{"paper_id":"0d250fe3-2198-4106-9c41-063c7c03aedf","body_text":"Development of reference materials for accurate determination of tryptophan in fish meal and soybean meal | 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 Development of reference materials for accurate determination of tryptophan in fish meal and soybean meal Zheng Jia, Lan Li, Jian Zhou, Mengrui Yang, Min Wang, Peiling Wei, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9412191/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Tryptophan, which is essential for various physiological processes, influences the palatability of animal feed. In this study, two novel reference materials (RMs) for quantifying tryptophan in fish meal and soybean meal were developed. The homogeneity and short-term and long-term stability of these materials were evaluated via high-performance liquid chromatography using α-methyltryptophan as the internal standard. Characterization of RM was conducted in six laboratories. The value and expanded uncertainties ( k = 2) of tryptophan in fish meal and soybean meal were (0.65 ± 0.04) ×10 − 2 and (0.54 ± 0.04) ×10 − 2 , respectively. The overall measurement uncertainty was evaluated by combining contributions from homogeneity, short-term stability, long-term stability, and characterization. Results of homogeneity testing showed that in the candidate materials, tryptophan was homogeneously distributed between and within bottles. Stability monitoring results indicated that the candidate materials were stable for six months under 4 ℃ storage condition and nine days under 20 ℃ transportation conditions. The developed RMs have been successfully applied for quality control and interlaboratory comparisons within the Chinese feed quality testing system. tryptophan reference material characterization homogeneity and stability measurement uncertainty fish meal and soybean meal Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Tryptophan, an essential amino acid, is involved in almost every physiological process in animals—from metabolism to neurotransmission to protein metabolism. Tryptophan is also a precursor for the synthesis of serotonin in animals, an important neuromediator associated with mood, stress response, sleep, and appetite regulation (López et al. 2025 ). Moreover, tryptophan is used in the synthesis of niacin, which is essential for many metabolic pathways, such as energy production, lipid metabolism, and DNA repair. In addition to physiological functions, tryptophan can influence the palatability of animal feed. A palatable diet encourages higher feed intake, enabling animals to meet the energy and nutrient requirements necessary for growth and productivity (Okuno et al. 2007 ; Yıldırım et al. 2020 ; Fouad et al. 2021 ). However, because animals are unable synthesize tryptophan endogenously, it must be supplied through the diet (Le Floc’h and Seve 2007 ). As feed ingredients, fish and soybean meal are the most widely used sources of high-quality protein within the feed industry (Couture et al. 2019 ; Patiño et al. 2024 ). Therefore, an accurate and reliable quantification method for tryptophan is essential for quality control and evaluation of protein sources and feed products. Numerous methods have been developed for the separation and quantification of analytes in complex matrices, such as spectroscopy (Reynolds 2003 ; Zhang et al. 2025 ), high-performance liquid chromatography (Çevikkalp et al. 2016 ; López et al. 2025 ), and electroanalysis (Admasu et al. 2024 ; Gowda et al. 2025 ). For the pretreatment of protein-bound tryptophan in feed ingredients and feedstuffs, alkaline hydrolysis, acid hydrolysis, and enzymatic methods have been used. Despite introducing improvers into hydrolysis solutions, the release of tryptophan has been reported to be incomplete during acid hydrolysis and enzymatic methods. Thus, alkaline hydrolysis has become the common method of choice for tryptophan determination. Different alkalis, such as NaOH, LiOH, and Ba(OH) 2 , were used for protein hydrolysis in previous reports (Landry and Delhaye 1994 ; Yust et al. 2004 ; Ravindran and Bryden 2005 ). There are several official standards for tryptophan quantification in feed, including AOAC methods 988.15 (1988) ( ‘988.15, tryptophan in foods and food and feed ingredients’ , 1988), ISO 13904 (2016) ( ‘Animal feeding stuffs’ , 2016), European Commission (EC) regulation 152/2009 (European Union Commission Regulation (EU) No 152, 2009 ), and GB/T 15400 − 2019 (GB/T15400- 2018 Determination of Tryptophan in Feeds, 2018 ). The use of the alkaline hydrolysis process with different alkalis and high-performance chromatography with an ultraviolet or a fluorescence detector for tryptophan quantification has attained a universal consensus, and α-methyltryptophan was adopted as the internal standard in some official standards. In China, high-performance liquid chromatography (HPLC) and the ultraviolet spectrophotometry method in GB/T 15400 − 2019 were recommended as the reference method for the determination of tryptophan in feed. Reference materials (RMs) can be used at all stages of measurement processes, including for testing laboratory quality control and validating analytical methods. Matrix RMs have physical qualities similar to real samples, which is highly valuable for supporting laboratories in validating their analytical methods (Kawamoto et al. 2019 ; Zhou et al. 2023 ; Chen et al. 2024 ). Studies have used feed matrix RMs for quantifying elements (Kawamoto et al. 2019 ; Yan et al. 2022 ), crude protein, crude fiber, and crude ash (Jia et al. 2023 ). To the best of the authors knowledge, this is the first study investigating RMs for tryptophan quantification in feed ingredients. Thus, the aim of this research was to first prepare fish meal and soybean meal reference candidates having good homogeneity and stability under short-term and long-term storage conditions. Then, develop an accurate and traceable method for the quantification of tryptophan in the matrix. Finally, apply the optimized method for characterization and uncertainty evaluation. 2. Material and methods 2.1 Equipment Tryptophan was analyzed using a high-performance liquid chromatograph (1290 Infinity, Agilent Technologies, USA), coupled with a fluorescence detector (1260 FLD, Agilent Technologies, USA). Fluorescence detection was carried out at an excitation wavelength of 283 nm and emission wavelength of 343 nm. A Poroshell 120 SB-Aq analytical column (100 mm × 4.6 mm ID; particle size: 2.7 µm) was selected for the separation of tryptophan. The mobile phase consisted of acetonitrile and 0.05 M phosphate buffer, with a flow rate of 1.00 mL/min. The injection volume and column temperature were 10 µL and 28 ℃, respectively. Ultrapure water was obtained from a Thermo GenPure UV-TOC water purification system (Langenselbold, Germany). The following equipment was used in this study: an electronic balance (Sartorius, Germany), a nitrogen blower (EYEL4 MG-2200, Japan), a centrifuge (Sigma 3K15, Osterode, Germany), and a drying oven (Dess, Japan). 2.2 Reagents and standards Standard L-tryptophan with a certified purity of 99.7% and an uncertainty of 0.6% (coverage factor k = 2) was purchased from the National Institute of Metrology, China (GBW09233). The internal standard α-methyltryptophan was obtained from TRC (purity: 98%). Lithium hydroxide, potassium hydroxide, potassium dihydrogen phosphate, phosphoric acid, and hydrochloric acid with a GR grade were provided by Sinopharm Chemistry Reagent Co., Ltd. (Beijing, China). High-performance liquid chromatography–grade acetonitrile was obtained from Fisher scientific. A standard stock solution of tryptophan (5 mg/mL) was prepared in alkaline water containing 1 mL of 0.01 mol/L potassium hydroxide solution in 100 mL ultrapure water. The stock solution was stable at 4℃. A 5 mg/mL solution of the internal standard α-methyltryptophan was prepared in a 0.1 mol/L potassium hydroxide solution and stored at 4 ℃. 2.3 Preparation of fish meal and soybean meal reference material Approximately 40 kg each of fish and soybean meals were obtained from commercial manufacturers to develop RMs. A large-scale grinder was utilized to grind the RMs. After grinding, the samples were sieved through a sieve plate, and those with a mesh size larger than 60 mesh were collected. Subsequently, the RMs were separately mixed multiple times in a 50 L mixer to obtain a homogenized mixture. The homogenized RMs were then packed into 1000 glass bottles, with each packaging unit containing approximately 1 g of the sample. Following this, the samples were sterilized via gamma-ray irradiation at an average dose of 5.5 kGy for 4 h. Finally, the RMs were stored at 4 ℃. 2.4 Analytical methods After optimizing the pretreatment parameters, analytical measurement of tryptophan was carried out as follows. A total of 75 mg of the feed sample was accurately weighed in a 20-mL PTFE hydrolysis tube liner with a PTFE screw-top, and 1.5 mL of a 4 N lithium solution was added into the sample. The tube liner was tightened after filling it with nitrogen using a nitrogen blower. After hydrolyzing in an oven at 110 ℃ for 20 h, the hydrolysates were transferred to a 50 mL volumetric flask containing approximately 40 mL of ultrapure water. A total of 1 mL of 6 mol/L hydrochloric acid was added to bring the solution to neutral pH. Subsequently, 0.5 mL of the internal standard solution was added. Further, water was added to the mark of the volumetric flask and shaken well. About 25 mL of the solution was centrifuged at 8000 r/min for 5 min. The supernatant was diluted 10 times and filtered via a 0.45 µm syringe filter into an autosampler vial. 2.5 Characterization study Collaborative assignment of reference values was carried out in six laboratories in accordance with the ISO Guide 35 requirements. All these laboratories have obtained ISO 17025 accreditation and participated in routine testing or risk assessment projects for the Chinese Ministry of Feed and Rural Affairs. Three units of randomly selected candidate samples, a tryptophan standard solution, and the internal standard were provided to each laboratory. The optimized method was recommended to the six laboratories for collaborative characterization. Three independent subsamples from each unit were analyzed, and individual results were subjected to normal analysis, the Dixon test for outliers, and the Cochran test for outlying variances. The average value from the above tests was taken as the reference value. 2.6 Homogeneity and stability study The optimized HPLC method using an internal standard was applied for the assessment of homogeneity and stability. For the homogeneity test, mass fractions of tryptophan in 25 bottles of RM candidate samples chosen randomly were analyzed. A one-way analysis of variance (ANOVA) with a confidence level of 95% and linear regression were performed. Short-term stability tests were carried out at 20 ℃ and 60 ℃ for 0, 1, 3, 5, 7, and 9 days. Long-term stability was tested at 4 ℃ for 0, 1, 2, 4, and 6 months. Homogeneity and stability experiments were performed in triplicate using two randomly selected units of RM candidates. 3. Results and discussion 3.1 Optimization of sample hydrolysis condition and instrument Unlike most other amino acids, the hydrolysis of tryptophan must consider its labile nature in the presence of light and hydrogen ions. Researchers have attempted to improve the recovery of tryptophan from feedstuffs by introducing additives such as thioglycolic acid and pyridine borane during acid hydrolysis; however, in previous studies, tryptophan could not be completely released. Hence, alkaline hydrolysis of protein-bound tryptophan in feedstuffs, followed by reverse-phase chromatography, has become the suitable method for tryptophan determination. In this study, the differences between various hydrolysis solutions were compared first. The results showed that there was no significant difference in the detection of tryptophan between the sodium hydroxide and lithium hydroxide solutions, while the relative deviation of lithium hydroxide was better than that of sodium hydroxide. The hydrolysis solution amounts and hydrolysis time were optimized through a single variable experiment, and the results are shown in Fig. 1 . Considering that the tryptophan content was maximized and the relative deviation was as small as possible, 1.5 mL of 4 N lithium hydroxide solution was selected as the optimum solution, and 20 h was chosen as the optimum hydrolysis time for tryptophan in fish and soybean meals. The chromatographic conditions were also optimized with the aim of achieving anti-interference capabilities in matrix, simultaneous separation between the target analyte and internal standard, and ideal analysis efficiency. To this end, various mobile phases composed of methanol and acetonitrile with various concentrations of phosphate buffer were examined. The results showed that 5% acetonitrile with 95% 0.05 mol/L phosphate buffer yielded a better baseline and peak pattern than methanol. 3.2 Method validation Linearity, limit of detection (LOD), limit of quantification (LOQ), precision, and recovery were determined to validate the proposed quantification method. LOD and LOQ of the optimized method were determined to be 12.5 and 100 mg/kg, respectively, on the basis of signal-to-noise ratios of 3:1 and 10:1, respectively. Under the optimized experimental conditions, the calibration curves showed excellent linearity over a wide concentration range of 0.01–5.0 µg/mL, along with a satisfactory correlation coefficient ( R 2 = 0.9991). A recovery analysis was performed by spiking a sample with a known concentration of the standard, resulting in recovery rates of 92.4–100% in fish meal and 93.8–107% in soybean meal. These results indicate that the method is appropriate for reference value assignment. 3.3 Homogeneity To evaluate the homogeneity of tryptophan in fish and soybean meals, 22 fish meal and 18 soybean meal samples were randomly selected, and their tryptophan amounts were determined using the optimized HPLC method. The contents of tryptophan within a bottle and between bottles were analyzed using the ANOVA method. The statistical result of F = 1.29 obtained for tryptophan was less than the critical value of F 0.05 (24.50) = 1.86. The results are shown in Fig. 2 , indicating that there are no significant differences at the considered confidence level. 3.4 Short-term and long-term stability A stability study of tryptophan in fish and soybean meals under transportation and storage conditions was performed. A trend analysis was carried out to statistically evaluate the short-term and long-term stability of tryptophan in the fish and soybean meal RMs. The slope was considered statistically insignificant when | β 1 |< t 0.95,3 · s ( β 1 ). The results are shown in Fig. 3 and Table 1 , indicating that the RM was stable for at least six months at 4 ℃ and for nine days at 20 ℃ and 60 ℃. The linear regression plots for studying long-term stability during six months of storage at 4 ℃ are also presented in Fig. 3 . Table 1 Short-term stability of tryptophan in fish meal and soybean meal RMs (%) Time (days) Fish meal Soybean meal 20 ℃ 60 ℃ 20 ℃ 60 ℃ 1 0.640 0.657 0.508 0.506 3 0.643 0.640 0.524 0.517 5 0.645 0.652 0.539 0.503 7 0.646 0.644 0.527 0.534 9 0.647 0.635 0.529 0.536 β 1 8.5×10 − 4 2.0×10 − 3 2.25×10 − 3 3.85×10 − 3 β 0 0.640 0.653 0.514 0.506 s 2 4.9×10 − 6 6.0×10 − 5 1.0×10 − 4 5.4×10 − 4 s ( β 1 ) 1.42×10 − 3 2.86×10 − 2 1.59×10 − 3 3.68×10 − 3 t 0.95, 3 · s ( β 1 ) 4.52×10 − 3 9.10×10 − 2 5.05×10 − 3 1.17×10 − 2 Conclusion | β 1 |< t 0.95,3 s ( β 1 ), stable | β 1 |< t 0.95,3 s ( β 1 ), stable 3.5 Characterization study The characterization of tryptophan in fish and soybean meal RMs was performed in six laboratories. The standard solution, three units of the sample, and an internal standard were supplied by the organizer’s laboratory, and the optimized HPLC method was recommended as the reference method for characterization. First, data were statistically analyzed using the Skewness coefficient and kurtosis coefficient methods and regarded as having a normal distribution. Then, Dixon and Cochran tests were conducted to evaluate the outliers and outlying variances in the measurement results. The results submitted by the six participating laboratories are shown in Fig. 4 . The results showed that there were no outliers or outlying variances in the dataset at a confidence level of 95%. Finally, the characterization values of tryptophan in fish and soybean meals were assigned to be 0.65% and 0.54%, respectively. 3.6 Uncertainty The uncertainty of the reference value ( U RM ) is expressed by the following equation, according to ISO Guide 35: $$\\:{U}_{\\text{R}\\text{M},\\text{r}\\text{e}\\text{l}}={u}_{\\text{R}\\text{M},\\:\\text{r}\\text{e}\\text{l}}\\times\\:k=\\sqrt{{{u}_{\\text{c}\\text{h}\\text{a}\\text{r},\\text{r}\\text{e}\\text{l}}}^{2}+{{u}_{\\text{b}\\text{b},\\text{r}\\text{e}\\text{l}\\:}}^{2}{{u}_{\\text{l}\\text{t}\\text{s},\\text{r}\\text{e}\\text{l}}}^{2}+{{u}_{\\text{s}\\text{t}\\text{s},\\text{r}\\text{e}\\text{l}}}^{2}}\\times\\:k$$ , where U RM,rel is the relative combined uncertainty; k = 2 is the coverage factor at a confidence level of 95%; u char,rel is the uncertainty in characterizing the reference value, which is divided into two parts: u A and u B ; u bb,rel is the uncertainty in homogeneity; u lts,rel is the uncertainty in long-term stability; and u sts,rel is the uncertainty in short-term stability. Table 2 summarizes the contribution of each factor in the above equation to the overall combined uncertainties for tryptophan in the two RMs. For fish meal, the major contributor to the overall combined uncertainty was the uncertainty in characterization, followed by uncertainties in long- and short-term stabilities, while the contribution from the uncertainty in homogeneity was minor. For soybean meal, the major contributors to the overall combined uncertainty were the uncertainties in long-term stability and characterization, followed by uncertainties in the short-term stability and homogeneity. According to Table 2 , tryptophan in the two RMs had a significant influence on the characterization uncertainty component. The relative expanded uncertainties of the tryptophan in fish meal and soybean meal were 5.32% and 5.78%, respectively. Table 2 Contributions of uncertainties in characterization ( u char,rel ), homogeneity ( u bb,rel ), long-term stability ( u lts,rel ), and short-term stability ( u sts,rel ) to the combined uncertainty of different RMs. Uncertainty component Source Evaluation Fish meal Soybean meal \\(\\:{u}_{\\text{c}\\text{h}\\text{a}\\text{r},\\text{r}\\text{e}\\text{l}}\\) (%) Characterization process \\(\\:{u}_{\\text{c}\\text{h}\\text{a}\\text{r},\\text{r}\\text{e}\\text{l}}=\\sqrt{{{u}_{\\text{A},\\text{r}\\text{e}\\text{l}}}^{2}+{{u}_{\\text{B},\\text{r}\\text{e}\\text{l}}}^{2}}\\) 2.26 1.92 \\(\\:{u}_{\\text{A},\\text{r}\\text{e}\\text{l}}\\) (%) Standard deviation of multiple laboratory measurements \\(\\:{u}_{A}=\\sqrt{\\frac{{\\sum\\:}_{i=1}^{n}{(\\stackrel{-}{{x}_{i}}-\\stackrel{̿}{x})}^{2}}{n\\times\\:(n-1)}},\\:\\:{u}_{A,\\text{r}\\text{e}\\text{l}}=\\frac{{u}_{A}}{\\overline{x}}\\) 0.82 0.51 \\(\\:{u}_{\\text{B},\\text{r}\\text{e}\\text{l}}\\) (%) Preparation of standard solution, \\(\\:{u}_{\\text{s}\\text{t}\\text{d},\\text{r}\\text{e}\\text{l}}\\) ; Preparation of internal standard, \\(\\:{u}_{\\text{I}\\text{S},\\text{r}\\text{e}\\text{l}}\\) ; Balance weighing of sample, \\(\\:{u}_{\\text{M},\\text{r}\\text{e}\\text{l}}\\) ; Standard curve linearity, \\(\\:{u}_{\\text{l}\\text{i}\\text{n},\\text{r}\\text{e}\\text{l}}\\) \\(\\:{u}_{\\text{B},\\text{r}\\text{e}\\text{l}}=\\sqrt{{{u}_{\\text{s}\\text{t}\\text{d},\\text{r}\\text{e}\\text{l}}}^{2}+{{u}_{\\text{I}\\text{S},\\text{r}\\text{e}\\text{l}}}^{2}{{u}_{\\text{M},\\text{r}\\text{e}\\text{l}}}^{2}+{{u}_{\\text{l}\\text{i}\\text{n},\\text{r}\\text{e}\\text{l}}}^{2}}\\) 2.11 1.85 \\(\\:{u}_{\\text{b}\\text{b},\\text{r}\\text{e}\\text{l}}\\) (%) Homogeneity test \\(\\:{u}_{\\text{b}\\text{b}}=\\sqrt{\\frac{{HS}_{bb}-{HS}_{wb}}{n}}{u}_{\\text{b}\\text{b},\\text{r}\\text{e}\\text{l}}=\\frac{{u}_{\\text{b}\\text{b}}}{{\\stackrel{-}{x}}_{\\text{b}\\text{b}}}\\) 0.49 0.59 \\(\\:{u}_{\\text{l}\\text{t}\\text{s},\\text{r}\\text{e}\\text{l}}\\) (%) Long-term stability study \\(\\:{u}_{\\text{l}\\text{t}\\text{s}}=s\\left({\\text{b}}_{1}\\right)\\bullet\\:t,\\:{u}_{\\text{l}\\text{t}\\text{s},\\text{r}\\text{e}\\text{l}}=\\frac{{\\text{u}}_{\\text{l}\\text{t}\\text{s}}}{{\\stackrel{-}{\\text{x}}}_{\\text{l}\\text{t}\\text{s}}}\\) 1.31 2.08 \\(\\:{u}_{\\text{s}\\text{t}\\text{s},\\text{r}\\text{e}\\text{l}}\\) (%) Short-term stability study \\(\\:{u}_{\\text{s}\\text{t}\\text{s}}=s\\left({\\text{b}}_{1}\\right)\\bullet\\:t,\\:{u}_{\\text{s}\\text{t}\\text{s},\\text{r}\\text{e}\\text{l}}=\\frac{{\\text{u}}_{\\text{s}\\text{t}\\text{s}}}{{\\stackrel{-}{\\text{x}}}_{\\text{s}\\text{t}\\text{s}}}\\) 0.97 1.64 \\(\\:{\\text{U}}_{\\text{R}\\text{M},\\text{r}\\text{e}\\text{l}\\:}\\) (%) Relative expanded uncertainty \\(\\:{U}_{\\text{R}\\text{M},\\text{r}\\text{e}\\text{l}}={u}_{\\text{c},\\text{r}\\text{e}\\text{l}}\\times\\:2(coverage\\:factor\\:k=2.00\\:at\\:the\\:confidence\\:level\\:of\\:95\\%)\\) 5.32 5.78 C (%) Reference value \\(\\:{U}_{\\text{R}\\text{M}}={U}_{\\text{R}\\text{M},\\text{r}\\text{e}\\text{l}}\\times\\:2\\) 0.65 0.54 \\(\\:{U}_{\\text{R}\\text{M}}\\) (%) 0.04 0.04 4. Conclusions Two new matrix RMs for tryptophan in soybean and fish meals were successfully developed. The preparation of the RM and optimization of the characterization method are described in detail. Stability monitoring, homogeneity test, and characterization using the developed HPLC method, with α-methyltryptophan as the internal standard, were performed, yielding good accuracy and precision. The reference values of tryptophan in soybean and fish meal were assigned to be 0.54 ± 0.04% and 0.65 ± 0.04%, respectively, at a confidence level of 95% (coverage factor k = 2). The RMs demonstrated homogeneity and stability for at least six months at 4 ℃, while short-term stability monitoring showed that they were stable at 20 ℃ for nine days. These RMs have been approved as national RMs with the numbers GBW(E) 100573 and GBW(E) 100574. The novel RMs developed in this study have been used in laboratory comparisons of the Chinese feed quality testing system and found suitable for laboratory quality control and analytical method evaluation. Declarations Conflicts of Interest: The authors declare no conflict of interest. Funding: This work was supported by the Xinjiang Key Research and Development Program of China [grant number 2023B02015] and the innovation program of Chinese Academy of Agricultural Science. Author Contribution Author Contributions: Z.J.: Conceptualization, Methodology, Investigation, Validation, Software, Writing. L.L.: Investigation, Data curation. J.Z.: Validation, Investigation. M.Y.: Validation. M.W.: Supervision, Project administration. P.W.: Investigation. S.X.: Investigation. J.T.: Investigation. X.F.: Conceptualization. Acknowledgments: We are grateful to the following laboratories for their support in verifying the tryptophan amounts in the fish and soybean meal reference materials developed in this study: (1) Henan Supervision Institute of Veterinary Drug and Feed, (2)Feed products quality monitoring center of the agriculture and rural affairs ministry of China (Chengdu), (3) Chongqing Veterinary Medicine and Feed Testing Institute, (4) Analysis and Testing Center, Sichuan Academy of Agricultural Science, and (5) Henan Hairuizheng Testing Technology Co., Ltd. Data Availability Statement: All data are presented in the article. References AOAC of ficial method 988.15, tryptophan in foods and food and feed ingredients (1988) Admasu TG, Halefom TH, Debebe SE (2024) Attachment of ρ-aminobenzene sulphonic acid into magnetic Fe3O4 reduced graphene oxide and its application for sensitive determination of L-tryptophan in milk and banana samples. 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Food Chem 85(2):317–320. https://doi.org/10.1016/j.foodchem.2003.07.026 Zhang T, Zhu Z, Bian Y, Zhang X, Cheng L, Qin H, Yang B (2025) Terahertz time-domain spectroscopy for monitoring the dynamic process of tryptophan photooxidation and the concentration determination. J Mol Struct 1331:141640. https://doi.org/10.1016/j.molstruc.2025.141640 Zhou J, Yang M, Li F, Wang M, Zhang Y, Wei M, Li X, Qi X, Bai X, Chai Y (2023) Development of matrix certified reference material for accurate determination of docosahexaenoic acid in milk powder. Food Chem 406:135012. https://doi.org/10.1016/j.foodchem.2022.135012 Additional Declarations No competing interests reported. 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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-9412191\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":638139554,\"identity\":\"db92b9dd-f2ce-4e2b-8138-3fcc3ee5b8b1\",\"order_by\":0,\"name\":\"Zheng Jia\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Zheng\",\"middleName\":\"\",\"lastName\":\"Jia\",\"suffix\":\"\"},{\"id\":638139555,\"identity\":\"29b867d3-7dd0-4123-9792-24d83995909e\",\"order_by\":1,\"name\":\"Lan Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Lan\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":638139556,\"identity\":\"c4b9882b-bc95-41b7-b17d-e2aca73af353\",\"order_by\":2,\"name\":\"Jian Zhou\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jian\",\"middleName\":\"\",\"lastName\":\"Zhou\",\"suffix\":\"\"},{\"id\":638139557,\"identity\":\"5b049557-3ecb-4d16-971f-ab0ee100abe0\",\"order_by\":3,\"name\":\"Mengrui Yang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mengrui\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"},{\"id\":638139558,\"identity\":\"7208ce2b-39d6-4e19-93a8-49ae4a1e3a94\",\"order_by\":4,\"name\":\"Min Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Min\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":638139559,\"identity\":\"a88bb25d-2945-4399-99a6-52746ff43ff6\",\"order_by\":5,\"name\":\"Peiling Wei\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Animal Husbandry Quality Standards\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Peiling\",\"middleName\":\"\",\"lastName\":\"Wei\",\"suffix\":\"\"},{\"id\":638139560,\"identity\":\"32c2f33c-e026-4474-91e8-6962b30eab02\",\"order_by\":6,\"name\":\"Siyuan Xu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Siyuan\",\"middleName\":\"\",\"lastName\":\"Xu\",\"suffix\":\"\"},{\"id\":638139561,\"identity\":\"c6c27cb5-177c-4563-ac16-8b1d903b7067\",\"order_by\":7,\"name\":\"Jing Tian\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jing\",\"middleName\":\"\",\"lastName\":\"Tian\",\"suffix\":\"\"},{\"id\":638139562,\"identity\":\"a13457ab-04c2-4ca4-9819-d747566c7d8b\",\"order_by\":8,\"name\":\"Xia Fan\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqUlEQVRIiWNgGAWjYBAC9gYgkcBgQ4IWngNgLWmkamFgOEyKFvazxyQe1JyX528//oDh5w5itPDkJRskHLttOONMjgFj7xkitNgz5Bg+SGC7ncBwIIeBmbGNGFv43xgcSPh3LkH+/PMHRGqRANqS2HYgweBGggGxWt4YGyT2JRtuvPHG4GAvcQ7LMZP88c1OXu58+sMHP4nRggIOkKphFIyCUTAKRgEOAAD6fTVj0xtV4AAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Institute of Quality Standards and Testing Technology for Agro Products\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Xia\",\"middleName\":\"\",\"lastName\":\"Fan\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-04-14 07:54:09\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9412191/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9412191/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":109406072,\"identity\":\"47dd9c95-1886-410d-bc19-9b25e9e8878f\",\"added_by\":\"auto\",\"created_at\":\"2026-05-17 13:24:23\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":845570,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eEffect of different hydrolysis solutions (a), amounts of lithium hydroxide solution (b), hydrolysis time (c), and typical HPLC chromatograms (d) on tryptophan quantification.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9412191/v1/de3a1c23b329fddbd5b629ee.png\"},{\"id\":109406050,\"identity\":\"851c911c-274d-4cda-81d0-b881f6db24db\",\"added_by\":\"auto\",\"created_at\":\"2026-05-17 13:24:09\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":361354,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eHomogeneity test results for tryptophan in fish meal (a) and soybean meal (b). Error bars indicate the standard deviation of measurement for each bottle.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9412191/v1/2adc749c2c25757034c38ea7.png\"},{\"id\":109405906,\"identity\":\"4cd91c39-4f3d-4148-986c-802f1aab6bbf\",\"added_by\":\"auto\",\"created_at\":\"2026-05-17 13:22:11\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":287719,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLinear regression plots for long-term stability analysis during six months of storage at 4 ℃ for tryptophan in soybean meal (a) and fish meal (b) samples\\u003cstrong\\u003e.\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9412191/v1/9aed04db54832ccfbed30bb2.png\"},{\"id\":109406079,\"identity\":\"ea5a9bcd-0fca-4499-a979-b9a0ba3a6b9d\",\"added_by\":\"auto\",\"created_at\":\"2026-05-17 13:24:31\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":261759,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eResults obtained from the participating laboratories for the characterization of tryptophan in soybean meal (a) and fish meal (b). Error bars represent the standard deviation of measurement results for each laboratory.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9412191/v1/683b9773c5a72fb88433a358.png\"},{\"id\":109406428,\"identity\":\"6d7591cc-1133-4b63-b698-72dae9d896b8\",\"added_by\":\"auto\",\"created_at\":\"2026-05-17 13:28:09\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2031888,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9412191/v1/88075f1f-4e97-4cf8-b66c-0df1dd598916.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Development of reference materials for accurate determination of tryptophan in fish meal and soybean meal\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eTryptophan, an essential amino acid, is involved in almost every physiological process in animals\\u0026mdash;from metabolism to neurotransmission to protein metabolism. Tryptophan is also a precursor for the synthesis of serotonin in animals, an important neuromediator associated with mood, stress response, sleep, and appetite regulation (L\\u0026oacute;pez et al. \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e). Moreover, tryptophan is used in the synthesis of niacin, which is essential for many metabolic pathways, such as energy production, lipid metabolism, and DNA repair. In addition to physiological functions, tryptophan can influence the palatability of animal feed. A palatable diet encourages higher feed intake, enabling animals to meet the energy and nutrient requirements necessary for growth and productivity (Okuno et al. \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e; Yıldırım et al. \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Fouad et al. \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). However, because animals are unable synthesize tryptophan endogenously, it must be supplied through the diet (Le Floc\\u0026rsquo;h and Seve \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). As feed ingredients, fish and soybean meal are the most widely used sources of high-quality protein within the feed industry (Couture et al. \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Pati\\u0026ntilde;o et al. \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Therefore, an accurate and reliable quantification method for tryptophan is essential for quality control and evaluation of protein sources and feed products.\\u003c/p\\u003e \\u003cp\\u003eNumerous methods have been developed for the separation and quantification of analytes in complex matrices, such as spectroscopy (Reynolds \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e; Zhang et al. \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e), high-performance liquid chromatography (\\u0026Ccedil;evikkalp et al. \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e; L\\u0026oacute;pez et al. \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e), and electroanalysis (Admasu et al. \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e; Gowda et al. \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e). For the pretreatment of protein-bound tryptophan in feed ingredients and feedstuffs, alkaline hydrolysis, acid hydrolysis, and enzymatic methods have been used. Despite introducing improvers into hydrolysis solutions, the release of tryptophan has been reported to be incomplete during acid hydrolysis and enzymatic methods. Thus, alkaline hydrolysis has become the common method of choice for tryptophan determination. Different alkalis, such as NaOH, LiOH, and Ba(OH)\\u003csub\\u003e2\\u003c/sub\\u003e, were used for protein hydrolysis in previous reports (Landry and Delhaye \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e1994\\u003c/span\\u003e; Yust et al. \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e; Ravindran and Bryden \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThere are several official standards for tryptophan quantification in feed, including AOAC methods 988.15 (1988) (\\u003cem\\u003e\\u0026lsquo;988.15, tryptophan in foods and food and feed ingredients\\u0026rsquo;\\u003c/em\\u003e, 1988), ISO 13904 (2016) (\\u003cem\\u003e\\u0026lsquo;Animal feeding stuffs\\u0026rsquo;\\u003c/em\\u003e, 2016), European Commission (EC) regulation 152/2009 (European Union Commission Regulation (EU) No 152, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e), and GB/T 15400\\u0026thinsp;\\u0026minus;\\u0026thinsp;2019 (GB/T15400-\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e Determination of Tryptophan in Feeds, \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). The use of the alkaline hydrolysis process with different alkalis and high-performance chromatography with an ultraviolet or a fluorescence detector for tryptophan quantification has attained a universal consensus, and α-methyltryptophan was adopted as the internal standard in some official standards. In China, high-performance liquid chromatography (HPLC) and the ultraviolet spectrophotometry method in GB/T 15400\\u0026thinsp;\\u0026minus;\\u0026thinsp;2019 were recommended as the reference method for the determination of tryptophan in feed.\\u003c/p\\u003e \\u003cp\\u003eReference materials (RMs) can be used at all stages of measurement processes, including for testing laboratory quality control and validating analytical methods. Matrix RMs have physical qualities similar to real samples, which is highly valuable for supporting laboratories in validating their analytical methods (Kawamoto et al. \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Zhou et al. \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Chen et al. \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Studies have used feed matrix RMs for quantifying elements (Kawamoto et al. \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Yan et al. \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), crude protein, crude fiber, and crude ash (Jia et al. \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). To the best of the authors knowledge, this is the first study investigating RMs for tryptophan quantification in feed ingredients. Thus, the aim of this research was to first prepare fish meal and soybean meal reference candidates having good homogeneity and stability under short-term and long-term storage conditions. Then, develop an accurate and traceable method for the quantification of tryptophan in the matrix. Finally, apply the optimized method for characterization and uncertainty evaluation.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e\"},{\"header\":\"2. Material and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Equipment\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eTryptophan was analyzed using a high-performance liquid chromatograph (1290 Infinity, Agilent Technologies, USA), coupled with a fluorescence detector (1260 FLD, Agilent Technologies, USA). Fluorescence detection was carried out at an excitation wavelength of 283 nm and emission wavelength of 343 nm. A Poroshell 120 SB-Aq analytical column (100 mm \\u0026times; 4.6 mm ID; particle size: 2.7 \\u0026micro;m) was selected for the separation of tryptophan. The mobile phase consisted of acetonitrile and 0.05 M phosphate buffer, with a flow rate of 1.00 mL/min. The injection volume and column temperature were 10 \\u0026micro;L and 28 ℃, respectively. Ultrapure water was obtained from a Thermo GenPure UV-TOC water purification system (Langenselbold, Germany). The following equipment was used in this study: an electronic balance (Sartorius, Germany), a nitrogen blower (EYEL4 MG-2200, Japan), a centrifuge (Sigma 3K15, Osterode, Germany), and a drying oven (Dess, Japan).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Reagents and standards\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eStandard L-tryptophan with a certified purity of 99.7% and an uncertainty of 0.6% (coverage factor \\u003cem\\u003ek\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2) was purchased from the National Institute of Metrology, China (GBW09233). The internal standard α-methyltryptophan was obtained from TRC (purity: 98%). Lithium hydroxide, potassium hydroxide, potassium dihydrogen phosphate, phosphoric acid, and hydrochloric acid with a GR grade were provided by Sinopharm Chemistry Reagent Co., Ltd. (Beijing, China). High-performance liquid chromatography\\u0026ndash;grade acetonitrile was obtained from Fisher scientific.\\u003c/p\\u003e \\u003cp\\u003eA standard stock solution of tryptophan (5 mg/mL) was prepared in alkaline water containing 1 mL of 0.01 mol/L potassium hydroxide solution in 100 mL ultrapure water. The stock solution was stable at 4℃.\\u003c/p\\u003e \\u003cp\\u003eA 5 mg/mL solution of the internal standard α-methyltryptophan was prepared in a 0.1 mol/L potassium hydroxide solution and stored at 4 ℃.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Preparation of fish meal and soybean meal reference material\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eApproximately 40 kg each of fish and soybean meals were obtained from commercial manufacturers to develop RMs. A large-scale grinder was utilized to grind the RMs. After grinding, the samples were sieved through a sieve plate, and those with a mesh size larger than 60 mesh were collected. Subsequently, the RMs were separately mixed multiple times in a 50 L mixer to obtain a homogenized mixture. The homogenized RMs were then packed into 1000 glass bottles, with each packaging unit containing approximately 1 g of the sample. Following this, the samples were sterilized via gamma-ray irradiation at an average dose of 5.5 kGy for 4 h. Finally, the RMs were stored at 4 ℃.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 Analytical methods\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eAfter optimizing the pretreatment parameters, analytical measurement of tryptophan was carried out as follows. A total of 75 mg of the feed sample was accurately weighed in a 20-mL PTFE hydrolysis tube liner with a PTFE screw-top, and 1.5 mL of a 4 N lithium solution was added into the sample. The tube liner was tightened after filling it with nitrogen using a nitrogen blower. After hydrolyzing in an oven at 110 ℃ for 20 h, the hydrolysates were transferred to a 50 mL volumetric flask containing approximately 40 mL of ultrapure water. A total of 1 mL of 6 mol/L hydrochloric acid was added to bring the solution to neutral pH. Subsequently, 0.5 mL of the internal standard solution was added. Further, water was added to the mark of the volumetric flask and shaken well. About 25 mL of the solution was centrifuged at 8000 r/min for 5 min. The supernatant was diluted 10 times and filtered via a 0.45 \\u0026micro;m syringe filter into an autosampler vial.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5 Characterization study\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eCollaborative assignment of reference values was carried out in six laboratories in accordance with the ISO Guide 35 requirements. All these laboratories have obtained ISO 17025 accreditation and participated in routine testing or risk assessment projects for the Chinese Ministry of Feed and Rural Affairs. Three units of randomly selected candidate samples, a tryptophan standard solution, and the internal standard were provided to each laboratory. The optimized method was recommended to the six laboratories for collaborative characterization. Three independent subsamples from each unit were analyzed, and individual results were subjected to normal analysis, the Dixon test for outliers, and the Cochran test for outlying variances. The average value from the above tests was taken as the reference value.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.6 Homogeneity and stability study\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eThe optimized HPLC method using an internal standard was applied for the assessment of homogeneity and stability. For the homogeneity test, mass fractions of tryptophan in 25 bottles of RM candidate samples chosen randomly were analyzed. A one-way analysis of variance (ANOVA) with a confidence level of 95% and linear regression were performed. Short-term stability tests were carried out at 20 ℃ and 60 ℃ for 0, 1, 3, 5, 7, and 9 days. Long-term stability was tested at 4 ℃ for 0, 1, 2, 4, and 6 months. Homogeneity and stability experiments were performed in triplicate using two randomly selected units of RM candidates.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results and discussion\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Optimization of sample hydrolysis condition and instrument\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eUnlike most other amino acids, the hydrolysis of tryptophan must consider its labile nature in the presence of light and hydrogen ions. Researchers have attempted to improve the recovery of tryptophan from feedstuffs by introducing additives such as thioglycolic acid and pyridine borane during acid hydrolysis; however, in previous studies, tryptophan could not be completely released. Hence, alkaline hydrolysis of protein-bound tryptophan in feedstuffs, followed by reverse-phase chromatography, has become the suitable method for tryptophan determination. In this study, the differences between various hydrolysis solutions were compared first. The results showed that there was no significant difference in the detection of tryptophan between the sodium hydroxide and lithium hydroxide solutions, while the relative deviation of lithium hydroxide was better than that of sodium hydroxide. The hydrolysis solution amounts and hydrolysis time were optimized through a single variable experiment, and the results are shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Considering that the tryptophan content was maximized and the relative deviation was as small as possible, 1.5 mL of 4 N lithium hydroxide solution was selected as the optimum solution, and 20 h was chosen as the optimum hydrolysis time for tryptophan in fish and soybean meals. The chromatographic conditions were also optimized with the aim of achieving anti-interference capabilities in matrix, simultaneous separation between the target analyte and internal standard, and ideal analysis efficiency. To this end, various mobile phases composed of methanol and acetonitrile with various concentrations of phosphate buffer were examined. The results showed that 5% acetonitrile with 95% 0.05 mol/L phosphate buffer yielded a better baseline and peak pattern than methanol.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Method validation\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eLinearity, limit of detection (LOD), limit of quantification (LOQ), precision, and recovery were determined to validate the proposed quantification method. LOD and LOQ of the optimized method were determined to be 12.5 and 100 mg/kg, respectively, on the basis of signal-to-noise ratios of 3:1 and 10:1, respectively. Under the optimized experimental conditions, the calibration curves showed excellent linearity over a wide concentration range of 0.01\\u0026ndash;5.0 \\u0026micro;g/mL, along with a satisfactory correlation coefficient (\\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.9991). A recovery analysis was performed by spiking a sample with a known concentration of the standard, resulting in recovery rates of 92.4\\u0026ndash;100% in fish meal and 93.8\\u0026ndash;107% in soybean meal. These results indicate that the method is appropriate for reference value assignment.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Homogeneity\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eTo evaluate the homogeneity of tryptophan in fish and soybean meals, 22 fish meal and 18 soybean meal samples were randomly selected, and their tryptophan amounts were determined using the optimized HPLC method. The contents of tryptophan within a bottle and between bottles were analyzed using the ANOVA method. The statistical result of \\u003cem\\u003eF\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1.29 obtained for tryptophan was less than the critical value of \\u003cem\\u003eF\\u003c/em\\u003e\\u003csub\\u003e0.05\\u003c/sub\\u003e(24.50)\\u0026thinsp;=\\u0026thinsp;1.86. The results are shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, indicating that there are no significant differences at the considered confidence level.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4 Short-term and long-term stability\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eA stability study of tryptophan in fish and soybean meals under transportation and storage conditions was performed. A trend analysis was carried out to statistically evaluate the short-term and long-term stability of tryptophan in the fish and soybean meal RMs. The slope was considered statistically insignificant when |\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e|\\u0026lt; \\u003cem\\u003et\\u003c/em\\u003e\\u003csub\\u003e0.95,3\\u003c/sub\\u003e \\u0026middot;\\u003cem\\u003es\\u003c/em\\u003e(\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e). The results are shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e and Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, indicating that the RM was stable for at least six months at 4 ℃ and for nine days at 20 ℃ and 60 ℃. The linear regression plots for studying long-term stability during six months of storage at 4 ℃ are also presented in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e.\\u003c/p\\u003e \\u003c/div\\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\\u003eShort-term stability of tryptophan in fish meal and soybean meal RMs (%)\\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\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eTime (days)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eFish meal\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eSoybean meal\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20 ℃\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e60 ℃\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e20 ℃\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e60 ℃\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.640\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.657\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.508\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.506\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.643\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.640\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.524\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.517\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.645\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.652\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.539\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.503\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.646\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.644\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.527\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.534\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.647\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.635\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.529\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.536\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e\\u003cb\\u003e1\\u003c/b\\u003e\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8.5\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;4\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.0\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.25\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.85\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e\\u003cb\\u003e0\\u003c/b\\u003e\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.640\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.653\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.514\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.506\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003es\\u003c/em\\u003e\\u003csup\\u003e\\u003cb\\u003e2\\u003c/b\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4.9\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;6\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6.0\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;5\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.0\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;4\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5.4\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;4\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003es\\u003c/em\\u003e(\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.42\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.86\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.59\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3.68\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003et\\u003c/em\\u003e\\u003csub\\u003e0.95, 3\\u003c/sub\\u003e \\u0026middot;\\u003cem\\u003es\\u003c/em\\u003e(\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4.52\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e9.10\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.05\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;3\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.17\\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eConclusion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e|\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e|\\u0026lt; \\u003cem\\u003et\\u003c/em\\u003e\\u003csub\\u003e0.95,3\\u003c/sub\\u003e\\u003cem\\u003es\\u003c/em\\u003e(\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e), stable\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e|\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e|\\u0026lt; \\u003cem\\u003et\\u003c/em\\u003e\\u003csub\\u003e0.95,3\\u003c/sub\\u003e\\u003cem\\u003es\\u003c/em\\u003e(\\u003cem\\u003eβ\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e), stable\\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 \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e\\u003cem\\u003e3.5 Characterization study\\u003c/em\\u003e\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eThe characterization of tryptophan in fish and soybean meal RMs was performed in six laboratories. The standard solution, three units of the sample, and an internal standard were supplied by the organizer\\u0026rsquo;s laboratory, and the optimized HPLC method was recommended as the reference method for characterization. First, data were statistically analyzed using the Skewness coefficient and kurtosis coefficient methods and regarded as having a normal distribution. Then, Dixon and Cochran tests were conducted to evaluate the outliers and outlying variances in the measurement results. The results submitted by the six participating laboratories are shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e. The results showed that there were no outliers or outlying variances in the dataset at a confidence level of 95%. Finally, the characterization values of tryptophan in fish and soybean meals were assigned to be 0.65% and 0.54%, respectively.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e\\u003cem\\u003e3.6 Uncertainty\\u003c/em\\u003e\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eThe uncertainty of the reference value (\\u003cem\\u003eU\\u003c/em\\u003e\\u003csub\\u003eRM\\u003c/sub\\u003e) is expressed by the following equation, according to ISO Guide 35:\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Equa\\\" class=\\\"Equation\\\"\\u003e \\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equa\\\" name=\\\"EquationSource\\\"\\u003e\\n$$\\\\:{U}_{\\\\text{R}\\\\text{M},\\\\text{r}\\\\text{e}\\\\text{l}}={u}_{\\\\text{R}\\\\text{M},\\\\:\\\\text{r}\\\\text{e}\\\\text{l}}\\\\times\\\\:k=\\\\sqrt{{{u}_{\\\\text{c}\\\\text{h}\\\\text{a}\\\\text{r},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}+{{u}_{\\\\text{b}\\\\text{b},\\\\text{r}\\\\text{e}\\\\text{l}\\\\:}}^{2}{{u}_{\\\\text{l}\\\\text{t}\\\\text{s},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}+{{u}_{\\\\text{s}\\\\text{t}\\\\text{s},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}}\\\\times\\\\:k$$\\u003c/div\\u003e \\u003c/div\\u003e,\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003ewhere \\u003cem\\u003eU\\u003c/em\\u003e\\u003csub\\u003eRM,rel\\u003c/sub\\u003e is the relative combined uncertainty; \\u003cem\\u003ek\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2 is the coverage factor at a confidence level of 95%; \\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003echar,rel\\u003c/sub\\u003e is the uncertainty in characterizing the reference value, which is divided into two parts: \\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003eA\\u003c/sub\\u003e and \\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003eB\\u003c/sub\\u003e; \\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003ebb,rel\\u003c/sub\\u003e is the uncertainty in homogeneity; \\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003elts,rel\\u003c/sub\\u003e is the uncertainty in long-term stability; and \\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003ests,rel\\u003c/sub\\u003e is the uncertainty in short-term stability.\\u003c/p\\u003e \\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e summarizes the contribution of each factor in the above equation to the overall combined uncertainties for tryptophan in the two RMs. For fish meal, the major contributor to the overall combined uncertainty was the uncertainty in characterization, followed by uncertainties in long- and short-term stabilities, while the contribution from the uncertainty in homogeneity was minor. For soybean meal, the major contributors to the overall combined uncertainty were the uncertainties in long-term stability and characterization, followed by uncertainties in the short-term stability and homogeneity. According to Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, tryptophan in the two RMs had a significant influence on the characterization uncertainty component. The relative expanded uncertainties of the tryptophan in fish meal and soybean meal were 5.32% and 5.78%, respectively.\\u003c/p\\u003e \\u003c/div\\u003e \\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\\u003eContributions of uncertainties in characterization (\\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003echar,rel\\u003c/sub\\u003e), homogeneity (\\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003ebb,rel\\u003c/sub\\u003e), long-term stability (\\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003elts,rel\\u003c/sub\\u003e), and short-term stability (\\u003cem\\u003eu\\u003c/em\\u003e\\u003csub\\u003ests,rel\\u003c/sub\\u003e) to the combined uncertainty of different RMs.\\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\\u003eUncertainty\\u003c/p\\u003e \\u003cp\\u003ecomponent\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSource\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eEvaluation\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFish meal\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eSoybean meal\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{c}\\\\text{h}\\\\text{a}\\\\text{r},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCharacterization process\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{c}\\\\text{h}\\\\text{a}\\\\text{r},\\\\text{r}\\\\text{e}\\\\text{l}}=\\\\sqrt{{{u}_{\\\\text{A},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}+{{u}_{\\\\text{B},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.26\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.92\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{A},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eStandard deviation of multiple laboratory measurements\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{A}=\\\\sqrt{\\\\frac{{\\\\sum\\\\:}_{i=1}^{n}{(\\\\stackrel{-}{{x}_{i}}-\\\\stackrel{̿}{x})}^{2}}{n\\\\times\\\\:(n-1)}},\\\\:\\\\:{u}_{A,\\\\text{r}\\\\text{e}\\\\text{l}}=\\\\frac{{u}_{A}}{\\\\overline{x}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\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\\u003e0.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{B},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePreparation of standard solution, \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{s}\\\\text{t}\\\\text{d},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e; Preparation of internal standard, \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{I}\\\\text{S},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e; Balance weighing of sample, \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{M},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e; Standard curve linearity, \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{l}\\\\text{i}\\\\text{n},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{B},\\\\text{r}\\\\text{e}\\\\text{l}}=\\\\sqrt{{{u}_{\\\\text{s}\\\\text{t}\\\\text{d},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}+{{u}_{\\\\text{I}\\\\text{S},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}{{u}_{\\\\text{M},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}+{{u}_{\\\\text{l}\\\\text{i}\\\\text{n},\\\\text{r}\\\\text{e}\\\\text{l}}}^{2}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{b}\\\\text{b},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHomogeneity test\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{b}\\\\text{b}}=\\\\sqrt{\\\\frac{{HS}_{bb}-{HS}_{wb}}{n}}{u}_{\\\\text{b}\\\\text{b},\\\\text{r}\\\\text{e}\\\\text{l}}=\\\\frac{{u}_{\\\\text{b}\\\\text{b}}}{{\\\\stackrel{-}{x}}_{\\\\text{b}\\\\text{b}}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.49\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.59\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{l}\\\\text{t}\\\\text{s},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eLong-term stability study\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{l}\\\\text{t}\\\\text{s}}=s\\\\left({\\\\text{b}}_{1}\\\\right)\\\\bullet\\\\:t,\\\\:{u}_{\\\\text{l}\\\\text{t}\\\\text{s},\\\\text{r}\\\\text{e}\\\\text{l}}=\\\\frac{{\\\\text{u}}_{\\\\text{l}\\\\text{t}\\\\text{s}}}{{\\\\stackrel{-}{\\\\text{x}}}_{\\\\text{l}\\\\text{t}\\\\text{s}}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.31\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.08\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{s}\\\\text{t}\\\\text{s},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eShort-term stability study\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{\\\\text{s}\\\\text{t}\\\\text{s}}=s\\\\left({\\\\text{b}}_{1}\\\\right)\\\\bullet\\\\:t,\\\\:{u}_{\\\\text{s}\\\\text{t}\\\\text{s},\\\\text{r}\\\\text{e}\\\\text{l}}=\\\\frac{{\\\\text{u}}_{\\\\text{s}\\\\text{t}\\\\text{s}}}{{\\\\stackrel{-}{\\\\text{x}}}_{\\\\text{s}\\\\text{t}\\\\text{s}}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.64\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{\\\\text{U}}_{\\\\text{R}\\\\text{M},\\\\text{r}\\\\text{e}\\\\text{l}\\\\:}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eRelative expanded uncertainty\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{U}_{\\\\text{R}\\\\text{M},\\\\text{r}\\\\text{e}\\\\text{l}}={u}_{\\\\text{c},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\times\\\\:2(coverage\\\\:factor\\\\:k=2.00\\\\:at\\\\:the\\\\:confidence\\\\:level\\\\:of\\\\:95\\\\%)\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.32\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5.78\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eC\\u003c/em\\u003e (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eReference value\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{U}_{\\\\text{R}\\\\text{M}}={U}_{\\\\text{R}\\\\text{M},\\\\text{r}\\\\text{e}\\\\text{l}}\\\\times\\\\:2\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.54\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{U}_{\\\\text{R}\\\\text{M}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e(%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.04\\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. Conclusions\",\"content\":\"\\u003cp\\u003e \\u003cdiv class=\\\"BlockQuote\\\"\\u003e \\u003cp\\u003eTwo new matrix RMs for tryptophan in soybean and fish meals were successfully developed. The preparation of the RM and optimization of the characterization method are described in detail. Stability monitoring, homogeneity test, and characterization using the developed HPLC method, with α-methyltryptophan as the internal standard, were performed, yielding good accuracy and precision. The reference values of tryptophan in soybean and fish meal were assigned to be 0.54\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.04% and 0.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.04%, respectively, at a confidence level of 95% (coverage factor \\u003cem\\u003ek\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2). The RMs demonstrated homogeneity and stability for at least six months at 4 ℃, while short-term stability monitoring showed that they were stable at 20 ℃ for nine days. These RMs have been approved as national RMs with the numbers GBW(E) 100573 and GBW(E) 100574. The novel RMs developed in this study have been used in laboratory comparisons of the Chinese feed quality testing system and found suitable for laboratory quality control and analytical method evaluation.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003ch2\\u003eConflicts of Interest:\\u003c/h2\\u003e \\u003cp\\u003eThe authors declare no conflict of interest.\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eFunding:\\u003c/h2\\u003e \\u003cp\\u003eThis work was supported by the Xinjiang Key Research and Development Program of China [grant number 2023B02015] and the innovation program of Chinese Academy of Agricultural Science.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eAuthor Contributions: Z.J.: Conceptualization, Methodology, Investigation, Validation, Software, Writing. L.L.: Investigation, Data curation. J.Z.: Validation, Investigation. M.Y.: Validation. M.W.: Supervision, Project administration. P.W.: Investigation. S.X.: Investigation. J.T.: Investigation. X.F.: Conceptualization.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgments:\\u003c/h2\\u003e \\u003cp\\u003eWe are grateful to the following laboratories for their support in verifying the tryptophan amounts in the fish and soybean meal reference materials developed in this study: (1) Henan Supervision Institute of Veterinary Drug and Feed, (2)Feed products quality monitoring center of the agriculture and rural affairs ministry of China (Chengdu), (3) Chongqing Veterinary Medicine and Feed Testing Institute, (4) Analysis and Testing Center, Sichuan Academy of Agricultural Science, and (5) Henan Hairuizheng Testing Technology Co., Ltd.\\u003c/p\\u003e\\u003ch2\\u003eData Availability Statement:\\u003c/h2\\u003e \\u003cp\\u003eAll data are presented in the article.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eAOAC of ficial method 988.15, tryptophan in foods and food and feed ingredients (1988)\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAdmasu TG, Halefom TH, Debebe SE (2024) Attachment of ρ-aminobenzene sulphonic acid into magnetic Fe3O4 reduced graphene oxide and its application for sensitive determination of L-tryptophan in milk and banana samples. 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Food Chem 406:135012. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.foodchem.2022.135012\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.foodchem.2022.135012\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"tryptophan, reference material, characterization, homogeneity and stability, measurement uncertainty, fish meal and soybean meal\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9412191/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9412191/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eTryptophan, which is essential for various physiological processes, influences the palatability of animal feed. In this study, two novel reference materials (RMs) for quantifying tryptophan in fish meal and soybean meal were developed. The homogeneity and short-term and long-term stability of these materials were evaluated via high-performance liquid chromatography using α-methyltryptophan as the internal standard. Characterization of RM was conducted in six laboratories. The value and expanded uncertainties (\\u003cem\\u003ek\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;2) of tryptophan in fish meal and soybean meal were (0.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.04) \\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e and (0.54\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.04) \\u0026times;10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;2\\u003c/sup\\u003e, respectively. The overall measurement uncertainty was evaluated by combining contributions from homogeneity, short-term stability, long-term stability, and characterization. Results of homogeneity testing showed that in the candidate materials, tryptophan was homogeneously distributed between and within bottles. Stability monitoring results indicated that the candidate materials were stable for six months under 4 ℃ storage condition and nine days under 20 ℃ transportation conditions. The developed RMs have been successfully applied for quality control and interlaboratory comparisons within the Chinese feed quality testing system.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Development of reference materials for accurate determination of tryptophan in fish meal and soybean meal\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-05-15 10:40:40\",\"doi\":\"10.21203/rs.3.rs-9412191/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-05-06T09:10:43+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2026-04-15T05:13:44+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2026-04-15T05:13:33+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Food Analytical Methods\",\"date\":\"2026-04-14T07:47:22+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"1203e3eb-4045-4b87-b613-3eaab478bcbe\",\"owner\":[],\"postedDate\":\"May 15th, 2026\",\"published\":true,\"recentEditorialEvents\":[{\"type\":\"reviewersInvited\",\"content\":\"7\",\"date\":\"2026-05-06T09:10:43+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-05-15T10:40:40+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-05-15 10:40:40\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9412191\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9412191\",\"identity\":\"rs-9412191\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}