Increasing Throughput in Micronutrient Analysis in Fruit Juice

Fruit juice is considered a convenient beverage with a pleasant taste and greater nutritional value than carbonated beverages. Since well-documented information is available about the nutrition content of the original fruit itself, the expected nutritional value of the final juice product for 100% juice can be calculated. Manufacturers may also fortify their juice products with micronutrients in order to make the products appealing to consumers and to address market requirements.

Food products need to be supplied with detailed labelling. Quantifying the content of food products, including micronutrients, for both quality and safety concerns in addition to regulatory label-claim requirements, is imperative for food manufacturers and processors. Analytical testing is performed to monitor raw materials for elemental contaminants before use and to corroborate the micronutrient content of the final juice product.

The generated analytical data, in combination with statistical analysis, helps optimize nutrient yield or productivity wherever possible, highlighting the need for an accurate and precise analysis.

For multi-element analyses, ICP-OES is typically preferred. However, a flame atomic absorption (AA) system is also useful due to its speed, ease of use, and cost effectiveness. The drawback is the requirement to analyze each sample individually for each element, thus affecting sample throughput..

The use of a fast, high-throughput sample automation system can overcome this issue by reducing the analysis time per sample significantly despite analyzing the samples multiple times. In this way, higher sample throughput is achieved than with manual sample introduction.

Moreover, the use of an automated sample introduction system improves the accuracy of the analysis while allowing the chemist to concentrate on other tasks. This article discusses the micronutrient analysis of different commercial juice products by means of flame AA equipped with a high-throughput sample automation system.

Experimental Procedure

Samples and Sample Preparation

The juice samples analyzed in this work were prepared from 100% juice, including two different varieties of grape juice, two different brands of orange juice and apple juice, a vegetable-fruit juice blend, and a pomegranate juice.

The analytical elements of interest are representative of micronutrients typically listed on product labels. Minimal sample preparation was required, only involving acidifying the juices with nitric acid.  After splitting the samples, spiking of the elements of interest was performed to obtain a set of the split samples.

Instrumental Conditions

A PerkinElmer PinAAcle™ 900T atomic absorption spectrometer operating in flame mode in conjunction with a FAST Flame 2 sample automation accessory was used to perform all analyses. Table 1 lists the elements of interest and instrument conditions used for juice sample analyses. Sample introduction components consisted of a high-sensitivity nebulizer, a 10 cm burner head, and a standard spray chamber.

Table 1. PinAAcle 900 instrument and analytical conditions

Element Cu Fe Mg Zn Mn K Na Ca
Mode Absorption Absorption Absorption Absorption Absorption Emission Emission Absorption
Wavelength (nm) 324.75 248.33 285.21 213.86 279.48 766.49 589.00 422.67
Slit (nm) 0.7 0.2 0.7 0.7 0.2 0.2 0.2 0.7
Acetylene Flow (L/min) 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.7
Air Flow (L/min) 10 10 10 10 10 10 10 10
Burner Head Rotation 0 ° 0 ° 45 ° 0 ° 0 ° 45 ° 45 ° 45 °
Acquisition Time (sec) 1 1 1 1 1 1 1 1
Replicates 3 3 3 3 3 3 3 3
Sample Flow Rate (mL/min) 6 6 6 6 6 6 6 6
Intermediate Standard (mg/L) 1 5 20 2 1 200 200 100
Auto-Diluted Calibration Standards (mg/L) 0.05
Calibration Curve Type Non-Linear Through Zero Non-Linear Through Zero Non-Linear Through Zero Non-Linear Through Zero Non-Linear Through Zero Non-Linear Through Zero Non-Linear Through Zero Non-Linear Through Zero

A single intermediate standard prepared in 2% HNO3/deionized water was used to perform external calibrations. The dilution of the single intermediate standard was performed using the in-line dilution capabilities of the FAST Flame 2 accessory. The addition of La2O3 to the standards, samples, and diluents at a concentration of 0.5% by weight controlled ionization during the analysis of potassium (K), sodium (Na), and calcium (Ca).

The FAST Flame 2 accessory features a switching valve, peristaltic pump, and high-speed autosampler, achieving quick sample turnaround with no sample-to-sample memory effect, short signal stabilization times, and fast rinse-out.

A sample loop is rapidly filled by vacuum, and the sample is then injected while the autosampler moves to the next sample. This scheme eliminates the time delay associated with peristaltic pumping or self-aspiration and removes the lengthy rinse-in and rinse-out times associated with autosampler movement and flushing, thus lowering complete sample-to-sample analytical times to 15 seconds.

The mechanical pumping ability of the FAST Flame 2 accessory for sample injection eliminates deviations caused by changes in tubing length, sample viscosity and dissolved solids.

The in-line dilution capability of the FAST Flame 2 accessory enables automated generation of all required calibration standards, requiring the analyst to prepare only a single intermediate standard.

Moreover, QC over-range samples can be identified with the FAST Flame 2 accessory. This is followed by automated sample rerun for QC over-range samples at an increased dilution factor using the in-line dilution capability of the accessory in order to bring the signal within the calibration range. This way, accurate measurements are ensured, while allowing a successful QC check.

Experimental Results

Here, a single intermediate standard was used to create the calibration curves for individual elements, with the corresponding calibration results summarized in Table 2. The calibration standards show excellent correlation, demonstrating the advantage of the automatic in-line sample and standard dilution capabilities of the FAST Flame 2 accessory. From the independent calibration verification recoveries, the validity of the calibration and the accuracy of the standards created through the dilution system are ensured.

Table 2. Calibration results

Element Correlation Coefficient ICV Concentration (mg/L) Measured ICV (mg/L) ICV (% Recovery)
Cu 0.99999 0.500 0.508 102
Fe 0.99997 2.50 2.56 102
Mg 0.99998 10.0 10.3 103
Mn 0.99961 0.500 0.503 101
Zn 0.99954 1.00 1.00 100
K 0.99900 100 91.8 91.8
Na 0.99979 20.0 20.8 104
Ca 0.99998 50.0 47.4 94.8

Figure 1 depicts the analytical results of the juice samples, showing a relatively consistent elemental concentration with a few exceptions. The Ca concentration in Orange Juice B labelled as "Calcium Fortified" showed the highest calcium concentration, in line with the label claim.

For all juice samples, K and Mg levels are consistent, but Na levels vary significantly among the juice samples, with the fruit/vegetable juice blend having the highest concentration.   In addition, Mn concentration is also higher in the vegetable-fruit juice blend, as well as in the two grape juices, than the other samples.

Results from analyses of juice samples

Figure 1. Results from analyses of juice samples

This elemental distribution shows the significance of monitoring and quantifying these micronutrients in order to corroborate product quality and labeling accuracy. Due to the differences in concentrations between the elements and juices, different dilution factors were used. The FAST Flame accessory automatically determined and performed the dilution factors (Table 3) in-line.

Table 3. In-line dilution factors

Sample Cu Fe Mg Mn Zn K Na Ca
Apple A 2 2 5 2 2 30 2 3
Apple B 2 2 5 2 2 30 2 3
White Grape 2 2 5 3 2 30 2 5
Concord Grape 2 2 5 5 2 30 2 5
Orange A 2 2 10 2 2 30 2 3
Orange B 2 2 10 2 2 30 2 20
Fruit-Vegetable 2 2 8 3 2 30 4 3
Pomegranate 2 2 8 2 2 30 2 3

Spiking of samples with all elements at the levels presented in Table 4 was performed to determine any potential matrix effects from the different juices. Figure 2 depicts the corresponding spike recoveries, which were within 10% of the estimated values for all elements, with the exceptions of potassium in one of the grape and one of the orange juices where K recovered between 110-120%.

Per-sample matrix matching was not required for the recoveries. Two recovery values were beyond 110% for K (Concorde Grape and Orange B) due to the spike levels of 91.9 and 95.1 mg/kg, respectively, which are considerably less than the actual K concentrations in the samples.

Table 4. Pre-digestion spike levels (all units in mg/kg)

Sample Cu Fe Mg Mn Zn K Na Ca
Apple A 0.494 0.494 4.94 0.494 0.494 94.1 94.1 37.7
Apple B 0.508 0.508 5.08 0.508 0.508 92.0 92.0 36.8
White Grape 0.500 0.500 5.00 0.500 0.500 90.4 90.4 36.2
Concord Grape 0.475 0.475 4.75 0.475 0.475 91.9 91.9 36.8
Orange A 0.502 0.502 5.02 0.502 0.502 93.2 93.2 37.3
Orange B 0.484 0.484 4.84 0.484 0.484 95.1 95.1 38.0
Fruit-Vegetable 0.486 0.486 4.86 0.486 0.486 89.1 89.1 35.6
Pomegranate 0.479 0.479 4.79 0.479 0.479 95.8 95.8 38.3

The spike concentrations were not ideal in all cases as they were established before the analyses. However, remarkable recoveries were observed. Due to the presence of very high Ca level in Orange B, its Ca spike recovery was not reported here.

All other samples and elements reported to have accurate results with good spike recovery as a result of simple spiking and rapid sampling with minimal labor and little or no sample preparation.

Spike recoveries in the juice samples.

Figure 2. Spike recoveries in the juice samples.

The use of the FAST Flame accessory minimizes human error during standard creation by reducing the number of standards from one intermediate and five final standards to a single intermediate standard.

The concentration of elements of interest varied enough to fall out of the calibration curve, but the samples were automatically diluted in real time by the FAST Flame 2 accessory in order to allow the absorbances to fall within the calibration curve to produce accurate analyses. This capability also eliminates analyst interference, additional sample handling, and extensive re-prep.

The FAST Flame 2 accessory improved sample throughput by almost 4X by drastically shortening the total analytical time for each sample when compared to typical autosampler performance.

Moreover, there was a reduction in the sample turnaround time by 45 seconds without compromising the benefits of fully automated sample dilution, calibration standard preparation and sample analysis. Furthermore, the FAST Flame 2 accessory provides full automation advantages and better throughput compared to the manual operation of the AA.


The results clearly demonstrate the capability of the PinAAcle 900 AA spectrometer to perform reliable and effective analysis of fruit juice samples for elements of interests over a broad concentration range.

The combination of the FAST Flame 2 accessory and the PinAAcle 900 reduces human error during preparation of calibration standards and samples while improving laboratory throughput and productivity.

The PinAAcle 500 Flame AA spectrometer can also be used to obtain equivalent results. For smaller sample batches or in applications that require no auto-dilution, the same analyses can be performed without using a FAST Flame accessory.

This information has been sourced, reviewed and adapted from materials provided by PerkinElmer.

For more information on this source, please visit PerkinElmer.


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