000167872 001__ 167872 000167872 005__ 20260219141450.0 000167872 0247_ $$2doi$$a10.1007/s12161-025-02862-3 000167872 0248_ $$2sideral$$a147548 000167872 037__ $$aART-2025-147548 000167872 041__ $$aeng 000167872 100__ $$aFerreira, Dennis Silva 000167872 245__ $$aCalibration Models for Macronutrient (Ca, K, and Mg) Determination in Food Samples Using Laser-Induced Breakdown Spectroscopy: Instruments Comparison and Error Structure Information for Enhanced Predictive Accuracy 000167872 260__ $$c2025 000167872 5060_ $$aAccess copy available to the general public$$fUnrestricted 000167872 5203_ $$aLaser-induced breakdown spectroscopy (LIBS) is gaining prominence in analytical chemistry for direct elemental analysis in solid samples, although its sensitivity remains limited, typically ranging from 1000 mg kg⁻¹ to 100%. Error structure utilization can improve accuracy; however, few LIBS studies employ this approach. Data fusion, although promising, is underutilized due to its high cost and low analytical frequency. This study compares calibration models—partial least squares (PLS), principal component regression (PCR), error covariance penalized regression (ECPR), and maximum likelihood principal component regression (MLPCR)—for analyzing Ca, K, and Mg in non-conventional food plants. Two LIBS instruments, featuring CCD and ICCD detectors, were evaluated individually and through data fusion. ECPR and MLPCR outperformed conventional methods, with ECPR showing superior results. Detection limits ranged from 0.003 g 100g⁻¹ (Mg) to 0.2 g 100g⁻¹ (K), and sensitivity varied between 1.12 and 12.65 (signal area)(g 100g⁻¹)⁻¹. Data fusion significantly improves analytical accuracy, and while cost and frequency factors should be evaluated, the benefits often justify its use for high-precision applications. 000167872 540__ $$9info:eu-repo/semantics/embargoedAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es 000167872 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000167872 700__ $$0(orcid)0000-0001-5557-7825$$aBuil-García, Juan$$uUniversidad de Zaragoza 000167872 700__ $$0(orcid)0000-0002-8581-4972$$aAnzano, Jesús M.$$uUniversidad de Zaragoza 000167872 700__ $$aPereira-Filho, Edenir Rodrigues 000167872 700__ $$aPereira, Fabiola Manhas Verbi 000167872 7102_ $$12009$$2750$$aUniversidad de Zaragoza$$bDpto. Química Analítica$$cÁrea Química Analítica 000167872 773__ $$g18, 10 (2025), 2190-2197 [8 pp.]$$pFood Analytical Methods$$tFOOD ANALYTICAL METHODS$$x1936-9751 000167872 8564_ $$s577282$$uhttps://zaguan.unizar.es/record/167872/files/texto_completo.pdf$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2026-07-14 000167872 8564_ $$s1507682$$uhttps://zaguan.unizar.es/record/167872/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2026-07-14 000167872 909CO $$ooai:zaguan.unizar.es:167872$$particulos$$pdriver 000167872 951__ $$a2026-02-19-14:14:15 000167872 980__ $$aARTICLE