zhpsЖурнал прикладной спектроскопииZhurnal Prikladnoii Spektroskopii0514-7506B. I. Stepanov Institute of Physics of the National Academy of Scienceszhps-1095Research ArticleСтатьиКоличественный анализ азота в сложных удобрениях с использованием лазерной атомно-эмиссионной спектроскопии в сочетании с методом многомерной регрессииQuantitative Analysis of Nitrogen in Compound Fertilizers Using Laser-Induced Breakdown Spectroscopy Coupled with Multivariate RegressionLuC.LuC.

Хэфэй

Hefei

ShiCh.ShiCh.

Хэфэй

Hefei

lucphu1983@163.comDaiH.DaiH.

Хэфэй

Hefei

LvG.LvG.

Хэфэй

Hefei

ZhangZh.ZhangZh.

Хэфэй

Hefei

JinF.JinF.

Хэфэй

Hefei

HuB.HuB.

Хэфэй

Hefei

Школа передовых производственных технологий Хэфэйского университетаSchool of Advanced Manufacturing Engineering at Hefei University202228072022894541547Copyright © Lu C., Shi C., Dai H., Lv G., Zhang Z., Jin F., Hu B., 20222022Lu C., Shi C., Dai H., Lv G., Zhang Z., Jin F., Hu B.Lu C., Shi C., Dai H., Lv G., Zhang Z., Jin F., Hu B.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://zhps.ejournal.by/jour/article/view/1095

С помощью лазерной атомно-эмиссионной спектроскопии (LIBS) проведен количественный анализ концентрации азота в сложных удобрениях. Тридцать два образца использованы в качестве калибровочного набора, восемь образцов — в качестве проверочного набора. Для построения моделей и устранения матричного эффекта использованы частичная регрессия методом наименьших квадратов и регрессия опорных векторов методом наименьших квадратов (LS-SVR). Для модели частичной регрессии методом наименьших квадратов коэффициенты корреляции для наборов калибровки  и прогнозирования составили 0.837 и 0.794. С использованием метода LS-SVR коэффициенты корреляции для наборов калибровки и прогнозирования улучшены до 0.994 и 0.993. Таким образом, метод  LS-SVR повышает точность анализа. Средняя абсолютная ошибка прогноза 0.023%. Показано, что LIBS в сочетании с LS-SVR является надежным и точным методом определения концентрации азота в сложных удобрениях.

Quantitative analyses of the nitrogen concentration in compound fertilizer were performed using laserinduced breakdown spectroscopy (LIBS). Thirty-two samples were used as a calibration set, and eight samples were used as a validation set. To eliminate the matrix effect, partial least-squares regression (PLSR) and least-squares support vector regression (LS-SVR) were used to establish models. For the partial leastsquares regression model, the correlation coefficients for the calibration and prediction sets were 0.837 and 0.794, respectively. While using the LS-SVR method, the correlation coefficients for the calibration and prediction sets were improved to 0.994 and 0.993, respectively. Therefore, the LS-SVR method improved the analysis accuracy. The prediction mean absolute error was 0.023%. The results indicate that LIBS coupled with  LS-SVR is a reliable and accurate method for determining the nitrogen concentration in compound fertilizer.

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The authors declare that there are no conflicts of interest present.