Evaluation of physicochemical models for rapidly estimating cattle manure nutrient content

文献类型： 外文期刊

第一作者： Chen, Longjian

作者： Chen, Longjian;Han, Lujia;Yan, Zengling;Xing, Li

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期刊名称：BIOSYSTEMS ENGINEERING （ 影响因子：4.123； 五年影响因子：4.508 ）

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收录情况： SCI

摘要： With the increasing concern over the potential pollution from farm wastes, there is a need for rapid and robust methods that can evaluate livestock manure nutrient content. Physicochemical models which related cattle manure nutrient content (ammonium nitrogen, AN; total potassium, TK; total nitrogen, TN; total phosphorus, TP) to its physicochemical properties (specific gravity, dry matter, electrical conductivity, pH) have been reported by previous researchers. This study reviewed previous physicochemical models and compiled the observed data drawn from a wide selection of sources to validate various physicochemical models. Several statistical parameters, including the coefficient of determination R2, the modelling efficiency statistic, the mean squared error of prediction, the mean bias, and the linear bias, were calculated to evaluate model performance on the data sets. The results showed that the relationship (AN = 0.136EC - 0.523) developed by Scotford et al. (1998b), provided satisfactory predictions for AN with R2 = 0.75. The equation (TP = 0.01DM + 0.057) developed by Higgins et al. (2004) gave reasonable prediction for TP with R2 = 0.77. The corrected TK model (TK = 0.184EC + 0.042) greatly reduced systemic errors and hence improved TK prediction with R2 = 0.87. Compared with prediction models for other nutrient contents, TN physicochemical models provided far from satisfactory predictions but equations used by Marino et al. (2008) was the best (R2 = 0.62).

分类号： S18

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