AOAC Food Authenticity SMPRs (TT & NTT)

AOAC INTERNATIONAL Food Authenticity/Fraud Program

Standard Method Performance Requirements (SMPR)

(Targeted & Non-Targeted Testing) February 2020

AOAC INTERNATIONAL 2275 Research Blvd., Suite 300 Rockville, MD, 20850

UNITED STATES dboyd@aoac.org

AOAC SMPR 2020.XXX; Draft AOAC Standard Method Performance Requirements (SMPRs) for 1 Targeted Testing (TT) of formaline/formaldehyde, starch, soy protein as Adulterants for Evaluation of 2 Liquid Raw Bovine Milk; Version 3; February 13, 2020

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Intended Use 5 AOACI SMPRs ® describe the minimum recommended performance characteristics to be used during 6 the evaluation of a method. The evaluation may be an on-site verification, a single-laboratory 7 validation, or a multi-site collaborative study. 8 9 SMPRs are written and adopted by AOACI using the consensus of stakeholders representing the 10 industry, government, and academic and/or research institutions. AOACI SMPRs are used by AOACI 11 expert review panels (ERPs) in their evaluation of validation study data for method being considered 12 for Performance Tested Methods SM or AOACI Official Methods of Analysis SM and can be used as 13 acceptance criteria for verification at user laboratories.

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1. Applicability

This document contains assessment parameters on the performance of Targeted Testing (TT) methods to monitor liquid raw bovine milk for the detected presence of Economically Motivated Adulterants (EMAs) such as formaline/formaldehyde, starch and soy protein.

2. Analytical Technique

A targeted method to be used to detect, identify and quantify liquid raw bovine milk for the detected presence of Economically Motivated Adulterants (EMAs) such as formaline/formaldehyde,

starch and soy protein.

Any method capable of detecting, identifying the presence of the defined adulterants and quantifying the amount (proportion/concentration) present in the food item will be considered.

The scope of the TT method will be defined by the authentic samples and or reference standard

material (if available) used in validating the method.

3. Definitions

Applicability Statement — a general statement about the intended purpose and scope of the method entailing key aspects of expected achievements for the specific situation and circumstances. Key points to cover are the intended matrix, the purpose, and an indication of sensitivity, selectivity,

enforcement and action levels where available.

Authentic Samples — Samples representative of the genuine commodity. Ideally these samples should represent the food’s or ingredient’s variability seen naturally in the commodity. The authentic samples and or reference standard materials used to validate the method will be used to

properly define the TT method testing scope.

Economically Motivated Adulteration —The fraudulent addition of non-authentic substances or removal or replacement of authentic substances without the purchaser’s knowledge for economic

gain of the seller.

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Single Laboratory Validation (SLV) — Demonstration by one laboratory of method performance on

samples described in Table 1.

Multi-laboratory Validation (MLV) — Demonstration between laboratories using adulterated samples created by a third-party group and supplied blindly to the participating laboratories.

4. Method Performance Requirements

(Table 1: Method Performance Requirements for formaline/formaldehyde in raw bovine milk)

Analytical Parameter

Acceptance Criteria 10 – 400 μg/L (ppb)

Analytical Range (μg/L [ppb])

LOQ

≥ 10 ppb 80 – 120 %

Recovery

NOTES: 1. A colorimetric method of 1906 vintage (Hehner’s Test) which was modified by Richmond and Boseley was claimed to be able to easily detect 1 part of formaldehyde in 200,000 parts of milk (i.e 5 x 10 -6 [5ppm]); but the test’s response is enhanced by casein, lactoalbumin, and vanillin (all milk components). Test is therefore not selective to formaldehyde alone. SF Acree; J Biol Chem. (1906), v2:145 -148 (Ref A). 2. A recent HPLC method with UV detection validated as per ISO 17025 claims to be able to detect formaldehyde residues in milk over an analytical range of 0.010 to 0.40 ppm (10 – 400 ppb) with an LOQ of 0.020 ppm (200 ppb); Flavia Borges de Freitas Rezende et al. Microchemical Journal 2017 vol 134 pp 383-389 (Ref B) 3. Three recently published methods using mid IR, direct infusion MS, and/or FTIR were all able to readily detect and quantify formaldehyde fortified to milk at 0.074 g/L (74 ppm). Gondim, CDS et al., Food Chem 2017, v230 pp 68 -75 (Ref D); Tatiane Meline Guer reiro et al., Food Research International, volume 108 pp 498- 504 (2018) (Ref E); Habib Asseiss Neto et al., BioData Mining (2019) volume 12 p13-? (Ref F) 4. I recommend an analytical range of 10 - 400 ppb for formaldehyde residues in bovine milk 5. Reference to authentic/reference standards (whenever available) 54 (Table 2: Method Performance Requirements for starch in raw bovine milk) 55 Analytical Parameter Acceptance Criteria Analytical Range (ppm) 1 - 10 LOQ ≥ 1 Recovery 80 – 120 % Accuracy ± 20% NOTES: Reference publications D and E were both able to readily measure 5 g/L (5 ppm) of starch in milk. Recommend we peg the analytical range to 1- 10 ppm as agreed upon in our last meeting 56 (Table 3: Method Performance Requirements for soy protein in raw bovine milk) 57 Analytical Parameter Acceptance Criteria Analytical Range (ppm) 1 - 5 LOQ ≥ 1 Recovery 80 – 120 % Accuracy ± 20 %

NOTES: We don’t have a recent reference publication for the analytical range, but we can leave it at 1- 5 ppm as agreed upon 58 5. System Suitability Tests and/or Analytical Quality Control 59 Suitable methods will include blanks, and appropriate check standards. 60 6. Reference Materials 61 A detailed description of the process used to obtain and evaluate authentic/reference standard 62 materials (sources), and of the test protocol used for validating the method must be provided. 63 7. Validation Guidance 64 a. Data demonstrating method performance is required.

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b. Samples: Complete documentation for the collection and use of authentic samples must be supplied by the method authors. The scope of “authentic” samples used to validate the method must be applicable to the defined scope of the TT method. Expansion of the scope is possible with the inclusion of additional authentic samples and abbreviated validation using the protocol

listed in this SMPR.

c. For single lab validation studies, the method will be evaluated using prescribed adulterated materials as shown in Table 1. Methods approved at this level will proceed to a second level of evaluation (multi-laboratory) where blinded samples containing unknown adulterants will be

sent to participating laboratories.

d. Statistical analysis of interlaboratory studies. Sample size needed to meet performance

requirement on proportion.

8. Maximum Time-to-Results

None.

AOAC SMPR 2020.XXX; Draft AOAC Standard Method Performance Requirements (SMPRs) for 1 Targeted Testing (TT) of Other Vegetable Oils and Low-Quality Olive Oils as Adulterants for Evaluation 2 of Extra Virgin Olive Oil (EVOO); Version 3; February 13, 2020 5 AOACI SMPRs ® describe the minimum recommended performance characteristics to be used during 6 the evaluation of a method. The evaluation may be an on-site verification, a single-laboratory 7 validation, or a multi-site collaborative study. 8 9 SMPRs are written and adopted by AOACI using the consensus of stakeholders representing the 10 industry, government, and academic and/or research institutions. AOACI SMPRs are used by AOACI 11 expert review panels (ERPs) in their evaluation of validation study data for method being considered 12 for Performance Tested Methods SM or AOACI Official Methods of Analysis SM and can be used as 13 acceptance criteria for verification at user laboratories. 3 4 Intended Use

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1. Applicability

This document contains assessment parameters on the performance of Targeted Testing (TT) methods to monitor extra virgin olive oil (EVOO) for the detected presence of Economically Motivated Adulterants (EMAs) such as other vegetable oils and low-quality olive oils.

2. Analytical Technique

A targeted method to be used to detect, identify and quantify EVOO for possible EMAs such as other

vegetable oils and low-quality olive oils.

Any method capable of detecting, identifying the presence of the defined adulterants and quantifying the amount (proportion/concentration) present in the food item will be considered.

The scope of the TT method will be defined by the authentic samples and or reference standard

material (if available) used in validating the method.

3. Definitions

Applicability Statement — a general statement about the intended purpose and scope of the method entailing key aspects of expected achievements for the specific situation and circumstances. Key points to cover are the intended matrix, the purpose, and an indication of sensitivity, selectivity,

enforcement and action levels where available.

Authentic Samples — Samples representative of the genuine commodity. Ideally these samples should represent the food’s or ingredient’s variability seen naturally in the commodity. The authentic samples and or reference standard materials used to validate the method will be used to

properly define the TT method testing scope.

Economically Motivated Adulteration —The fraudulent addition of non-authentic substances or removal or replacement of authentic substances without the purchaser's knowledge for economic

gain of the seller.

False Origin — Extra Virgin Olive Oil containing mislabelled geographic and botanical sources.

Authentic EVOO — Type(s) of EVOO used to validate the method. The method’s scope of authenticity is defined by the EVOO(s) used in validating the methods

Single Laboratory Validation (SLV) — Demonstration by one laboratory of method performance on

samples described in Table 1.

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Multi-laboratory Validation (MLV) — Demonstration between laboratories using adulterated samples created by a third-party group and supplied blindly to the participating laboratories.

4. Method Performance Requirements

(Table 1: Method Performance Requirements for Other Vegetable Oils in EVOO)

Analytical Parameter Analytical Range (%)

Acceptance Criteria 10 – 50% OF EVOO

LOQ

≥ 10 %

Recovery Accuracy

80 – 120 %

± 20%

NOTES: At least 2 recent publications report fortifying EVOO with between 10 and 50 % of other vegetable oils and demonstrating by Raman, UV-VIS and IMS Technology that it is possible to detect adulteration and quantify them to well characterized % of adulteration. For soybean oil adulteration, it was demonstrated through ESI-MS that adulterations over the 1% to 90% range were easily detectable and quantifiable to as low as 1% fortification In one study for soybean adulteration, soybean edible oil in different concentrations (10, 50, 100, 150, 200, 250 and 300 g/kg) were added to EVOO corresponding to 1, 5, 10, 15, 20, 25 and 30 % adulteration, resp. Detection of adulteration (sunflower oil) in extra virgin olive oils by using UV-IMS and chemometric analysis. Food Control, Volume 85, March 2018, Pages 292-299. Rocío Garrido-Delgado, Ma. Eugenia Muñoz-Pérez, Lourdes Arce. https://doi.org/10.1016/j.foodcont.2017.10.012 Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil (hazelnut oil) using mid infrared and Raman spectroscopic data. Food Chemistry, Volume 217, 15 February 2017, Pages 735-742. Konstantia Georgouli, Jesus Martinez Del Rincon, Anastasios Koidis. https://doi.org/10.1016/j.foodchem.2016.09.011 Rapid methodology via mass spectrometry to quantify addition of soybean oil in extra virgin olive oil: A comparison with traditional methods adopted by food industry to identify fraud Food Research International, Volume 102, December 2017, Pages 43-50. Roberta da Silveira, Julianna Matias Vágula, Ingrid de Lima Figueiredo, Thiago Claus, … Jesui Vergilio Visentainer https://doi.org/10.1016/j.foodres.2017.09.076 Comparative chemometric analysis of fluorescence and near infrared spectroscopies for authenticity confirmation and geographical origin of Argentinean extra virgin olive oils. Food Control, Volume 96, February 2019, Pages 22-28. Ana M. Jiménez-Carvelo, Valeria A. Lozano, Alejandro C. Olivieri. https://doi.org/10.1016/j.foodcont.2018.08.024 Multivariate modeling for detecting adulteration of extra virgin olive oil with soybean oil using fluorescence and UV–Vis spectroscopies: A preliminary approach. LWT - Food Science and Technology, Volume 85, Part A, November 2017, Pages 9-15. Karla Danielle Tavares Melo Milanez, Thiago César Araújo Nóbrega, Danielle Silva Nascimento, Matías Insausti, … Márcio José Coelho Pontes https://doi.org/10.1016/j.lwt.2017.06.060 Detection of olive oil adulteration with waste cooking oil via Raman spectroscopy combined with iPLS and SiPLS. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, Volume 189, 15 January 2018, Pages 37-43. Yuanpeng Li, Tao Fang, Siqi Zhu, Furong Huang, … Yong Wang. https://doi.org/10.1016/j.saa.2017.06.049 59 (Table 2: Method Performance Requirements for Low-Quality Olive Oils in EVOO) 60 Analytical Parameter Acceptance Criteria Analytical Range (%) 10 – 50 % of EVOO LOQ ≥ 10% Recovery 80 – 120 % Accuracy ± 20% NOTES: Recommend we use the same analytical ranges in terms of % EVOO for low quality olive oils A comparative study of mid-infrared, UV–Visible and fluorescence spectroscopy in combination with chemometrics for the detection of adulteration of fresh olive oils with old olive oils. Food Control, Volume 105, November 2019, Pages 209-218. Oguz Uncu, Banu Ozen https://doi.org/10.1016/j.foodcont.2019.06.013

Chaotic parameters from fluorescence spectra to resolve fraudulent mixtures of fresh and expired protected designation of origin extra virgin olive oils. Talanta, Volume 195, 1 April 2019, Pages 1-7 Miguel Lastra-Mejías, Regina Aroca-Santos, Manuel Izquierdo, John C. Cancilla, … José S. Torrecilla. https://doi.org/10.1016/j.talanta.2018.10.102 61 5. System Suitability Tests and/or Analytical Quality Control 62 Suitable methods will include blanks, and appropriate check standards. 63 6. Reference Materials 64 A detailed description of the process used to obtain and evaluate authentic/reference standard 65 materials (sources), and of the test protocol used for validating the method must be provided. 66 7. Validation Guidance 67 a. Data demonstrating method performance is required. b. Samples: Complete documentation for the collection and use of authentic samples must be supplied by the method authors. The scope of “authentic” samples used to validate the method must be applicable to the defined scope of the TT method. Expansion of the scope is possible with the inclusion of additional authentic samples and abbreviated validation using the protocol

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listed in this SMPR.

c. For single lab validation studies, the method will be evaluated using prescribed adulterated materials as shown in Table 1. Methods approved at this level will proceed to a second level of evaluation (multi-laboratory) where blinded samples containing unknown adulterants will be

sent to participating laboratories.

d. Statistical analysis of interlaboratory studies. Sample size needed to meet performance

requirement on proportion.

8. Maximum Time-to-Results

None.

AOAC SMPR 2020.XXX; Draft AOAC Standard Method Performance Requirements (SMPRs) for 1 Targeted Testing (TT) of Barley and Malt Extract, Beet Sugar Syrup, Corn and Cane Sugar Syrup, C-4 2 Plant Sugar and High Fructose Corn Sugar for Adulteration of Floral and Acacia Honey ; Version 3; 3 February 13, 2020 6 AOACI SMPRs ® describe the minimum recommended performance characteristics to be used during 7 the evaluation of a method. The evaluation may be an on-site verification, a single-laboratory 8 validation, or a multi-site collaborative study. 9 10 SMPRs are written and adopted by AOACI using the consensus of stakeholders representing the 11 industry, government, and academic and/or research institutions. AOACI SMPRs are used by AOACI 12 expert review panels (ERPs) in their evaluation of validation study data for method being considered 13 for Performance Tested Methods SM or AOACI Official Methods of Analysis SM and can be used as 14 acceptance criteria for verification at user laboratories. 4 5 Intended Use

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1. Applicability

This document contains assessment parameters on the performance of Targeted Testing methods to monitor honey for the detected presence of the following Economically Motivated Adulterants (EMA) barley and malt extract, beet sugar syrup, corn and cane sugar syrup, C-4 plant sugar and

high fructose corn sugar in Floral and Acacia Honey .

2. Analytical Technique

A Targeted method to be used to monitor and enforce regulatory requirements for foods and ingredients for detected and identified EMAs. Any method capable of detecting, identifying the presence of a defined adulterating ingredient and quantifying the amount (proportion/

concentration) present in the food item will be considered.

The scope of the TT method will be defined by the available authentic honey samples used in

validating the method.

3. Definitions

Applicability Statement – a general statement about the intended purpose and scope of the method entailing key aspects of expected achievements for the specific situation and circumstances. Key points to cover are the intended matrix, the purpose, and an indication of sensitivity, selectivity,

enforcement and action levels where available

Authentic Samples – Samples representative of the genuine commodity. Ideally these samples should represent the food’s or ingredient’s variability seen naturally in the commodity. The authentic samples and/or standard reference materials used to validate the method will be used to

properly define the TT method testing scope.

Economically Motivated Adulteration – The fraudulent addition of non-authentic substances or removal or replacement of authentic substances without the purchaser's knowledge for economic

gain of the seller.

False Origin – Honeys containing mislabelled geographic and botanical sources.

Authentic Honey – The type(s) of honey used to generate the baseline fingerprint. The method’s scope of authenticity is defined by the honey(s) used in generating the baseline fingerprint.

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Single Laboratory Validation – Demonstration by one laboratory of method performance on the

validation samples described in Table 1.

Multi-laboratory Validation – Demonstration between laboratories using adulterated samples created by a third-party group and supplied blindly to the participating laboratories.

4. Method Performance Requirements

(Table 1: Method Performance Requirements for Barley and Malt extract in honey)

Analytical Parameter Analytical Range (%)

Acceptance Criteria

10 – 50% (w/w) OF EVOO

LOQ

≥ 10 %

Recovery Accuracy

80 – 120 %

± 20%

NOTES: Check for publication and analytical range

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(Table 2: Method Performance Requirements for Beet Sugar Syrup in honey)

Analytical Parameter Analytical Range (%)

Acceptance Criteria

10 – 50 (w/w) % of EVOO

LOQ

≥ 10%

Recovery Accuracy

80 – 120 %

± 20%

NOTES: Detection of honey adulteration with beet sugar using stable isotope methodology. Food Chemistry, Volume 61, Issue 3, 31 March 1998, Pages 281-286. González Mart ı́ n, E Marqués Mac ı́ as, J Sánchez Sánchez, B González Rivera. https://doi.org/10.1016/S0308-8146(97)00101-5 A usual aspect of our work involves the analysis of honey samples for later sale, following current Spanish legislation. Such analyses essentially consist of studying pollen sediments, and sensory and physicochemical analyses. With this background, it seemed appropriate to investigate possible adulterations due to the addition of sugar (beet and cane). To do this, we selected 49 samples of honey obtained from 14 floral types and used them for pollinic and sensory analyses and to detect possible adulterations due to the addition of beet sugar products (treating the oligosaccharide fraction contained in the honey with the galactose oxidase reaction) or due to corn syrup addition (with normal δ13C stable carbon isotope ratios). After classifying the samples according to the results of the pollen and sensory analyses, further assays were conducted. From the results it was concluded that 15% of the samples had been adulterated with beet sugar and 4% with cane sugar. The implementation of many analyses for each sample means that the results can be intercorrelated very well. 62 (Table 3: Method Performance Requirements for Corn and Cane Sugar Syrup in honey) 63 Analytical Parameter Acceptance Criteria Analytical Range (%) 5 – 95 % (w/w) OF SUGAR to EVOO LOQ ≥ 10 % LOD Recovery 80 – 120 % Accuracy ± 20%

NOTES: 1. Fingerprint targeted compounds in authenticity of sugarcane honey - An approach based on chromatographic and statistical data. LWT, Volume 96, October 2018, Pages 82-89. Pedro Silva, Catarina L. Silva, Rosa Perestrelo, Fernando M. Nunes, José S. Câmara. https://doi.org/10.1016/j.lwt.2018.04.076 Sugarcane honey (SCH) is a black syrup recognized by its excellent quality, being produced in Madeira Island using the regional sugarcane cultivars and following a traditional and peculiar manufacturing and storage processes. However, some low-quality commercial products have been labeled as SCH but do not respect its criteria, revealing the need of develop powerful strategies in order to detect and prevent adulterations. The knowledge of furanic derivatives (FDs) profile, produced during browning reactions that occurs during food processing and storage, emerged as a promising strategy in food quality and fraud prevention. Therefore, the aim of this study was to establish the FDs profiling of typical SCH produced by certified and non-certified producers, in different geographical regions (Madeira and Brazil), based on microextraction by packed sorbent (MEPS) combined with ultra-high performance liquid chromatography (UHPLC) as a useful approach to define its typicality and authenticity. These parameters are defined through the differentiation and discrimination of FDs profiles among other sugarcane-derived products using multivariate statistical analysis (ANOVA with post-hoc Tukey, principal components analysis, partial least square, linear discriminant analysis and hierarchical clustering). The results demonstrated that SCH samples from non-certified producers present the highest levels of FDs. In addition, SCH samples from Brazil present higher levels of FDs than samples from Madeira region. The obtained results revealed that the proposed approach is a valuable strategy to establish the typicality of SCH, ensuring its quality, authenticity, safety control and a useful support regarding the application of SCH from Madeira Island to EU certification. 2. Thermal properties of honey as affected by the addition of sugar syrup. Journal of Food Engineering, Volume 213, November 2017, Pages 69-75. Lara Sobrino-Gregorio, María Vargas, Amparo Chiralt, Isabel Escriche . https://doi.org/10.1016/j.jfoodeng.2017.02.014 Ensuring the authenticity of honey is a priority for producers and regulatory authorities. The aim of this work was to evaluate the thermal properties (using a Differential Scanning Calorimeter “DSC”) of ten types of sugar syrup, six types of honey and mixtures of sunflower honey with all these syrups at different proportions simulating the adulteration of honey (ratio honey/syrup: 80/20; 90/10; 95/05). The glass transition temperature (Tg midpoint) ranged from 60.2 °C to 67.3 °C in honey samples and from 32.8 °C to 95.8 °C in syrup samples. The differences in sugar composition of the syrups mainly affect their thermal properties. In the adulterated samples, the glass transition temperature was affected by the type of syrup, proportionally to the adulteration level. These results offer compelling evidence that the DSC can be used for the identification of addition of syrup to honey, although to be conclusive a greater number of honey types must be considered. 3. Detection of adulteration in honey samples added various sugar syrups with 13C/12C isotope ratio analysis method. Food Chemistry, Volume 138, Issues 2–3, 1 June 2013, Pages 1629-1632 , Murat Tosun https://doi.org/10.1016/j.foodchem.2012.11.068 Honey can be adulterated in various ways. One of the adulteration methods is the addition of different sugar syrups during or after honey production. Starch-based sugar syrups, high fructose corn syrup (HFCS), glucose syrup (GS) and saccharose syrups (SS), which are produced from beet or canes, can be used for adulterating honey. In this study, adulterated honey samples were prepared with the addition of HFCS, GS and SS (beet sugar) at a ratio of 0%, 10%, 20%, 40% and 50% by weight. 13C/12C analysis was conducted on these adulterated honey samples using an isotope ratio mass spectrometer in combination with an elemental analyser (EA–IRMS). As a result, adulteration using C4 sugar syrups (HFCS and GS) could be detected to a certain extent while adulteration of honey using C3 sugar syrups (beet sugar) could not be detected. Adulteration by using SS (beet sugar) still has a serious detection problem, especially in countries in which beet is used in manufacturing sugar. For this reason, practice and analysis methods are needed to meet this deficit and to detect the adulterations precisely in the studies that will be conducted. 64 (Table 4: Method Performance Requirements for C-4 Plant Sugar in honey) 65 Analytical Parameter Acceptance Criteria Analytical Range (%) 0.20 – 50% (w/w) OF EVOO LOQ ≥ 38 % LOD 0.11 % Recovery 80 – 120 % Accuracy ± 20% NOTES: 1. In-house validation for the determination of honey adulteration with plant sugars (C4) by Isotope Ratio Mass Spectrometry (IR-MS). LWT – Food Science and Technology, Volume 57, Issue 1, June 2014, Pages 9-15 . Mehmet Fatih Cengiz, M. Zeki Durak, Musa Ozturk https://doi.org/10.1016/j.lwt.2013.12.032 The objective of any analytical measurement is to obtain consistent, reliable, and accurate data. Validated analytical methods play a major role in achieving this goal. Although there have been many studies reporting about the isotopic compositions of

honeys, little has been documented regarding the validation of these methods. In this study, an Isotope Ratio Mass Spectrometry (IR-MS) method for the determination of honey adulteration was validated in-house in terms of selectivity, stability, linearity, accuracy, repeatability, sensitivity, and recovery. This study was the first attempt to describe some important method validation parameters, such as the limit of detection (LOD), limit of quantification (LOQ), and recovery for the IR-MS studies. The LOD of the method was 0.11%, and the LOQ was 0.38% based on the percent adulteration ratio. The recovery value for spiked blank honey sample with the in-house standard was 98.57%. To evaluate the usefulness of the method, 13 different brands of honey samples were collected from markets in Turkey and analyz ed. The ranges of δ13C values of analyzed honey samples and their protein fractions were from −12.87 ± 0.01 to −25.56 ± 0.08‰ and from −23.77 ± 0.09 to −25.98 ± 0.06‰, respectively. Adulteration was found in one honey sample.

66 67

(Table 5: Method Performance Requirements for High Fructose Corn Sugar in honey)

68

Analytical Parameter Analytical Range (%)

Acceptance Criteria 10 – 50 % (w/w)

LOQ

≥ 10 %

Recovery Accuracy

80 – 120 %

± 20%

NOTES: 1. Determination of high fructose corn syrup concentration in Uruguayan honey by 13 C analyses. LWT, Volume 73, November 2016, Pages 649-653. Verónica Berriel, Carlos Perdomo https://doi.org/10.1016/j.lwt.2016.07.004 The methodology of internal standard which relies on the difference between the isotopic composition in terms of δ 13 C of honey and its proteins, has been extensively used in many countries to assess honey adulteration with high fructose corn syrup (HFCS) or other C4-adulterants, but there have been no reports of such studies in Uruguay. To obtain this information, 51 honey samples were collected from different outlets in two Uruguayan regions. The δ13C com position of honey varied between −26.89 and 23.72‰, while that of its proteins ranged between −26.49 and −24.61‰. When the international value of −1.0‰ was used as the maximum accepted difference between the isotopic values of proteins and honeys, it was determined that 5.9% of samples were adulterated with HFCS, but when this limit was replaced by the locally determined threshold of 0.80‰, the proportion of adulterated samples increased to 7.8%. Both values, however, were lower than most of those reported internationally, which suggest that honey fraud is not widespread in Uruguay. 2. Detection of honey adulteration by high fructose corn syrup and maltose syrup using Raman spectroscopy . Journal of Food Compositionand Analysis, Volume 28, Issue 1, November 2012, Pages 69-74 Shuifang Li, Yang Shan, Xiangrong Zhu, Xin Zhang, Guowei Ling https://doi.org/10.1016/j.jfca.2012.07.006 Raman spectroscopy was used to detect adulterants such as high fructose corn syrup (HFCS) and maltose syrup (MS) in honey. HFCS and MS were each mixed with authentic honey samples in the following ratios: 1:10 (10%), 1:5 (20%) and 1:2.5 (40%, w/w). Adaptive iteratively reweighted penalized least squares (airPLS) was chosen to remove background of spectral data. Partial least squares-linear discriminant analysis (PLS-LDA) was used to develop a binary classification model. Classification of honey authenticity using PLS-LDA showed a total accuracy of 91.1% (authentic honey vs. adulterated honey with HFCS), 97.8% authentic honey vs. adulterated honey with MS) and 75.6% (authentic honey vs. adulterated honey with HFCS and MS), respectively. Classification of honey adulterants (e.g. HFCS or MS) using PLS-LDA gave a total accuracy of 84.4%. The results showed that Raman spectroscopy combined with PLS-LDA was a potential technique for detecting adulterants in honey. 3. Adulteration of honey with high-fructose corn syrup: Detection by different methods. Food Chemistry, Volume 48, Issue 2, 1993, Pages 209-212 . E-S. M. Abdel-Aal, H. M. Ziena, M. M. Youssef https://doi.org/10.1016/0308-8146(93)90061-J Pure honey was deliberately adulterated with high-fructose corn syrup (HFCS) at levels of 10%, 20%, 30%, 40%, and 50% (w/w). Sugar composition as a fingerprint was determined by HPLC for all samples. The following compositional properties were determined for pure and adulterated honey: moisture, total soluble solids, nitrogen, apparent viscosity, hydroxymethylfurfural (HMF), ash, sodium, calcium, potassium, proline, refractive index and diastatic activity. Statistical analysis revealed that the following compositional properties were highly significantly negatively correlated with sugar composition: dry matter, apparent viscosity, sodium, potassium, proline, and nitrogen. In contrast, ash, calcium, HMF, and moisture were highly significantly positively correlated with sugar composition for pure and adulterated honey. Accordingly, such simple tests can be applied as good indicators for detecting the adulteration of honey with HFCS at adulteration levels ranging from 10% to 50%. 4. Determination of Chinese honey adulterated with high fructose corn syrup by near infrared spectroscopy. Food Chemistry, Volume 128, Issue 4, 15 October 2011, Pages 1110-1114. Lanzhen Chen, Xiaofeng Xue, Zhihua Ye, Jinghui Zhou, … Jing Zhao https://doi.org/10.1016/j.foodchem.2010.10.027 The use of fibre optic diffuse reflectance near infrared spectroscopy (NIR) in combination with chemometric techniques has been investigated to discriminate authenticity of honey. NIR spectra of unadulterated honey and adulterated honey samples with high fructose corn syrup were registered within 10,000–4000 cm − 1 spectral region. Discriminant partial least squares (DPLS) models were constructed to distinguish between unadulterated honey and adulterated honey samples and main bands responsible for the discrimination of samples are in the range of 6000–10,000 cm − 1 . For these models, the correct classification rate for calibration samples were above 90%. Hundred percentage of unadulterated honey and 95% of adulterated honey samples from test set were correctly classified after appropriate preprocessing of first derivative, 13 smoothing points, followed by mean centering pre-treatment and eight model factors, respectively. Our results showed that NIR spectroscopy data with chemometrics techniques can be applied to rapid detecting honey adulteration with high fructose corn syrup. 5. Detection of honey adulteration of high fructose corn syrup by Low Field Nuclear Magnetic Resonance (LF 1H NMR). Journal of Food Engineering, Volume 135, August 2014, Pages 39-43, Roberta de Oliveira Resende Ribeiro, Eliane Teixeira Mársico, Carla da Silva Carneiro, Maria Lúcia Guerra Monteiro, … Edgar Francisco Oliveira de Jesus. https://doi.org/10.1016/j.jfoodeng.2014.03.009

The effect of honey adulteration by high fructose corn syrup in different concentrations from 0% (pure honey) to 100% (pure high fructose corn syrup) was investigated using Low Field Nuclear Magnetic Resonance spectroscopy (LF 1H NMR) and physicochemical analytical methods. The LF 1H NMR data were analyzed by bi-exponential fitting and compared with physicochemical data. The physicochemical parameters demonstrated that water content, water activity, pH and color differed significantly in honey samples adulterated with different concentrations of high fructose corn syrup. These differences were also observed by transverse relaxation (T2). Bi-exponential fitting of T2 resulted in the observation of two water populations in all samples, T21 and T22, with relaxation times in the range of 1.26–1.60 ms and 3.33–7.38 ms, respectively. Relaxation times increased with higher percentages of high fructose syrup in adulterated honey. Linear correlations were observed between the T2, T21 and T22 parameters and physicochemical data, suggesting that LF 1H NMR can be used to discriminate pure blossom honey from honey adulterated with high fructose corn syrup. 69 5. System Suitability Tests and/or Analytical Quality Control 70 Suitable methods will include blanks, and appropriate check standards. 71 6. Reference Materials 72 A detailed description of the process used to obtain and evaluate authentic/reference standard 73 materials (sources), and of the test protocol used for validating the method must be provided. 74 7. Validation Guidance 75 a. Data demonstrating method performance is required. b. Samples: Complete documentation for the collection and use of authentic samples must be supplied by the method authors. The scope of “authentic” samples used to validate the method must be applicable to the defined scope of the TT method. Expansion of the scope is possible with the inclusion of additional authentic samples and abbreviated validation using the protocol

76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93

listed in this SMPR.

c. For single lab validation studies, the method will be evaluated using prescribed adulterated materials as shown in Table 1. Methods approved at this level will proceed to a second level of evaluation (multi-laboratory) where blinded samples containing unknown adulterants will be

sent to participating laboratories.

d. Statistical analysis of interlaboratory studies. Sample size needed to meet performance

requirement on proportion.

8. Maximum Time-to-Results

None.

AOAC SMPR 2020.XXX; Draft AOAC Standard Method Performance Requirements (SMPRs) for Non- 1 Targeted Testing (NTT) of Ingredients for Food Authenticity/Fraud Evaluation of Liquid Raw Bovine Milk; 2 version 3; January 28, 2020 3 4 Intended Use 5 AOAC SMPRs describe the minimum recommended performance characteristics to be used during the 6 evaluation of a method. The evaluation may be an on-site verification, a single-laboratory validation, 7 or a multi-site collaborative study. SMPRs are written and adopted by AOAC stakeholder panels 8 composed of representatives from the industry, regulatory organizations, contract laboratories, test 9 kit manufacturers, and academic institutions. AOAC SMPRs are used by AOAC expert review panels in 10 their evaluation of validation study data for method being considered for Performance Tested 11 MethodsSM or AOAC Official Methods of Analysis SM , and can be used as acceptance criteria for 12 verification at user laboratories. 13 14 1. Applicability 15 This document contains assessment parameters on the performance of Non-Targeted Testing 16 methods to monitor liquid raw bovine milk for the probable presence of Economically Motivated 17 Adulterants (EMA). 18 This SMPR was designed to evaluate Non-Targeted Testing (NTT) methods developed to assess 19 potential economic adulteration in defined commodities. The SMPR was purposely designed with 20 general descriptions to be applicable to a broad range of innovative analytical platforms and 21 chemometric approaches. Binary analytical results of “Authentic” or “Not Authentic” on defined 22 samples from the performance of the method will be used to perform the evaluations by the Expert 23 Review Panel. 24 25 Complete documentation of the collection and use of authentic samples is to be supplied by the 26 method authors. The scope of authentic samples will be the applicable scope of the NTT method and 27 expansion of the scope is possible with the inclusion of additional authentic samples into the baseline 28 calibration, and validation using the protocol listed in this SMPR. 29 30 2. Analytical Technique 31 A non-targeted method to be used to evaluate foods and ingredients for possible EMAs. Any method 32 generating a baseline fingerprint of the authentic material and comparing test sample fingerprints to 33 assess differences will be considered. The final binary result identifies test samples as either authentic 34 or potentially adulterated. This method demonstrates reliability using the requirements listed in this 35 SMPR. 36 37 For single lab validation studies, the method will be evaluated using prescribed adulterated materials 38 as shown in Table 1. Methods approved at this level will proceed to a second level of evaluation (i.e., 39 multi-laboratory validation) where blinded samples containing unknown adulterants will be sent to 40 laboratories participating in the ensuing multi-laboratory validation. 41 42 The scope of the NTT method will be defined by the authentic samples used in generating the baseline 43 Applicability Statement – a general statement about the intended purpose and scope of the method 47 entailing key aspects of expected achievements for the specific situation and circumstances. Key 48 fingerprint. 44 45 3. Definitions 46

points to cover are the intended matrix, the purpose, and an indication of sensitivity, specificity, and 49 significance (USP Appendix XVIII). 50 51 Authentic Samples – Samples representative of the genuine commodity. These samples should 52 represent the food’s or ingredient’s variability seen naturally in the commodity. The authentic 53 samples used to generate the product fingerprint will be used to properly define the NTT method 54 testing scope. 55 56 Baseline Fingerprint – A food-specific model created by software evaluation of collected analytical 57 data. 58 59 Economically Motivated Adulteration – The fraudulent addition of non-authentic substances or 60 removal or replacement of authentic substances without the purchaser's knowledge for economic 61 gain of the seller (USP Appendix XVIII). 62 63 Authentic Liquid Raw Bovine Milk – The milk used to generate the baseline fingerprint which defines 64 the method’s scope of authenticity. 65 66 Single Laboratory Validation – Demonstration by one laboratory of method performance on samples 67 described in Table 1. 68 69 Multilaboratory Validation – Demonstration between laboratories using adulterated samples created 70 by a third-party group and supplied blindly to the participating laboratories. 71 72 4. Method Performance Requirements 73 (Table 1: Method Performance Requirements for raw bovine milk) 74 75 Test Adulterant % Adulterant in Test Materials Number of Samples to be Tested 1 Number of Test Results Qualified as Adulterated

Baseline

None (Authentic Milk)

0%

Establish Baseline Fingerprint 2

Validation using Authentic Samples 3

None

0%

30

0

Validation 4 Validation 4 Validation 4 Validation 4 Validation 4 Validation 4 Validation 4 Validation 4

Urea

0.06%

30 30 30 30 30 30 30 30

30 30 30 30 30 30

Melamine

0.015%

Water

0.5% 0.1%

Sucrose

Whey

1%

Vegetable Oils (Notably soy oil)

0.1%

Maltodextrin

0.1% 0.1%

30

76 77 78 79 80

Starch 30 1. Multiple samples from the same batch of adulterated material can be used for method evaluation. 2. Full details on protocol used to establish an authentic fingerprint must be supplied. 3. Method validation using authentic samples shall cover the entire scope used in creating the baseline fingerprint. 4. Method validation using adulterated samples shall cover the entire scope used in creating the baseline fingerprint.

5. System Suitability Tests and/or Analytical Quality Control 81 Suitable methods will include blanks, and appropriate check standards. 82 83 6. Reference Materials 84 Detailed protocols used to identify reference materials as authentic and to create adulterated samples 85 must be supplied. 86 87 7. Validation Guidance 88 a) Data demonstrating method performance is required. 89 b) Available guidance documents : 90 a. AOAC INTERNATIONAL Guidelines for Validation of Botanical Identification Methods, Journal of 91 AOAC International Vol. 95, No. 1, 2012 92 b. Statistical analysis of interlaboratory studies. LII. Sample size needed to meet performance 93 requirement on proportion. http://lcfltd.com/AOAC/tr347-SAIS-LII-sample-size-needed-for-PR-for- 94 proportion.pdf 95 c. United States Pharmacopeia (USP). Appendix XVIII: Guidance on Developing and Validating Non- 96 targeted Methods for Adulteration Detection. Food Chemicals Codex, 3rd supplement to 11th ed.; 97 USP: Rockville, MD, 2019 98 99 8. Maximum Time-to-Results 100 None. 101

AOAC SMPR 2020.XXX; Draft AOAC Standard Method Performance Requirements (SMPRs) for Non- 1 Targeted Testing (NTT) of Ingredients for Food Authenticity/Fraud Evaluation of Extra Virgin Olive Oil; 2 version 3; January 28, 2020 3 4 Intended Use 5 AOAC SMPRs describe the minimum recommended performance characteristics to be used during the 6 evaluation of a method. The evaluation may be an on-site verification, a single-laboratory validation, 7 or a multi-site collaborative study. SMPRs are written and adopted by AOAC stakeholder panels 8 composed of representatives from the industry, regulatory organizations, contract laboratories, test 9 kit manufacturers, and academic institutions. AOAC SMPRs are used by AOAC expert review panels in 10 their evaluation of validation study data for method being considered for Performance Tested 11 MethodsSM or AOAC Official Methods of Analysis SM , and can be used as acceptance criteria for 12 verification at user laboratories. 13 14 1. Applicability 15 This document contains assessment parameters on the performance of Non-Targeted Testing (NTT) 16 methods to monitor extra virgin olive oil (EVOO) for the probable presence of Economically Motivated 17 Adulterants (EMA). 18 19 This SMPR was designed to evaluate Non-Targeted Testing (NTT) methods developed to assess 20 potential economic adulteration in defined commodities. The SMPR was purposely designed with 21 general descriptions to be applicable to a broad range of innovative analytical platforms and 22 chemometric approaches. Binary analytical results of “Authentic” or “Not Authentic” on defined 23 samples from the performance of the method will be used to perform the evaluations by the Expert 24 Review Panel. 25 26 Complete documentation of the collection and use of authentic samples is to be supplied by the 27 method authors. The scope of authentic samples will be the applicable scope of the NTT method and 28 expansion of the scope is possible with the inclusion of additional authentic samples into the baseline 29 calibration, and validation using the protocol listed in this SMPR. 30 31 2. Analytical Technique 32 A non-targeted method to be used to evaluate foods and ingredients for possible EMAs. Any method 33 generating a baseline fingerprint of the authentic material and comparing test sample fingerprints to 34 assess differences will be considered. The final binary result identifies test samples as either authentic 35 or potentially adulterated. This method demonstrates reliability using the requirements listed in this 36 SMPR. 37 38 For single lab validation studies, the method will be evaluated using prescribed adulterated materials 39 as shown in Table 1. Methods approved at this level will proceed to a second level of evaluation (i.e., 40 multi-laboratory validation) where blinded samples containing unknown adulterants will be sent to 41 laboratories participating in the ensuing multi-laboratory validation. 42 43 The scope of the NTT method will be defined by the authentic samples used in generating the baseline 44 Applicability Statement – a general statement about the intended purpose and scope of the method 48 entailing key aspects of expected achievements for the specific situation and circumstances. Key 49 points to cover are the intended matrix, the purpose, and an indication of sensitivity, specificity, and 50 significance (USP Appendix XVIII). 51 52 fingerprint. 45 46 3. Definitions 47

Authentic Samples – Samples representative of the genuine commodity. These samples should 53 represent the food’s or ingredient’s variability seen naturally in the commodity. The authentic 54 samples used to generate the product baseline fingerprint will be used to properly define the NTT 55 method testing scope. 56 57 Baseline Fingerprint – A food-specific model created by software evaluation of collected analytical 58 data. 59 60 Economically Motivated Adulteration – The fraudulent addition of non-authentic substances or 61 removal or replacement of authentic substances without the purchaser's knowledge for economic 62 gain of the seller (USP Appendix XVIII). 63 64 False Origin – Extra Virgin Olive Oil containing mislabeled geographic and botanical sources. 65 66 Authentic EVOO – The type(s) of EVOO used to generate the baseline fingerprint. The method’s scope 67 of authenticity is defined by the EVOO(s) used in generating the baseline fingerprint. 68 69 Single Laboratory Validation – Demonstration by one laboratory of method performance on samples 70 described in Table 1. 71 72 Multilaboratory Validation – Demonstration between laboratories using adulterated samples created 73 by a third-party group and supplied blindly to the participating laboratories. 74 75 4. Method Performance Requirements 76 (Table 1: Method Performance Requirements) 77 78 Test Adulterant %Adulterant in Test Materials Number of Samples to be Tested 1 Number of Test Results Qualified as Adulterated

Baseline

None (Authentic EVOO)

0%

Establish Baseline Fingerprint 2

Validation using Authentic Samples 3

0%

30

0

None

Validation 4

5%

30

30

Sunflower Oil

Validation

5%

30

30

Validation 4

Validation 4

5%

30

30

Corn Oil

Validation 4

5%

30

30

Hazelnut Oil

Validation 4

5%

30

30

Canola Oil

Validation 4

5%

30

30

Safflower Oil

Validation 4

5%

30

30

Non-EVOO

Validation 4 30 1. Multiple samples from the same batch of adulterated material can be used for method evaluation. 79 2. Full details on protocol used to establish an authentic fingerprint must be supplied. 80 3. Method validation using authentic samples shall cover the entire scope used in creating the baseline fingerprint. 81 4. Method validation using adulterated samples shall cover the entire scope used in creating the baseline fingerprint. 82 83 False Origin 5% 30

5. System Suitability Tests and/or Analytical Quality Control 84 Suitable methods will include blanks, and appropriate check standards. 85 86 6. Reference Materials 87 Detailed protocols used to identify reference materials as authentic and to create adulterated samples 88 must be supplied. 89 90 7. Validation Guidance 91 a) Data demonstrating method performance is required. 92 b) Available guidance documents : 93 a. AOAC INTERNATIONAL Guidelines for Validation of Botanical Identification Methods, Journal of AOAC 94 International Vol. 95, No. 1, 2012 95 b. Statistical analysis of interlaboratory studies. LII. Sample size needed to meet performance 96 requirement on proportion. http://lcfltd.com/AOAC/tr347-SAIS-LII-sample-size-needed-for-PR-for- 97 proportion.pdf 98 c. United States Pharmacopeia (USP). Appendix XVIII: Guidance on Developing and Validating Non- 99 targeted Methods for Adulteration Detection. Food Chemicals Codex, 3rd supplement to 11th ed.; 100 USP: Rockville, MD, 2019 101 102 8. Maximum Time-to-Results 103 None. 104