{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T06:41:54Z","timestamp":1775025714542,"version":"3.50.1"},"reference-count":28,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61505001"],"award-info":[{"award-number":["61505001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The rapid detection of the elements nitrogen (N), phosphorus (P), and potassium (K) is beneficial to the control of the compound fertilizer production process, and it is of great significance in the fertilizer industry. The aim of this work was to compare the detection ability of laser-induced breakdown spectroscopy (LIBS) coupled with support vector regression (SVR) and obtain an accurate and reliable method for the rapid detection of all three elements. A total of 58 fertilizer samples were provided by Anhui Huilong Group. The collection of samples was divided into a calibration set (43 samples) and a prediction set (15 samples) by the Kennard\u2013Stone (KS) method. Four different parameter optimization methods were used to construct the SVR calibration models by element concentration and the intensity of characteristic line variables, namely the traditional grid search method (GSM), genetic algorithm (GA), particle swarm optimization (PSO), and least squares (LS). The training time, determination coefficient, and the root-mean-square error for all parameter optimization methods were analyzed. The results indicated that the LIBS technique coupled with the least squares\u2013support vector regression (LS-SVR) method could be a reliable and accurate method in the quantitative determination of N, P, and K elements in complex matrix like compound fertilizers.<\/jats:p>","DOI":"10.3390\/s19153277","type":"journal-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T08:45:39Z","timestamp":1564130739000},"page":"3277","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Quantitative Analysis of Elements in Fertilizer Using Laser-Induced Breakdown Spectroscopy Coupled with Support Vector Regression Model"],"prefix":"10.3390","volume":"19","author":[{"given":"Wen","family":"Sha","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electric Engineering and Automation, Anhui University, Hefei 230061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangtao","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electric Engineering and Automation, Anhui University, Hefei 230061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wubing","family":"Xiao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electric Engineering and Automation, Anhui University, Hefei 230061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengpeng","family":"Ling","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Electric Engineering and Automation, Anhui University, Hefei 230061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cuiping","family":"Lu","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Decision, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"ref_1","first-page":"231","article-title":"Effective phosphorus detection in compound fertilizers by weight method","volume":"5","author":"Cui","year":"2016","journal-title":"Mod. 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