A Comparison of Methods: Titration vs DicromatII for the Measurement of Sodium Chloride (NaCl) Content in Dry Fermented Sausages

A Comparison of Methods: Titration vs DicromatII for the Measurement of Sodium Chloride (NaCl) Content in Dry Fermented Sausages | 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 Comparison of Methods: Titration vs DicromatII for the Measurement of Sodium Chloride (NaCl) Content in Dry Fermented Sausages Ciarán Crowley, Geraldine Duffy, Joseph P. Kerry This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7584102/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Accurate and reproducible determination of sodium chloride (NaCl) in processed meats is critical for product quality, safety, and regulatory compliance. This study compared the classical Mohr titration method with the DicromatII conductivity-based analyzer for quantifying NaCl in dry-fermented sausages. Validation was performed across three matrices: aqueous NaCl standards, fortified pepperoni homogenates, and commercial pepperoni products. Both methods exhibited excellent linearity (R² >0.99) in standard and fortified matrices. However, the DicromatII demonstrated consistently higher precision (%RSD 0.4–1.6%) and superior matrix tolerance, maintaining robust accuracy across all validation tiers. In commercial products, Mohr titration showed substantial variability, with weak correlation and poor agreement in most samples. The DicromatII, by contrast, offered reliable performance, reduced chemical handling, and strong repeatability, supporting its use in industrial meat analysis. This study represents the first direct validation-based comparison of these two methods in fermented meat matrices, highlighting the DicromatII as a safer and scalable alternative to traditional titration. Salt content Salt content Salt Titration Fermented Meat Proximal Composition Physicochemical 1. Introduction Sodium chloride (NaCl) plays a critical functional role in the manufacture of processed meats such as salami and pepperoni. Beyond its well-known contributions to flavour, salt facilitates protein extraction, moisture control, and microbial stability—especially in dry-cured products where concentration increases during dehydration. Accurate quantification of salt in such matrices is therefore vital for ensuring product consistency, regulatory compliance, and consumer transparency [ 1 – 4 ]. Traditionally, salt determination in meat products has relied on the Mohr titration—a classic argentometric method based on chloride precipitation with silver nitrate and chromate indicators [ 5 , 6 ]. While widely accepted, the Mohr method is subject to various limitations, including sensitivity to visual endpoint detection, matrix interference, and environmental concerns due to the use of hazardous reagents [ 10 ]. These drawbacks are particularly pronounced in complex food matrices such as cured meats, where pigments, emulsifiers, and ionic interference can affect both visual clarity and titration accuracy [ 16 ]. Instrumental salt measurement technologies, such as the DicromatII, offer an alternative. This device uses conductivity and temperature to quantify NaCl levels rapidly, without sample dilution, and can operate across a broad concentration range [ 7 ]. Previous studies have explored instrumental methods like ion chromatography, flame emission, and atomic absorption spectrometry [ 8 – 10 ], yet limited comparative validation has been performed in fermented meat matrices—especially using standardized performance metrics like trueness, precision, and matrix agreement. This study addresses that gap by systematically comparing the Mohr titration and DicromatII methods across three validation tiers: aqueous standards, fortified pepperoni matrices, and commercial sausage products. By applying recognized validation criteria [ 11 – 13 ], this work provides a robust evaluation of both methods, highlighting their practical strengths and limitations. To our knowledge, this is the first direct validation-based comparison of the Mohr and DicromatII methods in dry-fermented meats, offering insight into method suitability for industrial salt analysis. Its addition is also tightly regulated in many regions under labeling legislation such as Codex standards [ 20 ]. The objective of this study was to compare the use of the DicromatII instrument against a standard titration method to assess performance in determining salt levels, firstly in brine solutions and secondly, in a more complex food matrix as presented by pepperoni. 2. Materials and Methods 2.1 Experimental design An initial experiment was set up to assess the salt content of NaCl-dH 2 O standard solutions by the DicromatII instrument. Standard solutions were initially Mohr titrated and subsequently quantified for NaCl content by DicromatII. To test the DicromatII’s ability to accurately measure NaCl content in a diluted pepperoni matrix, a pepperoni of known composition was homogenised, and Mohr titrated to validate its salt content. This value was then calibrated into the instrument. This pepperoni homogenate solution was fortified with standard quantities of NaCl. This series of NaCl-fortified pepperoni homogenate solutions were Mohr titrated and subsequently quantified by DicromatII. The fortification results obtained from each method were compared by validation calculations to determine the parameters of method accuracy. Following this trial, a series of commercial pepperoni products were prepared and quantified by both methods, to observe the applied effectiveness of both methods. 2.2 Preparation of Standards and Test solutions 2.2.1 Preparation of NaCl-Distilled water standard solutions Accurately weighed quantities of salt (NaCl) (Sigma- Aldrich): 0.5 g; 1.0 g; 2.5 g and 5.0 g were added to five x 100 mL volumetric flasks, respectively. The NaCl was added via funnel, and remaining traces were rinsed into the flask using distilled water, with washings added to the relevant volumetric flasks. Distilled water, approximately 40 mL, was added to each of the flasks containing NaCl. The flasks were swirled gently to dissolve the NaCl. Each flask was brought to volume to the graduation mark with distilled water. All flasks were stopped and inverted several times to ensure solutions were fully mixed. The NaCl concentrations, by volume, in each of these standard solutions were: 0.0% (a standard without NaCl addition); 0.5%. 1.0%; 2.5% and 5.0%. The purpose of preparing these samples was to assess the performance of both salt testing approaches using a simplified, non-complex, non-meat sample media. Three independent preparations were made for each concentration level. Each of the independent preparations of each standard solution were Mohr titrated in triplicate as described in section 2.3.1 . Each standard solution was subsequently quantified for salt content via DicromatII and the Mohr titrated values were used for calibration as described in section 2.3.2 . 2.2.2 Preparation of Pepperoni Homogenate Solutions 1:10 Dilution Two independent pepperoni types were analyzed in this study. The first sample type is an in-house manufactured pepperoni of known composition which was manufactured three times independently. Its composition was as follows, (64% pork meat, 31% beef fat and 1% NaCl). This pepperoni product was used to calibrate the DicromatII instrument to a pepperoni matrix as described in section 2.3.2 . Following initial calibration, the pepperoni homogenate dilution served as a stock solution for the addition of standard quantities of NaCl. Each fortified pepperoni matrix standard was Mohr titrated in triplicate and subsequently quantified for salt via DicromatII and used to create a calibrated range for the measurement of the second sample type, commercially available pepperoni products. Samples of commercially available pepperoni were purchased (n = 9) from local retail outlets and analyzed for NaCl content by Mohr titration and DicromatII respectively. The preparation procedure to homogenize and dilute pepperoni samples was identical for the pepperoni used for calibration and for commercial products. Pepperoni samples were homogenized to a paste in the BUCHI Mixer B-400 (BÜCHI Labortechnik AG, Switzerland). Homogenates were diluted in distilled water to create a 1:10 dilution. Pepperoni homogenates (50 g) were suspended in 450 mL of hot (≈ 80°C) water. The solution was transferred into a 500 mL Duran bottle (DURAN®, DWK Life Sciences Ltd. Stoke-on-Trent, UK.), sealed, and shaken vigorously by hand for 2 min. The homogenates were allowed to rest overnight and refrigerated at 3°C, to allow maximum dissociation of salt from the pepperoni matrix. These samples were then filtered through Whatman filter paper #1 into 250 mL Duran bottles. The pepperoni homogenate solution used for calibration was prepared three times independently from three separate 50 g portions from within each batch. Each commercial pepperoni sample was purchased three times independently, three independent homogenate dilutions were prepared, and each solution was tested in triplicate for both Mohr titration and DicromatII methods as described in section 2.3.1 and 2.3.2 , respectively. 2.2.3 Fortification of Pepperoni Homogenate solution with standard quantities of NaCl. Accurately weighed quantities of NaCl: 0.5 g; 1.0 g; 2.5 g and 5.0 g were added to each of five 100mL volumetric flasks. The NaCl was added via funnel, and remaining traces were rinsed into the flask using distilled water with filtered homogenate (rested overnight refrigerated at 3°C), with the washings added to the relevant volumetric flasks. To each of these flasks, approx. 40 mL of homogenate solution prepared in section 2.2.2 was added. The flasks then swirled gently until the NaCl had fully dissolved. Each flask was brought to volume to the graduation mark to 100 mL using the homogenate solution. The concentration of additional NaCl by volume to each of these fortified standard solutions was: 0% (a standard without NaCl addition); 0.5%. 1.0%; 2.5% and 5.0%, respectively. 2.3 Analytical methods: 2.3.1 Mohr titration Test solutions (10 mL) were pipetted into 100 mL conical flasks. Thirty-five drops of potassium dichromate indicator (5%) (Sigma-Aldrich) were added to each test solution, in accordance with the procedure described in the DicromatII user manual. Test solutions were titrated with 0.1 M silver nitrate (Sigma-Aldrich) until the luminous yellow colour converted to a permanent brick-red colour. The titration volume was recorded, and salt content calculated as follows: titration volume (mL) x molarity of silver nitrate (0.1 M) x 0.585 (correction factor). The titration procedure was identical for all samples analyzed. 2.3.2. DicromatII Calibration and operation. Calibration of NaCl- Water standard solutions. The DicromatII instrument (DicromatII, Noramar Co., USA.) was turned on and set to calibration mode. Calibration was carried out in accordance with the DicromatII user manual. The DicromatII instrument allows for the storage of multiple sample-specific calibrations generated and stored on an in-built software. Following the triplicate Mohr titration of each NaCl-water standard, each sample solution was measured by DicromatII in calibration mode. Each standard solution was calibrated into the DicromatII instrument as a “set point”. The salt content of each standard solution was quantified by DicromatII in triplicate. Once the reading of each replicate had stabilized, the value detected by the DicromatII was recorded and the “set point” was calibrated as the mean salt content recorded by Mohr titration. This procedure was continued on all five standard solutions, calibrating five “set points” into the DicromatII software. Calibration to the pepperoni matrix. The second calibration was to calibrate the DicromatII to detect the salt content of a pepperoni matrix solution. The in-house manufactured pepperoni homogenate solution prepared in Section 2.2.2 was used for calibration. The solution was Mohr titrated in triplicate to determine its salt content. The DicromatII instrument was turned on in calibration mode and a new “set point” was opened. The DicromatII probe was inserted into the sample solution. Once the reading had stabilized, the value detected was recorded, and the “set point” was calibrated as the mean salt content recorded by Mohr titration. This calibration procedure was repeated for each fortified standard in triplicate, with each solution establishing a new “set point “on the DicromatII software. Commercial samples To evaluate the salt content of sample solutions, the DicromatII instrument was set in continuous measuring mode. Test-solution (150 mL) was poured into a clean dry 250 mL beaker, so that the instrumental probe, when inserted, was fully submerged in the sample solution. The instrument allowed sufficient time to stabilize for each measurement (~ 20 seconds), and results were then recorded. The probe was rinsed between samples in clean distilled water and then patted dry with clean dry toweling paper [ 7 ]. 2.3 Method Validation and Statistical Analysis The performance of the DicromatII II and Mohr titration methods was validated in accordance with standard analytical guidelines for method evaluation in food matrices, including those from [ 11 ], [ 12 ], and [ 13 ]. 2.3.1. Validation Criteria and Overview Method validation encompassed six key parameters: linearity, accuracy (trueness), precision (repeatability), matrix effect, method agreement, and reproducibility. These were assessed in different matrix contexts using appropriate statistical tests (see Table 1 ). Table 1 Summary of method validation across three matrix types, detailing NaCl ranges, replication, and analytical parameters assessed, including linearity, accuracy, precision, and inter-method agreement. Study Part Matrix NaCl Range (%) Replicates per Level Total N Analyses Performed Standards NaCl in distilled water 0, 0.5, 1.0, 2.5, 5.0 6 per level (n = 30) 60 Linearity, Accuracy, Precision, Method Comparison. Fortified Matrix 1:10 pepperoni homogenate + NaCl 0, 0.5, 1.0, 2.5, 5.0 6 per level (n = 30) 60 Linearity, Accuracy, Precision, Method Comparison Commercial Samples Commercial pepperoni products Native (unknown) 9 per product (n = 81) 162 Precision, Method Comparison (t-test, ICC, correlation) 2.3.2. Standard NaCl-Water Solutions (Matrix-Free) Aqueous NaCl standards (0–5% w/v) were prepared and measured in six replicates per concentration (n = 30 per method). The following evaluations were performed: Linearity Linear regression was conducted; (NaCl added vs. measured salt %) to determine slope, intercept, R², and standard error of the estimate. Perfect linearity (R² >0.99) was expected. Precision Repeatability at each concentration level was assessed by calculating mean, standard deviation (SD), and percent relative standard deviation (%RSD). Accuracy (Trueness): Percent recovery was calculated by comparing measured values to expected values across concentrations. Bias and Inter-method Agreement Paired-samples t-tests, Pearson correlation coefficients, and residual plots were used to compare methods. 2.3.3. Fortified Matrix Standards (Pepperoni Homogenate + NaCl) To simulate real sample interference, a 1:10 (w/v) pepperoni homogenate in distilled water was used as a diluent for NaCl standards. The same concentration series (0–5%) and replicates (n = 30 per method) were used. Linearity and Matrix Effects Linear regression analysis was repeated, and slopes and intercepts were compared to matrix-free data. Matrix effects were inferred from differences in intercept or slope. Accuracy and Precision Percent recovery and %RSD were calculated as above. Matrix Comparison ANCOVA (Analysis of Covariance) or slope-interaction comparisons (via regression) were used to statistically test differences between the matrix-free and fortified datasets [ 14 ]. 2.3.4. Commercial Pepperoni Samples A total of 9 commercial pepperoni products were analyzed, with nine replicates of each (n = 81 per method). Each homogenate was prepared 1:10 in water (w/v). The following evaluations were applied: Precision : Within-sample %RSD was calculated to assess method repeatability in real-world matrices. Method Agreement : Paired t-tests evaluated systematic differences in mean salt results. Pearson correlation coefficients assessed the degree of linear association between methods within each product. Intraclass correlation coefficients (ICCs) measured the reproducibility of readings between methods for each product [ 15 ]. Effect sizes (Cohen’s d) were calculated to estimate practical significance of method differences. Reproducibility : ICCs (absolute agreement, two-way mixed model) were used to assess consistency across replicate readings. 2.3.5. Additional Statistical Notes Bland-Altman and Deming regression analyses were prepared but not presented herein due to space constraints. These are available in supplementary materials. All statistical analyses were performed using IBM SPSS Statistics v28.0 (IBM Corp., Armonk, NY). A significance threshold of α = 0.05 was used for all hypothesis testing. 3. Results 3.1. Linearity and Calibration Performance Linearity was confirmed for both the DicromatII and Mohr titration methods across both standard matrices (Table 2 ). In the NaCl-water system, the DicromatII II achieved a perfect linear relationship (R² = 1.000) with a slope of 0.926 and near-zero intercept (0.025), indicating excellent analytical response. The Mohr method also showed high linearity (R² = 0.997), but with a slightly higher intercept (0.118), suggesting minor overestimation at lower salt levels. In the fortified pepperoni matrix, linearity was maintained (R² >0.95 for both methods), though intercepts increased significantly for both (1.092 for DicromatII; 1.009 for Mohr), indicating a clear matrix effect. Despite this, the DicromatII maintained a lower standard error (0.135 vs. 0.410), supporting better robustness to matrix interference. 3.2. Precision and Repeatability Precision results (%RSD) are detailed in (Table 3 ). In standard NaCl-water solutions, DicromatII showed excellent repeatability (%RSD < 1.1%) at all levels, except for 2.5% where RSD slightly rose to 1.10%. Mohr titration exhibited more variability, particularly at 2.5% (1.66%) and 0.5% (1.72%). In the fortified pepperoni matrix, DicromatII again demonstrated consistent performance (%RSD range: 0.41–1.59%), while the Mohr method showed reduced repeatability, especially at 2.5% and 5% NaCl, where RSDs exceeded 2% (3.71% and 2.19%, respectively). These results indicate that DicromatII consistently outperformed Mohr titration in precision, particularly in complex food matrices. 3.3. Accuracy and Recovery In both standard matrices, recovery values aligned closely with expected NaCl concentrations. Mean recovery for DicromatII was consistently between 95–99%, whereas the Mohr method showed a wider spread and occasional overestimation, particularly at lower concentrations. 3.4. Method Agreement in Commercial Samples Paired-samples t-tests and intraclass correlation coefficients (ICCs) revealed significant variation in agreement between methods depending on the product analyzed (Table 4 ). While Commercial Sample 1 demonstrated excellent agreement (ICC = 0.948, p = 0.002, Cohen’s d = 0.45), most other samples showed poor to unacceptable agreement. Samples 2–5 exhibited strong and statistically significant negative mean differences (e.g., − 0.763% in Sample 5), large effect sizes (Cohen’s d < − 5), and ICC values near zero or negative, suggesting substantial disagreement between methods in certain products. Only Sample 9 approached moderate agreement (ICC = 0.393, p = 0.732). 3.5. Correlation Between Methods Table 5 summarizes Pearson correlation coefficients across matrices and samples. Correlation was excellent in the standard and fortified matrices (r = 0.999 and 0.997, respectively), confirming high consistency during controlled validation. However, correlation was weak or absent in most commercial samples. Only Sample 1 exhibited a strong correlation (r = 0.962), while others ranged from inverse (e.g., Sample 3: r = − 0.456) to no relationship (Sample 8: r = − 0.004). These results further support the presence of matrix-specific interferences in commercial formulations that impact titration reliability. Table 2 Linearity and regression model statistics for both methods across standard and fortified matrices, including slope, intercept, R², standard error, and sample size (n). Matrix Standard Fortified Method DicromatII Mohr DicromatII Mohr Slope 0.926 0.97 0.948 0.982 Intercept 0.025 0.118 1.092 1.009 R² 1 0.997 0.994 0.951 Std. Error 0.026 0.092 0.135 0.41 n 29 29 45 45 Table 3 Repeatability is expressed as relative standard deviation (%RSD) for both methods across NaCl concentrations in standard and fortified matrices. Matrix Standard Fortified NaCl (%) DicromatII RSD (%) Mohr RSD (%) DicromatII RSD (%) Mohr RSD (%) 0.5 0.95 1.72 0.41 0.7 1.0 0.37 1.13 0.82 2.71 2.5 1.1 1.66 1.59 3.71 5.0 0.49 0.77 0.6 2.19 Table 4 Agreement between Mohr titration and DicromatII methods for nine commercial pepperoni samples. Agreement metrics include mean differences (D–M), significance (p-values), effect size Sample Mean Difference (D-M) p-value Cohen’s d ICC (Single Measures) Interpretation Sample 1 0.123 0.002 0.45 0.948 Excellent Sample 2 -0.132 0.006 -1.24 0.047 Poor Sample 3 -0.24 < 0.001 -3.21 -0.027 Unacceptable Sample 4 -0.519 < 0.001 -6.36 -0.008 Unacceptable Sample 5 -0.763 < 0.001 -5.14 -0.011 Unacceptable Sample 6 0.092 0.048 0.78 0.108 Poor Sample 7 0.383 0.019 0.98 0.039 Poor Sample 8 0.198 0.001 1.59 -0.001 Unreliable Sample 9 -0.036 0.732 -0.11 0.393 Moderate Table 5 Pearson correlation between Mohr titration and DicromatII results across standard, fortified, and commercial samples. Correlation strength is interpreted based on coefficient magnitude and significance. Sample Pearson r p-value Interpretation Standard 0.999 < 0.001 Excellent Fortified 0.997 < 0.001 Excellent Sample 1 0.962 < 0.001 Very strong Sample 2 0.118 0.763 None Sample 3 -0.456 0.217 Inverse Sample 4 -0.5 0.17 Inverse Sample 5 -0.455 0.219 Inverse Sample 6 0.234 0.545 Weak Sample 7 0.314 0.411 Weak Sample 8 -0.004 0.992 None Sample 9 0.478 0.162 Moderate 4. Discussion 4.1. Performance in Standard Solutions The excellent linearity observed for both the DicromatII and Mohr methods in distilled water standards aligns with expectations for salt quantification in clean matrices. The DicromatII analyzer achieved perfect correlation (R² = 1.000) and minimal intercept, confirming its suitability for direct calibration without extensive baseline correction. In contrast, the slightly elevated intercept in the Mohr method may reflect practical constraints associated with visual endpoint detection, particularly at low concentrations. These findings are consistent with prior validation studies comparing potentiometric and volumetric chloride assays [ 11 , 17 ]. 4.2. Influence of the Pepperoni Matrix on Analytical Behavior A marked shift in regression intercepts was observed in the fortified pepperoni matrix for both methods, highlighting the impact of food matrix interference. While both methods retained high linearity, the increase in intercept values (to 1.09 for DicromatII; 1.01 for Mohr) indicates that even a 1:10 dilution was insufficient to completely suppress matrix effects. This could be attributed to residual protein, fat, or spice-derived ions interfering with chloride detection — especially in titration, where chromate endpoint sensitivity may be diminished by pigment and turbidity. Interestingly, the DicromatII method displayed greater robustness, with lower standard error and reduced %RSDs across all NaCl levels. These findings suggest that conductivity-based salt measurement may be better suited for fermented or highly seasoned matrices where endpoint detection becomes unreliable. 4.3. Precision and Trueness Across Methods Across all matrices, the DicromatII consistently delivered lower %RSD values, demonstrating superior repeatability — particularly important in routine industrial analysis. The Mohr method showed acceptable precision in aqueous standards, but significantly higher variation in fortified and commercial samples. This discrepancy echoes earlier critiques of visual titration methods in complex matrices [ 16 ] and supports a move toward automated conductometric methods in modern QA workflows. Recovery rates (available in supplementary materials) also favoured the DicromatII, which maintained 95–99% recovery, while the Mohr occasionally overestimated salt content, especially at lower concentrations. This may be due to chloride interaction with matrix constituents or silver chromate formation dynamics at low ionic strength. 4.4. Agreement and Applicability in Commercial Samples The most striking divergence between methods was observed in the commercial pepperoni dataset. While Sample 1 showed excellent agreement across all metrics (ICC = 0.948, r = 0.962), most other products demonstrated statistically and practically significant disagreement. Samples 3–5 yielded high mean differences, large negative effect sizes (Cohen’s d < − 5), and negative ICCs, indicating unreliable interchangeability. These discrepancies likely reflect variations in fat, spice, and emulsifier content across commercial brands — all of which can affect chloride binding, visual endpoint clarity, and ionic conductivity. The weak or inverse Pearson correlations further emphasize that Mohr titration may not be reliable without prior matrix-specific calibration or dilution optimization. 4.5. Implications for Salt Quantification in Processed Meats From a practical standpoint, the findings strongly support the use of potentiometric or conductometric methods like DicromatII in processed meat applications. These methods offer superior linearity, precision, and resilience to matrix effects, minimizing the risk of inaccurate salt estimation — which is crucial for regulatory compliance and sensory optimization. Moreover, the inconsistencies observed with titration underscore the need for method validation within the actual matrix of use, rather than relying solely on standard solutions. This is particularly critical in cured meat products, where salt plays a dual role in preservation and flavour, and where even small deviations in reported values can have microbiological or sensory consequences. 4.6. Study Strengths and Limitations This study employed a robust, matrix-tiered validation structure (standard, fortified, commercial), enabling nuanced assessment of analytical behavior under realistic conditions. However, it was limited by the absence of certified reference materials or gravimetric baseline data. Additionally, the Mohr method was applied in its classical format; performance may improve with instrumental titration setups or matrix-specific standard additions. 4.7. Conclusion Overall, the DicromatII demonstrated superior performance in terms of linearity, precision, and matrix tolerance, making it a reliable option for salt determination in both laboratory and industrial contexts. The Mohr titration method, while acceptable in clean matrices, exhibited considerable limitations in commercial pepperoni products. Future studies may explore hybrid approaches, such as conductivity-titration correlation modeling or matrix-adapted correction factors, to further improve salt quantification in complex foods. 5. Conclusions This study validated the use of the DicromatII conductivity-based method as a reliable and efficient alternative to the traditional Mohr titration for the quantification of sodium chloride in dry-fermented sausages. Across standard NaCl solutions and fortified pepperoni matrices, both methods showed excellent linearity and agreement. However, DicromatII consistently demonstrated superior precision, lower limits of detection and quantification, and greater reproducibility, particularly in complex matrices. In commercial pepperoni samples, agreement between the two methods diminished, with the Mohr titration showing higher variability and reduced correlation. Deming regression and Bland-Altman analyses further revealed the limitations of titration in real-world applications. The DicromatII method offered greater ease of use, reduced chemical handling, and robust performance, making it a suitable candidate for routine salt determination in meat quality control and product development settings. This validation supports the wider adoption of automated, instrumental salt analysis as a safer and scalable solution for the meat industry, particularly where high-throughput testing is required. Declarations Author Contributions Conceptualization: Ciarán Crowley (C.C.), Joseph P. Kerry (J.K.) Methodology: C.C., J.K., Geraldine Duffy (G.D.) Investigation: C.C. Data Curation & Formal Analysis: C.C. Writing – Original Draft: C.C. Writing – Review & Editing: J.K., Supervision: J.K., G.D. 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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-7584102","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":521694094,"identity":"06357eda-516b-4bbb-a687-26337015ee53","order_by":0,"name":"Ciarán Crowley","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYBACNmbmAwYJFTZy/OwNQK6BBUQ4AY8WPna2hIIPZ9KMJXsOgLRIENYix8+j8HFm2+HEDTfAyiSIcRgP42YeNubEhptvTDf8KJBgMDh++AHDgwp8WngPG/PwsBk3zs4xu9kDdJjBmTQDhoQz+LTwpRnzSPDINkvnmN3gAWm5wcPAkNiG12Hmv4EqGdskz5jd/APX8g+vFgPDGQkGij0SPGa3EbY04NPClmDw4UCCsQRPWtltGQMJHkmgXw4kHMOtRb7/8AGDxH//5eyPH952880fGzm+44cfPvxRg1sLBuABEQdI0DAKRsEoGAWjAAsAAO6PS2E/gepWAAAAAElFTkSuQmCC","orcid":"","institution":"University College Cork","correspondingAuthor":true,"prefix":"","firstName":"Ciarán","middleName":"","lastName":"Crowley","suffix":""},{"id":521694097,"identity":"90e5b346-21a3-4e09-9b51-43f7a3fc0e55","order_by":1,"name":"Geraldine Duffy","email":"","orcid":"","institution":"Teagasc Ashtown Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Geraldine","middleName":"","lastName":"Duffy","suffix":""},{"id":521694098,"identity":"c20da7f4-cd7b-4333-8a86-5f54b5e38506","order_by":2,"name":"Joseph P. Kerry","email":"","orcid":"","institution":"University College Cork","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"P.","lastName":"Kerry","suffix":""}],"badges":[],"createdAt":"2025-09-10 14:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7584102/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7584102/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92382122,"identity":"7edbbc24-e361-40fd-9ed0-653f3d244686","added_by":"auto","created_at":"2025-09-29 06:29:17","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37540,"visible":true,"origin":"","legend":"","description":"","filename":"SaltPaperManuscript10.9.25FoodAnalyticalMethodsJournal.docx","url":"https://assets-eu.researchsquare.com/files/rs-7584102/v1/65de413e79a77aa4501d0efe.docx"},{"id":92382121,"identity":"a492555b-b9ee-4cee-abc4-b0645513c06c","added_by":"auto","created_at":"2025-09-29 06:29:17","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4757,"visible":true,"origin":"","legend":"","description":"","filename":"87f973328a0e44e4acd3aa9a5b383477.json","url":"https://assets-eu.researchsquare.com/files/rs-7584102/v1/f64af41e6b39f545b37adf7c.json"},{"id":92382125,"identity":"26914a50-9954-4557-9b8e-6ec602a18f45","added_by":"auto","created_at":"2025-09-29 06:29:17","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79335,"visible":true,"origin":"","legend":"","description":"","filename":"87f973328a0e44e4acd3aa9a5b3834771enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7584102/v1/7ff3940505f0840780fc2055.xml"},{"id":92382124,"identity":"8c978818-f401-4059-b36b-cf4a8b6d8deb","added_by":"auto","created_at":"2025-09-29 06:29:17","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78432,"visible":true,"origin":"","legend":"","description":"","filename":"87f973328a0e44e4acd3aa9a5b3834771structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7584102/v1/4dbee11802f0358348a6609f.xml"},{"id":92382123,"identity":"362fc894-4a3d-47ca-bf3c-f3e25613e572","added_by":"auto","created_at":"2025-09-29 06:29:17","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":83717,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7584102/v1/9fbed4a7ab5273561ddd9286.html"},{"id":92382470,"identity":"0737d317-7222-474e-ab7a-df4073aaa00c","added_by":"auto","created_at":"2025-09-29 06:37:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1155578,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7584102/v1/573ac6a1-19e9-4b23-a860-eed92301e9eb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Comparison of Methods: Titration vs DicromatII for the Measurement of Sodium Chloride (NaCl) Content in Dry Fermented Sausages","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSodium chloride (NaCl) plays a critical functional role in the manufacture of processed meats such as salami and pepperoni. Beyond its well-known contributions to flavour, salt facilitates protein extraction, moisture control, and microbial stability\u0026mdash;especially in dry-cured products where concentration increases during dehydration. Accurate quantification of salt in such matrices is therefore vital for ensuring product consistency, regulatory compliance, and consumer transparency [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTraditionally, salt determination in meat products has relied on the Mohr titration\u0026mdash;a classic argentometric method based on chloride precipitation with silver nitrate and chromate indicators [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While widely accepted, the Mohr method is subject to various limitations, including sensitivity to visual endpoint detection, matrix interference, and environmental concerns due to the use of hazardous reagents [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These drawbacks are particularly pronounced in complex food matrices such as cured meats, where pigments, emulsifiers, and ionic interference can affect both visual clarity and titration accuracy [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eInstrumental salt measurement technologies, such as the DicromatII, offer an alternative. This device uses conductivity and temperature to quantify NaCl levels rapidly, without sample dilution, and can operate across a broad concentration range [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Previous studies have explored instrumental methods like ion chromatography, flame emission, and atomic absorption spectrometry [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], yet limited comparative validation has been performed in fermented meat matrices\u0026mdash;especially using standardized performance metrics like trueness, precision, and matrix agreement.\u003c/p\u003e\u003cp\u003eThis study addresses that gap by systematically comparing the Mohr titration and DicromatII methods across three validation tiers: aqueous standards, fortified pepperoni matrices, and commercial sausage products. By applying recognized validation criteria [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], this work provides a robust evaluation of both methods, highlighting their practical strengths and limitations. To our knowledge, this is the first direct validation-based comparison of the Mohr and DicromatII methods in dry-fermented meats, offering insight into method suitability for industrial salt analysis. Its addition is also tightly regulated in many regions under labeling legislation such as Codex standards [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe objective of this study was to compare the use of the DicromatII instrument against a standard titration method to assess performance in determining salt levels, firstly in brine solutions and secondly, in a more complex food matrix as presented by pepperoni.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Experimental design\u003c/h2\u003e\u003cp\u003eAn initial experiment was set up to assess the salt content of NaCl-dH\u003csub\u003e2\u003c/sub\u003eO standard solutions by the DicromatII instrument. Standard solutions were initially Mohr titrated and subsequently quantified for NaCl content by DicromatII. To test the DicromatII\u0026rsquo;s ability to accurately measure NaCl content in a diluted pepperoni matrix, a pepperoni of known composition was homogenised, and Mohr titrated to validate its salt content. This value was then calibrated into the instrument. This pepperoni homogenate solution was fortified with standard quantities of NaCl. This series of NaCl-fortified pepperoni homogenate solutions were Mohr titrated and subsequently quantified by DicromatII. The fortification results obtained from each method were compared by validation calculations to determine the parameters of method accuracy. Following this trial, a series of commercial pepperoni products were prepared and quantified by both methods, to observe the applied effectiveness of both methods.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Preparation of Standards and Test solutions\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Preparation of NaCl-Distilled water standard solutions\u003c/h2\u003e\u003cp\u003eAccurately weighed quantities of salt (NaCl) (Sigma- Aldrich): 0.5 g; 1.0 g; 2.5 g and 5.0 g were added to five x 100 mL volumetric flasks, respectively. The NaCl was added via funnel, and remaining traces were rinsed into the flask using distilled water, with washings added to the relevant volumetric flasks. Distilled water, approximately 40 mL, was added to each of the flasks containing NaCl. The flasks were swirled gently to dissolve the NaCl. Each flask was brought to volume to the graduation mark with distilled water. All flasks were stopped and inverted several times to ensure solutions were fully mixed. The NaCl concentrations, by volume, in each of these standard solutions were: 0.0% (a standard without NaCl addition); 0.5%. 1.0%; 2.5% and 5.0%. The purpose of preparing these samples was to assess the performance of both salt testing approaches using a simplified, non-complex, non-meat sample media. Three independent preparations were made for each concentration level. Each of the independent preparations of each standard solution were Mohr titrated in triplicate as described in section \u003cspan refid=\"Sec9\" class=\"InternalRef\"\u003e2.3.1\u003c/span\u003e. Each standard solution was subsequently quantified for salt content via DicromatII and the Mohr titrated values were used for calibration as described in section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e2.3.2\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Preparation of Pepperoni Homogenate Solutions 1:10 Dilution\u003c/h2\u003e\u003cp\u003eTwo independent pepperoni types were analyzed in this study. The first sample type is an in-house manufactured pepperoni of known composition which was manufactured three times independently. Its composition was as follows, (64% pork meat, 31% beef fat and 1% NaCl). This pepperoni product was used to calibrate the DicromatII instrument to a pepperoni matrix as described in section \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e2.3.2\u003c/span\u003e. Following initial calibration, the pepperoni homogenate dilution served as a stock solution for the addition of standard quantities of NaCl. Each fortified pepperoni matrix standard was Mohr titrated in triplicate and subsequently quantified for salt via DicromatII and used to create a calibrated range for the measurement of the second sample type, commercially available pepperoni products. Samples of commercially available pepperoni were purchased (n\u0026thinsp;=\u0026thinsp;9) from local retail outlets and analyzed for NaCl content by Mohr titration and DicromatII respectively.\u003c/p\u003e\u003cp\u003eThe preparation procedure to homogenize and dilute pepperoni samples was identical for the pepperoni used for calibration and for commercial products. Pepperoni samples were homogenized to a paste in the BUCHI Mixer B-400 (B\u0026Uuml;CHI Labortechnik AG, Switzerland). Homogenates were diluted in distilled water to create a 1:10 dilution. Pepperoni homogenates (50 g) were suspended in 450 mL of hot (\u0026asymp;\u0026thinsp;80\u0026deg;C) water. The solution was transferred into a 500 mL Duran bottle (DURAN\u0026reg;, DWK Life Sciences Ltd. Stoke-on-Trent, UK.), sealed, and shaken vigorously by hand for 2 min. The homogenates were allowed to rest overnight and refrigerated at 3\u0026deg;C, to allow maximum dissociation of salt from the pepperoni matrix. These samples were then filtered through Whatman filter paper #1 into 250 mL Duran bottles. The pepperoni homogenate solution used for calibration was prepared three times independently from three separate 50 g portions from within each batch. Each commercial pepperoni sample was purchased three times independently, three independent homogenate dilutions were prepared, and each solution was tested in triplicate for both Mohr titration and DicromatII methods as described in section \u003cspan refid=\"Sec9\" class=\"InternalRef\"\u003e2.3.1\u003c/span\u003e and \u003cspan refid=\"Sec10\" class=\"InternalRef\"\u003e2.3.2\u003c/span\u003e, respectively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Fortification of Pepperoni Homogenate solution with standard quantities of NaCl.\u003c/h2\u003e\u003cp\u003eAccurately weighed quantities of NaCl: 0.5 g; 1.0 g; 2.5 g and 5.0 g were added to each of five 100mL volumetric flasks. The NaCl was added via funnel, and remaining traces were rinsed into the flask using distilled water with filtered homogenate (rested overnight refrigerated at 3\u0026deg;C), with the washings added to the relevant volumetric flasks. To each of these flasks, approx. 40 mL of homogenate solution prepared in section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.2.2\u003c/span\u003e was added. The flasks then swirled gently until the NaCl had fully dissolved. Each flask was brought to volume to the graduation mark to 100 mL using the homogenate solution. The concentration of additional NaCl by volume to each of these fortified standard solutions was: 0% (a standard without NaCl addition); 0.5%. 1.0%; 2.5% and 5.0%, respectively.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Analytical methods:\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 Mohr titration\u003c/h2\u003e\u003cp\u003eTest solutions (10 mL) were pipetted into 100 mL conical flasks. Thirty-five drops of potassium dichromate indicator (5%) (Sigma-Aldrich) were added to each test solution, in accordance with the procedure described in the DicromatII user manual. Test solutions were titrated with 0.1 M silver nitrate (Sigma-Aldrich) until the luminous yellow colour converted to a permanent brick-red colour. The titration volume was recorded, and salt content calculated as follows: titration volume (mL) x molarity of silver nitrate (0.1 M) x 0.585 (correction factor). The titration procedure was identical for all samples analyzed.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2. DicromatII Calibration and operation.\u003c/h2\u003e\u003cp\u003eCalibration of NaCl- Water standard solutions. The DicromatII instrument (DicromatII, Noramar Co., USA.) was turned on and set to calibration mode. Calibration was carried out in accordance with the DicromatII user manual. The DicromatII instrument allows for the storage of multiple sample-specific calibrations generated and stored on an in-built software. Following the triplicate Mohr titration of each NaCl-water standard, each sample solution was measured by DicromatII in calibration mode. Each standard solution was calibrated into the DicromatII instrument as a \u0026ldquo;set point\u0026rdquo;. The salt content of each standard solution was quantified by DicromatII in triplicate. Once the reading of each replicate had stabilized, the value detected by the DicromatII was recorded and the \u0026ldquo;set point\u0026rdquo; was calibrated as the mean salt content recorded by Mohr titration. This procedure was continued on all five standard solutions, calibrating five \u0026ldquo;set points\u0026rdquo; into the DicromatII software.\u003c/p\u003e\u003cp\u003eCalibration to the pepperoni matrix. The second calibration was to calibrate the DicromatII to detect the salt content of a pepperoni matrix solution. The in-house manufactured pepperoni homogenate solution prepared in Section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.2.2\u003c/span\u003e was used for calibration. The solution was Mohr titrated in triplicate to determine its salt content. The DicromatII instrument was turned on in calibration mode and a new \u0026ldquo;set point\u0026rdquo; was opened. The DicromatII probe was inserted into the sample solution. Once the reading had stabilized, the value detected was recorded, and the \u0026ldquo;set point\u0026rdquo; was calibrated as the mean salt content recorded by Mohr titration. This calibration procedure was repeated for each fortified standard in triplicate, with each solution establishing a new \u0026ldquo;set point \u0026ldquo;on the DicromatII software.\u003c/p\u003e\u003cp\u003eCommercial samples\u003c/p\u003e\u003cp\u003eTo evaluate the salt content of sample solutions, the DicromatII instrument was set in continuous measuring mode. Test-solution (150 mL) was poured into a clean dry 250 mL beaker, so that the instrumental probe, when inserted, was fully submerged in the sample solution. The instrument allowed sufficient time to stabilize for each measurement (~\u0026thinsp;20 seconds), and results were then recorded. The probe was rinsed between samples in clean distilled water and then patted dry with clean dry toweling paper [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Method Validation and Statistical Analysis\u003c/h2\u003e\u003cp\u003eThe performance of the DicromatII II and Mohr titration methods was validated in accordance with standard analytical guidelines for method evaluation in food matrices, including those from [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1. Validation Criteria and Overview\u003c/h2\u003e\u003cp\u003eMethod validation encompassed six key parameters: linearity, accuracy (trueness), precision (repeatability), matrix effect, method agreement, and reproducibility. These were assessed in different matrix contexts using appropriate statistical tests (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eSummary of method validation across three matrix types, detailing NaCl ranges, replication, and analytical parameters assessed, including linearity, accuracy, precision, and inter-method agreement.\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudy Part\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMatrix\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNaCl Range (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReplicates per Level\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal N\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAnalyses Performed\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStandards\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNaCl in distilled water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0, 0.5, 1.0, 2.5, 5.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 per level (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLinearity, Accuracy, Precision, Method Comparison.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFortified Matrix\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1:10 pepperoni homogenate\u0026thinsp;+\u0026thinsp;NaCl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0, 0.5, 1.0, 2.5, 5.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 per level (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eLinearity, Accuracy, Precision, Method Comparison\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommercial Samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommercial pepperoni products\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNative (unknown)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 per product (n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePrecision, Method Comparison (t-test, ICC, correlation)\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=\"Section3\"\u003e\u003ch2\u003e2.3.2. Standard NaCl-Water Solutions (Matrix-Free)\u003c/h2\u003e\u003cp\u003eAqueous NaCl standards (0\u0026ndash;5% w/v) were prepared and measured in six replicates per concentration (n\u0026thinsp;=\u0026thinsp;30 per method). The following evaluations were performed:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eLinearity\u003c/strong\u003e\u003cp\u003eLinear regression was conducted; (NaCl added vs. measured salt %) to determine slope, intercept, R\u0026sup2;, and standard error of the estimate. Perfect linearity (R\u0026sup2; \u0026gt;0.99) was expected.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePrecision\u003c/strong\u003e\u003cp\u003eRepeatability at each concentration level was assessed by calculating mean, standard deviation (SD), and percent relative standard deviation (%RSD).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eAccuracy\u003c/em\u003e (Trueness): Percent recovery was calculated by comparing measured values to expected values across concentrations.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eBias and Inter-method Agreement\u003c/strong\u003e\u003cp\u003ePaired-samples t-tests, Pearson correlation coefficients, and residual plots were used to compare methods.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e2.3.3. Fortified Matrix Standards (Pepperoni Homogenate\u0026thinsp;+\u0026thinsp;NaCl)\u003c/h2\u003e\u003cp\u003eTo simulate real sample interference, a 1:10 (w/v) pepperoni homogenate in distilled water was used as a diluent for NaCl standards. The same concentration series (0\u0026ndash;5%) and replicates (n\u0026thinsp;=\u0026thinsp;30 per method) were used.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eLinearity and Matrix Effects\u003c/strong\u003e\u003cp\u003eLinear regression analysis was repeated, and slopes and intercepts were compared to matrix-free data. Matrix effects were inferred from differences in intercept or slope.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAccuracy and Precision\u003c/strong\u003e\u003cp\u003ePercent recovery and %RSD were calculated as above.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMatrix Comparison\u003c/strong\u003e\u003cp\u003eANCOVA (Analysis of Covariance) or slope-interaction comparisons (via regression) were used to statistically test differences between the matrix-free and fortified datasets [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e2.3.4. Commercial Pepperoni Samples\u003c/h2\u003e\u003cp\u003eA total of 9 commercial pepperoni products were analyzed, with nine replicates of each (n\u0026thinsp;=\u0026thinsp;81 per method). Each homogenate was prepared 1:10 in water (w/v). The following evaluations were applied:\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePrecision\u003c/span\u003e: \u003cem\u003eWithin-sample %RSD\u003c/em\u003e was calculated to assess method repeatability in real-world matrices.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMethod Agreement\u003c/span\u003e: \u003cem\u003ePaired t-tests\u003c/em\u003e evaluated systematic differences in mean salt results. \u003cem\u003ePearson correlation\u003c/em\u003e coefficients assessed the degree of linear association between methods within each product. \u003cem\u003eIntraclass correlation coefficients\u003c/em\u003e (ICCs) measured the reproducibility of readings between methods for each product [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. \u003cem\u003eEffect sizes\u003c/em\u003e (Cohen\u0026rsquo;s d) were calculated to estimate practical significance of method differences. \u003cem\u003eReproducibility\u003c/em\u003e: ICCs (absolute agreement, two-way mixed model) were used to assess consistency across replicate readings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e2.3.5. Additional Statistical Notes\u003c/h2\u003e\u003cp\u003eBland-Altman and Deming regression analyses were prepared but not presented herein due to space constraints. These are available in supplementary materials. All statistical analyses were performed using IBM SPSS Statistics v28.0 (IBM Corp., Armonk, NY). A significance threshold of α\u0026thinsp;=\u0026thinsp;0.05 was used for all hypothesis testing.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Linearity and Calibration Performance\u003c/h2\u003e\u003cp\u003eLinearity was confirmed for both the DicromatII and Mohr titration methods across both standard matrices (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the NaCl-water system, the DicromatII II achieved a perfect linear relationship (R\u0026sup2; = 1.000) with a slope of 0.926 and near-zero intercept (0.025), indicating excellent analytical response. The Mohr method also showed high linearity (R\u0026sup2; = 0.997), but with a slightly higher intercept (0.118), suggesting minor overestimation at lower salt levels.\u003c/p\u003e\u003cp\u003eIn the fortified pepperoni matrix, linearity was maintained (R\u0026sup2; \u0026gt;0.95 for both methods), though intercepts increased significantly for both (1.092 for DicromatII; 1.009 for Mohr), indicating a clear matrix effect. Despite this, the DicromatII maintained a lower standard error (0.135 vs. 0.410), supporting better robustness to matrix interference.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Precision and Repeatability\u003c/h2\u003e\u003cp\u003ePrecision results (%RSD) are detailed in (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In standard NaCl-water solutions, DicromatII showed excellent repeatability (%RSD\u0026thinsp;\u0026lt;\u0026thinsp;1.1%) at all levels, except for 2.5% where RSD slightly rose to 1.10%. Mohr titration exhibited more variability, particularly at 2.5% (1.66%) and 0.5% (1.72%). In the fortified pepperoni matrix, DicromatII again demonstrated consistent performance (%RSD range: 0.41\u0026ndash;1.59%), while the Mohr method showed reduced repeatability, especially at 2.5% and 5% NaCl, where RSDs exceeded 2% (3.71% and 2.19%, respectively). These results indicate that DicromatII consistently outperformed Mohr titration in precision, particularly in complex food matrices.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Accuracy and Recovery\u003c/h2\u003e\u003cp\u003eIn both standard matrices, recovery values aligned closely with expected NaCl concentrations. Mean recovery for DicromatII was consistently between 95\u0026ndash;99%, whereas the Mohr method showed a wider spread and occasional overestimation, particularly at lower concentrations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Method Agreement in Commercial Samples\u003c/h2\u003e\u003cp\u003ePaired-samples t-tests and intraclass correlation coefficients (ICCs) revealed significant variation in agreement between methods depending on the product analyzed (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). While Commercial Sample 1 demonstrated excellent agreement (ICC\u0026thinsp;=\u0026thinsp;0.948, p\u0026thinsp;=\u0026thinsp;0.002, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.45), most other samples showed poor to unacceptable agreement.\u003c/p\u003e\u003cp\u003eSamples 2\u0026ndash;5 exhibited strong and statistically significant negative mean differences (e.g., \u0026minus;\u0026thinsp;0.763% in Sample 5), large effect sizes (Cohen\u0026rsquo;s d \u0026lt; \u0026minus;\u0026thinsp;5), and ICC values near zero or negative, suggesting substantial disagreement between methods in certain products. Only Sample 9 approached moderate agreement (ICC\u0026thinsp;=\u0026thinsp;0.393, p\u0026thinsp;=\u0026thinsp;0.732).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Correlation Between Methods\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes Pearson correlation coefficients across matrices and samples. Correlation was excellent in the standard and fortified matrices (r\u0026thinsp;=\u0026thinsp;0.999 and 0.997, respectively), confirming high consistency during controlled validation.\u003c/p\u003e\u003cp\u003eHowever, correlation was weak or absent in most commercial samples. Only Sample 1 exhibited a strong correlation (r\u0026thinsp;=\u0026thinsp;0.962), while others ranged from inverse (e.g., Sample 3: r = \u0026minus;\u0026thinsp;0.456) to no relationship (Sample 8: r = \u0026minus;\u0026thinsp;0.004). These results further support the presence of matrix-specific interferences in commercial formulations that impact titration reliability.\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\u003eLinearity and regression model statistics for both methods across standard and fortified matrices, including slope, intercept, R\u0026sup2;, standard error, and sample size (n).\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMatrix\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eStandard\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eFortified\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMethod\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDicromatII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMohr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDicromatII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMohr\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.982\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.951\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45\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\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRepeatability is expressed as relative standard deviation (%RSD) for both methods across NaCl concentrations in standard and fortified matrices.\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eMatrix\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eStandard\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eFortified\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNaCl (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDicromatII RSD (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMohr RSD (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDicromatII RSD (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMohr RSD (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.19\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\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAgreement between Mohr titration and DicromatII methods for nine commercial pepperoni samples. Agreement metrics include mean differences (D\u0026ndash;M), significance (p-values), effect size\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=\"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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean Difference (D-M)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eICC (Single Measures)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUnacceptable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.519\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUnacceptable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-5.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUnacceptable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.383\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUnreliable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.732\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.393\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eModerate\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\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePearson correlation between Mohr titration and DicromatII results across standard, fortified, and commercial samples. Correlation strength is interpreted based on coefficient magnitude and significance.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson r\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStandard\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFortified\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVery strong\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInverse\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInverse\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInverse\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWeak\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWeak\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample 9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\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"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Performance in Standard Solutions\u003c/h2\u003e\u003cp\u003eThe excellent linearity observed for both the DicromatII and Mohr methods in distilled water standards aligns with expectations for salt quantification in clean matrices. The DicromatII analyzer achieved perfect correlation (R\u0026sup2; = 1.000) and minimal intercept, confirming its suitability for direct calibration without extensive baseline correction. In contrast, the slightly elevated intercept in the Mohr method may reflect practical constraints associated with visual endpoint detection, particularly at low concentrations. These findings are consistent with prior validation studies comparing potentiometric and volumetric chloride assays [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Influence of the Pepperoni Matrix on Analytical Behavior\u003c/h2\u003e\u003cp\u003eA marked shift in regression intercepts was observed in the fortified pepperoni matrix for both methods, highlighting the impact of food matrix interference. While both methods retained high linearity, the increase in intercept values (to 1.09 for DicromatII; 1.01 for Mohr) indicates that even a 1:10 dilution was insufficient to completely suppress matrix effects. This could be attributed to residual protein, fat, or spice-derived ions interfering with chloride detection \u0026mdash; especially in titration, where chromate endpoint sensitivity may be diminished by pigment and turbidity.\u003c/p\u003e\u003cp\u003eInterestingly, the DicromatII method displayed greater robustness, with lower standard error and reduced %RSDs across all NaCl levels. These findings suggest that conductivity-based salt measurement may be better suited for fermented or highly seasoned matrices where endpoint detection becomes unreliable.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Precision and Trueness Across Methods\u003c/h2\u003e\u003cp\u003eAcross all matrices, the DicromatII consistently delivered lower %RSD values, demonstrating superior repeatability \u0026mdash; particularly important in routine industrial analysis. The Mohr method showed acceptable precision in aqueous standards, but significantly higher variation in fortified and commercial samples. This discrepancy echoes earlier critiques of visual titration methods in complex matrices [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and supports a move toward automated conductometric methods in modern QA workflows.\u003c/p\u003e\u003cp\u003eRecovery rates (available in supplementary materials) also favoured the DicromatII, which maintained 95\u0026ndash;99% recovery, while the Mohr occasionally overestimated salt content, especially at lower concentrations. This may be due to chloride interaction with matrix constituents or silver chromate formation dynamics at low ionic strength.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Agreement and Applicability in Commercial Samples\u003c/h2\u003e\u003cp\u003eThe most striking divergence between methods was observed in the commercial pepperoni dataset. While Sample 1 showed excellent agreement across all metrics (ICC\u0026thinsp;=\u0026thinsp;0.948, r\u0026thinsp;=\u0026thinsp;0.962), most other products demonstrated statistically and practically significant disagreement. Samples 3\u0026ndash;5 yielded high mean differences, large negative effect sizes (Cohen\u0026rsquo;s d \u0026lt; \u0026minus;\u0026thinsp;5), and negative ICCs, indicating unreliable interchangeability.\u003c/p\u003e\u003cp\u003eThese discrepancies likely reflect variations in fat, spice, and emulsifier content across commercial brands \u0026mdash; all of which can affect chloride binding, visual endpoint clarity, and ionic conductivity. The weak or inverse Pearson correlations further emphasize that Mohr titration may not be reliable without prior matrix-specific calibration or dilution optimization.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003e4.5. Implications for Salt Quantification in Processed Meats\u003c/h2\u003e\u003cp\u003eFrom a practical standpoint, the findings strongly support the use of potentiometric or conductometric methods like DicromatII in processed meat applications. These methods offer superior linearity, precision, and resilience to matrix effects, minimizing the risk of inaccurate salt estimation \u0026mdash; which is crucial for regulatory compliance and sensory optimization.\u003c/p\u003e\u003cp\u003eMoreover, the inconsistencies observed with titration underscore the need for method validation within the actual matrix of use, rather than relying solely on standard solutions. This is particularly critical in cured meat products, where salt plays a dual role in preservation and flavour, and where even small deviations in reported values can have microbiological or sensory consequences.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003e4.6. Study Strengths and Limitations\u003c/h2\u003e\u003cp\u003eThis study employed a robust, matrix-tiered validation structure (standard, fortified, commercial), enabling nuanced assessment of analytical behavior under realistic conditions. However, it was limited by the absence of certified reference materials or gravimetric baseline data. Additionally, the Mohr method was applied in its classical format; performance may improve with instrumental titration setups or matrix-specific standard additions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e\u003ch2\u003e4.7. Conclusion\u003c/h2\u003e\u003cp\u003eOverall, the DicromatII demonstrated superior performance in terms of linearity, precision, and matrix tolerance, making it a reliable option for salt determination in both laboratory and industrial contexts. The Mohr titration method, while acceptable in clean matrices, exhibited considerable limitations in commercial pepperoni products. Future studies may explore hybrid approaches, such as conductivity-titration correlation modeling or matrix-adapted correction factors, to further improve salt quantification in complex foods.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study validated the use of the DicromatII conductivity-based method as a reliable and efficient alternative to the traditional Mohr titration for the quantification of sodium chloride in dry-fermented sausages. Across standard NaCl solutions and fortified pepperoni matrices, both methods showed excellent linearity and agreement. However, DicromatII consistently demonstrated superior precision, lower limits of detection and quantification, and greater reproducibility, particularly in complex matrices.\u003c/p\u003e\u003cp\u003eIn commercial pepperoni samples, agreement between the two methods diminished, with the Mohr titration showing higher variability and reduced correlation. Deming regression and Bland-Altman analyses further revealed the limitations of titration in real-world applications. The DicromatII method offered greater ease of use, reduced chemical handling, and robust performance, making it a suitable candidate for routine salt determination in meat quality control and product development settings.\u003c/p\u003e\u003cp\u003eThis validation supports the wider adoption of automated, instrumental salt analysis as a safer and scalable solution for the meat industry, particularly where high-throughput testing is required.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Ciar\u0026aacute;n Crowley (C.C.), Joseph P. Kerry (J.K.)\u003c/p\u003e\n\u003cp\u003eMethodology: C.C., J.K., Geraldine Duffy (G.D.)\u003c/p\u003e\n\u003cp\u003eInvestigation: C.C.\u003c/p\u003e\n\u003cp\u003eData Curation \u0026amp; Formal Analysis: C.C.\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; Original Draft: C.C.\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; Review \u0026amp; Editing: J.K.,\u003c/p\u003e\n\u003cp\u003eSupervision: J.K., G.D.\u003c/p\u003e\n\u003cp\u003eFunding Acquisition: J.K.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding. It was supported by internal resources of University College Cork, Ireland.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCapuano E, van der Veer G, Verheijen PJJ, et al. Comparison of a sodium-based and a chloride-based approach for the determination of sodium chloride content of processed foods in the Netherlands. J Food Compos Anal. 2013;31:129\u0026ndash;136. https://doi.org/10.1016/j.jfca.2013.04.004\u003c/li\u003e\n\u003cli\u003eFeiner G. Chapter 4 \u0026ndash; Additives. In: Salami. Academic Press; 2016:59\u0026ndash;88.\u003c/li\u003e\n\u003cli\u003eDurack E, Alonso-Gomez M, Wilkinson M. Salt: A review of its role in food science and public health. Curr Nutr Food Sci. 2008;4(4):290\u0026ndash;297. https://doi.org/10.2174/157340108786263702\u003c/li\u003e\n\u003cli\u003ePalumbo SA, Smith JL, Zaika LL. Sausage drying: Factors affecting the percent yield of pepperoni. J Food Sci. 1976;41(5):1270\u0026ndash;1272. https://doi.org/10.1111/j.1365-2621.1976.tb01149.x\u003c/li\u003e\n\u003cli\u003eSezey M, Adun P. Validation of Mohr titration method to determine salt in olive and olive brine. J Turk Chem Soc A Chem. 2019;6(3):329\u0026ndash;334. https://dergipark.org.tr/en/download/article-file/770647\u003c/li\u003e\n\u003cli\u003eLiang J, Ishikawa S. Novel technique for measuring salt concentrations in food using silver dichromate. Curr Res Food Sci. 2024;9:100880. https://doi.org/10.1016/j.crfs.2024.100880\u003c/li\u003e\n\u003cli\u003ePerez-Palacios T, Salas A, Mu\u0026ntilde;oz A, Oca\u0026ntilde;a ER, Antequera T. Sodium chloride determination in meat products: Comparison of the official titration-based method with atomic absorption spectrometry. J Food Compos Anal. 2022;108:104425. https://www.sciencedirect.com/science/article/pii/S0889157522000436\u003c/li\u003e\n\u003cli\u003eRasmussen LB, Lassen AD, Hansen K, et al. Salt content in canteen and fast-food meals in Denmark. Food Nutr Res. 2010;54:2100. https://doi.org/10.3402/fnr.v54i0.2100\u003c/li\u003e\n\u003cli\u003eDini I, Di Lorenzo R, Senatore A, et al. Validation of a rapid analysis to determine sodium chloride levels in canned tomatoes. J Food Meas Charact. 2023;17:4015\u0026ndash;4025. https://doi.org/10.1007/s11694-023-01932-6\u003c/li\u003e\n\u003cli\u003eNascimento EdS, Tenuta Filho A. Chemical waste risk reduction and environmental impact generated by laboratory activities in research and teaching institutions. Braz J Pharm Sci. 2010;46(2):187\u0026ndash;198. https://doi.org/10.1590/S1984-82502010000200002\u003c/li\u003e\n\u003cli\u003eAOAC International. Appendix F: Guidelines for Standard Method Performance Requirements. In: Official Methods of Analysis of AOAC International. 20th ed. AOAC; 2016.\u003c/li\u003e\n\u003cli\u003eISO 5725-2. Accuracy (Trueness and Precision) of Measurement Methods and Results \u0026ndash; Part 2: Basic Method for the Determination of Repeatability and Reproducibility. Geneva, Switzerland: International Organization for Standardization; 1994.\u003c/li\u003e\n\u003cli\u003eEurachem. The Fitness for Purpose of Analytical Methods: A Laboratory Guide to Method Validation and Related Topics. 2nd ed. 2014. https://www.eurachem.org/images/stories/Guides/pdf/validity_2014.pdf\u003c/li\u003e\n\u003cli\u003eTabachnick BG, Fidell LS. Using Multivariate Statistics. 6th ed. Pearson; 2013.\u003c/li\u003e\n\u003cli\u003eShrout PE, Fleiss JL. Intraclass correlations: Uses in assessing rater reliability. Psychol Bull. 1979;86(2):420\u0026ndash;428. https://doi.org/10.1037/0033-2909.86.2.420\u003c/li\u003e\n\u003cli\u003eSebranek JG, Jackson-Davis AL, Myers KL, Lavieri NA. Meat enhancement using phosphate and lactate-based ingredients: A review. Meat Sci. 2001;70:443\u0026ndash;458. https://doi.org/10.1016/j.meatsci.2004.02.010\u003c/li\u003e\n\u003cli\u003eMedina-Jaramillo C, Gomez-Delgado E, Martinez-Bustos F, et al. Validation of chloride determination in food matrices using potentiometric and turbidimetric methods. Molecules. 2019;24(10):1\u003c/li\u003e\n\u003cli\u003eBland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307\u0026ndash;310. \u003c/li\u003e\n\u003cli\u003eIBM Corp. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp; Released 2021.\u003c/li\u003e\n\u003cli\u003eCodex Alimentarius Commission. General Standard for the Labelling of Prepackaged Foods (CXS 1-1985). FAO/WHO; 2023.\u003c/li\u003e\n\u003cli\u003e21. Reyes FGR, Pereira RCL, Daroda RB. Analytical methods for sodium determination in processed foods: A review. Trends Food Sci Technol. 2020;96:158\u0026ndash;168.\u003c/li\u003e\n\u003cli\u003eEuropean Chemicals Agency (ECHA). Guidance on the Application of the CLP Criteria: Chromates. ECHA; 2021. https://echa.europa.eu\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Salt content, Salt content, Salt Titration, Fermented Meat, Proximal Composition, Physicochemical","lastPublishedDoi":"10.21203/rs.3.rs-7584102/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7584102/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccurate and reproducible determination of sodium chloride (NaCl) in processed meats is critical for product quality, safety, and regulatory compliance. This study compared the classical Mohr titration method with the DicromatII conductivity-based analyzer for quantifying NaCl in dry-fermented sausages. Validation was performed across three matrices: aqueous NaCl standards, fortified pepperoni homogenates, and commercial pepperoni products. Both methods exhibited excellent linearity (R\u0026sup2; \u0026gt;0.99) in standard and fortified matrices. However, the DicromatII demonstrated consistently higher precision (%RSD 0.4\u0026ndash;1.6%) and superior matrix tolerance, maintaining robust accuracy across all validation tiers. In commercial products, Mohr titration showed substantial variability, with weak correlation and poor agreement in most samples. The DicromatII, by contrast, offered reliable performance, reduced chemical handling, and strong repeatability, supporting its use in industrial meat analysis. This study represents the first direct validation-based comparison of these two methods in fermented meat matrices, highlighting the DicromatII as a safer and scalable alternative to traditional titration.\u003c/p\u003e","manuscriptTitle":"A Comparison of Methods: Titration vs DicromatII for the Measurement of Sodium Chloride (NaCl) Content in Dry Fermented Sausages","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-29 06:29:12","doi":"10.21203/rs.3.rs-7584102/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-06T14:53:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T20:04:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-27T14:42:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"243052667111041862459408204693948731430","date":"2025-09-23T08:02:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196420850362641561703581244254154717411","date":"2025-09-19T16:34:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155977750979284996926222806532388257549","date":"2025-09-19T07:44:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"232833674289973276687846274201052618050","date":"2025-09-18T15:13:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"144821362570529787318458150789597717747","date":"2025-09-18T09:00:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-18T07:48:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T22:45:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-15T22:44:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Food Analytical Methods","date":"2025-09-10T14:40:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c2776c90-39f5-424e-9527-7d7319cf3aa8","owner":[],"postedDate":"September 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-17T23:53:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-29 06:29:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7584102","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7584102","identity":"rs-7584102","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}