PMID- 32729853
OWN - NLM
STAT- MEDLINE
DCOM- 20210514
LR  - 20210514
IS  - 1759-9679 (Electronic)
IS  - 1759-9660 (Linking)
VI  - 12
IP  - 29
DP  - 2020 Aug 7
TI  - Artificial neural network employment for element determination in Mugil cephalus 
      by ICP OES in Pontal Bay, Brazil.
PG  - 3713-3721
LID - 10.1039/d0ay00799d [doi]
AB  - Fish are important sources of protein, making them very significant in the human 
      diet. Although the consumption of this food is beneficial for health, it is 
      essential that the product does not contain inorganic components above the limits 
      recommended by the current legislation. Therefore, a method for determination of 
      elements in fish (Mugil cephalus) samples was optimized. A simplex centroid 
      mixture design with restriction was applied for optimization of the acid 
      digestion of samples in an open system under reflux in order to evaluate the best 
      ratio between the reagents HNO(3), H(2)O(2) and H(2)O. The results indicated that 
      more intense analyte signals were obtained when a mixture containing 3.6 mL of 
      HNO(3) (65% v/v), 0.4 mL of H(2)O(2) (30% v/v) and 6.0 mL of H(2)O was used. The 
      accuracy of the method was assessed with a CRM of oyster tissue (NIST 1566b). The 
      method presented relative standard deviations (RSDs) of 3.54%; 3.82%; 4.81% and 
      3.50% for Zn, Fe, Cu and S, respectively. The detection limits were 0.002 mg 
      kg(-1) for Cu and Zn and 0.02 mg kg(-1) for Fe and S. The proposed method was 
      applied for the determination of Zn, Fe, Cu and S in fish samples. A Kohonen 
      Self-Organizing Map (KSOM) with K-means implementation was applied to better 
      delimit the boundary between groups and the spatial and temporal influence on how 
      concentrations of the chemical elements were perceived. To verify the separation, 
      the Davies-Bouldin and Silhouette indices were used, obtaining 0.5374 and 0.8541, 
      respectively, indicating satisfactory separation.
FAU - Batista, Milana Aboboreira Simoes
AU  - Batista MAS
AD  - Departamento de Ciencias Exatas e Tecnologicas, Universidade Estadual de Santa 
      Cruz, Campus Soane Nazare de Andrade, Km 16 BR-415, Ilheus, Bahia 45662-900, 
      Brazil. erikgps@gmail.com.
FAU - Santos, Luana Novaes
AU  - Santos LN
FAU - Chagas, Bruna Cirineu
AU  - Chagas BC
FAU - Lobo, Ivon Pinheiro
AU  - Lobo IP
FAU - Novaes, Cleber Galvao
AU  - Novaes CG
FAU - Guedes, Wesley Nascimento
AU  - Guedes WN
FAU - de Jesus, Raildo Mota
AU  - de Jesus RM
FAU - Amorim, Fabio Alan Carqueija
AU  - Amorim FAC
FAU - Pacheco, Clissiane Soares Viana
AU  - Pacheco CSV
FAU - Moreira, Luana Santos
AU  - Moreira LS
FAU - da Silva, Erik Galvao Paranhos
AU  - da Silva EGP
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20200710
PL  - England
TA  - Anal Methods
JT  - Analytical methods : advancing methods and applications
JID - 101519733
RN  - BBX060AN9V (Hydrogen Peroxide)
SB  - IM
MH  - Animals
MH  - *Bays
MH  - Brazil
MH  - Employment
MH  - Humans
MH  - *Hydrogen Peroxide
MH  - Neural Networks, Computer
EDAT- 2020/07/31 06:00
MHDA- 2021/05/15 06:00
CRDT- 2020/07/31 06:00
PHST- 2020/07/31 06:00 [entrez]
PHST- 2020/07/31 06:00 [pubmed]
PHST- 2021/05/15 06:00 [medline]
AID - 10.1039/d0ay00799d [doi]
PST - ppublish
SO  - Anal Methods. 2020 Aug 7;12(29):3713-3721. doi: 10.1039/d0ay00799d. Epub 2020 Jul 
      10.