. This lack of QA methods also increases the risk of adulteration with cheaper fruit from other species. The goal of this research is to provide orthogonal molecular methods to authenticate Acerola fruit ingredients and discuss the benefits and constraints of these two different methods. This research supports quality assurance (QA) programs with fit-for-purpose methods for verifying the authenticity of acerola species ingredients from suppliers.\u003c/p\u003e","manuscriptTitle":"Development of molecular diagnostic methods to distinguish Acerola species for quality assurance of food, dietary supplements and natural health products","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-15 16:06:07","doi":"10.21203/rs.3.rs-6372499/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"331350085781394653147855902010868822697","date":"2025-05-15T04:48:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51069781554501231474978492926272259808","date":"2025-05-13T07:40:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-13T07:23:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-21T11:28:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-14T04:10:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-11T04:18:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-04T00:41:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ed826c46-48d7-40a3-8bcb-2c768f42c553","owner":[],"postedDate":"May 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":48489610,"name":"Biological sciences/Biological techniques"},{"id":48489611,"name":"Biological sciences/Chemical biology"},{"id":48489612,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-08-11T16:01:31+00:00","versionOfRecord":{"articleIdentity":"rs-6372499","link":"https://doi.org/10.1038/s41598-025-12408-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-08-04 15:57:00","publishedOnDateReadable":"August 4th, 2025"},"versionCreatedAt":"2025-05-15 16:06:07","video":"","vorDoi":"10.1038/s41598-025-12408-6","vorDoiUrl":"https://doi.org/10.1038/s41598-025-12408-6","workflowStages":[]},"version":"v1","identity":"rs-6372499","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6372499","identity":"rs-6372499","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}