Preparation of a soluble solid sample by a continuous ultrasound assisted dissolution system for the flow-injection atomic absorption spectrometric determination of iron in milk powder and infant formula

Yebra, M. C.; Moreno-Cid, A.; Cespón, R. M.; Cancela, S.

doi:10.1016/j.talanta.2003.08.010

Cited by 32 publications

(5 citation statements)

References 6 publications

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“…Thus, the determination of trace elements in powdered milk is important for nutritional purposes , . Some wet chemistry methods were applied for iron and zinc content determination in powdered milk, such as flow-injection atomic absorption spectrometry , reaction cell inductively coupled plasma mass spectrometry , electrothermal atomization atomic absorption spectrometry , and slurry sampling electrothermal vaporization inductively coupled plasma mass spectrometry . However, these methods are time-consuming, laborious, expensive, and require complex and professional laboratory operations.…”

Section: Introductionmentioning

confidence: 99%

Exploring Near and Midinfrared Spectroscopy to Predict Trace Iron and Zinc Contents in Powdered Milk

Shi

et al. 2009

J. Agric. Food Chem.

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Near infrared (NIR) and mid-infrared (MIR) spectroscopy were investigated to predict iron and zinc contents in powdered milk. A hybrid variable selection method, namely, uninformative variable elimination (UVE) combined with successive projections algorithm (SPA), was applied to select the most effective wavenumber variables from full 2756 NIR and 3727 MIR variables, respectively. Finally, 18 NIR and 18 MIR variables were selected for iron content prediction, and 17 NIR and 12 MIR variables for zinc content prediction. The obtained effective wavenumber variables were input into partial least-squares (PLS) and least-squares-support vector machines (LS-SVM), respectively. The selected MIR variables obtained much better results than NIR to predict both iron and zinc contents in both the PLS and LS-SVM models. The iron content prediction results based on LS-SVM with 18 MIR spectra were as follows: coefficient of determination (r(2)) was 0.920, residual predictive deviation (RPD) was 3.321, and root-mean-square error of prediction (RMSEP) was 1.444. The zinc content prediction results based on LS-SVM with 12 selected MIR spectra were as follows:r(2) was 0.946, RPD was 4.361, and RMSEP was 0.321. The good performance shows that UVE-SPA is a powerful variable selection tool. The overall results indicate that MIR spectroscopy incorporated to UVE-SPA-LS-SVM could be applied as an alternative fast and accurate method to determine trace mineral content in powdered milk, such as iron and zinc.

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Section: Introductionmentioning

confidence: 99%

Exploring Near and Midinfrared Spectroscopy to Predict Trace Iron and Zinc Contents in Powdered Milk

Shi

et al. 2009

J. Agric. Food Chem.

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“…With the use of the HIUS technology, the main processing can be improved such as controlling certain undesirable microorganisms, inactivating some enzymes, reducing the time of fermentation, enhancing cellular growth and proliferation, accelerating acidification, promoting enzyme activities, and increasing substrate transfer rate (Gholamhosseinpour & Hashemi, 2019; Nguyen et al, 2009). As shown in Figure 4, HIUS can be employed in wide areas of milk processing such as pasteurization (Scudino et al, 2020), fermentation (Abesinghe et al, 2019), microorganism inactivation (Akdeniz & Akalın, 2020; Arroyo et al, 2011; Bermúdez‐Aguirre & Barbosa‐Cánovas, 2008), extraction (Rathnakumar et al, 2021), homogenization (Aernouts et al, 2015; Liu et al, 2021), microfiltration (Zhang et al, 2021), ultrafiltration (Jin et al, 2014; Jin et al, 2017), creaming (Juliano et al, 2011; Leong, 2020), viscosity decreasing (Desphande & Walsh, 2017), dissolution (Wu et al, 2020; Yebra et al, 2004), and so on. Table 1 represents the applications of HIUS in the milk industry with their mechanism and results.…”

Section: Ultrasound Applicationsmentioning

confidence: 99%

Ultrasound assisted processing of milk: Advances and challenges

Firouz

Sardari

Soofiabadi

et al. 2022

J Food Process Engineering

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High-intensity ultrasound (HIUS) is a green technology that has improved various processes in the food industry. HIUS leads to improved heat and mass transfer rates, providing a faster processing technique and limiting production costs by increasing process efficiency. In food processing, ultrasound is regarded as a promising emerging technology with the potential to speed up processes and produce high quality products. This article describes recent applications of power ultrasound for physical milk processing, mentions the advantage and disadvantages of this technology, evaluates the physical and chemical effects of HIUS on the modification of milk, and novel research areas leading to the promotion and solving the challenges ahead. It is concluded that HIUS is a useful tool for milk processing, because of its positive effects on the quality and retaining their initial nutritional properties and sensory characteristics. It can also be considered that the forthcoming research will lead to the improvement and industrialization of this technology. Practical ApplicationsAs a very important food item in the human diet, milk has very sensitive components that usually undergo undesirable changes during processing. Power ultrasound is an emerging green technology that has a great potential for application in dairy processing that can significantly reduce such unfavorable changes. It has been proven that ultrasound has an appropriate capability to accelerate processes, reduce energy consumption and increase productivity. This technology has been successfully used in pasteurization, homogenization, filtration, and drying of milk in laboratory scale.Ultrasound has a very high potential for industrialization in the dairy industry and draws a promising perspective for its conventional applications in the production of dairy products in the not-too-distant future.

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“…Yebra and co-workers have devised several ultrasound-assisted extraction procedures: for the determination of Ca in seafood, 22 Zn in milk powder 23 and Fe in milk powder. 24 Jimenez et al 25 created virgin olive oil emulsions for the determination of several elements as indicators of geographical origin and type of olive, whereas Reis et al simply injected 26 used lubricating oils for the determination of wear metals Cr, Cu, Fe and Pb. Anzano et al determined Zn in foods by a FAAS method that was calibrated by a FI gradient procedure 27 and Koscielniak and co-workers 28 described two FI-based calibration methods: the integrated calibration method and the complementary dilution method, 29 which were applied for the determination of Ca and Mg by FAAS.…”

Section: Flow Injectionmentioning

confidence: 99%

Atomic spectrometry update. Advances in atomic emission, absorption and fluorescence spectrometry, and related techniques

Evans

Day

Palmer

et al. 2005

J. Anal. At. Spectrom.

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Preparation of a soluble solid sample by a continuous ultrasound assisted dissolution system for the flow-injection atomic absorption spectrometric determination of iron in milk powder and infant formula

Cited by 32 publications

References 6 publications

Exploring Near and Midinfrared Spectroscopy to Predict Trace Iron and Zinc Contents in Powdered Milk

Exploring Near and Midinfrared Spectroscopy to Predict Trace Iron and Zinc Contents in Powdered Milk

Ultrasound assisted processing of milk: Advances and challenges

Atomic spectrometry update. Advances in atomic emission, absorption and fluorescence spectrometry, and related techniques

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