Insights into Analytical Precision: Understanding the Factors Influencing Accurate Vitamin A Determination in Various Samples
Abstract
:1. Introduction
- Historical progress in vitamin A analysis techniques.
- Quantitative vitamin A analysis: diverse analytical approaches.
- Deciphering the factors: unveiling the complexities of analytical precision.
- The crucial role of quality control: navigating the path to reliable results.
- Reflection and future prospects: charting the course for enhanced analytical precision.
2. Historical Progress in Vitamin A Analysis Techniques
3. Quantitative Vitamin A Analysis: Diverse Analytical Approaches
3.1. Colorimetric Assays
- The Carr and Price assay: This method involves the quantitative evaluation of retinol utilizing antimony trichloride (SbCl3) as a crucial component [43].
- Trifluoroacetic acid-based colorimetric determination: This technique relies on the interaction of a vitamin A solution in food or feed materials with several Lewis acids, resulting in the transient manifestation of a blue color [41].
3.2. Spectrophotometric Analyses
3.3. Chromatographic Techniques
- a.
- High-performance liquid chromatography (HPLC)
- b.
- Gas–liquid chromatography (GLC)
- c.
- Liquid–liquid chromatography (LLC)
- d.
- Waters UltraPerformance Convergence Chromatography (UPC)
- e.
- Ultra-high-performance liquid chromatography–tandem triple quadrupole mass spectrometry (UHPLC-MS/MS)
3.4. Nuclear Magnetic Resonance (NMR) Spectroscopy
3.5. Near-Infrared Spectroscopy (NIRS)
3.6. Enzyme-Linked Immunosorbent Assays (ELISAs) for Biological Tissues
4. Deciphering the Factors: Unveiling the Complexities of Analytical Precision
- Source of vitamin A: The susceptibility of various sources or commercial products of vitamin A to degradation can vary significantly due to differences in their formulation [94] (Figure 2). Factors such as light, oxygen, temperature, and moisture play crucial roles in the degradation process. Consequently, these variations can potentially influence the analytical outcomes, even if the initial activity of multiple vitamin A sources in an identical premix composition is similar. Furthermore, repeatability in retinol analysis is influenced by the physical properties of the vitamin A source (beadlet) utilized during the production of the premix or feed [8]. It is inversely correlated with the concentration of vitamin A present in the sample.
- 2.
- Type of sample: Different types of samples, such as premix, feed, blood, or other tissues, may necessitate distinct analytical methodologies [43].
- 3.
- Quality of the sample: The accuracy of analytical procedures can be significantly impacted by the quality of the sample. Contaminants or interfering substances within the sample can exert substantial influence on the physicochemical processes utilized during analysis [23].
- 4.
- Representativeness of the sample: Ensuring a representative sample is imperative. Ideally, the laboratory should only determine the amount of vitamin A present in the sample. If the sample does not accurately reflect the entire batch, the precision achieved is rendered ineffective.
- 5.
- Method of analysis: The precision of the outcomes can be influenced by the analytical approach employed [95]. Various methodologies may exhibit varied sensitivities to distinct configurations of vitamin A [23]. Furthermore, variations in the adherence of analysts to established and sanctioned protocols within a specific methodology may also exert an influence [96].
- 6.
- Laboratory: An empirical analysis reveals that the discrepancy in the precision of vitamin A analysis among different laboratories surpasses the variation attributed to differences in analytical methods [96]. Certain techniques or procedures can significantly contribute to substantial interlaboratory variation [96]. Examples of such techniques include the inconsistent reporting or calculation of results, particularly when comparing retinol palmitate with retinyl acetate. Furthermore, modifications made to the vitamin A analysis procedure, which lack validation through rigorous interlaboratory collaborative studies or statistically sound within-laboratory comparisons with validated test methods, can also be a source of significant variability. Additionally, within-laboratory sampling techniques may further compound this issue.
- 7.
- Storage conditions: The stability of vitamin A is known to be influenced by various storage conditions, including temperature, light exposure, and oxygen levels [97]. The improper storage of laboratory samples under such conditions can significantly impact the precision and reliability of the analysis.
- 8.
- Target tissue cellularity, integrity, and function (for biological tissues): Vitamin A status is characterized by the cellular structure, integrity, and functional capabilities of the target tissues. Unlike some biochemical indicators, any compromise in these aspects may require several weeks of restoration following vitamin A repletion or depletion [98].
- 9.
- Sample preparation approaches: It is crucial to emphasize the importance of obtaining an adequately sized initial sample for the evaluation. Moreover, it is essential to refrain from presuming uniform dispersion of vitamin A throughout the sample during the analysis [11]. Following the grinding process, it is imperative to ensure comprehensive remixing of the ground sample and repeat this process before proceeding with the weighing of a test portion [11].
- 10.
- Sample quantity for analysis: The precision of the chemical analysis of vitamin A in feed or premix samples is significantly affected by the weight of the sample. Dry vitamin A supplements are composed of beadlets (Figure 3 and Table 2) that contain multiple units of retinyl acetate [99]. When assessing a small sample of the feed, there might be a limited number of particles per sample [100]. A recent study by Inerowicz et al. [8] indicated that the relative standard deviations for vitamin A determinations in feed varied between 10.5–24.7% and 2.26–10.7% for sample sizes of 10 g and 100 g, respectively (Table 3). The findings of the study suggest that the mass of the sample can considerably influence the accuracy of vitamin A testing in animal feed materials.
- 11.
- Analytical standards as benchmarks for the identification and quantification of retinol: The variability in the purity of these standards is a critical factor contributing to the observed inconsistencies among laboratories engaged in vitamin A analysis. In the comparison with the recognized US Pharmacopeia (USP) standard retinyl acetate, varying standards often display significant disparities in measurements, with values fluctuating between 50% and 140% of the officially stated value [11]. Regrettably, certain laboratories fail to validate the vitamin A content of the reference materials and exhibit insufficient quality control protocols for their analytical methods [96]. Laboratories exhibiting exemplary accuracy and precision continuously validate reference materials and incorporate in-house quality control samples, employing robust statistical methodologies to ensure and confirm the reliability of their results [96].
- 12.
- Extraction during analytical procedure: In certain instances, the presence of significant quantities of carotenoids following hydrolysis in the solution, coupled with a low concentration of vitamin A, might necessitate the implementation of multiple extraction procedures [102]. In the context of high-fat samples, the formation of extra soaps during the saponification process has the potential to influence the partition coefficient, thereby favoring the aqueous alcohol phase. Consequently, in such scenarios, it becomes imperative to conduct multiple extractions to ensure the efficient separation of retinol into the solvent [11]. According to Moore et al. [96], the primary cause of variation in retinol analysis in feed among various laboratories is, in fact, the vitamin extraction procedure.
- 13.
- Evaporation in the analytical phase: During the process of solvent evaporation, the thermal degradation of retinol solutions can occur, particularly at temperatures exceeding 40 degrees Celsius [11]. Thus, it is vital to control and maintain the temperature below this threshold to prevent the degradation of retinol. Additionally, it is essential to minimize the exposure of the retinol residues to ambient air, as this could potentially compromise the stability of the solution [11].
- 14.
- Other factors: During the analytical process, other factors, such as the isomerization of all-trans retinol, quality control protocols, precise equipment calibration, potential human errors, systematic and bias errors, and various other influences, could potentially impact the final analytical results [11].
5. The Crucial Role of Quality Control: Navigating the Path to Reliable Results
5.1. The Pivotal Role of Quality Control
5.2. Implementing Stringent Protocols and Standard Operating Procedures
5.3. Navigating the Challenges of Consistency and Accuracy
6. Reflection and Future Prospects: Charting the Course for Enhanced Analytical Precision
7. Conclusions
- The accurate determination of vitamin A is crucial for animal health and product quality.
- Historical advancements in analysis techniques have evolved from basic methods to sophisticated chromatographic and spectroscopic approaches, improving precision and sensitivity.
- Various factors, including sample quality, the method of analysis, and storage conditions, significantly impact analytical precision in retinol determination, necessitating a comprehensive understanding and careful consideration.
- Emphasizing the critical role of quality control through stringent protocols and regular proficiency testing is essential for ensuring consistent and reliable results.
- Future progress in analytical precision lies in the integration of advanced technologies, such as miniaturized devices and data-driven approaches, promising to overcome current challenges and enhance accuracy in vitamin A analysis.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
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Ascertained Level (c), IU/kg | Relative Leeway | Absolute Leeway | Extrapolated Leeway |
---|---|---|---|
2000–<3720 | - | - | 2.1696·c0.8495 IU |
3720–<7800 | - | - | 2340 IU |
7800–<100,000 | 30% | - | - |
100,000–<125,000 | - | 30,000 IU | - |
125,000–<375,000 | 24% | - | - |
375,000–<450,000 | - | 90,000 IU | - |
450,000–<1,020,000 | 20% | - | - |
1,020,000–<7,570,000 | - | - | 20% |
7,570,000–≤460,000,000 | - | - | 2.1696·c0.8495 IU |
>460,000,000 | - | - | 2309·c0.5 IU |
Vitamin A Source | Initial Mass, g | Density, g/cm3 @ 21.9 °C c | Number of Particles Measured | Particle Size Measurements a,b | ||||
---|---|---|---|---|---|---|---|---|
Average, mm | Median, mm | Minimum, mm | Maximum, mm | SD | ||||
1 | 221.0 | 0.60 | 2074 a | 0.466 | 0.456 | 0.065 | 1.179 | 0.156 |
2 | 109.5 | 0.63 | 2415 b | 0.333 | 0.323 | 0.047 | 0.738 | 0.102 |
Sample | Vitamin A, IU/kg | |||||
---|---|---|---|---|---|---|
Poultry Feed (Conditioner) | Poultry Feed (Texturized) | Mineral Mix | ||||
Quantity, g | 10 | 100 | 10 | 100 | 10 | 100 |
1 | 6112 | 5898 | 20,875 | 24,476 | 164,762 | 176,587 |
2 | 5230 | 5748 | 18,851 | 18,443 | 163,719 | 171,192 |
3 | 5352 | 5654 | 24,575 | 21,794 | 184,971 | 173,370 |
4 | 4875 | 5779 | 15,140 | 22,853 | 176,246 | 177,037 |
5 | 6736 | 6223 | 23,810 | 19,640 | 180,409 | 168,987 |
6 | 7801 | 6346 | 22,685 | 19,642 | 203,235 | 180,078 |
7 | 6575 | 6430 | 34,162 | 16,716 | 138,778 | 173,772 |
8 | 7294 | 5923 | 26,550 | 19,186 | 184,375 | 180,673 |
9 | 6818 | 4926 | 22,687 | 23,999 | 170,451 | 170,817 |
10 | 5768 | 5490 | 18,112 | 19,503 | 151,056 | 171,569 |
11 | 5682 | 5153 | 25,915 | 21,724 | 185,745 | 180,100 |
12 | 4646 | 5283 | 31,337 | 18,976 | 168,742 | 181,044 |
13 | 6904 | 6181 | 22,925 | 19,556 | 190,880 | 170,998 |
14 | 5907 | 5228 | 28,815 | 18,182 | 205,806 | 177,503 |
15 | 5746 | 5870 | 16,339 | 20,145 | 183,401 | 177,366 |
16 | 5389 | 5400 | 14,127 | 22,279 | 204,112 | 175,273 |
Average 1 | 6052 | 5721 | 22,930 | 20,450 | 178,500 | 175,400 |
SD | 893 | 448 | 5673 | 2181 | 18,670 | 3972 |
RSD, % | 14.8 | 7.82 | 24.7 | 10.7 | 10.5 | 2.26 |
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Shastak, Y.; Pelletier, W.; Kuntz, A. Insights into Analytical Precision: Understanding the Factors Influencing Accurate Vitamin A Determination in Various Samples. Analytica 2024, 5, 54-73. https://doi.org/10.3390/analytica5010004
Shastak Y, Pelletier W, Kuntz A. Insights into Analytical Precision: Understanding the Factors Influencing Accurate Vitamin A Determination in Various Samples. Analytica. 2024; 5(1):54-73. https://doi.org/10.3390/analytica5010004
Chicago/Turabian StyleShastak, Yauheni, Wolf Pelletier, and Andrea Kuntz. 2024. "Insights into Analytical Precision: Understanding the Factors Influencing Accurate Vitamin A Determination in Various Samples" Analytica 5, no. 1: 54-73. https://doi.org/10.3390/analytica5010004