基于Kjeldahl与Dumas方法的农作物秸秆总氮含量分析

凯氏定氮法(Kjeldahl)与杜马斯燃烧法(Dumas)是测定农业生物质总氮含量的主要检测手段,但二者的测定结果数值存在差异。该研究获取农作物秸秆样本(水稻、小麦、玉米、油菜和棉花)共计1 179个,分别采用Kjeldahl和Dumas方法测定总氮(TKN和TCN,total Kjeldahl nitrogen and total combustion nitroyen)含量,通过多种统计与分析方法,系统分析比较了不同农作物秸秆总氮含量及其分布的异同和相关关系。结果表明:不同农作物秸秆氮含量分布均呈非正态分布,建议采用中位数统计;5种秸秆总体的TKN质量分数为(7.12±1.87) g/kg,TCN质量分数为(8.00±2.13) g/kg,TKN含量显著小于TCN含量;小麦和棉花秸秆的TKN含量和TCN含量与其他秸秆间均存在显著差异(P <0.05);不同生物质TKN含量与TCN含量关系不同,建议采用最小中位数二乘法进行拟合分析。研究结果可为农作物秸秆科学利用提供数据及方法互通性支撑。

Analysis of the total nitrogen content of crop residues determined by using Kjeldahl and Dumas methods

The Kjeldahl and combustion(Dumas) methods are the main methods used to determine total nitrogen(TKN and TCN) content in agriculture biomass. However, the results obtained using these methods differ because of differences in their underlying principles. Herein, we used these two methods to determine the total nitrogen content in 1 179 crop residues(rice straw, wheat straw, corn stover, rape stalk, cotton stalk) from China, and systematically analyzed and compared in total nitrogen content and their distributions in the collected crop residues by different types with these two methods. Seven common distributions(Normal, Lognormal, Gamma, Weibull, Exponential, Laplace, Lorentz) were used to determine the data distribution types of TKN and TCN in different crop residues. The correlation between the two methods was explored using ordinary least squares regression(OLS), orthogonal regression(Orth), and least median square regression(LMS). Finally, the research reviewed the correlation between different biomass(food, flowers, grass, soil, crop, crop residues, sewage sludge and animal manure, etc.) results of two methods for measuring nitrogen content. The results showed: The distributions of nitrogen content were non-normal distributions in different crop residues. The total TKN and TCN contents were the same distributions in rice straw, wheat straw, rape stalk and total crop residues which approximately followed Lognormal, Gamma, Lognormal and Lognormal respectively. The median method was recommended for data statistics, and results from low to high were:1) TKN: wheat straw(5.66 ± 1.07 g/kg), rape stalk(7.10 ± 1.87 g/kg), rice straw(8.20 ± 1.42 g/kg), corn stover(8.82 ±2.23 g/kg), cotton stalk(10.42 ± 1.45 g/kg);2) TCN: wheat straw(6.17 ± 1.17 g/kg), rape stalk(8.50 ± 2.45 g/kg), rice straw(8.59 ± 1.45 g/kg), corn stover(10.10 ± 1.91 g/kg), cotton stalk(11.75 ± 1.48 g/kg). It was found that TKN was significantly lower than TCN in all types of crop residues(P < 0.05). TKN and TCN values were also significantly different among wheat straw, cotton stalk and other crop residues(P < 0.05). Although the fitting efficiencies of OLS, Orth and LMS were the same on the determination coefficient(R2) scale, the fitting results were different. LMS was recommended because it reduced the effect of outliers compared with three methods, observed from kernel density – scatter plots. Five types of crop residues and the total had different fitting result between TKN and TCN. The correlation between TKN and TCN for total crop residues was quantified as the LMS equation. In addition, there was a gap of the linear relationships between TKN and TCN in different types of biomass. The slope of plant biomass was generally lower than that of animal manure, whose potential reason was different forms and contents of nitrogen in different biomass(ammonium nitrogen, nitrate nitrogen, nitrite nitrogen,heterocyclic nitrogen, and nucleic acid nitrogen, etc.). The results may provide extensive and reliable data for reference from large sample size, and methods support for the scientific utilization of nitrogen in crop residues.