Manure; Calcuim; Laser-induced breakdown spectroscopy; Genetic algorithm;ELEMENTAL ANALYSIS; MEAT

In order to enhance the efficiency and safety of manure resource utilization, a rapid quantitative analysis of calcuim (Ca) content in manure is of great significance. In the presented study, the application of laser-induced breakdown spectroscopy (LIES) technique was used to quantitatively analyze Ca content in manure. Genetic algorithm (GA) was also applied to the LIBS to optimize the model. The dominant factors of LIES were set: 80 collection dots with 15% laser energy, 400 mu m spot size, delay time of 1. 0 mu s, and preforming pressure at 20 tons (T). The modeling results showed that the initial linear model constructed from the characteristic wavebands of Ca presented low precision and accuracy, partial least squares (PLS) models with wavebands at 190 similar to 950 nm exhibited the effects with coefficient of determination for the validation set (R-v(2)) and relative prediction deviation (RPD) of 0. 85 and 2. 13, respectively. The PLS model considered 12 variables, which were selected with GA in the waveband at 190 similar to 950 nm, and presented the R-v(2) and RPD of 0. 90 and 3. 04, respectively. They had presented relatively better results by avoiding complicated sample processing. It is pertinent to note that the efficiency of this method increased by a large margin when the variables were selected based on GA analysis. The results showed that LIES combined with GA can be used for quantitative analysis of Ca in manure.