{"title":"用碱性过硫酸钾消化法测定淀粉样品中碳水化合物含量的新方法","authors":"","doi":"10.1016/j.jfca.2024.106645","DOIUrl":null,"url":null,"abstract":"<div><p>In the present work, a novel method for the determination of carbohydrate content in starch samples was developed by using the alkaline potassium persulfate digestion. This method was used to determine the total carbon and nitrogen content of the starch samples. Based on the total nitrogen content, the protein content of the starch samples was computed, and the protein's carbon content was subtracted from the total carbon content to determine the starch samples' carbohydrate content. The test findings validated the capacity of the proposed method in quantifying the carbohydrate content in starch samples as well as its strong intra-day and daylight stability. The results obtained through this method were compared with those obtained through acid hydrolysis by measuring the carbohydrate content in 9 kinds of samples, yielding an intra-group correlation coefficient of 0.986 (P = 0.000, n = 9), and the 95 % confidence interval was 0.938–0.997. Comparison between the enzymatic method and the proposed method showed that the intra-group correlation coefficient was 0.976 (P = 0.000, n = 9), and the 95 % confidence interval was (0.608 ∼ 0.996). The standard addition recovery rate ranged from 95 % to 105 %, using 9.09×10<sup>−2</sup> mg/100 mg and 0.44×10<sup>−2</sup> mg/100 mg as the upper and lower detection limits, respectively.</p></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new method for the determination of carbohydrate content in starch samples by alkaline potassium persulfate digestion\",\"authors\":\"\",\"doi\":\"10.1016/j.jfca.2024.106645\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the present work, a novel method for the determination of carbohydrate content in starch samples was developed by using the alkaline potassium persulfate digestion. This method was used to determine the total carbon and nitrogen content of the starch samples. Based on the total nitrogen content, the protein content of the starch samples was computed, and the protein's carbon content was subtracted from the total carbon content to determine the starch samples' carbohydrate content. The test findings validated the capacity of the proposed method in quantifying the carbohydrate content in starch samples as well as its strong intra-day and daylight stability. The results obtained through this method were compared with those obtained through acid hydrolysis by measuring the carbohydrate content in 9 kinds of samples, yielding an intra-group correlation coefficient of 0.986 (P = 0.000, n = 9), and the 95 % confidence interval was 0.938–0.997. Comparison between the enzymatic method and the proposed method showed that the intra-group correlation coefficient was 0.976 (P = 0.000, n = 9), and the 95 % confidence interval was (0.608 ∼ 0.996). The standard addition recovery rate ranged from 95 % to 105 %, using 9.09×10<sup>−2</sup> mg/100 mg and 0.44×10<sup>−2</sup> mg/100 mg as the upper and lower detection limits, respectively.</p></div>\",\"PeriodicalId\":15867,\"journal\":{\"name\":\"Journal of Food Composition and Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Food Composition and Analysis\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0889157524006793\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Composition and Analysis","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0889157524006793","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
A new method for the determination of carbohydrate content in starch samples by alkaline potassium persulfate digestion
In the present work, a novel method for the determination of carbohydrate content in starch samples was developed by using the alkaline potassium persulfate digestion. This method was used to determine the total carbon and nitrogen content of the starch samples. Based on the total nitrogen content, the protein content of the starch samples was computed, and the protein's carbon content was subtracted from the total carbon content to determine the starch samples' carbohydrate content. The test findings validated the capacity of the proposed method in quantifying the carbohydrate content in starch samples as well as its strong intra-day and daylight stability. The results obtained through this method were compared with those obtained through acid hydrolysis by measuring the carbohydrate content in 9 kinds of samples, yielding an intra-group correlation coefficient of 0.986 (P = 0.000, n = 9), and the 95 % confidence interval was 0.938–0.997. Comparison between the enzymatic method and the proposed method showed that the intra-group correlation coefficient was 0.976 (P = 0.000, n = 9), and the 95 % confidence interval was (0.608 ∼ 0.996). The standard addition recovery rate ranged from 95 % to 105 %, using 9.09×10−2 mg/100 mg and 0.44×10−2 mg/100 mg as the upper and lower detection limits, respectively.
期刊介绍：
The Journal of Food Composition and Analysis publishes manuscripts on scientific aspects of data on the chemical composition of human foods, with particular emphasis on actual data on composition of foods; analytical methods; studies on the manipulation, storage, distribution and use of food composition data; and studies on the statistics, use and distribution of such data and data systems. The Journal''s basis is nutrient composition, with increasing emphasis on bioactive non-nutrient and anti-nutrient components. Papers must provide sufficient description of the food samples, analytical methods, quality control procedures and statistical treatments of the data to permit the end users of the food composition data to evaluate the appropriateness of such data in their projects.
The Journal does not publish papers on: microbiological compounds; sensory quality; aromatics/volatiles in food and wine; essential oils; organoleptic characteristics of food; physical properties; or clinical papers and pharmacology-related papers.
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