Evaluation of trace element contents of dried apricot samples from Turkey

Saraçoğlu, Sibel; Tüzen, Mustafa; Soylak, Mustafa

doi:10.1016/j.jhazmat.2009.01.011

Cited by 103 publications

(82 citation statements)

References 35 publications

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“…Nickel has also been reported to be a carcinogenic element (Cassaret & Doull's, 1996). Our study determined that the concentrations of these minerals in these fruits were within the acceptable range since the daily recommended dose should not exceed 13000 µg for Al (World Health Organization, 1996) and 1000 µg for Ni (Padovani et al, 2006 (Saracoglu et al, 2009), which is consistent with the results found in the present study. Cr is an essential mineral for human metabolism.…”

Section: Minerals Analysis By Usn-icp-oessupporting

confidence: 91%

Mineral characterization of native fruits from the southern region of Brazil

Pereira¹,

Boschetti²,

Rampazzo³

et al. 2014

Food Sci. Technol (Campinas)

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Section: Minerals Analysis By Usn-icp-oessupporting

confidence: 91%

Mineral characterization of native fruits from the southern region of Brazil

Pereira¹,

Boschetti²,

Rampazzo³

et al. 2014

Food Sci. Technol (Campinas)

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“…Many different apricot varieties have been investigated by many researchers in the world and different phytochemical contents have been determined for each apricot variety [17][18][19][20][21][22][23][24][25][26].…”

Section: +mentioning

confidence: 99%

Fractionation and Speciation of Cu in Different Processing Apricots

Erdoğan¹,

Erdemoğlu²,

Güçer³

2017

J Nutr Food Sci

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An analytical procedure was proposed to study the operational fraction of Cu in ripe-fresh, sun-dried and sulphited-dried apricots harvested from either treated Bordeaux mixture or unexposed trees. Based on the methods that consists pressurized liquid extraction procedure and solid phase extraction to separate diverse Cu fractions on different sorbents such as Dowex 50Wx8-40 and Amberlite XAD-7, and then flame atomic absorption spectrometry (FAAS) and ion selective electrode were used for off-line determination of Cu concentrations in the effluents obtained.Total copper concentrations in different processing the apricot samples exposed to Bordeaux mixture were 4.58, 4.48 and 4.25 µg/g in ripe fresh, sun-dried, sulphuring-sun drying, respectively. However, Cu concentrations in the organic apricot samples were determined 2.92; 2.97 and 2.25 µg/g. While circa 40-59% of total copper are extractable with water solvent including about 67-68% cationic copper, 25-33% organically bound copper and 26-44% labile in Kabaaşı apricot samples. Besides, while about 27-48% of total copper are extractable with methanol: water solvents containing about 40-23% cationic copper, 60-78% organically bound copper and 56-71% of copper was absorbed in the stomach.It was applied to analytical procedures for Cu speciation in the apricot samples were verified and validated.

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“…Some foods, such as vegetables, fruits, nuts, red meat, and shellfish, are known as sources of copper. Although Cu can play a critical role in various biochemical processes (11), a constant diet of this element results in the dissolution of the barrier that keeps undesirable toxins from entering the brain. Critical doses of this element can cause adverse health effects such as fatigue, hair loss, inflammation of brain tissues, panic attacks, premenstrual syndrome, anorexia, allergies, liver and kidney dysfunction, and also cancer (12).…”

Section: Introductionmentioning

confidence: 99%

Predicting arsenic and heavy metals contamination in groundwater resources of Ghahavand plain based on an artificial neural network optimized by imperialist competitive algorithm

Alizamir

Sobhanardakani

2017

Environ Health Eng Manag

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Background: The effects of trace elements on human health and the environment gives importance to the analysis of heavy metals contamination in environmental samples and, more particularly, human food sources. Therefore, the current study aimed to predict arsenic and heavy metals (Cu, Pb, and Zn) contamination in the groundwater resources of Ghahavand Plain based on an artificial neural network (ANN) optimized by imperialist competitive algorithm (ICA). Methods: This study presents a new method for predicting heavy metal concentrations in the groundwater resources of Ghahavand plain based on ANN and ICA. The developed approaches were trained using 75% of the data to obtain the optimum coefficients and then tested using 25% of the data.

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Evaluation of trace element contents of dried apricot samples from Turkey

Cited by 103 publications

References 35 publications

Mineral characterization of native fruits from the southern region of Brazil

Mineral characterization of native fruits from the southern region of Brazil

Fractionation and Speciation of Cu in Different Processing Apricots

Predicting arsenic and heavy metals contamination in groundwater resources of Ghahavand plain based on an artificial neural network optimized by imperialist competitive algorithm

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