Stability and Determination of Metamizole Sodium by Capillary Electrophoresis Analysis Combined
- 格式:pdf
- 大小:212.56 KB
- 文档页数:5
第28卷第11期2016年11月化学研究与应用^Chemical Research and Application Vol.28,No. 11 Nov. ,2016文章编号:1004-1656(2016) 11-1610-04注射液中酚磺乙胺及焦亚硫酸钠含量的同时测定杨凤珍%袁华,范小振,张文育(沧州师范学院化学与化工学院,河北沧州061001)摘要:©磺乙胺及焦亚硫酸钠均在酸性的吐温80-罗丹明6G体系中产生化学发光,但具体发光条件不同,因此利用化学发光分析法,在同一体系中根据不同条件可对针剂注射液中酚磺乙胺及焦亚硫酸钠的含量进行同时测定。
酚磺乙胺的质量浓度在〇.〇5 ~3.(Vg• m T1范围内与光信号呈现良好的线性关系,检出限为0. 01网• m l/1,相对标准偏差小于3.5% 〇 = 5)。
测定焦亚硫酸钠的工作曲线线性范围为0. 07 ~ 5. 0叫•m l/1,检出限为0.02叫•m l/1,相对标准偏差小于4.2%〇= 5)。
该测定方法可用于针剂药物中酚磺乙胺及焦亚硫酸钠的含量测定,结果令人满意。
关键词:化学发光;酸磺乙胺;焦亚硫酸钠;吐温80;罗丹明6G中图分类号=0657. 3 文献标志码:ASimultaneous determination of etamsylate and sodium pyrosulfite in injectionY A N G Feng-z h e n*,Y U A N H u a,F A N X ia o-z h e n,Z H A N G W e n-yu(College of Chemistry and Chemical engineering,Cangzhou Normal University,Cangzhou 061001,China) Abstract:The chemiluminescence emission was generated by mixing etamsylate or sodium pyrosulfite with acidic tween80-rhoda- mine6G. The specific luminescent conditions were different, so the content of etamsylate and sodium pyrosulfite could be determined in the same chemiluminescence system according to the different conditions. The quantitation range was from 0. 05 to 3. Ojjig • mL 1with a detection limit of 0. 01 jjig • mL 1 ,and a relative standard deviation of less than 3. 5% (n = 5)for etamsylate. The working curve liner range was 0. 07 to 5. Ojjig *mL4with a detection limit of 0. 02 |jig *mL 1 , and arelative standard deviation of less than 4. 2% (n = 5)for the determination of sodium pyrosulfite. The proposed method was applied to the quantitation of etamsylate and sodium pyrosulfite in injection with satisfactory results.Key words :chemiluminescence ;etamsylate ; sodium pyrosulfite ;tween80;rhodamine 6G酚磺乙胺又名止血敏。
《Meta分析系列之十五_Meta分析的进展与思考》篇一Meta分析系列之十五_Meta分析的进展与思考Meta分析系列之十五:Meta分析的进展与思考一、引言随着科学研究的深入发展,Meta分析作为一种重要的统计方法,被广泛应用于多个学科领域,成为了研究热点之一。
本文旨在探讨Meta分析的进展及其在科学研究中的应用与思考。
二、Meta分析的概述Meta分析是一种利用统计方法对多个独立研究结果进行综合分析的技术,其目的是为了解决单个研究结果可能存在的局限性,提高研究结果的可靠性和稳定性。
Meta分析通过整合多个独立研究的数据,从而揭示出更具有普遍性的结论。
三、Meta分析的进展自Meta分析技术问世以来,其在多个领域的应用已经取得了显著的进展。
以下是近年来Meta分析的主要进展:1. 拓展应用领域:Meta分析不再局限于医学、心理学等传统领域,而是逐渐扩展到生物学、社会科学等多个领域。
这些领域的学者们开始运用Meta分析技术来探讨各种问题,如基因多态性与疾病的关系、社会现象的成因等。
2. 改进方法与技术:随着计算机技术的发展,Meta分析的方法与技术也在不断改进。
例如,利用大数据技术,Meta分析可以更准确地提取和分析大量数据,从而提高了结果的准确性。
此外,随机效应模型、贝叶斯统计等方法的应用,使得Meta分析更加适用于异质性较高的研究数据。
3. 优化检索策略:Meta分析中一个重要的步骤是确定检索策略和选择合适的研究文献。
随着数据库技术的不断发展,研究人员可以更加便捷地检索和筛选相关文献,提高了Meta分析的效率和准确性。
四、Meta分析在科学研究中的应用与思考1. 科学决策的依据:Meta分析可以为政策制定和科学决策提供依据。
通过对大量相关研究的综合分析,可以揭示出某一现象或问题的普遍规律,为政策制定提供科学依据。
例如,在公共卫生领域,通过Meta分析可以评估不同干预措施的效果,为政策制定者提供决策依据。
《Meta分析系列之十五_Meta分析的进展与思考》篇一Meta分析系列之十五_Meta分析的进展与思考Meta分析系列之十五:Meta分析的进展与思考一、引言随着科学研究的深入发展,Meta分析作为一种重要的统计方法,逐渐在各个领域中发挥着越来越重要的作用。
本文旨在探讨Meta分析的进展,以及在当代科学研究中的思考与应用。
二、Meta分析的概述Meta分析,即元分析,是一种利用统计方法对多个独立研究结果进行综合分析的方法。
它通过对不同研究结果进行量化评估和合并,从而得出更可靠、更全面的结论。
Meta分析在许多领域都有广泛的应用,如医学、心理学、社会科学等。
三、Meta分析的进展(一)方法论的完善随着Meta分析的不断发展,其方法论得到了进一步的完善。
在研究设计、数据采集、统计分析等方面,都出现了更多的方法和工具。
例如,通过系统评价和文献计量学的方法,可以更全面地收集和筛选相关研究;通过随机效应模型等统计方法,可以更准确地评估不同研究结果之间的异质性。
(二)应用领域的拓展Meta分析的应用领域不断扩大,不仅在医学、心理学、社会科学等领域得到广泛应用,还在生物学、计算机科学等领域得到尝试。
这表明Meta分析具有广泛的应用前景和潜力。
(三)与其他方法的结合Meta分析可以与其他统计方法相结合,如系统评价、网络元分析等,从而更好地解决实际问题。
此外,随着大数据和人工智能技术的发展,Meta分析与这些技术的结合也将为科学研究带来更多的可能性。
四、对Meta分析的思考(一)研究质量的保证在进行Meta分析时,需要保证所纳入的研究质量可靠。
这需要对研究的设计、数据采集、统计分析等方面进行全面评估。
同时,还需要注意研究间的异质性,避免因异质性过大而影响结果的可靠性。
(二)结果解读的准确性在进行Meta分析时,需要准确解读结果。
这需要对统计方法和结果进行深入理解,避免误解或误用。
同时,还需要注意结果的适用范围和局限性,避免过度解读或滥用结果。
[生物工程]Nature medicine近期精彩文章摘要2004年10月大麻素可能与异位妊娠有关发表在10月号《自然—医学》上的一篇研究报告首次揭示了大麻素与异位妊娠的关系。
这篇研究报告表明,胚胎在输卵管内的运送过程中,大麻素类受体起了重要作用。
异位妊娠是指受精卵在子宫内膜以外的部位植入和发育生长,胚胎持续停留在输卵管就会形成输卵管妊娠。
Sudhansu Dey及合作者通过老鼠实验发现,如果由于遗传或药物作用使得大麻素受体CB1不起作用,则大量胚胎会滞留在输卵管内,最终导致受孕失败。
因为乙型交感神经刺激剂能够部分抵消这种效应,研究人员提出,在胚胎正常进入子宫的“旅途”中,大麻素和肾上腺素受体共同调节着输卵管的运动。
除了揭示出生殖管道中胚胎运送的新的调节机制而外,这一成果对于异位妊娠的临床研究也颇具价值。
2004年10月新生儿肺性高血压新疗法在发生氰化物中毒时,常常采用吸入亚硝酸盐来消除毒性。
10月号《自然—医学》发表的一篇“快报”表明,吸入亚硝酸盐还可用于治疗新生儿肺性高血压。
这是一种具有致命危险的疾病,会引起肺部血管收缩,导致机体血氧水平低下。
Gordon Power等利用患此病的新生羊羔测试吸入亚硝酸盐的疗效,结果发现这种疗法能使血压持续保持较低水平,并且没有明显副作用。
2004年10月精密观察血管10月号《自然—医学》发表了一篇技术报告,介绍了一种能比以往更清晰地观察活体组织及其相连血管的新方法,这一新方法可望为诊断治疗研究“锻造”一柄利器。
Fabian Kiessling及合作者试验了一种新型的“测定体积计算断层摄影扫描仪”,能够实现高分辨率三维成像。
利用此项技术,研究人员对移植到老鼠体内的人类肿瘤结构进行了分析,比现有技术如磁共振和血管造影等更清楚地观察到了肿瘤的状况。
他们甚至成功地观察到了肿瘤中直径50微米的小血管,同时还能清楚地区分活组织与死组织。
2004年9月肿瘤追踪9月号《自然医学》上发表的一篇研究报告介绍了一项在活体内追踪肿瘤细胞的新技术。
收稿日期:2016-03-25修回日期:2016-04-10基金项目:军队预研基金资助项目(51333030103)作者简介:袁园(1990-),女,河南洛阳人,助理工程师。
研究方向:通信对抗。
*摘要:利用LFM 信号频谱的熵随着调频率减小而降低的性质,提出了一种基于频谱熵最小化的LFM 信号调频率的估计SEM 方法。
建立参数待估的相位补偿因子,通过搜索得到使得补偿后信号频谱熵全局最小的调频率估值。
在搜索过程中,采用两级搜索策略,并引入牛顿迭代算法,有效降低了算法复杂度。
理论推导和仿真结果证明,该算法为有偏算法,估计偏差量与初始频率相关,理论估计方差比较CR 下界低12dB 。
对雷达实测回波信号进行验证,与离散多项式变换算法相比发现,提出算法估计的鲁棒性更好,并具有较高的测速精度,具有一定的应用价值。
关键词:LFM 信号,最小熵,有偏估计,Cramer-Rao 下界中图分类号:TN911.7文献标识码:A基于熵最小化的LFM 信号调频率估计算法*袁园,蔡啸,郭蓓蓓(中国洛阳电子装备试验中心,河南洛阳471003)Estimation Method of LFM Signal Chirp RateBased on Entropy MinimizationYUAN Yuan ,CAI Xiao ,GUO Bei-bei(Luoyang Electronic Equipment Testing Center ,Luoyang 471003,China )Abstract :Based on the fact that the spectrum entropy decreases with the chirp rate being smaller ,this paper proposes a spectrum entropy minimization (SEM )based chirp rate estimation method.A phase filter is established and the chirp rate estimation is accomplished via minimization of the spectrum entropy.In this process ,a two-step search strategy is utilized.In step one ,a large searching step is chosen to achieve the coarse estimation of the parameter and then Newton iterative search algorithm is used in step two to estimation the chirp rate accurately.Theoretical derivation shows that the proposed algorithm is biased ,which is related to the fractional part of the initial frequency and the variance is about 12dB lower than Cramer-Rao lower bound.Simulation result proves the correctness of the derivation and the comparison with classic discrete polynomial phase transform is made.Key words :LFM signal ,minimum entropy ,biased estimation ,cramer-rao lower bound 0引言线性调频(Linear Frequency Modulation ,LFM )信号以其良好的时域压缩特性和大的发射能量等诸多优点,在雷达、声呐、生物医学及通信工程等领域得到了广泛应用。
3 JUNE 2011 VOL 332 SCIENCE 1160PERSPECTIVESPropagating bacteria in a lab f or thousands of genera-tions may seem tedious, oreven irrelevant, to most evolution-ary biologists. Nonetheless, such experiments provide an opportunity to deduce quantitative principles ofevolution and directly test them in controlled environments. Combined with modern sequencing technolo-gies, as well as theory, recent micro-bial experiments have suggested a critical role for genetic interactions among mutations, called epistasis, in determining the pace of evolution. T wo papers in this issue, by Khan et al . on page 1193 ( 1) and Chou et al . ( 2) on page 1190, present precise experimental measurements of these epistatic interactions.Microbial evolution experiments in a simple, constant environmentreveal a characteristic pattern: At fi rst, a population rapidly acquires benef icial mutations, but then adaptation progressively slows sothat thousands of generations pass between subsequent benefi cial substitutions ( 3). Unexpected outcomes, however, can and do occur even in these simple experimental conditions. Populations evolve a dramatically elevated mutation rate ( 4), discover rare phe-notypic innovations ( 5), or diverge into dis-tinct lineages that either coexist ( 6) or com-pete vigorously as each strain races to acquire more adaptive mutations ( 7). Recent theory suggests that a common cause underlies all these phenomena: the structure of epistatic interactions among mutations.Epistasis describes how the fi tness conse-quence of a mutation depends on the status of the rest of the genome. In one extreme exam-ple, called sign epistasis, a mutation may be benefi cial if it arises on one genetic back-ground, but detrimental on another. Although interactions among genes may seem an obvi-ous fact of biology, the myriad possible forms of epistasis have made it diffi cult to formu-late predictive evolutionary models or to infer such interactions from empirical data. Nev-ertheless, epistasis is at the heart of classi-cal theories, such as the evolution of sex ( 8), and also of modern concepts such as robust-ness and evolvability (a population’s ability to evolve) ( 9). Moreover, recent theoretical work ( 10) suggests that the overall dynami-cal pattern of adaptation observed in long-term microbial experiments can be explained by a prevalence of what is called antagonistic epistasis, in which benefi cial mutations con-fer less benefi t in combination than they do individually.To quantify epistasis among benef icial mutations and to test these theoretical predic-tions, both Khan et al . and Chou et al . exam-ined the initial substitutions that occurred in populations of bacteria adapting in the labo-ratory. The researchers identifi ed the hand-ful of mutations across the genome that had substituted in an evolved strain, and then con-structed intermediate strains containing com-binations of these mutations. By measuringthe fi tness benefi ts conferred by these muta-tions, individually and in combination, the researchers were able to directly quantify the extent and form of epistasis (see the fi gure).Both studies found a predominance of antagonistic epistasis, which impeded the rate of ongoing adaptation relative to a null model of independent mutational eff ects. Chou et al . further interpreted the prevalence of antagonistic epistasis in terms of meta-bolic costs and benefi ts. The concordance of results from the two studies is noteworthy, especially because Khan et al . analyzed Esch-erichia coli populations [from the long-term experiments of Lenski ( 3)], whereas Chou et al . studied an engineered strain of Methylo-bacterium extorquens . The remarkable preci-sion with which both studies quantifi ed epis-tasis among benefi cial mutations was made possible only by leveraging whole-genome sequencing combined with the ability to reconstruct mutational combinations andassay them in the same environment in whichthe mutations fi rst arose.The view of epistasis across a genome that emerges from this work contrasts sharply In Evolution, the Sum Is Less than Its PartsEVOLUTIONSergey Kryaz himskiy ,1,2 Jeremy A. Draghi ,1 Joshua B. Plotkin 1Laboratory experiments with bacteria shedlight on how epistatic interactions infl uence the pace of evolution.Ancestor strain Adapted strain Reconstruct intermediates Evolves in labDiminishing returns Fitness W abFitness W b Fitness W a 1st mutation 2nd mutation 3rdmutation F i t n e s sAntagonistic epistasis W ab < W a • W b Antagonistic epistasis. Bacteria adapt to a laboratory environment by acquiring benefi cial mutations. Khan et al . and Chou et al . identifi ed the mutations that accrued in an adapted strain, and measured their fi tness benefi ts (growth advantage relative to the ancestor). The mutations conferred smaller marginal benefi ts in combination than they didindividually. This antagonistic epistasis causes progressively slower rates of adaptation over time.C R E D I T : A D A P T E D B Y P . H U E Y /S C I E N C E1Department of Biology, University of Pennsylvania, Phila-delphia, PA 19103, USA. 2Department of Organismic andEvolutionary Biology, Harvard University, Cambridge, MA 02138,USA.E-mail:******************.eduPublished by AAASo n J u n e 2, 2011w w w .s c i e n c e m a g .o r g D o w n l o a d e d f r o mPERSPECTIVESwith the type of epistasis found among adap-tive mutations within a single protein ( 11). Notably, Weinreich et al. studied mutations in an antibiotic resistance gene, β-lactamase, and found a prevalence of sign epistasis, which limits the number of genetic paths that evolution can follow ( 11). In contrast, the epistasis documented by Khan et al. and Chou et al. exerts less constraint on the order of substitutions that increase fi tness, so that the specifi c path that evolution will take is less predictable. At the same time, the pre va-lence of antagonistic epistasis measured by the two groups ensures a predictable tempo of adaptation characterized by diminishing marginal returns ( 10).Although these new experiments suggest a consistent principle of how epistasis shapes the pattern of adaptation, many questions must be answered before their results can be extended to evolution outside the labora-tory. It remains unclear, for instance, whether these results would be altered by changing fundamental evolutionary parameters, such as population size, rate of mutation, and rate of re combination. Likewise, it is uncle ar whether experiments in simple environments,with only one or a few niches for coexistingstrains, will refl ect the pattern of adaptation inmore complex ecologies, such as Pseudomo-nas fl uorescens in structured environments( 6). Nonetheless, the compelling consistencybe twe e n the se two studie s should inspireefforts to test the generality of their fi ndings,by measuring epistasis in a wide range ofexperimental and even natural systems.These studies, and the long-term labora-tory evolution experiments from which theyderive, represent a resounding achievementfor the reductionist approach to studyingbiology. The mechanistic picture they paintof evolution is complex but not incompre-hensible; although epistatic interactions leadto surprising phenomena, the advantagesof a frozen “fossil record” of laboratory-raised isolates, and the ease of manipulat-ing—and, now, fully sequencing—evolvedstrains enables researchers to tease apart andexamine the underlying causes of these phe-nomena. Moreover, the theory and conceptsdeveloped to explain these simple experi-me nts may have broad payoffs. Alre ady,epistasis has been implicated in the evolu-tion of drug resistance in infl uenza viruses( 12) and in bacterial pathogens ( 13). Ulti-mately, populations of bacteria tediouslypropagated in the lab may be key to predict-ing the next moves of the most mutable anddangerous human pathogens.References1. A. I. Khan, D. M. Dinh, D. Schneider, R. E. Lenski, T. F.Cooper, Science332, 1193 (2011).2. H.-H. Chou, H.-C. Chiu, N. F. Delaney, D. Segrè, C. J.Marx, Science332, 1190 (2011).3. S. F. Elena, R. E. Lenski, Nat. Rev. Genet.4, 457 (2003).4. P. D. Sniegowski, P. J. Gerrish, R. E. Lenski, Nature387,703 (1997).5. Z. D. Blount, C. Z. Borland, R. E. Lenski, Proc. Natl. Acad.Sci. U.S.A.105, 7899 (2008).6. P. B. Rainey, M. Travisano, Nature394, 69 (1998).7. R. J. Woods et al., Science331, 1433 (2011).8. A. S. Kondrashov, Nature336, 435 (1988).9. G. P. Wagner, L. Altenberg, Evolution50, 967 (1996).10. S. Kryazhimskiy, G. Tkačik, J. B. Plotkin, Proc. Natl. Acad.Sci. U.S.A.106, 18638 (2009).11. D. M. Weinreich, N. F. Delaney, M. A. Depristo, D. L.Hartl, Science312, 111 (2006).12. J. D. Bloom, L. I. Gong, D. Baltimore, Science328, 1272(2010).13. S. Trindade et al., PLoS Genet.5, e1000578 (2009).10.1126/science.1208072Behavior and the Dynamic Genome GENOMICSAlison M. Bell 1,3 and Gene E. Robinson 2,3Does behavior evolve through gene expression changes in the brain in response to the environment?W he n circumstance s change, an organism’s fi rst response is oftenbehavioral. But how does adap-tive behavior evolve, given that it requires constant and often instantaneous interac-tions between an individual and its environ-ment? The dominant view emphasizes new random DNA mutation as the starting point. This may lead to behavioral variation. If the resulting variants have different fi tness values, then natural selection could result in behavioral evolution through changes in allele frequencies across generations. An alternative theory proposes environmentally induced change in an organism’s behavior as the starting point ( 1), and “phenotypic plas-ticity” that is inherited across generations through an unspecifi ed process of “genetic assimilation” ( 2). Despite numerous exam-ples ( 3), the latter as a driver of behavioralevolution has never been widely accepted,perhaps as a reaction against Lamarckian-ism—the idea that characteristics acquiredby habit, use, or disuse can be passed onacross ge ne rations. Howe ve r, be havioralgenetics and genomics, especially for ani-mals in natural populations, lend some plau-sibility to the phenotypic plasticity view.The ability to analyze genome-wide geneexpression through “transcriptomics” hasshown that the genome responds dynami-cally to stimuli ( 4). One illustrative exam-ple is the honey bee. The African honey bee(Apis mellifera scutellata) responds muchmore fi ercely when its hive is attacked thando other subspecies of honey bee. Evolu-tionary changes in brain gene expressionmay have resulted in an increase in respon-siveness to alarm pheromone (the chemicalbees use to alert each other to danger) forAfrican honey bees ( 5). About 10% of thesame genes regulated in the brain by alarmpheromone are also differentially expressedbe twe e n African and the le ss aggre ssiveEuropean honey bees. These genes, actingover both physiological and evolutionarytime scales, provide a possible mechanismfor how behavioral plasticity might driverapid behavioral evolution through changesin gene regulation. In an environment withmore predators, colonies producing morebees with lower thresholds for respondingto alarm pheromone would have fared bet-ter, which would then result in a popula-tion with patterns of gene expression whoseoutput was an “aroused” behavior, even inthe absence of alarm pheromone. Althoughthis view does not rule out the possibilitythat these differences in aggression arosethrough new mutation, the transcriptomicsagrees with the idea of “genetic accommo-dation” ( 3), the modern, more inclusive ver-sion of genetic assimilation, which couldinvolve e ithe r e volutionary incre ase s ordecreases in plasticity. In certain environ-ments, plastic genotypes might be favored,but in other environments, nonplastic gen-otypes might be preferred instead. Futurestudies will determine whether differencesin honey bee aggression can be explainedby selection on regulatory regions of the1Department of Animal Biology, University of Illinois,Urbana-Champaign, IL 61801, USA. 2Department of Ento-mology, University of Illinois, Urbana-Champaign, IL 61801,USA. 3Neuroscience Program, Program in Ecology, Evolution-ary Biology and Conservation, Institute for Genomic Biology,University of Illinois, Urbana-Champaign, IL 61801, USA.E-mail:******************.eduPublished by AAAS o n J u n e 2 , 2 0 1 1 w w w . s c i e n c e m a g . o r g D o w n l o a d e d f r o m SCIENCE VOL 332 3 JUNE 20111161。
第2章生活史进化张大勇生活史进化对策的研究起始于本世纪40年代末~50年代初,主要是由动物种群统计学(demography)和进化理论相结合而形成的。
在1920~1950年这一时期,生态学家已经开始广泛地运用寿命表方法研究动物种群,因而对于生活史的定量种群统计学后果已经具备了一个有效的分析方法。
这种方法考察的是特定年龄个体的死亡率和生育率。
生态学家已清楚地知道,这些生活史参数无论是在种内还是在种间都有很大的变异。
种群遗传学和数量遗传学的迅猛发展同时也为达尔文关于表型性状适应价值的论述提供了坚实基础。
在第1章内,我们已经提到,早期的种群生态学并不关注种群内部的遗传变异,而种群遗传学也基本上忽略了种群动态过程。
二者之间的有机结合是生态学领域内长期没有得到很好解决的一个难题;而这对于生活史对策研究却是至关重要的。
尽管Fisher(1930)早在30年代就已经提出应把种群统计学性状看作为表型的一部分并探索它们的适应性基础,但人们公认现代生活史进化理论创立于40年代末到50年代初Lack(1947)关于鸟类窝卵数、Medawar(1946,1952)关于衰老、以及Cole(1954)关于单次生殖/多次生殖进化的研究。
其后,生活史进化方面的研究蓬勃兴起,有关文献可说是浩如烟海。
但在本章内我们并不打算对整个领域进行全面地综述,而是选择几个有代表性的核心问题介绍其理论背景和发展趋势。
如果读者想要更全面地了解该领域,可以参阅Roff(1992)以及Stearns (1992)的专著。
侧重于基础理论方面的书籍有Charlesworth(1994)。
在进入本章具体内容之前,我们有必要首先熟悉一下生活史进化研究的基本途径—表型优化理论(参见第3章)。
2.1 进化生物学中的表型优化研究途径近些年,进化生物学家和生态学家已经开始广泛采用工程学和经济学领域内的数学方法来认识生命的多样性问题(Maynard Smith 1978)。
1 IntroductionVitamin C occurs in different concentrations in a vari-ety of natural samples. It is added to several pharma-ceutical products as an essential ingredient, a stabilizer for vitamin B complex, and as an antioxidant.Consequent upon its desirable effects, it is widely used in the treatment of certain diseases such as scurvy,common cold, anemia, haemorrhagic disorders, wound healing, and even infertility, to mention some stark cases. It is considered essential for the development and regeneration of muscles, bones, teeth and skin.The increasing use of pharmaceuticals and other natural samples containing vitamin C has meant that the practi-cising chemists should develop analytical procedures for its determination which are simple to operate, rapid,accurate, sensitive and selective. The desire to develop methods with ideal characteristics has resulted a large number of procedures with varying applicability. Many instrument-based analyses including fluorometry 1–4,HPLC 5–10, polarography 11–13and enzymatic 14,15methods are reported in the literature. But due to their inherent limitations, these techniques are not commonly used for routine analyses. However, photometric methods are particularly attractive because of their speed and sim-plicity. Consequently, a large number of such proce-dures have been developed for the determination of ascorbic acid (AA). Though some short reviews 16–18have been reported, a critical assessment of these meth-ods is desirable to examine their salient features and utility. This review is an attempt to assess exclusively the existing spectrophotometric methods for the deter-mination of vitamin C as regards their simplicity, rapid-ity, Beer’s law range, sensitivity, selectivity and applic-ability. It is primarily based on the information collect-ed through the Chemical Abstracts for the period 1970to mid-1997.2 Results and DiscussionSeveral dyes such as 2,6-dichlorophenolindophenol (DCIP), dimethoxydiquinone (DMDQ), ninhydrin, fast red AL salt and 2′,7′-dichlorofluorescein etc . have been used for the determination of vitamin C. Among these dyes, DCIP has been most extensively studied. It is included in the official titrimetric methods as reported in different pharmacopoeias 19–21and it also forms the basis of many colorimetric methods. The blue dye DCIP is reduced to the colorless form on addition of ascorbic acid as shown in Fig.1, but it gives a pink color to the acidic solutions. Using the dye, ascorbic acid present in human urine 22and processed potatoes 23has been determined. The excess dye can be extracted with xylene or butanol.24Many substances which are capable of reducing the dye resulting from the prepara-tion and processing of food samples interfere. Flow dialysis proposed by Gary et al .25and continuous flow systems have been used to monitor the decrease in absorbance of DCIP. Such automated systems appear to be justified only when routine analysis of a largeANALYTICAL SCIENCES OCTOBER 1998, VOL. 14Photometric Methods for the Determination of Vitamin CSatya P. A RYA †, Meenakshi M AHAJAN and Preeti J AINDepartment of Chemistry, Kurukshetra University, Kurukshetra –136119, Haryana State, IndiaThe importance of vitamin C to the human body is widely acknowledged throughout the globe. The deficiency of this vitamin leads to various diseases. In view of its importance, numerous methods including spectrophotometric ones have been developed for its determination in pharmaceuticals, foods and biological samples. A comprehensive review of the available spectophotometric methods for the determination of ascorbic acid is presented.Keywords Vitamin C determination, spectrophotometric method†To whom correspondence should be addressed.Fig.1The reduction of DCIP with ascorbic acid.Ascorbic acidDCIP(Oxidized, Blue-Pink)Dehydroascorbic acid DCIP (Reduced, Colorless)number of samples is needed; otherwise it is tedious to use for a single estimation.Dimethoxydiquinone 26gives a violet-colored product with ascorbic acid in a phosphate buffer (pH 6.6). The reduced “indigoid” quinhydrone form is perhaps responsible for the formation of violet-colored product as shown in Fig. 2. After diluting with dioxane,absorbance of the colored solution which is stable over 24 h only under dark conditions is measured at 510 nm.Heating leads to a decrease in color intensity. Beer’s law holds good up to 80 µg ml –1with a detection limit of 10 µg ml –1. Riboflavin and copper interfere. The interference of iron(II) sulfate responsible for precipita-tion can be removed by centrifugation. Though the method is not sufficiently sensitive (ε=1.62×103), it can still be applied to the analysis of citrus fruits 27after extracting the colored product into chloroform (λmax =530 nm). Lin et al .28and Pandey 29reported pro-cedures based on the reaction of ascorbic acid with fast Red AL salt (1)(zinc chloride salt of diazotized 1-aminoanthraquinone) and tetrachlorobenzoquinone (2).The reaction of (1)proceeds in acid medium but the blue color develops only after the addition of alkali,which exhibits three absorption bands between 500–630 nm. If one uses the latter reagent (2), ascorbic acid is determined at 336 nm (ε=535 cm 2mol –1) via a decrease in absorbance of 7×10–4M tetrachlorobenzo-quinone (chloranil) in 80% acetone –water (v/v) medi-um. With these methods, mixtures of ascorbic acid with thiols like o -mercaptobenzoic acid, mercaptosuc-cinic acid, 3-mercaptopropionic acid can not be resolved.Methylene Blue 30, (3)and ninhydrin 31,32(4)find applications with the determination of ascorbic acid in food products. The colorless form of the dye (3)is extracted into chloroform after its reduction with ascor-bic acid; back oxidation of the dihydro derivative to Methylene Blue has been used for the assay of ascorbic acid (λmax =653 nm). The method is reported to be highly sensitive. The reaction of ascorbic acid with ninhydrin carried out on a boiling water bath using 80% aqueous solution as a medium in 0.01 M NH 4OH is used for its determination in pharmaceuticals (λmax =415 nm), but without added advantages.In the sixties, many methods based on the coupling of ascorbic acid with aniline diazonium salts were report-ed. A purplish or blue colored species is produced by these salts with ascorbic acid in alkaline medium.Diazotized-4-methoxy-2-nitroaniline couples withascorbic acid in oxalic acid medium in the presence of ethanol or isopropanol, giving a purplish color in alka-line solutions. Though Fe(II), Sn(II) and dehydroascor-bic acid (DHAA) do not interfere, the presence of reductones and reductic acid requires formaldehyde condensation. Low contents of vitamin C in the pres-ence of flavanoids and pectic substances are also detected. The reaction of ascorbic acid with 4-nitrobenzene diazonium fluoroborate in acetic acid medium was used for its determination at λmax 415 nm.But the mixture has to be kept for 25 min in the dark,followed by the addition of sodium hydroxide. The sensitivity of a large number of stabilized diazonium salts was evaluated; diazotized 4-nitroaniline-2:5-dimethoxy-aniline was found to give the most intense color reaction.Enzymic 33–35colorimetric determinations of ascorbic acid in commercial vitamin C tablets and in fruits and vegetables were made by measuring the absorbance at 358 nm or 320 nm of the resulting products obtained by oxidation of o -phenylenediamine/1,4-diaminobenzene using ascorbate oxidase or peroxidase in presence of H 2O 2at pH 5.3. Ascorbic acid is determined after oxi-dation with mercuric chloride and condensing the DHAA with 4,5-disubstituted phenylenediamine 36,which gives the quinoxaline derivative used for absorbance measurement. The method involving 4-nitro-1,2-phenylenediamine 37(λmax =375 nm) is very complex and laborious, since it involves many time-consuming steps including purification of the sample with anionic Sephadex column.In the recent past, the determination of oxidized and reduced vitamin C in pharmaceuticals, foods and bio-logical samples has gained importance since AA and DHAA redox couple is an important component of many biological systems. Simultaneous measurement of both AA and DHAA using HPLC has been carried out by various workers 38–45in different laboratories.Rose and Nahrwold 38determined AA and DHAA by monitoring UV absorbance at 254 nm and 210 nm respectively for the analysis of foods, biological sam-ples and pharmaceutical preparations. Graham and Donald 39have carried out the analysis at 254 nm after extracting the food samples with 62.5 mM metaphos-phoric acid using an ion exchange column (Aminex-HPX 87H). Both these forms have also been deter-mined in vegetable samples 40using a UV detector (254nm). Yasui and Hayashi 41made such determinations by converting to compounds having λmax at 300 nm under alkaline conditions. Derivatization of DHAA is accel-erated in the presence of sodium borohydride.Validation of the micromethod for the determination of the oxidized and reduced vitamin C in plasma by HPLC fluorescence method has been reported by Tessier et al .45These methods are useful and a single step HPLC assay of such detections has been helpful in overcoming the burden of derivatization.Ascorbic acid gives colored species with substituted benzene such as m -dinitrobenzene 46in formaldehydeFig.2Reduction reaction of dimethoxydiquinone (DMDQ).‘Indigoid’quinhydroneDMDQand trinitrobenzene47in tartrate buffer when studied for its determination over the concentration ranges 2–50 and 0–125 µg ml–1of ascorbic acid respectively. Methanolic solution of resorcinol48gives a pale yellow color (λmax=425 nm) with ascorbic acid in hydrochloric acid medium, obeying Beer’s law for 80–400 µg ml–1. 4-Chloro-7-nitrobenzofurazane49forms a bluish green colored species with ascorbic acid in presence of 0.2 M sodium hydroxide. The absorbance is measured at 582 nm after diluting the reaction contents with 50% (v/v) aqueous acetone solution. Beer’s law is obeyed in the concentration range 5–20 µg ml–1. The colored prod-uct is stable for 30 min only when kept away from direct sunlight or artificial day light. The method is reported free from the interference of all other vitamins and minerals present in multivitamin preparations and can be applied to the analysis of pharmaceuticals, fresh fruit juices and vegetables.Hashmi et al.50proposed a method based on the reac-tion of 2,3,5-triphenyltetrazolium chloride with ascor-bic acid in alkaline medium. The pink solution is allowed to stand in the dark for 30 min at 25˚C; it obeys Beer’s law over the range 5–25 µg ml–1. Sugars (>15 µg ml–1) except sucrose interfere by forming a similar color to that of the reagent. Riboflavin, cyanocobalamin and folic acid interfere due to their own color. Beutler et al.51,52investigated the use of methylthiazolyltetrazolium salt in presence of ascorbate oxidase enzyme and 3-(4,5-dimethylthiazolyl-2-yl)-2,5-diphenyltetrazolium chloride or bromide in the pres-ence of 5-methylphenazinium methyl sulfate (electron carrier) at pH 3.5 for the determination of ascorbic acid in foods, fruit juices and vegetables juices. These reac-tions involve the formation of formazon (λmax=578 nm). The interference of sulfur dioxide requires treat-ment with formaldehyde, and color interference from dark juices is removed by decolorization with 1% polyvinylpolypyrrolidone before filtration. Sorbitol, alcohol and oxalate interfere with the ascorbic acid oxi-dase. However, the effect of oxalate can be checked by adding a slight excess of Ca(II) ions. Other derivatives such as 2,5-diphenyl-3-thiazolyl tetrazolium chloride53 at pH 12.2, 2-(p-iodophenyl)-3-(p-nitrophenyl)-5-phenyltetrazolium chloride at pH 10.5 (λmax=540 nm) and 2,2′,5,5′-tetra-(4-nitrophenyl)-3,3′-(3,3′-dimethoxy-4,4′-biphenyl)ditetrazolium chloride54have also been employed for the assay of ascorbic acid.The coupling of 2,4-dinitrophenylhydrazine (DNPH) with ketonic groups of DHAA and diketogulonic acid (DKGA) has been the basis of many methods for the determination of total vitamin C contents. Proteins present in the samples are precipitated by adding trichloroacetic acid (TCA) and aliquots of filtrate are shaken with acid–washed charcoal (norit) or activated charcoal55to clarify the solutions and to oxidize AA to DHAA. A reducing medium is produced by adding thiourea prior to DNPH addition, otherwise unspecific coloration is given by oxidants. The osazones (λmax=545 nm) thus formed during the 3 h incubation at 37˚C by the reaction of DNPH and DHAA are dis-solved by adding 85% H2SO4. Vitamin C can be extracted with metaphosphoric acid–stannous chloride solution without charcoal treatment for differential determination of DKGA, DHAA and AA in the same tissue extracts. The interference of sugars can be mini-mized by carrying out incubation at 15˚C and measur-ing the absorbance only after adding sulfuric acid for 75 min.56The use of several acid mixtures has been proposed for replacing the tedious dropwise addition of sulfuric acid. Lack of specificity is found with many of these methods; interfering osazones can be separated by chromatographic methods such as TLC57and HPLC58, but at the cost of making these procedures tedious and cumbersome. The nature of DNPH meth-ods for total vitamin C also makes it amenable to auto-matic flow through analyses.59–61 Phenylhydrazinium chloride62produces a yellow color (λmax=395 nm) when treated with ascorbic acid in0.1 M HCl medium. The reaction contents are kept for1 h in an incubator or water bath at 50±2˚C, thus mak-ing the method time-consuming. Beer’s law is obeyed in the range 25–100 µg of ascorbic acid. No interfer-ence is observed from other vitamins, minerals, glucose, sucrose, excipients and reducing agents. However, the presence of excessive amounts of riboflavin requires the addition of 0.5 g talc, which imparts a yellow color to the solution. 3-Methyl-2-benzothiazolone hydrazone63reacts in the presence of sodium metaperiodate to form a blue colored solution (λmax=630 nm) which helps in the determination of ascorbic acid over the range 6–14 meq ml–1.Wang64suggested the use of potassium iodate for the determination of vitamin C in pharmaceuticals. The absorbance is measured either in the UV region (288 nm) or in the visible region (445 nm). Besides aqueous phase measurements, the yellow precipitate can be extracted into chloroform65(λmax=514 nm). The ICl2–generated in the oxidation of AA by iodate66in acid medium in the presence of Cl–ions has been used to iodinate 2′,7′-dichlorofluorescein dye. The iodinated dye (λmax=525 nm) obeys Beer’s law up to 300 µg (ε=8.81×103). Soft drinks67have been analyzed using the reaction of iodine in an acetic acid medium (λmax= 350 nm). Sirividya and Balasubramanian68reported an indirect procedure based on the oxidation of ascorbic acid by a known excess of iodate in the presence of acid for the analysis of pharmaceuticals and fresh fruit juices. The unreacted iodate is used for hydroxylamine oxidation to generate nitrite, which is then diazotized with sulfanilic acid. The resulting diazonium salt is coupled with N-(1-naphthyl)ethylenediamine dihy-drochloride to form an azo dye (λmax=540 nm). The procedure is a complicated one as it involves many steps.The reaction of hexacyanoferrate(III)69(5)was used for the determination of micro quantities of vitamin C by measuring the decrease in color intensity of the reagent (5)(λmax=420 nm) in McIlvaine buffer (pH 5.2)solutions. Beer’s law is restricted within the range 180–270 µg of AA. A 200-fold amount of glucose, urea,citric acid and tartaric acid; 50-fold excess of creatineand 2-fold excess of creatinine do not interfere, but apositive error is observed even with very small quanti-ties of uric acid. In general, all such reagents thatreduce hexacyanoferrate(III) or oxidize hexacyanofer-rate(II) under experimental conditions interfere.Further the utility of the method is limited to colorlesssolutions. Yet another method involving the oxidationof phthalophenone to phenolphthalein by the reagent(5)in alkaline solution was proposed by Al-Tamrah.70This obeys Beer’s law up to 7 µg ml–1(λmax=553 nm). Sugars are tolerated only in microgram amounts. Therelative standard deviation and detection limit are0.65% and 0.1 µg ml–1respectively.Direct UV spectrophotometry71–73with backgroundcorrection methods such as thermal decomposition, UVlight irradiation, catalytic destruction and alkaline treat-ment has been used for the determination of AA in softdrinks, fruit juices and pharmaceuticals. However, therate of thermal decomposition is found to be very low72and fruit juice samples that are unstable to alkalinetreatment, have fine particles, have a deep coloration orcontain high concentrations of caffeine, saccharin,caramel and tannic acid can not be analyzed. Somemethods based on the Cu(II)-catalyzed oxidation arereported for the assay of pharmaceuticals, fruits andbeverages74–77allowing the determination of AA up to120 µg ml–1at λmax=267 nm. Fe(II) interferes seriously. Only minute amounts of folic acid are tolerated. Thepresence of Al(III), Mg(II) or Zn(II) gives a negativeerror due to their catalytic effect.Some methods involving the coinage metal (Cu, Ag,Au) complexes have been worked out. The reductionof Cu(II) in a biphasic system of isopentyl alcohol andan aqueous solution of pH 4.6 to Cu(I), followed by itscomplexation with cuproine to give a colored complex(λmax=454 nm), was reported by Contreras et al.78for the analysis of foods and vegetables. Fresh fruits andvegetables and dehydrated samples were analyzed afterextracting with 5% HPO3and with a 1:1 mixture of0.5% HPO3and 0.05 M H2SO4respectively. Also thecolored complexes of Cu(I) with 2,2-biquinoline79(λmax=540 nm), rhodanine80(λmax=473 nm) and 2,9-dimethyl-1,10-phenanthroline81–83(λmax=450 nm) have been used to determine ascorbic acid in different sam-ples. However, the method using 2,9-dimethyl-1,10-phenanthroline obeys Beer’s law over the range 2–20µg ml–1, though it requires 1 h waiting time for full color intensity. These methods based on the complex-ation of reduced Cu(I) are rather unselective, since sub-stances such as Fe(II), cysteine, or sodium thiosulfatewhich lead to the reduction of Cu(II) to Cu(I) interfereseriously. The gelatin complexes84,85of Ag(I)(λmax=415 nm; ε=2.2×103) and Au(III) (λmax=540 nm;ε=2.3×103) give colored products on adding AA to their alkaline solutions. The procedure as suggested by Pal et al.84is not interfered with by glycine, alanine, fruc-tose, sucrose, citric acid, tartaric acid or other reducingagents.Analytical applications of Molybdenum Blue formedon reduction of phosphomolybdate complex86, ammoni-um molybdate87–89or molybdic acid90have been report-ed by many workers for the determination of ascorbicacid in pharmaceuticals, fruits and vegetables, pastriesand beverages. Ammonium molybdate–sulfuric acidsystem requires 1 h for complete development of colorwith ascorbic acid.87However, such waiting time canbe decreased to 15 min by the addition of metaphos-phoric acid–acetic acid solution.88The colored speciesobeys Beer’s law over the range 2–32 µg ml–1at 760nm (ε=4.3×104). Serious interferences are observed due to phenolic compounds such as catechins, gallicacid, pyrogallol and gallotannins; thiosulfate ions andthiourea. Recently, P-Sb-Mo heteropoly acid91hasbeen used to produce heteropoly blue (λmax=710 nm) for the assay of ascorbic acid over the range 1–50 µgml–1(ε=3.68×103). The use of folin reagent92and folin phenol93(λmax=760 nm) has also been described for the assay of biological samples after deproteinizing withTCA. Beer’s law is obeyed up to 45 µg ml–1. Thecolor development is not obstructed by bovine serumalbumin, adenine, guanine, thymol and oxyhaemoglo-bin. Folin-ciocalteu94reagent reacts with ascorbic acidto give a blue colored complex (λmax=730 nm) as well. However, the method is time-consuming, as the fullcolor intensity requires 40–50 min. Ammonium meta-vanadate95gives a green color (λmax=680 nm) on heat-ing for 10 min in the presence of ascorbic acid.Though the method has been put to use for the analysisof some samples, it is not sufficiently sensitive.Many spectrophotometric methods based on thereduction of Fe(III) to Fe(II) with ascorbic acid, fol-lowed by the complexation of reduced Fe(II) with dif-ferent reagents, have been reported. Amongst them,α,α′-bipyridyl96–101and 1,10-phenanthroline102–109(o-phen) find extensive use in the development of analyti-cal procedures. Most of these methods are time-con-suming, as full color development is achieved onlyafter waiting for 30–60 min. Micromodification97ofthe procedure applicable to human plasma and animaltissue has been reported without the interference of glu-cose, fructose, sucrose, glutathione and cysteine.Recently, the procedure has been simplified by Aryaand Mahajan99so as to require only 5 min waiting time,instead of 30 or 60 min, with Beer’s law range up to 12µg ml–1(λmax=522 nm). Total ascorbic acid has been determined in blood plasma100after reducing DHAA with dithiothreitol at pH 6.5–8.0, removing the excess of dithiothreitol with N-ethylmaleimide and in urine101 by acidifying with TCA and shaking with activated chorcoal. The reduced Fe(II) forms a water-soluble colored complex with o-phenanthroline (λmax=510–515 nm) at pH 1.5–6.5, with obedience of Beer’s law up to 8 µg ml–1(ε=2.2×104). Background correction104 as achieved by Cu(II)-catalyzed oxidation is necessary for most samples, while the addition of NH4F106as theinhibitor of light reduction of Fe(III)-phen complex is needed in some cases. Selectivity for some of these methods is poor. However, an improvement using orange-red ferroin chelate in aqueous micellar medium formed in the presence of the cationic surfactant cetylpyridinium bromide109has been reported (ε=2.6×104at 510 nm). Ascorbic acid in fruits was determined after extracting the ternary complex of Fe(II) with α,α′-bipyridyl/o-phen and sulfophthalein110 dyes into chloroform (λmax=602 nm).Many other compounds including oximes111–113(6), 2-oximinocyclohexanone thiosemicarbazone114(2-OCHT) (7), 2-(5-bromo-2-pyridylazo)-5-dimethyl-aminophenol115(8)and 2-nitroso-5-(N-propyl-N-sulfo-propylamino)phenol116(9)have been investigated for their use in the analysis of pharmaceuticals and biologi-cal samples for ascorbic acid contents. The earlier reported extraction111of Fe(II)-dimethylglyoxime com-plex into chloroform, which allows the determination of 0.04–0.5 mM ascorbic acid, was modified by Arya et al.112They determined its concentration up to 14 µg ml–1at 514 nm. A proportionate decrease in color intensity of Fe(III)-resacetophenone oxime113complex in sodium acetate–acetic acid buffer (pH 5) with the increasing amounts of ascorbic acid was used for its assay in the range 3.5–17.5 µg (ε=4×103). The method using 2-OCHT determines ascorbic acid up to 12 µg ml–1(ε=1.49×104), but is interfered with by metal ions such as Cu(II), Co(II), Ni(II) and Pd(II), in addition to the interference caused by the oxalic acid, riboflavin, oxidants and reductants. Color-forming reactions of Fe(II) with ferrozine117–119(λmax=562 nm) in acidic solu-tions (pH 3–6), TPTZ120–122(λmax=593, 595 nm), quinaldic acid in presence of pyridine123(λmax=380 nm), picolinic acid in presence of pyridine124(λmax=400 nm) and nitroso-R salt125(λmax=705 nm) have been used for the determination of vitamin C in a variety of samples. The reagents picolinic acid and quinaldic acid, when complexed with iron(II) in the presence of pyridine, resulted in methods used successfully in the analysis of pharmaceuticals, food products and biologi-cal samples. The respective colored complexes getting extracted into chloroform obey Beer’s law in the range 0.4–5.6 µg ml–1and 2.5–25 µg ml–1ascorbic acid without the interference of common ingredients of the samples studied. Though the method using ferrozine117 is not interfered with by sucrose, glucose, mannose, fructose and formaldehyde, yet it suffers interferences from tartaric acid, citric acid, Co(II), Ni(II) and Fe(II). However, reactions of citric acid and tartaric acid can be masked by adding Al(III) or La(III) ions and that of iron(II) by passing the solution through a cation exchanger.Most of the reported methods based on the reducing action of ascorbic acid on metal ions invariably make use of an iron(III)–iron(II) redox system. A few use copper(II)–copper(I), vanadium(V)–vanadium(IV) or molybdenum/tungsten blue formation reactions, as mentioned earlier in the text. Arya et al. have reported a new redox system involving Cr(VI)-diphenyl-carbazide complex126(λmax=540 nm), which obeys Beer’s law up to 3.2 µg ml–1. Common additives of pharmaceutical preparations have no adverse effect on the absorbance of the complex. Another fast and facile method based on the proportionate decrease in absorbance of iron(III)-ferronate complex127(λmax=465 nm) by the addition of ascorbic acid was proposed by the same authors after extracting the complex into TBA/CHCl3solution. Beer’s law is valid up to 10 µg ml–1.3 ConclusionEven after the introduction of other instrument-based procedures, photometric methods continue to be of interest because of the ease in accessibility and their quick applicability to the routine analyses. The molar absorptivity for most of the colored species used in col-orimetric analysis of vitamin C lies over the range 103 to 1041 mol–1cm–1at the wavelength of maximum absorbance. This enables the precise determination of vitamin C in a variety of samples. The presence of cer-tain substances, especially the matrix constituents, may cause serious interferences. However, attempts to over-come such interferences either by using masking agents or making preliminary separations are invariably tried, but sometimes without much success, thus resulting in methods of varying selectivity. It has not been possible to categorize the methods based on the selectivity since the relevant data is found to be missing in the summary part of most methods reported in Chemical Abstracts. But none of the methods is found entirely specific for vitamin C. Despite the reporting of several new photo-metric methods, old procedures still continue to be cited in different pharmacopoeias, indicating either the lack of reliability or of general applicability of these methods of vitamin C determination. Research workers try to justify their work in terms of specific applica-tions, but seldom give an comparative account with other methods regarding analysis of particular type of matrix. Therefore, to incorporate the comparative use of such methods under specific analytical environment requires some patience.The authors wish to thank the Chairman, Department of Chemistry, Kurukshetra University, Kurukshetra, for necessary library facilities and Dr. Meenakshi Mahajan is grateful to CSIR for financial assistance.4 References1.H. Nie and S. Peng, Yingyang Xuebao, 6, 293 (1984).2.X. Shao and Y. Zhang, Guangpuxue Yu Guangpu Fenxi,14, 125 (1994).3.K. Vamos, Elmelz Ip., 43, 16 (1989).4.H. P. Huang, R. X. Cai, Y. M. Du and Y. E. Zeng, Chin.Chem.Lett., 6, 235 (1995).5. D. B. Dennison, G. B. Troy and L. D. Hunter, J.Agric.Food Chem., 29, 927 (1981).6.M. Yoshida, T. Nishimune and K. Sureki, Korean J.Pharmacol., 28, 53 (1992).7. E. Racz, K. Parlagh-Huszar and T. Kecskes, Period.Polytech.,Chem.Eng., 35, 23 (1991).8.H. Iwase, J.Chromatogr., 606, 277 (1992).9.R. Leubolt and H. Klein, J.Chromatogr., 640, 271 (1993).10.X. Chen and M. Sato, Anal.Sci., 11, 749 (1995).11. F. Sahbaz and G. Somer, Food Chem., 44, 141 (1992).12.R. Barbera, R. Farre, M. J. Legarda and R. Pintor,Alimentaria, 247, 89 (1993).13.G. Lu, Y. Wang, L. Yao and S. Hu, Food Chem., 51, 237(1994).14. A. Lechien, P. Valenta, H. W. Naurnberg and G. J.Partriarche, Fresenius’Z.Anal.Chem., 311, 105 (1982).15.I. D. H. C. Marques, E. T. A. Jr. Marques, A. C. Silva, W.M. Ledingham, E. H. M. Melo, V. L. da Silva and J. L.Lima Filho, Appl.Biochem.Biotechnol., 44, 81 (1994). 16.W. Zang, J. Wang and L. Jianyan, Huaxue Fence, 32, 239(1996).17.Y. Liu, Huaxue Shiji, 16, 282 (1994).18. F. Kober, Prax.Naturwiss.Chem., 37, 27 (1988).19.Indian Pharmacopoeia, Photolitho Press, Faridabad, p. 49,1985.20.Pharmacopoeia of the United States XVIII, pp. 51, 52,Mack Printing Co., Easton PA, 1970.21.British Pharmacopeia, p. 901, H. M. Stationary Office,London, 1988.22.T. Koba, M. Motomura, A. Tsuboi, T. Abekawa and K.Ito,Eisei Kensa, 35, 1565 (1986).23.M. J. Egoville, J. F. Sullivan, M. F. Kozempel and W. J.Jones, Am.Potato J., 65, 91 (1988).24.R. Hernandez and F. Bosch, Ars.Pharm., 15, 39 (1974).25.P. J. Gary, G. M. Owen and D. W. Lashley and P. C. Ford,Clin.Biochem., 7, 131 (1974).26.M. A. Eldawy, A. S. Tawfik and S. R. Elshabouri, Anal.Chem., 47, 461 (1975).27.T. Kamangar, A. B. Fawzi and R. H. Maghssoudi, J.Assoc.Off.Anal.Chem., 60, 528 (1977).28.S. Y. Lin, K. J. Duan and C. L. Tsung, Pharm.Acta.Helv., 69, 39 (1994).29.N. K. Pandey, Anal.Chem., 54, 793 (1982).30. A. M. Frigola Canovas and F. Bosch Serrat, An.Bromatol,40, 79 (1988).31.I. A. Biryuk, B. P. Zorya, V. V. Petrenko and S. B. But,Izobreteniya, 19, 194 (1993).32.I. A. Biryuk and V. V. Petrenko, Farm.Zh., 6, 52 (1991).33.M. R. Esteban and C. N. Ho, Microchem.J., 56, 122(1997).34.L. Casella, M. Gulloti, A. Marchesini and A. Petrarulo, J.Food Sci., 54, 374 (1989).35.W. Lee, S. M. Roberts and R. F. Labbe, Clin.Chem., 43,154 (1997).36.G. Szepesi, Fresenius’ Z.Anal.Chem., 265, 334 (1973).37. C. F. Bourgeosis and P. R. Mainguy, Intern.J.Vit.Nutr.Res., 45, 70 (1975).38.R. C. Rose and D. L. Nahrwold, Anal.Biochem., 114, 140(1981).39.W. D. Graham and A. Donald, J.Chromatogr., 594, 187(1992).40.T. Tsutui and T. Adachi, Kyoto-fu Eisei Kogai KenkyushoNenpo, 35, 42 (1990).41.Y. Yasui and M. Hayashi, Anal.Sci., 7, 125 (1991).42.M. O. Nisperos-Carriedo, B. S. Busling and P. E. Shaw, J.Agric.Food Chem., 40, 1127 (1992).43.J. Commack, A. Oke and R. N. Adama, J.Chromatogr.,565, 529 (1991).44.M. J. Esteve, R. Fare, A. Frigola and J. M. Garcia-Cantabella, J.Chromatogr.B.Biomed.Appl., 688, 345 (1997).45. F. Tessier, I. Birlouez-Aragon, G. Jani-Chantal and C.Jean, Vitam.Nutr.Res., 66, 166 (1996).46.S. Z. Qureshi, A. Saeed and T. Hasan, Anal.Lett., 22,1927 (1989).47.V. Nirmalchandar and N. Balasubramanian, Z.GesamteHyg.Ihre.Grenzgeb, 33, 497 (1987).48.R. G. Bhatkar and M. H. Saldonha, East Pharm., 25, 117(1982).49.O. H. Abdelmageed, P. Y. Khashaba, H. F. Askal, G. A.Saleh and I. H. Reffat, Talanta, 42, 573 (1995).50.M. H. Hashmi, A. S. Adil, A. Viegas and A. I. Ajmol,Mikrochim.Acta, 3, 457 (1970).51.H. O. Beutler and G. Beinstingl, Dtsch.Lebensm.Rundsch., 76, 69 (1980).52.H. O. Beutler, G. Beinstingl and G. Michal, Ber.—Int.Fruchtsaft Union Wiss—Tech.Komm, 16, 325 (1980). 53.P. W. Alxandrova and A. Nejtscheva, Mikrochim.Acta,1982 I, 387.54.P. V. Aleksandrova and A. Neicheva, Mikrochim.Acta,1979 II, 337.55.G. Xiao and G. Zhao, Shipin Yu Fajiao Gongye, 5, 35(1987).56.O. Pelletier and R. Brassard, J.Food Sci., 42, 1471(1977).57.Z. Zloch, Mikrochim.Acta, 1975, 213.58.S. Garcia-Castineiras, V. D. Bonnet, R. Figueroa and M.Miranda, J.Liq.Chromatogr., 4, 1619 (1981).59.O. Pelletier and R. Brassard, Adv.Automat.Anal.Technicon Int.Congr., 9, 73 (1973).60.O. Pelletier and R. Brassard, J.Assoc.Off.Anal.Chem.,58, 104 (1975).61.W. A. Behrens and R. Madere, Anal.Biochem., 92, 510(1979).62.N. Wahba, D. A. Yassa and R. S. Labib, Analyst[London], 99, 397 (1974).63.M. N. Reddy, G. K. Mohan, N. R. P. Singh and D. G.Sankar, Indian Drugs, 25, 204 (1988).64.Z. Wang, Yingyand Xuebao, 9, 174 (1987).65.W. Zhang, Zhongguo Yiyuan Yaoxue Zazhi, 12, 409(1992).66.N. Balasubramanian, S. Usha and K. Sirividya, IndianDrugs, 32, 73 (1995).67.Y. Yonemura, Y. Miura and T. Koh, Bunseki Kagaku, 39,567 (1990).68.K. Sirividya and N. Balasubramaninan, Analyst[London],121, 1653 (1996).69.N. Burger and V. Karas-Gasparec, Talanta, 20, 782(1973).70.S. A. Al-Tamrah, Anal.Chim.Acta, 209, 309 (1988).71.S. Baczyk and K. Swizinska, Farm.Pol., 31, 399 (1975).72.Y. S. Fung and S. F. Luk, Analyst[London], 110, 201(1985).73.Y. S. Fung and S. F. Luk, Analyst[London], 110, 1439(1985).74.O. W. Lau, S. F. Luk and K. S. Wong, Analyst[London],112, 1023 (1987).75.J. Yan, Zhongguo Yaoxue Zazhi, 25, 478 (1990).。