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Optimization of separation conditions for the determination of dichloroacetic acid and nitrite in water by suppressed ion chromatography
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Hai-Ping GAO1, Mei-Rong DENG2, Jing-Hua WANG3, *
Journal of Food Safety & Quality | 2026, 17(13) : 284 - 293
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Journal of Food Safety & Quality | 2026, 17(13): 284-293
• Food Analysis and Detection •
Optimization of separation conditions for the determination of dichloroacetic acid and nitrite in water by suppressed ion chromatography
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Hai-Ping GAO1, Mei-Rong DENG2, Jing-Hua WANG3, *
Affiliations
  • 1.Harbin Songbei District Center for Disease Control and Prevention, Harbin 150028, China
  • 2.Harbin Center for Disease Control and Prevention, Harbin 150056, China
  • 3.Institute of Natural Resources and Ecology, Heilongjiang Academy of Sciences, Harbin 150040, China
doi: 10.19812/j.cnki.jfsq11-5956/ts.20260115005
Outline
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Objective

To establish a method for the simultaneous determination of dichloroacetic acid (DCAA)and nitrite in water by suppressed ion chromatography, and optimize their separation conditions through response surface methodology.

Methods

Thermo Scientific Dionex IonPac™ AS19 anion exchange column was used. Taking the separation degree of DCAA and nitrite as the core evaluation index, the effects of 3 key factors (column temperature, DCAA concentration and eluent concentration) on the separation degree were investigated by single-factor experiments. Building upon this, a Box-Behnken central composite design was employed to construct a response surface model, thoroughly exploring the interactions between the factors and determining the optimal separation conditions.

Results

The optimal separation conditions obtained by response surface methodology were as follows: column temperature 25 ℃, DCAA mass concentration 1000 μg/L and eluent mass concentration 6 mmol/L (with nitrite mass concentration fixed at 100 μg/L as the experimental background). Under the optimized conditions, the separation degree between DCAA and nitrite reached 2.71, meeting the requirement for effective separation of components during detection. Methodological validation results demonstrated good linearity within a certain concentration range(determination coefficient r2>0.999), the relative standard deviations were below 3.5%, and spike recovery rates were 95%-107%. These findings indicated that the method possessed high accuracy and stability.

Conclusion

The detection method optimized in this study can effectively achieve simultaneous and accurate determination of DCAA and nitrite in water. It is characterized by simple operation, high efficiency and reliability, making it suitable for the routine monitoring of these 2 kinds of substances in actual drinking water. This provides strong technical support for water quality safety assessment.

response surface methodology  /  ion chromatography  /  dichloroacetic acid  /  nitrite  /  separation degree  /  optimization
高海萍, 邓美荣, 王菁华. 抑制型离子色谱法检测水中二氯乙酸和亚硝酸盐分离条件优化. 食品安全质量检测学报, 2026 , 17 (13) : 284 -293 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20260115005
Hai-Ping GAO, Mei-Rong DENG, Jing-Hua WANG. Optimization of separation conditions for the determination of dichloroacetic acid and nitrite in water by suppressed ion chromatography[J]. Journal of Food Safety & Quality, 2026 , 17 (13) : 284 -293 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20260115005
Year 2026 volume 17 Issue 13
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Article Info
doi: 10.19812/j.cnki.jfsq11-5956/ts.20260115005
  • Receive Date:2026-01-15
  • Online Date:2026-11-05
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  • Received:2026-01-15
Funding
Affiliations
    1.Harbin Songbei District Center for Disease Control and Prevention, Harbin 150028, China
    2.Harbin Center for Disease Control and Prevention, Harbin 150056, China
    3.Institute of Natural Resources and Ecology, Heilongjiang Academy of Sciences, Harbin 150040, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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