Journal of Food Composition and Analysis 22 (2009) 453–462
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Original Article
Development of rice reference material and its use for evaluation of analytical performance of food analysis laboratories Prapasri Puwastien *, Kunchit Judprasong, Naruemol Pinprapai Institute of Nutrition, Mahidol University at Salaya, Putthamonthon 4, Nakhon Pathom 73170, Thailand
A R T I C L E I N F O
A B S T R A C T
Article history: Received 16 October 2007 Received in revised form 14 April 2008 Accepted 16 January 2009
Data quality is one of the major concerns in development of food composition database and to editors of many peer-reviewed journals in accepting a scientific paper for publication. Regular use of a reference material and participation in a proficiency testing programme could improve the reliability of the analytical data. The objectives of this project were to prepare rice test material with assigned values and to use it to assess the analytical performance of laboratories which are involved in research and analysis of rice. The international guidelines, ISO Guide 35, ISO 13528 and ISO Guide 43, were followed as much as possible throughout the preparation of the reference material and the laboratory performance study. Brown rice (Jasmine variety) was ground to particle size which passed completely through a sieve with pore size 250 mm and packed in laminated aluminum foil bags under vacuum. Based on the analyses of representative nutrients – moisture, protein, iron, zinc and vitamin B1 – the samples were demonstrated homogeneous. Ten expert laboratories from various countries, 36 laboratories from Thailand, and 16 laboratories from ASEAN and Asia registered for the laboratory performance study. The samples were sent for analysis of selected proximate composition (moisture, protein, dietary fibre and ash), two minerals (iron, zinc), and one labile nutrient (vitamin B1) using routine analytical methods. The assigned values of the nutrients in the test materials, as robust mean robust SD or predicted SD, were established with their uncertainties. For proximate composition, 67–87% of participating laboratories showed good analytical performance. However, many of them showed questionable and unsatisfactory performance on the analyses of dietary fibre (55%) and vitamin B1 (47%). The evaluation of the results of moisture, protein and iron with their uncertainties against the assigned values of the test material using En score was also demonstrated. Finally, the consensus values of nutrients in the rice sample as mean SD were developed from the analytical results of laboratories with good performance for both within- and between-laboratories. This test material can be used as a reference material for internal and external quality control systems to improve the quality of the analytical data. ß 2009 Elsevier Inc. All rights reserved.
Keywords: Reference material Rice Nutrients Assigned value Analytical performance Food composition
1. Introduction Reliable analytical data are required by both food analysts and data users. Standardisation of the analytical methodology and development of a quality control system in a laboratory can help ensure analytical measurement validity and increase data quality and reliability. Reference materials play key roles in the development of the internal quality control system. It is well known that different methods of nutrient analysis or the same analytical methods with some modification are being used by different laboratories, resulting in some discrepancies in the analytical data. Proficiency testing is an external quality assessment designed to
* Corresponding author. Tel.: +66 2 4410217; fax: +66 2 4419344. E-mail address:
[email protected] (P. Puwastien). 0889-1575/$ – see front matter ß 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jfca.2009.01.006
assess the laboratory analytical performance which reflects the reliability of the analytical data. It assists in increasing confidence in analyst ability in the case of good performance, or in identifying laboratories with questionable and unsatisfactory results where improvement of the competency in nutrient analysis is required. Seven rounds of laboratory performance studies were conducted by the Institute of Nutrition, Mahidol University during 1989–2003 (Puwastien and Sungpuag, 1995; Puwastien and Raroengwichit, 2000; Puwastien et al., 1989, 1999, 2001, 2003) using different test materials with consensus assigned values. Two approaches were used to develop assigned values of food components: one from expert laboratories and another from good performance laboratories who participated in laboratory performance studies. With the collaborative study among expert laboratories in Australia, New Zealand, USA, Austria, and laboratories in ASEANFOODS member countries, nine food reference
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materials with consensus values for proximate composition and some minerals were produced. These materials were rice flour (AS-FRM1) and soybean flour (AS-FRM2) (Puwastien et al., 1989); cereal-soy (AS-FRM3) and fish flour (AS-FRM4) (Puwastien and Sungpuag, 1995); weaning food (AS-FRM-5) and fish powder (ASFRM-6) (Puwastien et al., 1999a); feed (AS-FRM-7) and fish meal (AS-FRM 8) (Puwastien et al., 2001); and milk powder (AS-FRM 9) (Puwastien et al., 2003). Since 2004, the International Year of Rice, various studies on nutritive values of different varieties of rice have been conducted for research and development, generation of food composition data, and for screening and selecting plant varieties. To evaluate performance of laboratories that have analyzed rice, a laboratory proficiency study on nutrient analysis was needed. Thus two main objectives of this study were (1) to prepare a candidate reference material (RM) of rice powder and study its physical and chemical characteristics and (2) to organise a laboratory performance study using the prepared candidate RM as test material. 2. Materials and methods 2.1. Preparation of candidate reference material (RM) 2.1.1. Test material for mineral analysis Test material used was brown rice, Jasmine variety, obtained from Center of Excellence for Rice Molecular Breeding and Product Development, Kasetsart University, Thailand. Three kilograms of the test material were frozen using liquid nitrogen in order to make rice to be brittle and facilitate the grinding process and then ground in a stainless steel grinding machine (to avoid iron and zinc contamination) until the fine particles passed completely through sieve No. 60 mesh (250 mm). The sample was mixed thoroughly manually, in a humidity controlled air conditioned room and then packed under vacuum in aluminum foil bags, about 10 g each. Bags were randomly divided into 2 sets, A and B, and then labeled with sample code number. These prepared samples were used for analyses of minerals (iron, zinc) and kept in a freezer at 20 8C. 2.1.2. Test material for analyses of proximate composition and vitamin B1 Another set of the test material, 15 kg, was ground using the Cyclotec sample mill until the fine particles passed completely through sieve No. 60 mesh (250 mm). The sample was then mixed thoroughly by a rotating mixer for 5 h in a humidity controlled air conditioned room and then packed under vacuum in aluminum foil bags, about 30 g each. Bags were randomly divided into 2 sets, A and B, and then labeled with sample code number. They were used for the analysis of proximate composition and vitamin B1. The samples were kept in a freezer at 20 8C. 2.2. Characteristics of the candidate reference material 2.2.1. Particle size distribution The particle size distribution of the test material for nutrient analysis (Section 2.1.2) was manually studied by sieve analysis. One hundred gram of the test material was passed through 3 standard sieves 60, 80 and 120 mesh, with pore sizes of 250, 180 and 125 mm, respectively. Each fraction was collected, weighed and recorded. Percent distribution at each fraction was calculated. 2.2.2. Homogeneity study Ten packages (5 from set A and 5 from set B) each of the prepared sub-samples for mineral analysis and for proximate analysis were selected at random. Homogeneity of the candidate material was evaluated by analyses of selected representative nutrients, i.e. iron and zinc (representative of trace elements), moisture and protein (representatives of proximate composition)
and vitamin B1 (representative of labile nutrient). The analyses were performed in two test portions from each package, in a random order. Each analysis was performed in one setting under repeated conditions, i.e. by competent analysts, on the same day using the same set of reagents and conditions. The results were statistically evaluated. 2.2.3. Stability study Since Vitamin B1 is the most labile nutrient in rice, its stability was checked throughout the storage period. The prepared candidate reference materials were kept at 20 8C. Five packages of the prepared sub-samples were randomly selected at 1, 6 and 12 months intervals for the first year and every 6 months thereafter. At each period, single analysis of vitamin B1 by HPLC in each sample was conducted. The stability of the vitamin was evaluated by comparing the results obtained at each period with the levels analysed at 0 month (using data from homogeneity study). 2.2.4. Chemical analyses of the components in the test materials Ten expert laboratories from different countries in OCEANIA, Europe, and North America collaborated to develop assigned values of nutrients in the test material. Each laboratory registered to analyse several and none of them analysed all of the assigned components. Since the number of derived data from expert laboratories would not be a sufficient number for reliable assigned values, the better assigned values for the measurands in the test material were derived from the analytical values of both expert laboratories and the participants of the performance study according to the ISO 13528, 2005. 2.3. Laboratory performance study Following closely the ISO Guide 43 (ISO Guide 43-1, 1997), a laboratory performance study for nutrient analyses was conducted. 2.3.1. Participants Fifty-six laboratories from various countries, mainly from ASEAN, registered to participate in the performance study. However, not all laboratories registered for analyses of all assigned measurands and four of them did not submit the report. 2.3.2. Distribution of samples and documents Two packages each of 10 g test material (package A and B with random number) for analysis of minerals and 30–40 g (package A and B with random number) for analysis of other components were sent to expert laboratories and oversea participants via airmail and by post for local laboratories. Five documents – instruction to the participants, report form, uncertainty form, questionnaire for method used and questionnaire for in-house quality control system – were sent electronically as attached files with a secret laboratory code number assigned to each laboratory. 2.3.3. Analytical components and methods of analysis Participating laboratories were assigned to analyse proximate composition (moisture, protein, dietary fibre, ash), minerals (iron and zinc), and vitamin B1 using their routine test methods. They were requested to analyse vitamin B1 within two weeks of receiving the samples. Two individual values (A and B) of each component, one from each package of the test material, were requested to be reported in the report form where unit of expression and number of significant decimal places were indicated. For the first trial, the participants were requested to report values for moisture, protein and iron with their uncertainty values (expanded uncertainty with a coverage factor of k = 2).
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2.3.4. Submission of the results Laboratories were requested to submit the report and related documents within 10 weeks after receiving the samples.
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2.4.4. Evaluation of laboratory performance The analytical results of all components submitted by the participating laboratories were evaluated first for within- and then for between-laboratory variations as follows.
2.4. Statistical analysis 2.4.1. Homogeneity of test materials The data of duplicate values of moisture, protein, iron, zinc and vitamin B1 derived from 10 sub-samples of rice powder were evaluated for within-sample variation using Cochran’s maximum range test (ISO 5725, 1981) which indicated the analytical precision. To determine the homogeneity (between sample variations) of the test materials, the data were evaluated using one-way ANOVA (ISO 5725, 1981) without removing any values. The measurement uncertainty associated with the sample homogeneity was estimated for information following the method used by National Measurement Institute (NMI), Australia (NARL, 2004; NMI, 2004). 2.4.2. Stability of vitamin B1 in the rice powder The results of single analysis of vitamin B1 in 5 random samples at each storage period were evaluated against the levels obtained from the analysis at 0 month. If the values fell in the range of mean 2SD value of vitamin B1 at 0 month, the results indicated the stability of the component. A slope of the regression line (linear least square) of the values during 12 months storage was also evaluated. 2.4.3. Assignment of component values in test materials
A. Within-laboratory variation: For each pair of the results (A and B), the difference between the values was used to evaluate within-laboratory variation by calculation of robust z-score(within) based on the variation [median and Normalised Inter-Quartile Range (NIQR) NATA (1996)] within the group of participants. z-scoreðwithinÞ ¼
where x is the difference between the values of A and B from pffiffiffi each laboratory= 2; median is the median of difference between the value of A and B obtained from participating laboratories; NIQR (normalised inter-quartile range) is (Quartile 3Quartile 1) 0.7413. B. Between-laboratory variation: For each pair of results, betweenlaboratory variation was evaluated by calculation of robust z-score(between). Two approaches were applied. 2.4.4.1. Approach 1. An average value of A and B was used to evaluate between-laboratory variations. The z-score was calculated based on the assigned value, which is the robust mean robust SD, estimated from the data of participants according to the ISO 13528 (2005). z-scoreðbetweenÞ ¼
A. According to ISO 13528 (2005): The assigned values of components in the test material were developed from the analytical data obtained from 10 expert laboratories and the participants of the performance study following the statistical process of ISO 13528 (2005). The process started by removing the known extreme values due to common errors such as using unaccepted analytical methods, misplacement of the decimal points, wrong unit of expression, etc. Then several steps were conducted to modify the extreme values, if any, until the robust mean and robust standard deviation were obtained. At the final step, the standard and expanded uncertainties of the assigned value were estimated. The obtained robust mean robust SD and the expanded uncertainties are the assigned values of the components in the test material. They were used to evaluate the laboratory performance in this study by using z-score and En-score (as a trial), respectively. B. According to ISO 13528 and target standard deviation (SD) of Horwitz (Horwitz et al., 1992): In some cases, variation of a set of analysed data obtained from various laboratories is too large. This occurs frequently for nutrients with low concentration or nutrients with complicated analytical methods. The high variation can be demonstrated by the percentage of coefficient variation (%CV) which is higher than the target values, such as %CV more than 10 for proximate composition or more than 15 for vitamins and minerals. The robust mean derived from the process of the ISO 13528 (2005) for the particular components will be used as the assigned mean value but the assigned robust SD was replaced by the target SD of Horwitz based on the robust mean value. Horwitz0 s Predicted Relative Standard Deviation or RSDp ¼ 210:5 log C where C = fraction concentration of the mean value of the component to be evaluated.
ðx medianÞ NIQR
ðx robust meanÞ robust SD
where x is average value of reported A and B of a nutrient per 100 g, obtained from each participating laboratory; Robust mean is the assigned value of the nutrient per 100 g according to ISO 13528; Robust SD is the standard deviation of the robust mean value according to ISO 13528. 2.4.4.2. Approach 2. In some cases, variation of a set of analysed data obtained from various laboratories was too large. Laboratory performance on the analysis of the particular components, i.e. dietary fibre, iron and vitamin B1, with large variance was evaluated based on the assigned robust mean of the reported values and the predicted SD obtained from Horwitz equation (ISO Guide 43-1, 1997). C. Estimation of En score (NARL, 2004): In this performance study, a trial on use of En score to evaluate the laboratory performance was also conducted on analyses of moisture, protein and iron. The En score was calculated as follows. xlab xref En ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 þ U2 Þ ðUlab ref where xlab is the mean of the results submitted by participants, xref is the robust mean of the assigned value derived from ISO 13528 (2005), Ulab is the expanded uncertainty of xlab and Uref is the expanded uncertainty of xref derived from ISO 13528 (2005). 2.5. Interpretation of laboratory performance study 2.5.1. Z-scores Results with an absolute z-score 2 were satisfactory. Values with the absolute z-score 2 < jz-scorej < 3 were identified as questionable results. Values with the absolute z-score 3 were identified as unsatisfactory values. These criteria were applied for
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both within- and between-laboratory variation. Absolute z-score
Interpretation
jzj 2 2 < jzj < 3 jzj 3
Satisfactory result Questionable result Unsatisfactory result (presented as extreme values)
An absolute En score of 1 indicates that the reported results and assigned values are in agreement (within their respective uncertainties). An absolute En score of >1 indicates that the reported results are different from the assigned value and that the uncertainty associated with the results has been understated. In this study, the En score was calculated and presented for information only. The values have not yet been included in the evaluation process of the laboratory performance. Fig. 1. Pattern of changes of vitamin B1 in sub-samples of rice flour test materials during one-year storage at 20 8C.
3. Results and discussion 3.1. Rice flour preparation Since iron and zinc were included as the target measurands, the grinder should be free from these minerals. Using the Cyclotec sample mill resulted in rice flour with uneven distribution of iron. A stainless steel grinder (with limited capacity) which provided homogenous distribution of iron and zinc was therefore used. To facilitate the grinding process due to the hard core of the rice, liquid nitrogen was used. The Cyclotec sample mill which has high speed and capacity is a proper instrument for preparation of rice flour to be used as test materials for other nutrient analyses.
Between-sample variation, which used to indicate sample homogeneity, was evaluated using the duplicate results of each representative nutrient derived from 10 packages. The F-values from ANOVA for all components in the prepared test materials were lower than the critical F-value. The results indicated that the sub-samples were considered sufficiently homogeneous to be used as test materials for laboratory performance study. For each of the analysed nutrients, an estimation of uncertainty associated with homogeneity was made following the method of NMI, Australia (NARL, 2004; NMI, 2004). A summary of homogeneity test results and statistical treatment including the uncertainty values is shown in Table 1.
3.2. Characteristics of the test material (candidate RM) 3.2.1. Particle size distribution of rice flour The prepared rice powder passed completely through 60 mesh sieve (
