Quantitative multiple-element simultaneous analysis of seaweed fertilizer by laser-induced breakdown spectroscopy

Abstract

Laser-induced breakdown spectroscopy, coupled with advanced chemometric methods, was used to quantitate multiple elements in a seaweed-based fertilizer. The influence of important parameters was determined using partial least squares regression (PLSR), support vector regression (SVR) and random forest (RF) optimizations. Optimal results for Mg, K and P were obtained using PLSR, whereas RF yielded the best results for Mn, Cu, Sr and Ca. The best predictions for Ba levels were obtained with SVR. The lowest root mean square errors in the prediction sets for Mn, Cu, Sr, Ba, Mg, K, P and Ca were 48.27 µg/g, 36.90 µg/g, 0.37 mg/g, 40.32 µg/g, 1.99 mg/g, 2.03 mg/g, 4.81 mg/g and 14.08 mg/g, respectively, with average relative standard deviations of 13.65%, 2.68%, 19.80%, 5.17%, 3.32%, 2.98%, 1.82% and 5.81%. The results showed that the optimal multivariate model depended on the specific element being analyzed. The proposed method provides a rapid means of determining multielement concentrations in seaweed-based fertilizers.

WITHDRAWN: Rapid quantitative analysis of calcium in infant formula powder assisted by long short-term memory with variable importance using laser-induced breakdown spectroscopy

“…This study created a valuable tool for the quality control of wheat our. Furthermore, to improve the accuracy of the analysis results, prediction models have been constructed by combining LIBS with a variety of chemometric methods, such as partial least squares (PLS) [26,27], random forest (RF) [28,29], and support vector machine [30,31].…”

LIBS assisted PCA analysis of multiple rare-earth elements (La, Ce, Nd, Sm, and Yb) in phosphorite deposits

“…By considering the 10 spectra of each sample, we have determined the average elemental composition of each PR sample by keeping the identical conditions as well as optimized LIBS parameters. To minimize the relative uncertainty in composition (μg/g), we measured the relative standard deviation error (RSDE) in composition (μg/g) of each component present represents the sample [ 13 , 20 , 67 ]. In Eqs.…”

“…Laser-induced breakdown spectroscopy (LIBS) is a developing spectroscopical analytical tool for the qualitative and quantitative study of various samples such as cement [ 10 , 11 ], steel [ 12 ], soil [ 13 , 14 , 15 ], pharmaceutical tablets [ 16 ], plants [ 17 ], aqueous solution [ 18 , 19 ], seaweed fertilizer [ 20 ] and neoplastic tissues [ 21 ]. It is a fast and globally responsive technique that requires minimal sample pre-treatment as required in conventional techniques such as ICP-MS and ICP-AES.…”

Kinetics of optical clearing of human skin studiedin vivousing portable Raman spectroscopy

“…Spectral classification was based on spectral characteristics of the skin. Principal component analysis (PCA), which is the most commonly used statistical tool in the field of multivariate data analysis [20], was used for unsupervised statistical analysis. Spectra were first normalized by the sum intensity of every pixel across the entire broadband spectral range to facilitate comparison of sample data of different spectral intensities.…”