A Reproducible HPLC Method for Phenolic and Carbohydrate Analysis in Juneberry (Amelanchier alnifolia Nutt.)

A Reproducible HPLC Method for Phenolic and Carbohydrate Analysis in Juneberry (Amelanchier alnifolia Nutt.) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Reproducible HPLC Method for Phenolic and Carbohydrate Analysis in Juneberry (Amelanchier alnifolia Nutt.) Gavin Smith, Bibek Adhikari, Sanam Parajuli, Ananda Nanjundaswamy, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9520495/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Amelanchier alnifolia Nutt. (Juneberry) is a native North American fruit that has gained increasing interest for its horticultural potential and presumed food values. Despite this growing interest, comprehensive nutritional and phytochemical characterization of Juneberry cultivars remains limited. This study describes the development of a high-performance liquid chromatography (HPLC) method for the extraction and quantification of phenolic compounds and carbohydrates within freeze-dried A . alnifolia samples. The phenolic compounds were extracted from the samples using a 1:1 methanol to water solution. The extract was then analyzed on a C30 reverse-phase column with a C18 guard column under gradient elution with HPLC-grade aqueous 5% o-phosphoric acid and methanol as the mobile phase. Both hydroxycinnamic acids and hydroxybenzoic acids, subclasses of phenolic acids, were analyzed using PDA detection at 310 nm and 215 nm, respectively. The soluble sugars, glucose and fructose as well as the soluble sugar alcohol sorbitol were extracted using HPLC-grade water and separated via a Ca 2+ monosaccharide column under isocratic conditions. Detection was performed by a refractive index detector (RID). This method provides a way to reproduce chromatographic separation, extraction, and quantification of high enough quality for comparative biochemical characterization of juneberry cultivars that can be applied to a broad range of fruits rich in phenolic compounds. Hydroxycinnamic acids Hydroxybenzoic acids Phenolic compounds Method development Antioxidant C30 column Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The Juneberry ( Amelanchier alnifolia Nutt., Family Rosaceae) is a small pome fruit comparable (Fig. 1 ) to the size of a blueberry (approximately 0.5–1.0 cm in diameter) with a tender exocarp enclosing numerous small seeds [ 1 ]. The fruits are rich in phytochemical compounds, including hydroxycinnamic acids, hydroxybenzoic acids (Fig. 2 ), and various forms of soluble sugars positioning Juneberry among phenolic‑rich berry matrices of nutritional and analytical relevance [ 2 ]Click or tap here to enter text.. Outside of their biochemical attributes, Juneberry has long held cultural, nutritional, and subsistence importance for Indigenous peoples of the US Northern Plains, particularly the Mandan, Hidatsa, and Arikara (MHA) Tribal Nations. Traditionally consumed fresh, dried, or incorporated into foods such as pemmican , Juneberries were a critical seasonal food source that supported winter survival and were embedded in cultural practices and intergenerational knowledge systems [ 1 , 3 ]. Natural Juneberry stands along the Missouri River were extensively reduced during the mid-20th-century construction of the Garrison Dam and the subsequent creation of Lake Sakakawea on the Fort Berthold Reservation, resulting in the loss of access to this culturally significant plant. Natural Juneberry stands along the Missouri River were extensively reduced during the mid-20th-century construction of the Garrison Dam and the subsequent creation of Lake Sakakawea on the Fort Berthold Reservation, resulting in the loss of access to this culturally significant plant. As a result, the reintroduction and cultivation of Juneberry have become priorities within Tribal communities for reasons that include cultural revitalization, food sovereignty, and nutritional health [ 3 ]. Despite this renewed interest, compared to commercial berries, Juneberries are under-researched in terms of varietal differences, nutrient composition, and their integration into traditional food matrices like pemmican . Production is also inconsistent across cultivars, and yearly yield is unpredictable, perhaps due to hybridization and polyploidy, complicating taxonomic identification. Despite this renewed interest, analytical studies characterizing Juneberry phytochemical and carbohydrate profiles remain limited, underscoring the need for reproducible and validated analytical methods [ 4 ]. Phenolic compounds in Juneberries consist of hydroxylated aromatic structures that contribute to the flavor, color, and oxidative stability and are commonly classified as flavonoids, phenolic acids, tannins, stilbenes, and lignans [ 5 , 6 ]. Phenolic compounds and content can significantly vary among cultivars. A standardized analysis protocol, especially a high-performance liquid chromatography (HPLC) method, essentially ensures reproducible quantification, enables comparisons across cultivars, and provides a robust foundation for biochemical investigations [ 7 , 8 ]. There is no published literature showcasing a validated HPLC method for the extraction and quantification of both phenolic acids and soluble carbohydrates in Juneberry samples. Here, we present a validated HPLC method for the extraction and quantification of individual phenolic acids and soluble carbohydrates from freeze-dried juneberry samples. The method integrates optimized solvent extraction procedures with chromatographic separation using a reverse phase C30 column and a photodiode array (PDA) detection for phenolic compounds, along with a Ca 2+ monosaccharide column with refractive index detection (RID) for carbohydrate analysis. These methods offer a reproducible and reliable framework for HPLC-based analysis of phenolic compounds and soluble carbohydrates in Juneberry samples. Experimental Section Reagents and Materials Analytical-grade methanol, 5% o-phosphoric acid, and HPLC-grade water were obtained from Fisher Scientific (Waltham, MA, USA). The phenolic standards: chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids were all obtained from MilliporeSigma (Sigma-Aldrich) (Burlington, MA, USA). The carbohydrate standards, including glucose, fructose, sucrose, and sorbitol, were also purchased from MilliporeSigma. Instrumentation Phenolic compounds were analyzed using the Shimadzu LC-40D HPLC system (Kyoto, Japan). This system includes the Nexera HPLC/UHPLC Degasser (DGU-403/405), System Controller (CBM-40), Column Oven (CTO-40C), and Autosampler (SIL-40/SIL-40C). UV detection was performed by the Nexera Photodiode Array Detector (SPD-M40). Chromatographic separation of phenolics was carried out using a C30 column (150 mm x 4.6 mm) fitted with a C18 guard column (Phenomenex, Torrance, CA, USA) and maintained at 40°C. Carbohydrates and sugar alcohol (sorbitol) were also analyzed using the same Shimadzu LC-40D HPLC system but the detector used was a Nextera Refractive Index Detector (RID-20A), replacing the (SPD-M40) PDA detector. Separation of the carbohydrates was performed on a Phenomenex Rezex RCM-Monosaccharide Ca²⁺ column (300mm x 7.8mm). The column temperature was maintained at 80°C, with the flow rate of 0.6mL/min for carbohydrate analysis. Methods Chromatographic Conditions Phenolic compounds were separated using a Phenomenex C30 reverse-phase column (150 mm x 4.6 mm) fitted with a C18 guard column. The column oven was set and maintained at 40°C. The mobile phase consisted of solvent A (5% o-phosphoric acid) and solvent B (methanol), delivered under gradient elution over 25 minutes of run time at a flow rate of 0.9 mL min − 1 . The gradient began at 70% solvent C and 30% solvent D and then transitioned to 50:50 (C to D) by the 20-minute mark. From 20 to 25 minutes, the concentration moved back toward the initial 70:30 composition. An injection volume of 10 µL was used for all phenolic standards and berry samples. Detection was performed using a Nexera Photodiode Array Detector (PDA) (SPD-M40). The chromatographs (Fig. 3 ) revealed that hydroxycinnamic acids (chlorogenic, caffeic, p-coumaric, and ferulic acids) exhibit absorption maxima at 310 nm, while hydroxybenzoic acids (gallic and vanillic acids) had maxima at 215 nm. Absorption spectra were acquired at both 310 nm and 215 nm for the best quantification of the chromatograph peaks and peak areas. The conditions described provided reproducible retention times and distinct peaks suitable for phenolic content quantification. The phenolic acids peak retention times ranged from 6–7, 8–9, 11–12, 12–13, 4–5, and 8–9 minutes for chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids, respectively. Carbohydrate separation was conducted on a Phenomenex Rezex RCM-Monosaccharide Ca²⁺ column (300mm x 7.8mm). The column oven was set and maintained at 80°C. HPLC-grade water was used as the mobile phase under isocratic elution at a flow rate of 0.6mL/min. An injection volume of 10 µL was used for all the carbohydrate standards and the juneberry samples. Detection was performed using a Nextera (RID-20A), replacing the (SPD-M40) PDA detector previously used for phenolics. This method created reproducible retention times that were suitable for the quantification of glucose, fructose, and sorbitol within a 25-minute run time. Standard and Stock Solution Preparation Phenolic standard solutions were prepared for the standards of chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids. Each phenolic standard was dissolved in a 50:50 methanol-water solvent (50% methanol). To obtain a 1:100 standard solution concentration, ~ 0.1 g of standard was dissolved in 100 mL of the 50% methanol solvent. Leaving the standard solutions at a concentration of ~ 1 mg/mL. The solutions were vortexed thoroughly until completely dissolved. The solutions were then filtered through 0.40 µm Phenomenex syringe filters to clean the solution of any particles before injection. Standard solutions were then analyzed through HPLC to determine the retention times. A stock solution was also made by combining ~ 0.1 g of each standard into the same 100 mL 50% methanol solution. From the stock solution, a 10-point calibration curve was created from 10 to100µg/mL (Fig. 4 ). After filtration and dilution, the vials for the calibration were then used to construct the calibration curve. A 10 µL injection volume and a flow rate of 0.9 mL/min-1 was employed on the C30 column with a C18 guard column for phenolics. The carbohydrate standard solutions were prepared in a similar manner. Glucose, fructose, sucrose, and sorbitol were each dissolved in HPLC-grade water. To obtain a 1:100 standard solution, 1 g of standard was dissolved in 100 mL of HPLC-grade water. Each solution was thoroughly vortexed until completely dissolved and then filtered through a 0.40 µm Phenomenex syringe filter to clean the solution of any particles before injection. The peak retention times for glucose, fructose, sucrose, and sorbitol ranged between 11–12, 13–14, 7–8, and 20–21 minutes, respectively. After filtration, the calibration solutions were injected 50 µL injection volume with a flow rate of 0.6mL/min-1 on the Phenomenex Rezex RCM-Monosaccharide Ca²⁺ column (300mm x 7.8mm). Sample Preparation Ripened berries of Amelanchier alnifolia representing four cutivars grown on the Fort Berthold Indian Reservation in north central North Dakota were collected on June 16, 2024. Following collection, the berries were stored on dry ice to preserve their biochemical integrity before arriving at the laboratory. After arriving at the laboratory, the berries were stored at -20°C until freeze-drying could be completed. To prepare for phenolic and carbohydrate analysis, all Juneberry fruits were freeze-dried to ensure preservation of the phenolic compounds, flavonoids, anthocyanins, and other thermally sensitive compounds. Freeze-drying was selected over hot air drying as it is significantly better than hot air drying at preserving thermally sensitive compounds, which tend to break down at higher temperatures [ 9 ]. They were freeze-dried at -80°C with a pressure of 0.001 bar for 72 hours using a Labconco (Kansas City, MO, USA) bench-top model freeze dryer with a 4.5 L chamber capacity. The resulting sample moisture content was measured at less than 0.1%. Following lyophilization, the dried Juneberries were ground manually into a fine powder using a mortar and pestle. The powdered samples were stored in 15 mL centrifuge tubes covered in tinfoil to protect them from UV light. Only whole, unprocessed juneberries were used, as food processing can substantially alter phenolic and carbohydrate concentrations [ 10 ]. All materials that were prepared for HPLC analysis were stored at -20°C until analysis. Samples were prepared for analysis using the same method as used for the standards. Samples, for phenolics, were analyzed at two time points: right after extraction (15 minutes) and after 24-hours extraction, in 50% methanol. Similarly, sugar being instantly soluble, only 15 minutes extractions in HPLC-grade water were subjected to carbohydrate analysis. Results and Discussion Drying and Extraction of Juneberry Samples The method used freeze-drying as a way to remove moisture from the juneberries. Freeze-drying is reported to effectively remove moisture from berries while preserving phenolic compounds and minimizing degradation associated with more thermally intensive methods [ 11 ]. The preservation shown by freeze-drying is also present within several other studies that show it has a higher capacity for preserving phenolic content and antioxidant capacity than hot-air or thermal drying [ 12 , 13 ]. Low temperature lyophilization minimizes the oxidative and thermal degradation that would have otherwise occurred if using methods such as sun or salt drying [ 14 ]. The low temperature lyophilization method minimizes the loss of hydroxybenzoic and hydroxycinnamic acids, which were the target of analysis in this study [ 12 , 14 ]. Freeze-drying also forms ice crystals that rupture cell walls, which facilitates the solvent penetration of the 50% methanol used, improving the release of phenolics into solution. The slower the rate of freezing, the larger the ice crystals created, the more damage done to the cells of the fruit, which facilitates the penetration of solvent and release of phenolic compounds [ 15 ]. In contrast, air and oven drying usually lead to a significant loss in the total phenolics of berries as well as other plant tissues when analyzed. Freeze-drying likely contributed substantially to the total phenolics that was quantified through HPLC analysis [ 12 , 14 , 15 ]. Carbohydrate preservation is also improved through the method of freeze-drying, particularly glucose, fructose, and sorbitol. Monosaccharides are chemically stable under cold conditions, and the implementation of freeze-drying prevents thermal degradation and browning of the sugars which are reactions that can occur during thermally intensive methods. Fructose can be especially sensitive to heat undergoing caramelization or Maillard reactions when exposed to elevated temperatures. Hot air drying has been shown to reduce the amount of measurable monosaccharide content within fruit tissues due to the transformation of those monosaccharides under heat [ 16 ]. Chromatographic Separation and Detection of Phenolics and Carbohydrates Till date, very few studies have reported chromatographic detection of phenolics in Juneberry fruits; however, all of them have followed different extraction methods [ 10 , 17 , 18 ]. The HPLC method developed through this study provided clean separation of six phenolic acid standards using a C30 column. The separation provided distinct retention times, which allowed for the identification of phenolic acids within the Juneberry samples via HPLC analysis. Separation and quantification of Phenolic compounds are challenging due to the inherent structural complexity and associated separation complexities [ 19 ]. Hydroxycinnamic acids (chlorogenic, caffeic, p-coumaric, and ferulic acids) exhibited absorption maxima at 310 nm while hydroxybenzoic acids (gallic and vanillic acids) showed maxima at 215 nm. The methanol and 5% o-phosphoric acid method created sharp symmetrical peaks across the 25-minute run time. This agrees with the effectiveness of reverse phase HPLC methods for berry phenolic compounds shown in other studies; for example, studies related to blueberries and other closely related berries have sorted both hydroxybenzoic and hydroxycinnamic acids with similar chromatographic methods [ 20 , 21 ] Click or tap here to enter text.. PDA detection allowed for the section of wavelength maxima specific to each class of phenolics being 310 nm for hydroxycinnamic acids and 215 nm for hydroxybenzoic acids. The dual wavelength approach taken allows for increased selectivity and sensitivity for phenolics that are structurally different from one another. A dual or multiple wavelength approach is commonly used in studies that quantify phenolic compounds within fruit samples [ 21 , 22 ] Click or tap here to enter text.. Juneberry samples were analyzed right after extraction and then 24-hours after initial extraction, allowing the 50% methanol to extract phenolics from the berries for 24-hours. The 50% methanol remained in contact with the freeze-dried samples during the 24-hour timeline allowing the solvent to penetrate deeper into the tissues, facilitating the release of tightly bound phenolic acids. The profiles for initial and 24-hour extraction were compared, and changes in phenolic concentrations were noted. The Ca²⁺ column with RID detection also produced distinct retention times which allowed for the identification of carbohydrates within the juneberry samples via HPLC analysis. Retention times matched the standard solutions that were run through HPLC analysis prior to the Juneberry samples. The elevated column temperature of 80°C led to peaks similar to that of phenolics in terms of being sharp and symmetrical with minimal trailing. HPLC-RID methods are commonly used to identify, analyze, and quantify carbohydrates within foods [ 23 – 26 ]Click or tap here to enter text.. The glucose, fructose, sucrose, and sorbitol concentrations were found in the ranges of 121.59-179.22, 130.87-217.69, 21.61–36.31, and 96.18-177.26 mg/g, respectively. The higher fructose compared to glucose, as shown by glucose:fructose < 1, aligns with earlier findings of Saskatoon fruits by Rogiers and Knowles [ 17 ]. The total sucrose content observed to be less than one-tenth of all the analyzed sugars is in agreement with that reported, in a different species of Juneberry ( A. lamarckii ), by Mikulic-Petkovsek et al. [ 10 ]. Comparison with Related Berry Matrices Juneberries should be viewed as a phenolic-rich fruit that extends beyond the six acids targeted in the present method, because mature juneberries contain anthocyanins, flavanols, and hydroxycinnamate-type phenolics, and genotype work has identified 29 polyphenolic compounds, including 9 phenolic acids, 9 flavanols, 7 flavan-3-ols, and 4 anthocyanins [ 27 , 28 ]. The current method captures a defined phenolic-acid subset of chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids rather than the full juneberry polyphenolic profile (Table 1 ). However, this targeted analysis remains important because chlorogenic and neochlorogenic acids were reported as the major phenolic acids across Saskatoon berry genotypes, accounting for most of the phenolic-acid concentration [ 28 ]. In the context of this study, the observed increase in chlorogenic acid after the 24-hour extraction is consistent with the broader literature on juneberries and supports the use of chlorogenic acid-centered profiling as a way to compare cultivars. Comparison with other related berries helps give context to these findings. In blueberries, chlorogenic acid is reported as the predominant phenolic acid in both low and highbush fruit in an HPLC-MS comparison of two predominant blueberry species on the US market [ 29 ]. This suggests that Juneberry and blueberry share phenolic-acid features, more specifically chlorogenic acid-rich fraction, even though both fruits contain a much broader flavonoid range [ 29 ]. The chokeberry is another great contrast because the black chokeberry fruit is recognized as an especially polyphenol-and anthocyanin-rich berry [ 30 ]. At the same time, however, chlorogenic acids also remain important in chokeberry, and were reported as the dominant phenolic compound in undigested black chokeberry fruit samples in a recent comparative study [ 31 ]. Altogether, these comparisons suggest that juneberries are chemically more similar to blueberries, while chokeberries contain a higher overall level of phenolics, especially pigment compounds like anthocyanins. A similar contextual comparison can be made for the carbohydrate fraction, where the current method has captured the glucose, fructose, sucrose, and sorbitol concentrations (Table 2 ). Saskatoon berry genotypes have been reported to contain fructose and glucose as the dominant sugars, with sorbitol also present as a major soluble carbohydrate [ 28 ]. A study carried out by Mikulic-Petkovsek et al. in A. lamarckii likewise identified glucose, fructose, and sorbitol as the main sugars, which matches the analyte panel selected in the present RID method [ 32 ]. By comparison, black chokeberry can be more sorbitol-driven, because sorbitol was reported as the main carbohydrate in fresh aronia fruit and represented 61%–68% of the low-molecular-weight carbohydrate fraction in Bulgarian samples [ 30 ]. This makes the current glucose, fructose, and sorbitol panel useful not only for within Juneberry cultivar comparisons, but also for distinguishing Juneberry from other dark-fruit carbohydrate profiles that are weighed differently across individual sugars and sugar alcohols. Table 1 Phenolic compound concentrations (µg/g) in Juneberry samples immediately after extraction (Initial) and following 24‑hour extraction, with percentage change. Phenolic Compound Extraction Time Sample 1 (µg/g) Sample 2 (µg/g) Sample 3 (µg/g) Sample 4 (µg/g) Chlorogenic acid Initial 56.42 77.70 44.75 92.99 24 h 80.73 92.59 64.45 128.84 Percent change (%) 43.10 19.16 44.03 38.54 Ferulic acid Initial 13.84 13.60 0.00 1.04 24 h 16.40 15.95 2.32 1.18 Percent change (%) 18.54 17.26 N/A 13.94 Caffeic acid Initial 11.40 2.60 5.25 25.00 24 h 11.21 1.87 5.03 33.40 Percent change (%) −1.67 −28.20 −4.13 33.62 p-Coumaric acid Initial 2.12 3.62 15.57 23.20 24 h 2.71 4.41 20.71 25.27 Percent change (%) 27.47 21.78 33.02 8.92 Vanillic acid Initial 55.52 24.30 31.97 118.83 24 h 102.49 28.53 37.28 127.04 Percent change (%) 84.59 17.43 16.62 6.91 Gallic acid Initial 89.04 86.72 71.69 112.35 24 h 149.78 108.73 102.74 132.58 Percent change (%) 68.23 25.37 43.31 18.01 We observed that with the increment in extraction time, the individual phenolic concentration increased by at least 8%, except for caffeic acid—decreased in—samples 1–3. Table 2 Carbohydrate concentrations (mg/g) in Juneberry samples immediately after extraction. Carbohydrates (mg/g) Sample 1 Sample 2 Sample 3 Sample 4 Glucose 179.22 151.26 121.59 161.83 Fructose 217.69 175.45 130.87 163.59 Glucose: Fructose 0.82 0.86 0.93 0.99 Sucrose 21.61 22.14 31.59 36.31 Sorbitol 173.43 96.18 148.19 177.26 Method Validation and Performance Calibration curves constructed from the 10-point dilution of the mixed phenolic stock solution showed a linearity of R 2 > 0.99 for all phenolic compounds (Fig. 4 ). This aligns with the validation parameters that have been reported in other fruit related phenolic HPLC methods [ 23 , 25 ]Click or tap here to enter text.. Prior to the calibration curve being constructed, standards of each phenolic acid were run through HPLC analysis. When running the standards through HPLC, the retention time was taken note of to compare to the stock solution from which the calibration curve was created and actual juneberry samples. The peaks and retention times of standards correlated directly with the peaks of the combined stock solution. Conclusion The HPLC method developed in this study provides a reliable and sensitive protocol for the extraction, separation, and quantification of both phenolic compounds and soluble carbohydrates in freeze-dried juneberry ( A. alnifolia ) fruit. Phenolics were extracted via 50% methanol and analyzed using a reverse phase C30 column with PDA detection and a mobile phase of 5% o-phosphoric acid and methanol. Carbohydrates were extracted and separated via HPLC-grade water with a Ca 2+ monosaccharide column and RID detection. Both methods resulted in strong linearity with precision and chromatographic resolution. Through freeze-drying, the method maximized the amount of preserved phenolic and carbohydrate structures. This ensured greater and more consistent yields while limiting structural degradation that is associated with more thermally intensive drying methods. This method relies only upon HPLC instrumentation and commonly used detectors. Aside from minor column and detector modifications, the method can be readily adopted in most biochemistry laboratories. While MS can provide valuable confirmatory information, it is not required for routine analysis in the presented method. As a result, HPLC offers a practical and substantially more cost‑effective alternative to MS-based methods, particularly for high‑throughput or bulk sample analysis. Abbreviations HPLC: High-performance liquid chromatography PDA: Photodiode array detector RID: Refractive index detector Declarations The authors declare no conflict of interests. Acknowledgements This project is supported by the USDA NIFA (Award #2025-38424-45225) and the South Dakota Agricultural Experiment Station. The authors also gratefully acknowledge Emily Ringgenberg, Ryan Johnson, and Vishnu Pasupuleti for their technical assistance in the laboratory. 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Saracila, M., et al., Comparative analysis of black chokeberry (Aronia melanocarpa L.) fruit, leaves, and pomace for their phytochemical composition, antioxidant potential, and polyphenol bioaccessibility . Foods, 2024. 13(12): p. 1856. Mikulic-Petkovsek, M., et al., Wild Prunus fruit species as a rich source of bioactive compounds . Journal of Food Science, 2016. 81(8): p. C1928–C1937. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 12 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers invited by journal 30 Apr, 2026 Editor assigned by journal 29 Apr, 2026 Submission checks completed at journal 28 Apr, 2026 First submitted to journal 24 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9520495","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635717883,"identity":"0a54a991-ba0d-43f6-b6b9-f08a011262ae","order_by":0,"name":"Gavin Smith","email":"","orcid":"","institution":"South Dakota State University","correspondingAuthor":false,"prefix":"","firstName":"Gavin","middleName":"","lastName":"Smith","suffix":""},{"id":635717884,"identity":"c3980e41-2511-4429-aa4d-779c86e27f1c","order_by":1,"name":"Bibek Adhikari","email":"","orcid":"","institution":"South Dakota State University","correspondingAuthor":false,"prefix":"","firstName":"Bibek","middleName":"","lastName":"Adhikari","suffix":""},{"id":635717885,"identity":"24346d29-5f2b-4fae-bd89-cf92fe0a68b6","order_by":2,"name":"Sanam Parajuli","email":"","orcid":"","institution":"South Dakota State University","correspondingAuthor":false,"prefix":"","firstName":"Sanam","middleName":"","lastName":"Parajuli","suffix":""},{"id":635717886,"identity":"40a3efa0-7149-44db-ae9d-9276712ad067","order_by":3,"name":"Ananda Nanjundaswamy","email":"","orcid":"","institution":"South Dakota State University","correspondingAuthor":false,"prefix":"","firstName":"Ananda","middleName":"","lastName":"Nanjundaswamy","suffix":""},{"id":635717887,"identity":"608979cb-fd46-420b-a364-025d95d5dbf3","order_by":4,"name":"Kerry Hartman","email":"","orcid":"","institution":"Nueta Hidatsa Sahnish College","correspondingAuthor":false,"prefix":"","firstName":"Kerry","middleName":"","lastName":"Hartman","suffix":""},{"id":635717888,"identity":"eace96e6-1585-4dbf-8530-abf2e4ff57ff","order_by":5,"name":"Madhav P. Nepal","email":"data:image/png;base64,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","orcid":"","institution":"South Dakota State University","correspondingAuthor":true,"prefix":"","firstName":"Madhav","middleName":"P.","lastName":"Nepal","suffix":""}],"badges":[],"createdAt":"2026-04-24 20:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9520495/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9520495/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108880739,"identity":"4efc7845-ba1d-4c33-8795-7a7d9f085427","added_by":"auto","created_at":"2026-05-09 16:43:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":989756,"visible":true,"origin":"","legend":"\u003cp\u003eFruiting twigs of Juneberry shrub bearing ripened berries (photo by Nathan Bronson, Menan Idaho).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9520495/v1/1cf8fdc0f3bcfb08c9a504cf.png"},{"id":108977114,"identity":"d436b625-f00d-492c-a101-6519c65f9329","added_by":"auto","created_at":"2026-05-11 11:30:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":123664,"visible":true,"origin":"","legend":"\u003cp\u003eChemical structure of phenolic acids targeted in the present HPLC method for Juneberry. Shown are hydroxycinnamic acids (chlorogenic, caffeic, p-coumaric, and ferulic acids) and hydroxybenzoic acids (gallic and vanillic acids). Chemical structures were drawn using PubChem Sketcher.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9520495/v1/17c4a318ea1c27be8a5015e5.png"},{"id":108880741,"identity":"c07b35e7-a9c1-4ba0-ba59-d60baee87c45","added_by":"auto","created_at":"2026-05-09 16:43:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":90888,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative HPLC chromatograms of phenolic acid standards detected by PDA at 310 nm (left; hydroxycinnamic acids) and 215 nm (right; hydroxybenzoic acids).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9520495/v1/da1220672e82fedf1145a48e.png"},{"id":108880742,"identity":"0a302d12-b781-4860-ad15-261261211abd","added_by":"auto","created_at":"2026-05-09 16:43:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":169392,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration curves for individual phenolic acid standards used for HPLC quantification.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9520495/v1/a4e26abf5763bf8bd5c084b8.png"},{"id":108979476,"identity":"ba5fe35f-166d-4a84-8fa6-d24cf7fca147","added_by":"auto","created_at":"2026-05-11 11:59:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1811939,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9520495/v1/ed0cd672-727f-4ba9-836d-c3331ad26858.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Reproducible HPLC Method for Phenolic and Carbohydrate Analysis in Juneberry (Amelanchier alnifolia Nutt.)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Juneberry (\u003cem\u003eAmelanchier alnifolia\u003c/em\u003e Nutt., Family Rosaceae) is a small pome fruit comparable (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to the size of a blueberry (approximately 0.5\u0026ndash;1.0 cm in diameter) with a tender exocarp enclosing numerous small seeds [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The fruits are rich in phytochemical compounds, including hydroxycinnamic acids, hydroxybenzoic acids (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and various forms of soluble sugars positioning Juneberry among phenolic‑rich berry matrices of nutritional and analytical relevance [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]Click or tap here to enter text.. Outside of their biochemical attributes, Juneberry has long held cultural, nutritional, and subsistence importance for Indigenous peoples of the US Northern Plains, particularly the Mandan, Hidatsa, and Arikara (MHA) Tribal Nations. Traditionally consumed fresh, dried, or incorporated into foods such as \u003cem\u003epemmican\u003c/em\u003e, Juneberries were a critical seasonal food source that supported winter survival and were embedded in cultural practices and intergenerational knowledge systems [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Natural Juneberry stands along the Missouri River were extensively reduced during the mid-20th-century construction of the Garrison Dam and the subsequent creation of Lake Sakakawea on the Fort Berthold Reservation, resulting in the loss of access to this culturally significant plant. Natural Juneberry stands along the Missouri River were extensively reduced during the mid-20th-century construction of the Garrison Dam and the subsequent creation of Lake Sakakawea on the Fort Berthold Reservation, resulting in the loss of access to this culturally significant plant. As a result, the reintroduction and cultivation of Juneberry have become priorities within Tribal communities for reasons that include cultural revitalization, food sovereignty, and nutritional health [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite this renewed interest, compared to commercial berries, Juneberries are under-researched in terms of varietal differences, nutrient composition, and their integration into traditional food matrices like \u003cem\u003epemmican\u003c/em\u003e. Production is also inconsistent across cultivars, and yearly yield is unpredictable, perhaps due to hybridization and polyploidy, complicating taxonomic identification. Despite this renewed interest, analytical studies characterizing Juneberry phytochemical and carbohydrate profiles remain limited, underscoring the need for reproducible and validated analytical methods [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePhenolic compounds in Juneberries consist of hydroxylated aromatic structures that contribute to the flavor, color, and oxidative stability and are commonly classified as flavonoids, phenolic acids, tannins, stilbenes, and lignans [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Phenolic compounds and content can significantly vary among cultivars. A standardized analysis protocol, especially a high-performance liquid chromatography (HPLC) method, essentially ensures reproducible quantification, enables comparisons across cultivars, and provides a robust foundation for biochemical investigations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. There is no published literature showcasing a validated HPLC method for the extraction and quantification of both phenolic acids and soluble carbohydrates in Juneberry samples.\u003c/p\u003e \u003cp\u003eHere, we present a validated HPLC method for the extraction and quantification of individual phenolic acids and soluble carbohydrates from freeze-dried juneberry samples. The method integrates optimized solvent extraction procedures with chromatographic separation using a reverse phase C30 column and a photodiode array (PDA) detection for phenolic compounds, along with a Ca\u003csup\u003e2+\u003c/sup\u003e monosaccharide column with refractive index detection (RID) for carbohydrate analysis. These methods offer a reproducible and reliable framework for HPLC-based analysis of phenolic compounds and soluble carbohydrates in Juneberry samples.\u003c/p\u003e\n\u003ch3\u003eExperimental Section\u003c/h3\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eReagents and Materials\u003c/h2\u003e \u003cp\u003eAnalytical-grade methanol, 5% o-phosphoric acid, and HPLC-grade water were obtained from Fisher Scientific (Waltham, MA, USA). The phenolic standards: chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids were all obtained from MilliporeSigma (Sigma-Aldrich) (Burlington, MA, USA). The carbohydrate standards, including glucose, fructose, sucrose, and sorbitol, were also purchased from MilliporeSigma.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInstrumentation\u003c/h3\u003e\n\u003cp\u003ePhenolic compounds were analyzed using the Shimadzu LC-40D HPLC system (Kyoto, Japan). This system includes the Nexera HPLC/UHPLC Degasser (DGU-403/405), System Controller (CBM-40), Column Oven (CTO-40C), and Autosampler (SIL-40/SIL-40C). UV detection was performed by the Nexera Photodiode Array Detector (SPD-M40). Chromatographic separation of phenolics was carried out using a C30 column (150 mm x 4.6 mm) fitted with a C18 guard column (Phenomenex, Torrance, CA, USA) and maintained at 40\u0026deg;C.\u003c/p\u003e \u003cp\u003eCarbohydrates and sugar alcohol (sorbitol) were also analyzed using the same Shimadzu LC-40D HPLC system but the detector used was a Nextera Refractive Index Detector (RID-20A), replacing the (SPD-M40) PDA detector. Separation of the carbohydrates was performed on a Phenomenex Rezex RCM-Monosaccharide Ca\u0026sup2;⁺ column (300mm x 7.8mm). The column temperature was maintained at 80\u0026deg;C, with the flow rate of 0.6mL/min for carbohydrate analysis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eChromatographic Conditions\u003c/h2\u003e \u003cp\u003ePhenolic compounds were separated using a Phenomenex C30 reverse-phase column (150 mm x 4.6 mm) fitted with a C18 guard column. The column oven was set and maintained at 40\u0026deg;C. The mobile phase consisted of solvent A (5% o-phosphoric acid) and solvent B (methanol), delivered under gradient elution over 25 minutes of run time at a flow rate of 0.9 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The gradient began at 70% solvent C and 30% solvent D and then transitioned to 50:50 (C to D) by the 20-minute mark. From 20 to 25 minutes, the concentration moved back toward the initial 70:30 composition. An injection volume of 10 \u0026micro;L was used for all phenolic standards and berry samples. Detection was performed using a Nexera Photodiode Array Detector (PDA) (SPD-M40). The chromatographs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) revealed that hydroxycinnamic acids (chlorogenic, caffeic, p-coumaric, and ferulic acids) exhibit absorption maxima at 310 nm, while hydroxybenzoic acids (gallic and vanillic acids) had maxima at 215 nm. Absorption spectra were acquired at both 310 nm and 215 nm for the best quantification of the chromatograph peaks and peak areas. The conditions described provided reproducible retention times and distinct peaks suitable for phenolic content quantification. The phenolic acids peak retention times ranged from 6\u0026ndash;7, 8\u0026ndash;9, 11\u0026ndash;12, 12\u0026ndash;13, 4\u0026ndash;5, and 8\u0026ndash;9 minutes for chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCarbohydrate separation was conducted on a Phenomenex Rezex RCM-Monosaccharide Ca\u0026sup2;⁺ column (300mm x 7.8mm). The column oven was set and maintained at 80\u0026deg;C. HPLC-grade water was used as the mobile phase under isocratic elution at a flow rate of 0.6mL/min. An injection volume of 10 \u0026micro;L was used for all the carbohydrate standards and the juneberry samples. Detection was performed using a Nextera (RID-20A), replacing the (SPD-M40) PDA detector previously used for phenolics. This method created reproducible retention times that were suitable for the quantification of glucose, fructose, and sorbitol within a 25-minute run time.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStandard and Stock Solution Preparation\u003c/h3\u003e\n\u003cp\u003ePhenolic standard solutions were prepared for the standards of chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids. Each phenolic standard was dissolved in a 50:50 methanol-water solvent (50% methanol). To obtain a 1:100 standard solution concentration, ~\u0026thinsp;0.1 g of standard was dissolved in 100 mL of the 50% methanol solvent. Leaving the standard solutions at a concentration of ~\u0026thinsp;1 mg/mL. The solutions were vortexed thoroughly until completely dissolved. The solutions were then filtered through 0.40 \u0026micro;m Phenomenex syringe filters to clean the solution of any particles before injection. Standard solutions were then analyzed through HPLC to determine the retention times. A stock solution was also made by combining\u0026thinsp;~\u0026thinsp;0.1 g of each standard into the same 100 mL 50% methanol solution. From the stock solution, a 10-point calibration curve was created from 10 to100\u0026micro;g/mL (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). After filtration and dilution, the vials for the calibration were then used to construct the calibration curve. A 10 \u0026micro;L injection volume and a flow rate of 0.9 mL/min-1 was employed on the C30 column with a C18 guard column for phenolics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe carbohydrate standard solutions were prepared in a similar manner. Glucose, fructose, sucrose, and sorbitol were each dissolved in HPLC-grade water. To obtain a 1:100 standard solution, 1 g of standard was dissolved in 100 mL of HPLC-grade water. Each solution was thoroughly vortexed until completely dissolved and then filtered through a 0.40 \u0026micro;m Phenomenex syringe filter to clean the solution of any particles before injection. The peak retention times for glucose, fructose, sucrose, and sorbitol ranged between 11\u0026ndash;12, 13\u0026ndash;14, 7\u0026ndash;8, and 20\u0026ndash;21 minutes, respectively.\u003c/p\u003e \u003cp\u003eAfter filtration, the calibration solutions were injected 50 \u0026micro;L injection volume with a flow rate of 0.6mL/min-1 on the Phenomenex Rezex RCM-Monosaccharide Ca\u0026sup2;⁺ column (300mm x 7.8mm).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample Preparation\u003c/h2\u003e \u003cp\u003eRipened berries of \u003cem\u003eAmelanchier alnifolia\u003c/em\u003e representing four cutivars grown on the Fort Berthold Indian Reservation in north central North Dakota were collected on June 16, 2024. Following collection, the berries were stored on dry ice to preserve their biochemical integrity before arriving at the laboratory. After arriving at the laboratory, the berries were stored at -20\u0026deg;C until freeze-drying could be completed. To prepare for phenolic and carbohydrate analysis, all Juneberry fruits were freeze-dried to ensure preservation of the phenolic compounds, flavonoids, anthocyanins, and other thermally sensitive compounds. Freeze-drying was selected over hot air drying as it is significantly better than hot air drying at preserving thermally sensitive compounds, which tend to break down at higher temperatures [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. They were freeze-dried at -80\u0026deg;C with a pressure of 0.001 bar for 72 hours using a Labconco (Kansas City, MO, USA) bench-top model freeze dryer with a 4.5 L chamber capacity. The resulting sample moisture content was measured at less than 0.1%.\u003c/p\u003e \u003cp\u003eFollowing lyophilization, the dried Juneberries were ground manually into a fine powder using a mortar and pestle. The powdered samples were stored in 15 mL centrifuge tubes covered in tinfoil to protect them from UV light. Only whole, unprocessed juneberries were used, as food processing can substantially alter phenolic and carbohydrate concentrations [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. All materials that were prepared for HPLC analysis were stored at -20\u0026deg;C until analysis. Samples were prepared for analysis using the same method as used for the standards. Samples, for phenolics, were analyzed at two time points: right after extraction (15 minutes) and after 24-hours extraction, in 50% methanol. Similarly, sugar being instantly soluble, only 15 minutes extractions in HPLC-grade water were subjected to carbohydrate analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDrying and Extraction of Juneberry Samples\u003c/h2\u003e \u003cp\u003eThe method used freeze-drying as a way to remove moisture from the juneberries. Freeze-drying is reported to effectively remove moisture from berries while preserving phenolic compounds and minimizing degradation associated with more thermally intensive methods [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The preservation shown by freeze-drying is also present within several other studies that show it has a higher capacity for preserving phenolic content and antioxidant capacity than hot-air or thermal drying [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Low temperature lyophilization minimizes the oxidative and thermal degradation that would have otherwise occurred if using methods such as sun or salt drying [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The low temperature lyophilization method minimizes the loss of hydroxybenzoic and hydroxycinnamic acids, which were the target of analysis in this study [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFreeze-drying also forms ice crystals that rupture cell walls, which facilitates the solvent penetration of the 50% methanol used, improving the release of phenolics into solution. The slower the rate of freezing, the larger the ice crystals created, the more damage done to the cells of the fruit, which facilitates the penetration of solvent and release of phenolic compounds [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In contrast, air and oven drying usually lead to a significant loss in the total phenolics of berries as well as other plant tissues when analyzed. Freeze-drying likely contributed substantially to the total phenolics that was quantified through HPLC analysis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCarbohydrate preservation is also improved through the method of freeze-drying, particularly glucose, fructose, and sorbitol. Monosaccharides are chemically stable under cold conditions, and the implementation of freeze-drying prevents thermal degradation and browning of the sugars which are reactions that can occur during thermally intensive methods. Fructose can be especially sensitive to heat undergoing caramelization or Maillard reactions when exposed to elevated temperatures. Hot air drying has been shown to reduce the amount of measurable monosaccharide content within fruit tissues due to the transformation of those monosaccharides under heat [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eChromatographic Separation and Detection of Phenolics and Carbohydrates\u003c/h2\u003e \u003cp\u003eTill date, very few studies have reported chromatographic detection of phenolics in Juneberry fruits; however, all of them have followed different extraction methods [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The HPLC method developed through this study provided clean separation of six phenolic acid standards using a C30 column. The separation provided distinct retention times, which allowed for the identification of phenolic acids within the Juneberry samples via HPLC analysis. Separation and quantification of Phenolic compounds are challenging due to the inherent structural complexity and associated separation complexities [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Hydroxycinnamic acids (chlorogenic, caffeic, p-coumaric, and ferulic acids) exhibited absorption maxima at 310 nm while hydroxybenzoic acids (gallic and vanillic acids) showed maxima at 215 nm. The methanol and 5% o-phosphoric acid method created sharp symmetrical peaks across the 25-minute run time. This agrees with the effectiveness of reverse phase HPLC methods for berry phenolic compounds shown in other studies; for example, studies related to blueberries and other closely related berries have sorted both hydroxybenzoic and hydroxycinnamic acids with similar chromatographic methods [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] Click or tap here to enter text..\u003c/p\u003e \u003cp\u003ePDA detection allowed for the section of wavelength maxima specific to each class of phenolics being 310 nm for hydroxycinnamic acids and 215 nm for hydroxybenzoic acids. The dual wavelength approach taken allows for increased selectivity and sensitivity for phenolics that are structurally different from one another. A dual or multiple wavelength approach is commonly used in studies that quantify phenolic compounds within fruit samples [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] Click or tap here to enter text..\u003c/p\u003e \u003cp\u003eJuneberry samples were analyzed right after extraction and then 24-hours after initial extraction, allowing the 50% methanol to extract phenolics from the berries for 24-hours. The 50% methanol remained in contact with the freeze-dried samples during the 24-hour timeline allowing the solvent to penetrate deeper into the tissues, facilitating the release of tightly bound phenolic acids. The profiles for initial and 24-hour extraction were compared, and changes in phenolic concentrations were noted.\u003c/p\u003e \u003cp\u003eThe Ca\u0026sup2;⁺ column with RID detection also produced distinct retention times which allowed for the identification of carbohydrates within the juneberry samples via HPLC analysis. Retention times matched the standard solutions that were run through HPLC analysis prior to the Juneberry samples. The elevated column temperature of 80\u0026deg;C led to peaks similar to that of phenolics in terms of being sharp and symmetrical with minimal trailing. HPLC-RID methods are commonly used to identify, analyze, and quantify carbohydrates within foods [\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]Click or tap here to enter text.. The glucose, fructose, sucrose, and sorbitol concentrations were found in the ranges of 121.59-179.22, 130.87-217.69, 21.61\u0026ndash;36.31, and 96.18-177.26 mg/g, respectively. The higher fructose compared to glucose, as shown by glucose:fructose\u0026thinsp;\u0026lt;\u0026thinsp;1, aligns with earlier findings of Saskatoon fruits by Rogiers and Knowles [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The total sucrose content observed to be less than one-tenth of all the analyzed sugars is in agreement with that reported, in a different species of Juneberry (\u003cem\u003eA. lamarckii\u003c/em\u003e), by Mikulic-Petkovsek et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eComparison with Related Berry Matrices\u003c/h2\u003e \u003cp\u003eJuneberries should be viewed as a phenolic-rich fruit that extends beyond the six acids targeted in the present method, because mature juneberries contain anthocyanins, flavanols, and hydroxycinnamate-type phenolics, and genotype work has identified 29 polyphenolic compounds, including 9 phenolic acids, 9 flavanols, 7 flavan-3-ols, and 4 anthocyanins [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The current method captures a defined phenolic-acid subset of chlorogenic, caffeic, p-coumaric, ferulic, gallic, and vanillic acids rather than the full juneberry polyphenolic profile (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, this targeted analysis remains important because chlorogenic and neochlorogenic acids were reported as the major phenolic acids across Saskatoon berry genotypes, accounting for most of the phenolic-acid concentration [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In the context of this study, the observed increase in chlorogenic acid after the 24-hour extraction is consistent with the broader literature on juneberries and supports the use of chlorogenic acid-centered profiling as a way to compare cultivars.\u003c/p\u003e \u003cp\u003eComparison with other related berries helps give context to these findings. In blueberries, chlorogenic acid is reported as the predominant phenolic acid in both low and highbush fruit in an HPLC-MS comparison of two predominant blueberry species on the US market [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This suggests that Juneberry and blueberry share phenolic-acid features, more specifically chlorogenic acid-rich fraction, even though both fruits contain a much broader flavonoid range [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The chokeberry is another great contrast because the black chokeberry fruit is recognized as an especially polyphenol-and anthocyanin-rich berry [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. At the same time, however, chlorogenic acids also remain important in chokeberry, and were reported as the dominant phenolic compound in undigested black chokeberry fruit samples in a recent comparative study [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Altogether, these comparisons suggest that juneberries are chemically more similar to blueberries, while chokeberries contain a higher overall level of phenolics, especially pigment compounds like anthocyanins.\u003c/p\u003e \u003cp\u003eA similar contextual comparison can be made for the carbohydrate fraction, where the current method has captured the glucose, fructose, sucrose, and sorbitol concentrations (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Saskatoon berry genotypes have been reported to contain fructose and glucose as the dominant sugars, with sorbitol also present as a major soluble carbohydrate [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A study carried out by Mikulic-Petkovsek et al. in \u003cem\u003eA. lamarckii\u003c/em\u003e likewise identified glucose, fructose, and sorbitol as the main sugars, which matches the analyte panel selected in the present RID method [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. By comparison, black chokeberry can be more sorbitol-driven, because sorbitol was reported as the main carbohydrate in fresh aronia fruit and represented 61%\u0026ndash;68% of the low-molecular-weight carbohydrate fraction in Bulgarian samples [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This makes the current glucose, fructose, and sorbitol panel useful not only for within Juneberry cultivar comparisons, but also for distinguishing Juneberry from other dark-fruit carbohydrate profiles that are weighed differently across individual sugars and sugar alcohols.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhenolic compound concentrations (\u0026micro;g/g) in Juneberry samples immediately after extraction (Initial) and following 24‑hour extraction, with percentage change.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenolic Compound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExtraction Time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample 1 (\u0026micro;g/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample 2 (\u0026micro;g/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSample 3 (\u0026micro;g/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSample 4 (\u0026micro;g/g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChlorogenic acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e92.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e128.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent change (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFerulic acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent change (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCaffeic acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent change (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;28.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep-Coumaric acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent change (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVanillic acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e118.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e127.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent change (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGallic acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e112.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e108.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e132.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent change (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe observed that with the increment in extraction time, the individual phenolic concentration increased by at least 8%, except for caffeic acid\u0026mdash;decreased in\u0026mdash;samples 1\u0026ndash;3.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCarbohydrate concentrations (mg/g) in Juneberry samples immediately after extraction.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrates (mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSample 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e179.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e151.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e121.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFructose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e217.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e130.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e163.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose: Fructose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSucrose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSorbitol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e173.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e148.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e177.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMethod Validation and Performance\u003c/h2\u003e \u003cp\u003eCalibration curves constructed from the 10-point dilution of the mixed phenolic stock solution showed a linearity of R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.99 for all phenolic compounds (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This aligns with the validation parameters that have been reported in other fruit related phenolic HPLC methods [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]Click or tap here to enter text..\u003c/p\u003e \u003cp\u003ePrior to the calibration curve being constructed, standards of each phenolic acid were run through HPLC analysis. When running the standards through HPLC, the retention time was taken note of to compare to the stock solution from which the calibration curve was created and actual juneberry samples. The peaks and retention times of standards correlated directly with the peaks of the combined stock solution.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe HPLC method developed in this study provides a reliable and sensitive protocol for the extraction, separation, and quantification of both phenolic compounds and soluble carbohydrates in freeze-dried juneberry (\u003cem\u003eA. alnifolia\u003c/em\u003e) fruit. Phenolics were extracted via 50% methanol and analyzed using a reverse phase C30 column with PDA detection and a mobile phase of 5% o-phosphoric acid and methanol. Carbohydrates were extracted and separated via HPLC-grade water with a Ca\u003csup\u003e2+\u003c/sup\u003e monosaccharide column and RID detection. Both methods resulted in strong linearity with precision and chromatographic resolution.\u003c/p\u003e \u003cp\u003eThrough freeze-drying, the method maximized the amount of preserved phenolic and carbohydrate structures. This ensured greater and more consistent yields while limiting structural degradation that is associated with more thermally intensive drying methods.\u003c/p\u003e \u003cp\u003eThis method relies only upon HPLC instrumentation and commonly used detectors. Aside from minor column and detector modifications, the method can be readily adopted in most biochemistry laboratories. While MS can provide valuable confirmatory information, it is not required for routine analysis in the presented method. As a result, HPLC offers a practical and substantially more cost‑effective alternative to MS-based methods, particularly for high‑throughput or bulk sample analysis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHPLC: High-performance liquid chromatography\u003c/p\u003e\n\u003cp\u003ePDA: Photodiode array detector\u003c/p\u003e\n\u003cp\u003eRID: Refractive index detector\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project is supported by the USDA NIFA (Award #2025-38424-45225) and the South Dakota Agricultural Experiment Station. The authors also gratefully acknowledge Emily Ringgenberg, Ryan Johnson, and Vishnu Pasupuleti for their technical assistance in the laboratory.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: KH, MPN and AKN: Investigation: GS, BA and SP, Data Analysis and Interpretation: GS, ANP, MPN. Writing of Original Draft GS and MN, Review \u0026amp; Editing: All authors. All authors have read and approved the final version of the manuscript and agreed to its submission to Chromatographia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings of this study are available upon request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHartman, K.E., \u003cem\u003eReestablishing the Juneberry on the Fort Berthold Indian Reestablishing the Juneberry on the Fort Berthold Indian Reservation: Cultural, horticultural, and educational connections Reservation: Cultural, horticultural, and educational connections\u003c/em\u003e. 2008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHigbee, J., et al., \u003cem\u003ePolyphenolic profiles of a variety of wild berries from the Pacific Northwest region of North America\u003c/em\u003e. Current Research in Food Science, 2023. 7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHartman, K., D. Alahakoon, and A. Fennell, \u003cem\u003eImpact of Water and Nutrient Supplementation on Yield of Prairie Plantings of Juneberry Amelanchier alnifolia Nutt., Cultivar and Windbreak Plantings\u003c/em\u003e. Horticulturae, 2023. 9(6): p. 653.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLachowicz, S., et al., \u003cem\u003ePhytochemical Composition and Antioxidant Capacity of Seven Saskatoon Berry (Amelanchier alnifolia Nutt.) Genotypes Grown in Poland\u003c/em\u003e. Molecules, 2017. 22(5): p. 853.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonz\u0026aacute;lez-G\u0026oacute;mez, D., et al., \u003cem\u003eSweet cherry phytochemicals: Identification and characterization by HPLC-DAD/ESI-MS in six sweet-cherry cultivars grown in Valle del Jerte (Spain)\u003c/em\u003e. Journal of Food Composition and Analysis, 2010. 23(6): p. 533\u0026ndash;539.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMajhi, S. and S. Manickam, \u003cem\u003eSemisynthesis of Bioactive Compounds and Their Biological Activities\u003c/em\u003e. Semisynthesis of Bioactive Compounds and their Biological Activities. 2024: Elsevier. 209\u0026ndash;242.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIaneselli, A., et al., \u003cem\u003eA Complete Analysis Pipeline for the Processing, Alignment and Quantification of HPLC\u0026ndash;UV Wine Chromatograms\u003c/em\u003e. Chromatographia, 2024. 87(3): p. 159\u0026ndash;166.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHałka-Grysińska, A., et al., \u003cem\u003eApplication High-Performance Thin-Layer Chromatography with Controlled Eluent Velocity to Determine Fingerprints of Various Poplar Species Buds Extracts: Optimization of Operating Variables\u003c/em\u003e. Chromatographia, 2024. 87(6): p. 399\u0026ndash;406.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKittibunchakul, S., et al., \u003cem\u003eEffects of freeze drying and convective hot-air drying on predominant bioactive compounds, antioxidant potential and safe consumption of maoberry fruits\u003c/em\u003e. LWT, 2023. 184.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMikulic-Petkovsek, M., D. Koron, and D. Rusjan, \u003cem\u003eThe impact of food processing on the phenolic content in products made from juneberry (Amelanchier lamarckii) fruits\u003c/em\u003e. Journal of Food Science, 2020. 85(2): p. 386\u0026ndash;393.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAraya-Farias, M., J. Makhlouf, and C. Ratti, \u003cem\u003eDrying of Seabuckthorn (Hippophae rhamnoides L.) Berry: Impact of Dehydration Methods on Kinetics and Quality\u003c/em\u003e. Drying Technology, 2011. 29(3): p. 351\u0026ndash;359.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSablani, S.S., et al., \u003cem\u003eEffects of Air and Freeze Drying on Phytochemical Content of Conventional and Organic Berries\u003c/em\u003e. Drying Technology, 2011. 29(2): p. 205\u0026ndash;216.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVargas-Madriz, \u0026Aacute;.F., et al., \u003cem\u003eImpact of Drying Process on the Phenolic Profile and Antioxidant Capacity of Raw and Boiled Leaves and Inflorescences of Chenopodium berlandieri ssp. berlandieri\u003c/em\u003e. Molecules, 2023. 28(20).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRad, S.B., et al., \u003cem\u003eEffect of drying methods on phenolic compounds and antioxidant activity of Capparis spinosa L. fruits\u003c/em\u003e. BMC Plant Biology, 2025. 25(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhatta, S., T.S. Janezic, and C. Ratti, \u003cem\u003eFreeze-drying of plant-based foods\u003c/em\u003e. Foods, 2020. 9(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrzykowski, A., et al., \u003cem\u003eEffect of Air-Drying and Freeze-Drying Temperature on the Process Kinetics and Physicochemical Characteristics of White Mulberry Fruits (Morus alba L.)\u003c/em\u003e. Processes, 2023. 11(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRogiers, S.Y. and N.R. Knowles, \u003cem\u003ePhysical and chemical changes during growth, maturation, and ripening of saskatoon (Amelanchier alnifolia) fruit\u003c/em\u003e. Canadian Journal of Botany, 1997. 75(8): p. 1215\u0026ndash;1225.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonno, D., et al., \u003cem\u003eServiceberry, a berry fruit with growing interest of industry: Physicochemical and quali-quantitative health-related compound characterisation\u003c/em\u003e. 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Journal of Food and Nutrition Research, 2014. 2(11): p. 781\u0026ndash;785.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMattila, P., J. Hellstr\u0026ouml;m, and R. T\u0026ouml;rr\u0026ouml;nen, \u003cem\u003ePhenolic acids in berries, fruits, and beverages\u003c/em\u003e. Journal of Agricultural and Food Chemistry, 2006. 54(19): p. 7193\u0026ndash;7199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeal, T., \u003cem\u003eQuantitative HPLC analysis of phenolic acids, flavonoids and ascorbic acid in four different solvent extracts of two wild edible leaves, Sonchus arvensis and Oenanthe linearis of North-Eastern region in India\u003c/em\u003e. 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C1928\u0026ndash;C1937.\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"chromatographia","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chro","sideBox":"Learn more about [Chromatographia](https://www.springer.com/journal/10337)","snPcode":"10337","submissionUrl":"https://submission.nature.com/new-submission/10337/3","title":"Chromatographia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Hydroxycinnamic acids, Hydroxybenzoic acids, Phenolic compounds, Method development, Antioxidant, C30 column","lastPublishedDoi":"10.21203/rs.3.rs-9520495/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9520495/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eAmelanchier alnifolia\u003c/em\u003e Nutt. (Juneberry) is a native North American fruit that has gained increasing interest for its horticultural potential and presumed food values. Despite this growing interest, comprehensive nutritional and phytochemical characterization of Juneberry cultivars remains limited. This study describes the development of a high-performance liquid chromatography (HPLC) method for the extraction and quantification of phenolic compounds and carbohydrates within freeze-dried \u003cem\u003eA\u003c/em\u003e. \u003cem\u003ealnifolia\u003c/em\u003e samples. The phenolic compounds were extracted from the samples using a 1:1 methanol to water solution. The extract was then analyzed on a C30 reverse-phase column with a C18 guard column under gradient elution with HPLC-grade aqueous 5% o-phosphoric acid and methanol as the mobile phase. Both hydroxycinnamic acids and hydroxybenzoic acids, subclasses of phenolic acids, were analyzed using PDA detection at 310 nm and 215 nm, respectively. The soluble sugars, glucose and fructose as well as the soluble sugar alcohol sorbitol were extracted using HPLC-grade water and separated via a Ca\u003csup\u003e2+\u003c/sup\u003e monosaccharide column under isocratic conditions. Detection was performed by a refractive index detector (RID). This method provides a way to reproduce chromatographic separation, extraction, and quantification of high enough quality for comparative biochemical characterization of juneberry cultivars that can be applied to a broad range of fruits rich in phenolic compounds.\u003c/p\u003e","manuscriptTitle":"A Reproducible HPLC Method for Phenolic and Carbohydrate Analysis in Juneberry (Amelanchier alnifolia Nutt.)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-09 16:43:00","doi":"10.21203/rs.3.rs-9520495/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-12T10:20:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"205564459718805021524535642987455731938","date":"2026-05-06T18:44:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316696132745834421531017704413998368375","date":"2026-05-04T08:03:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-30T17:43:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-29T15:39:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-28T05:55:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Chromatographia","date":"2026-04-24T19:54:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"chromatographia","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chro","sideBox":"Learn more about [Chromatographia](https://www.springer.com/journal/10337)","snPcode":"10337","submissionUrl":"https://submission.nature.com/new-submission/10337/3","title":"Chromatographia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"945ed8a7-9483-42c2-9ba6-53a90f00f827","owner":[],"postedDate":"May 9th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-12T10:20:41+00:00","index":16,"fulltext":""},{"type":"reviewerAgreed","content":"205564459718805021524535642987455731938","date":"2026-05-06T18:44:14+00:00","index":15,"fulltext":""},{"type":"reviewerAgreed","content":"316696132745834421531017704413998368375","date":"2026-05-04T08:03:53+00:00","index":11,"fulltext":""},{"type":"reviewersInvited","content":"8","date":"2026-04-30T17:43:52+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-09T16:43:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-09 16:43:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9520495","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9520495","identity":"rs-9520495","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}