Africa, an Emerging Exporter of Turmeric: Combating Fraud with Rapid Detection Systems
Abstract
:1. Introduction
2. Africa: An Emerging Exporter of Turmeric
2.1. History, Use and Variety of Turmeric in Africa
2.2. Turmeric Supply Chain (Top Exporters and Importers) in Africa
2.3. Processing of Turmeric in Africa
2.4. Turmeric Adulteration Affecting African Exporters
3. Turmeric Adulterants: Focus on Exposure and Associated Health Implications
3.1. Exposures to Adulterants in Turmeric and Associated Health Implications
3.2. Exposures to Lead (Through Lead Chromate) Adulterated Turmeric and Associated Health Effects
4. Detection of Adulterants in Turmeric Powder
4.1. Online Systematic Searching, PRISMA Analysis
4.2. Turmeric Adulteration Detection Methods
4.3. Frequently Reported Turmeric Adulterants in Rapid Global Alert Reports
4.4. Suitable Detection Systems for Lead in Turmeric Powder
Country (Sample Origin) | Method of Detection | Adul Terant | Frequency (%) | Mean Level mg/kg | Range or Max, mg/kg | References |
---|---|---|---|---|---|---|
Bangladesh | XRF | Pb ⱡ | / | 80 | <LOD-483 | [70] |
US (purchased from Bangladesh, India, Nepal, Pakistan, Morocco, US) | ICP-MS | Pb | 76/105 (72) | 160 | 2700 | [116] |
Bangladesh (9 districts) | ICP-MS, XRF | Pb ⱡ | 16/140 (11) | 1152 | / | [9] |
Bangladesh | ICP-MS, XRF | Pb ⱡ | 52/200 (26) | 690 | / | |
India | ICP-MS, XRF | Pb ⱡ | 0.2 | 0.7 | ||
Republic of Korea | ICP-MS | Pb | 13 (100) | 0.09 | 0.04–0.97 | [114] |
Republic of Georgia | ICP-MS, pXRF | Pb | 2 ** | 1897.06 * | 466–3328 | [82] |
India—Penta, Bihar | pXRF | Pb | 128 ** | 114.6 | <44–>363 | [71] |
Bangladesh, Pakistan | ICP-MS, pXRF | Pb ⱡ | 11 ** | 857 | 1.04–4221 | [47] |
India | ICP-MS, pXRF | Pb ⱡ | 11 ** | 1118 | 0–5279 | |
US (Kansas) | ICP-MS | Pb | 1 (100) | 6.86 | 6.86 | [73] |
US (also purchased from India) | ICP-OES | Pb | 71 ** | 205.33 Ⱡ | 0.06 Ⱡ–6504 | [80] |
ICP-OES/-MS | Pb | 13 ** | 0.12 | 0.07–0.28 | ||
South Asia (India, Pakistan, Sri Lanka, and Nepal) | ICP-OES/-MSpXRF | Pb | 51/356 (14) | 3 * (>LOD: 2) | 2936 | [10] |
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
EMA | Economically Motivated Adulteration |
FDA | Food and Drug Administration |
OEC | Observatory of Economic Complexity |
CBI | Centre for the Promotion of Imports from Developing Countries |
HSDB | Hazardous Substances Data Bank |
IARC | International Agency for Research on Cancer |
pXRF | Portable X-Ray Fluorescence |
PRISMA | Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
ICP-MS | Inductively Coupled Plasma-Mass Spectrometry |
ICP-OES | Inductively Coupled Plasma-Optical Emission Spectroscopy |
FSSAI | Food Safety and Standards Authority of India |
GPC | Gel Permeation Chromatography |
TLC | Thin-Layer Chromatography |
LIBS | Laser-Induced Breakdown Spectroscopy |
NIR | Near-Infrared |
FT-IR | Fourier-Transform Infrared |
FT-MIR | Fourier Transform Mid-Infrared |
PCA | Principal Component Analysis |
PLS-DA | Partial Least Squares Discriminant Analysis |
XRD | X-Ray Powder Diffraction |
FAAS | Flame Atomic Absorption Spectrometry |
ML | Maximum Limits |
EU | European Union |
EC | European Commission |
US | United States |
CDC | Centres for Disease Control and Prevention |
TNSRC | Tepi National Spices Research Centre |
LMIC | Low–Middle-Income Countries |
Appendix A
Country | Trade Value in 2022 | Trade Value in 2023 | Trade Value Growth (%) | % Total Turmeric Exported in 2023 | % Total Turmeric Exported in 2022 |
---|---|---|---|---|---|
Burkina Faso | 208 | 248 | 0.192308 | 0.00 | 0.00 |
Cote d’Ivoire | 632 | 11,744 | 17.58228 | 0.20 | 0.01 |
Cameroon | 2747 | 1656 | −0.39716 | 0.03 | 0.04 |
Democratic Republic of the Congo | 16 | 44 | 1.75 | 0.00 | 0.00 |
Djibouti | 568,864 | 106,439 | −0.81289 | 1.82 | 8.97 |
Egypt | 293,936 | 194,513 | −0.33825 | 3.33 | 4.64 |
Ethiopia | 2,698,590 | 3,331,579 | 0.234563 | 57.11 | 42.56 |
Ghana | 4958 | 1283 | −0.74123 | 0.02 | 0.08 |
Kenya | 121,391 | 107,934 | −0.11086 | 1.85 | 1.91 |
Morocco | 67,660 | 11,005 | −0.83735 | 0.19 | 1.07 |
Madagascar | 952,484 | 992,241 | 0.04174 | 17.01 | 15.02 |
Mauritius | 2347 | 462 | −0.80315 | 0.01 | 0.04 |
Malawi | 1 | 106 | 105 | 0.00 | 0.00 |
Nigeria | 1,000,216 | 439,084 | −0.56101 | 7.53 | 15.78 |
Togo | 14,044 | 2239 | −0.84057 | 0.04 | 0.22 |
Tunisia | 82,399 | 8888 | −0.89213 | 0.15 | 1.30 |
Tanzania | 115,966 | 10,292 | −0.91125 | 0.18 | 1.83 |
Uganda | 56,409 | 35,302 | −0.37418 | 0.61 | 0.89 |
South Africa | 354,072 | 530,539 | 0.498393 | 9.09 | 5.58 |
Angola | 0 | 14 | 1 | 0.00 | 0.00 |
Botswana | 0 | 6 | 1 | 0.00 | 0.00 |
Comoros | 0 | 1 | 1 | 0.00 | 0.00 |
Algeria | 0 | 113 | 1 | 0.00 | 0.00 |
Senegal | 0 | 25,762 | 1 | 0.44 | 0.00 |
Somalia | 0 | 19,897 | 1 | 0.34 | 0.00 |
Zambia | 0 | 2274 | 1 | 0.04 | 0.00 |
Benin | 11 | 0 | −1 | 0.00 | 0.00 |
Republic of the Congo | 42 | 0 | −1 | 0.00 | 0.00 |
Guinea | 5 | 0 | −1 | 0.00 | 0.00 |
Mali | 86 | 0 | −1 | 0.00 | 0.00 |
Mozambique | 205 | 0 | −1 | 0.00 | 0.00 |
Namibia | 334 | 0 | −1 | 0.00 | 0.01 |
Niger | 65 | 0 | −1 | 0.00 | 0.00 |
Rwanda | 910 | 0 | −1 | 0.00 | 0.01 |
South Sudan | 300 | 0 | −1 | 0.00 | 0.00 |
Sao Tome and Principe | 38 | 0 | −1 | 0.00 | 0.00 |
Eswatini | 1101 | 0 | −1 | 0.00 | 0.02 |
Zimbabwe | 3 | 0 | −1 | 0.00 | 0.00 |
Country | Trade Value in 2022 | Trade Value in 2023 | Trade Value Growth (%) | % Total Turmeric Exported in 2023 | % Total Turmeric Exported in 2022 |
---|---|---|---|---|---|
Angola | 11,814 | 42,562 | 260.2675 | 0.13 | 0.03 |
Burundi | 296 | 295 | −0.33784 | 0.00 | 0.00 |
Benin | 9874 | 28,179 | 185.3859 | 0.09 | 0.02 |
Burkina Faso | 3427 | 921 | −73.1252 | 0.00 | 0.01 |
Botswana | 18,419 | 17,674 | −4.04474 | 0.06 | 0.05 |
Central African Republic | 11,963 | 30,698 | 156.6079 | 0.10 | 0.03 |
Cote d’Ivoire | 333,805 | 261,674 | −21.6087 | 0.83 | 0.83 |
Cameroon | 130,723 | 83,244 | −36.3203 | 0.26 | 0.33 |
Democratic Republic of the Congo | 18,376 | 17,043 | −7.25403 | 0.05 | 0.05 |
Republic of the Congo | 4591 | 6710 | 46.15552 | 0.02 | 0.01 |
Comoros | 1187 | 4173 | 251.5586 | 0.01 | 0.00 |
Cape Verde | 6020 | 10,077 | 67.39203 | 0.03 | 0.02 |
Djibouti | 73,657 | 63,978 | −13.1406 | 0.20 | 0.18 |
Algeria | 3,702,310 | 2,588,220 | −30.0918 | 8.19 | 9.25 |
Egypt | 4,365,953 | 2,419,589 | −44.5805 | 7.65 | 10.91 |
Eritrea | 170 | 100 | −41.1765 | 0.00 | 0.00 |
Ethiopia | 69,397 | 197,474 | 184.557 | 0.62 | 0.17 |
Gabon | 35,713 | 7521 | −78.9404 | 0.02 | 0.09 |
Ghana | 28,990 | 30,569 | 5.446706 | 0.10 | 0.07 |
Guinea | 3737 | 7021 | 87.87798 | 0.02 | 0.01 |
Gambia | 3755 | 36,915 | 883.0892 | 0.12 | 0.01 |
Equatorial Guinea | 5305 | 18,764 | 253.7041 | 0.06 | 0.01 |
Kenya | 256,417 | 276,676 | 7.900802 | 0.88 | 0.64 |
Liberia | 6353 | 8374 | 31.81174 | 0.03 | 0.02 |
Libya | 4,251,963 | 3,045,085 | −28.384 | 9.63 | 10.63 |
Lesotho | 2944 | 4349 | 47.72418 | 0.01 | 0.01 |
Morocco | 15,183,390 | 12,571,001 | −17.2056 | 39.76 | 37.95 |
Madagascar | 8750 | 6702 | −23.4057 | 0.02 | 0.02 |
Mali | 9421 | 44,200 | 369.1646 | 0.14 | 0.02 |
Mozambique | 20,053 | 49,928 | 148.9802 | 0.16 | 0.05 |
Mauritania | 13,550 | 17,321 | 27.83026 | 0.05 | 0.03 |
Mauritius | 501,962 | 553,807 | 10.32847 | 1.75 | 1.25 |
Malawi | 1439 | 5050 | 250.9382 | 0.02 | 0.00 |
Namibia | 19,979 | 31,933 | 59.83282 | 0.10 | 0.05 |
Niger | 2423 | 8814 | 263.7639 | 0.03 | 0.01 |
Nigeria | 244,982 | 96,810 | −60.4828 | 0.31 | 0.61 |
Rwanda | 5994 | 1606 | −73.2065 | 0.01 | 0.01 |
Sudan | 133,041 | 97,640 | −26.6091 | 0.31 | 0.33 |
Senegal | 267,747 | 137,439 | −48.6683 | 0.43 | 0.67 |
Saint Helena | 1034 | 10,411 | 906.8665 | 0.03 | 0.00 |
Sierra Leone | 328 | 1808 | 451.2195 | 0.01 | 0.00 |
Somalia | 26,291 | 31,727 | 20.67628 | 0.10 | 0.07 |
South Sudan | 83,965 | 50,009 | −40.4407 | 0.16 | 0.21 |
Sao Tome and Principe | 90 | 100 | 11.11111 | 0.00 | 0.00 |
Eswatini | 123,493 | 105,624 | −14.4696 | 0.33 | 0.31 |
Seychelles | 96,711 | 88,542 | −8.44682 | 0.28 | 0.24 |
Togo | 3284 | 4093 | 24.63459 | 0.01 | 0.01 |
Tunisia | 3,513,144 | 2,933,842 | −16.4896 | 9.28 | 8.78 |
Tanzania | 7514 | 14,841 | 97.51131 | 0.05 | 0.02 |
Uganda | 128,914 | 127,493 | −1.10229 | 0.40 | 0.32 |
South Africa | 6,063,566 | 5,095,890 | −15.9589 | 16.12 | 15.16 |
Zambia | 15,745 | 34,378 | 118.3423 | 0.11 | 0.04 |
Zimbabwe | 172,441 | 290,945 | 68.72148 | 0.92 | 0.43 |
Guinea-Bissau | 0 | 40 | 100 | 0.00 | 0.00 |
Chad | 0 | 101 | 100 | 0.00 | 0.00 |
Country (Sample Origin) | Method of Detection | Adulterant Investigated | References |
---|---|---|---|
ADULTERANT: LEAD (CHROMATE) | |||
India (Allahabad) | Laser-induced breakdown spectroscopic (LIBS) technique | Lead and Chromium | [89] |
India | India’s Food Safety and Standards Authority (FSSAI) Physical and Chemical Methods | Lead chromate, | [124] |
Bangladesh | Semi-structured interviews and informal observations (N = 152 heads), Inductively coupled plasma-mass spectrometry (ICP-MS), and Portable/Handheld X-ray fluorescence analysis (pXRF) | Lead and Chromium | [54] |
Bangladesh | ICP-MS (LOD 0.001 µg/g Pb) | Lead | [54] |
Thailand | Raman spectroscopy with PLSR | Lead | [90] |
India | FSSAI: Physical and Chemical Methods (Do-at-home tests) | Lead chromate, | [125] |
Russia (Moscow) | Electrothermal atomic absorption spectroscopy (AAS) | Lead and Chromium | [126] |
Netherlands | FT-Raman spectroscopy and PLSR model | Lead chromate | [79] |
India | Powder X-ray diffraction (PXRD) method (LOD: 0.5%) | Lead chromate | [91] |
India | Diphenylcarbazide (DPC) colourimetric assay | Hexavalent chromium | [47] |
India | pXRF and ICP-MS | Lead | [47] |
Bangladesh, Pakistan | pXRF and ICP-MS | Lead | [47] |
South Asia (India, Sri Lanka, and Nepal) | pXRF analyzer (XRF, Olympus Delta DCC-4000). LOD = 2 ug/g Pb | Lead | [10] |
South Asia (India, Sri Lanka, and Nepal) | ICP-MS (LOD = 0.01 µg/g). For samples with Pb levels > LOD for pXRF. | Lead and Chromium | [10] |
South Asia (Pakistan) | Inductively coupled plasma-optical emissions spectrometry (ICP-OES, LOD = 0.5 µg/g) | Lead and Chromium | [10] |
South Asia (India, Pakistan, Sri Lanka, and Nepal) | The molar ratio of lead to chromium was calculated using the molar mass of lead (207.2 g/mol) and chromium (51.9961 g/mol). A molar ratio of lead to chromium close to 1:1 is suggestive of lead chromate. | Lead chromate (for samples with Pb levels >LOD) | [10] |
Bangladesh | Multi-faceted pre-/post-intervention as follows: (i) disseminating findings from scientific studies via news media that identified turmeric as a source of lead poisoning; (ii) educating consumers and businesspeople about the risks of lead chromate in turmeric via public notices and face-to-face meetings, and (iii) collaborating with the Bangladesh Food Safety Authority to utilize a rapid lead detection technology to enforce policy disallowing turmeric adulteration. | Lead | [59] |
Egypt | Multivariate chemometric models with those of artificial intelligent (AI) networks (AIN) to enhance the selectivity of spectral data for rapid assay, along with the PLS model, artificial neural network (ANN), and genetic algorithm (GA) | Lead chromate, | [94] |
India | LIBS and multivariate technique | Lead and Chromium | [48] |
USA | Desktop-based | Lead (Lead chromate) | [72] |
Adulterant: METANIL YELLOW | |||
India | Two-dimensional high-performance thin-layer chromatography (2D-HPTLC) method | Metanil yellow | [127] |
India | Preliminary colour test and thin-layer chromatography (TLC) | Metanil yellow | [128] |
India | India’s Food Safety and Standards Authority (FSSAI)’s Physical and Chemical Methods | Metanil yellow dye | [124] |
India | Ultraviolet-visible (UV-vis) spectrophotometer | Metanil yellow | [42] |
India (Allahabad) | Preliminary colour test and TLC | Metanil yellow | [129] |
USA | Fourier transform (FT)-Raman and Fourier-transform infrared spectroscopy (FT-IR) Spectroscopy | Metanil Yellow | [130] |
India | Machine vision-based approach with PCA | Metanil yellow | [131] |
India | TLC (Isopropyl alcohol as a diluent) | Metanil yellow, | [132] |
India | NIR spectroscopy with PCA and partial least square regression (PLSR) | Metanil yellow powder | [133] |
India | FT-MIR Spectroscopy/UV-Vis Spectroscopy/Electrical impedance spectroscopy (EIS) technique | Metanil Yellow | [134] |
India | Gradient reverse-phase high-pressure liquid chromatographic (LOD: 0.37–2.48 µg/mL) | Metanil yellow | [31] |
USA | Handheld near-infrared spectrometer and PCA-SIMCA Modelling | Metanil Yellow | [135] |
USA (Lincoln) | Handheld NIR spectrometer and Benchtop NIR spectrometer (LOD and LOQ for the handheld and benchtop were 0.33 and 1.10%, respectively) using partial least squares regression models | Metanil yellow | [136] |
India | FSSAI: Physical and Chemical Methods | Metanil yellow, | [137] |
India | FSSAI: Physical and Chemical Methods (Do-at-home tests) | Metanil yellow, | [125] |
India | Benzimidazole Based Bifunctional Sensor | Metanil yellow | [68] |
India | Deep neural network and random forests-driven computer vision framework | Metanil yellow | [138] |
Iran | Molecularly imprinted polymer dispersive solid-phase extraction and visible light spectrophotometry | Metanil yellow | [139] |
Philippines | ATR-FTIR spectroscopy was used in tandem with one-class support vector machine (OCSVM) | Metanil Yellow | [140] |
South Asia (India, Pakistan, Sri Lanka, and Nepal) | liquid chromatography-mass spectrometry (LC-MS) (LOD = 0.05 mg/kg) | Metanil yellow | [10] |
Egypt/Saudi Arabia | Fluorescence Europium doped carbon dots | Metanil yellow | [141] |
India | X-ray diffraction (XRD) and scanning electron microscopy (SEM) | Metanil yellow traces | [98] |
India | FSSAI: Physical and Chemical Methods | Metanil yellow | [142] |
Canada | 1H-NMR spectroscopy, in conjunction with multivariate | Synthetic Metanil yellow | [143] |
India | FSSAI: Physical and Chemical Methods | Metanil yellow | [144] |
Egypt | Multivariate chemometric models with those of artificial intelligent (AI) networks (AIN) to enhance the selectivity of spectral data for rapid assay, along with the PLS model, artificial neural network (ANN), and genetic algorithm (GA) | Metanil yellow | [94] |
India | FSSAI: Physical and Chemical Methods | Metanil yellow | [145] |
India | Ultra-high-performance liquid chromatography with photodiode array detector-based analytical method | Metanil yellow | [97] |
USA | Liquid chromatography-tandem mass spectrometry (LC-MS/MS) | Metanil yellow | [146] |
India | Low-resolution handheld NIR spectroscopic platform assisted with chemometric algorithm (PCA-DA and Soft Independent Modelling of Class Analogy (SIMCA)) | Metanil yellow powder | [147] |
India | LIBS and multivariate technique | Metanil yellow | [48] |
Iran | NIR spectroscopy associated with chemometric models (Soft Independent Modeling of Class Analogy (SIMCA) mode) | Metanil yellow | [148] |
India | UV-VIS spectrophotometer | Metanil yellow | [42] |
India (Allahabad) | Preliminary colour test and TLC | Metanil yellow | [129] |
Adulterant: OTHER CHEMICALS DYES | |||
Spain | High-resolution Nuclear Magnetic Resonance (1H-NMR) and chemometric treatment [Partial Least Squares-Discriminant Analysis (PLS-DA)]. | Sudan dye I, II, III, and IV | [49] |
India | High Performance Thin Layer Chromatography—Mass Spectrometry (HPTLC–MS) | Sudan dyes | [149] |
India (Allahabad) | Preliminary colour test and TLC | Sudan III | [129] |
Egypt | Gel permeation chromatography (GPC) and HPLC with diode array detection (HPLC-DAD) | Sudan dyes | [150] |
India | NIR spectroscopy and PCA | Sudan dye I | [151] |
India (Allahabad) | Preliminary colour test and TLC | Sudan III | [129] |
USA | FT-IR spectroscopy with partial least square regression (PLSR) model | Sudan Red G dye | [130] |
USA | Raman imaging and FT-IR spectroscopy | Sudan Red | [152] |
India | Benzimidazole Based Bifunctional Sensor | Sudan I and II | [68] |
USA | Liquid chromatography-tandem mass spectrometry (LC-MS/MS) | Sudan I and Sudan Red G | [146] |
India | Ultra-high-performance liquid chromatography with photodiode array detector-based analytical method | Sudan I | [97] |
India | Low-resolution handheld NIR spectroscopic platform assisted with chemometric algorithm (PCA-DA and Soft Independent Modelling of Class Analogy (SIMCA)) | Sudan dye-IV | [147] |
Pakistan | HPLC with a variable wavelength detector (VWD) | Sudan dyes (I-IV) | [50] |
Philippines | ATR-FTIR spectroscopy was used in tandem with one-class support vector machine (OCSVM) | Sudan I | [140] |
India | Multiple Random Forest coupled with a computer vision technique | Sudan dye-I | [138] |
Iran | NIR spectroscopy associated with chemometric models (Soft Independent Modeling of Class Analogy (SIMCA) mode) | Sudan Red | [148] |
India | TLC (Isopropyl alcohol as a diluent) | Aniline dyes | [132] |
India | FSSAI: Physical and Chemical Methods | Aniline dyes | [137] |
India | FSSAI: Physical and Chemical Methods | Aniline dyes | [145] |
India | FSSAI: Physical and Chemical Methods | Aniline dyes | [142] |
Philippines | ATR-FTIR spectroscopy was used in tandem with one-class support vector machine (OCSVM) | Orange II | [140] |
Egypt | Multivariate chemometric models with those of artificial intelligent (AI) networks (AIN) to enhance the selectivity of spectral data for rapid assay, along with the PLS model, artificial neural network (ANN), and genetic algorithm (GA) | Acid orange 7 | [94] |
Adulterant: OTHER TUMERIC SPECIES | |||
India | Randomly amplified polymorphic DNA (RAPD) Analysis, Polymerase chain reaction (PCR) amplification of the isolated DNA | Curcuma zedoaria | [153] |
India | DNA-based method (molecular method) | Other Curcuma spp. | [154] |
India | Molecular Sequence Characterized Amplified Region (SCAR) markers | Curcuma zedoaria and C. malabarica | [155] |
Algeria | Microscopic analysis and Multivariate analysis (Principal component analysis, PCA) | spp | [156] |
India | PCR amplification (DNA barcoding) | C. zedoaria | [157] |
Indonesia | 1H-NMR metabolite fingerprinting and multivariate analysis (combined with chemometrics of PCA and orthogonal projections to latent structures-discriminant analysis, OPLS-DA) | Curcuma manga | [158] |
Indonesia | 1H-NMR spectroscopy-based metabolite fingerprinting in combination with multivariate analysis (PLS-DA and OPLS-DA) | Curcuma heyneana and C. manga | [159] |
India | Near-infrared (NIR) spectroscopy with Multivariate calibrations including the nearest neighbour (kNN) and support vector machine (SVM) as well as PCA | Other turmeric powders | [160] |
Indonesia | Spectroscopy proton-nuclear magnetic resonance (1H-NMR) based metabolite fingerprinting and chemometrics (PCA and PLS-DA) | Curcuma heyneana | [158] |
Indonesia | FT-IR spectroscopy with Attenuated Total Reflection (ATR) and Chemometrics | Curcuma zedoaria and C. xanthorrhiza | [161] |
USA | FT-IR spectroscopy with partial least square regression (PLSR) model | White turmeric (C. zedoaria) | [130] |
Spain (Barcelona) | Targeted liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) with the characterization and classification using PCA and PLS-DA calculated on the Eigenvector Research Stand Alone Chemometric Software (SOLO) | Other Curcuma spp. | [162] |
USA | Raman imaging and FT-IR spectroscopy | White turmeric powder | [152] |
India | FT-NIR spectroscopy-based metabolic fingerprinting (and PCA and supervised PLS-DA) | Other Curcuma spp. | [163] |
Sri Lanka | Machine learning-based fraud detection web application | Mixed/fake turmeric powder | [164] |
Thailand | NIR and Raman spectroscopies with PLSR models | Variation in curcuminoid levels for authentication | [165] |
Canada | 1H-NMR spectroscopy, in conjunction with multivariate statistical analysis | Curcuma mangga and C. caesia, and Synthetic curcumin | [147] |
India | Gas Chromatography coupled with Mass Spectrometry (GC-MS) technique | Plant-based adulterants | [166] |
Taiwan | Loop-mediated isothermal amplification (LAMP) | Other Turmeric species | [167] |
USA | Carbon-14 and HPLC analyses as complementary methods | Synthetic curcumin | [168] |
India | ICP-MS; HPLC-PDA (photodiode array) and HPTLC-DS (densitometry) based on unique patterns (targeting: CIMP-1, i.e., (1E,4Z)-5-hydroxy-1-(4-hydroxy-3-methoxyphenyl) hexa-1,4-dien-3-one) with ESI-MS/MS (for confirmation) | Synthetic curcumin (presence of Boron (B) found as a qualitative indicator of SC (>250.0 mg/kg) and CLE (<2.0 mg/kg) by ICP-MS) | [169] |
Adulterant: SPENT TURMERIC | |||
India | Vis-NIR spectroscopy and machine learning (PA) | Spent turmeric | [170] |
Northern Ireland, UK | FT-IR spectroscopy coupled with chemometric analysis (PCA, OPLS-DA, and PLS-DA) and micro-FT-IR imaging | Spent turmeric | [8] |
Adulterant: CHALK | |||
India | Terahertz spectroscopy | Chalk powder | [171] |
India | India’s Food Safety and Standards Authority (FSSAI)’s Physical and Chemical Methods | Chalk powder | [124] |
India | FSSAI: Physical and Chemical Methods | Chalk | [137] |
India | FSSAI: Physical and Chemical Methods (Do-at-home tests) | Chalk (yellow-coloured) | [125] |
India | FSSAI: Physical and Chemical Methods | Chalk powder | [172] |
India | FSSAI: Physical and Chemical Methods | Chalk | [142] |
India | FSSAI: Physical and Chemical Methods | Chalk | [144] |
Adulterant: STARCH | |||
India | PCR amplification (DNA barcoding) | Starch (cassava, wheat, barley, and rye) | [157] |
India | FSSAI: Physical and Chemical Methods | Starch (maize, wheat, rice) | [137] |
India | FSSAI: Physical and Chemical Methods (Do-at-home tests) | Starch (corn), | [125] |
Korea (Chuncheon) | Molecular markers using quantitative real-time PCR | Starch (Z. mays, corn) | [173] |
Sri Lanka | Ultraviolet-visible-near infrared (UV-vis-NIR) multispectral imaging and multivariate statistical analysis | Starch (large rice particles) | [174] |
Brazil | IR spectroscopy and multivariate analysis (PCA) | Starch | [175] |
India | Visible-NIR spectroscopy with Machine Learning Methods (logistic regression (LR), K-nearest neighbour (KNN), and support vector machines (SVM)) | Starch | [176] |
India | Vis-NIR spectroscopy with PCA | Starch | [177] |
India | Enhanced CNN in combination with deep learning (DL) | Starch (rice powder) | [178] |
India | NIR spectroscopy with PCA | Starch | [179] |
India | Colour images | Starch | [180] |
South Asia (India, Pakistan, Sri Lanka, and Nepal) | American Spice Trade Association Method 8 | Starch | [10] |
Belgium | A robust set of qPCR methods (molecular method) | Starch (corn, Zea mays) and four other botanicals | [181] |
Philippines | ATR-FTIR spectroscopy was used in tandem with one-class support vector machine (OCSVM) | Starch (corn) | [140] |
Iran | Visible and short wavelengths of NIR hyperspectral imaging (Vis-SWNIR-HSI) combined with different chemometric techniques [multivariate curve resolution-alternating least squares (MCR-ALS) and mean-field independent component analysis (MF-ICA)], coupled with PCA (to find the pattern of authentic samples) and PLS-DA (for discrimination of the of adulterants) | Starch (corn flour, rice flour, wheat flour, and zedoary) | [182] |
India | Improved convolutional neural network (CNN) | Wheat flour | [183] |
Russia (Moscow) | Species-specific PCR | Wheat DNA | [126] |
Mexico | Cavity Perturbation Technique (CPT) | Starch and | [128] |
Northern Ireland, UK | FT-IR spectroscopy coupled with chemometric analysis (PCA, OPLS-DA, and PLS-DA) and micro-FT-IR imaging | Starch (rice flour and corn flour) | [8] |
Canada | 1H-NMR spectroscopy, in conjunction with multivariate | Starch (cassava) | [147] |
India | FSSAI: Physical and Chemical Methods | Starch (maize, wheat, rice) | [145] |
India | Low-resolution handheld NIR spectroscopic platform assisted with chemometric algorithm (PCA-DA and Soft Independent Modelling of Class Analogy (SIMCA)) | Starch (corn powder) | [147] |
China | Front-face synchronous fluorescence spectroscopy (FFSFS) and fluorescence titration coupled with partial least square (PLS) (LOD 5%) | Starch (maize flour) | [184] |
Iran | NIR spectroscopy coupled with chemometrics (PCA and PLSR) | Starch (wheat flour and bread powder) | [185] |
Russia | Fourier transform near-infrared (FT-NIR) spectroscopy with principal component analysis (PCA) and partial least square regression (PLSR) | Starch (corn) | [186] |
Adulterant: OTHER ARTIFICIAL COLOUR AND BULKING AGENTS | |||
India | FSSAI: Physical and Chemical Methods | Coloured saw dust | [187] |
India | FSSAI: Physical and Chemical Methods | Yellow lead salts | [137] |
India | FSSAI: Physical and Chemical Methods | Yellow lead salts | [142] |
India | FSSAI: Physical and Chemical Methods | Yellow lead salts | [145] |
India | FSSAI: Physical and Chemical Methods | Yellow lead salt, | [144] |
India | FSSAI: Physical and Chemical Methods | Yellow soapstone powder | [144] |
India | FSSAI: Physical and Chemical Methods | Yellow soapstone | [172] |
India | FSSAI: Physical and Chemical Methods (Do-at-home tests) | Sawdust | [125] |
Sri Lanka | Multispectral imaging | Tartrazine (synthetic yellow azo dye, E number—E102) | [188] |
India | Multispectral images on the smartphone | Tartrazine-coloured rice flour | [179] |
Iran | Improved convolutional neural network (CNN) with MLP, Fuzzy, SVM, GBT, and EDT algorithms | Chickpea powder and chickpea powder mixed with food colouring | [189] |
Mexico | Cavity Perturbation Technique (CPT) | Egg-yellow colour | [128] |
India | FSSAI: Physical and Chemical Methods | Artificial colour | [187] |
India | Antenna-based sensor | Artificial yellow colour | [190] |
India | FSSAI: Physical and Chemical Methods | Artificial colour, | [144] |
Iran | NIR spectroscopy coupled with chemometrics (PCA and PLSR) | Pistachio hull | [185] |
Egypt/Algeria | HPLC, UV, FT-IR and 1H NMR and HPLC with Chemometric analysis (principal component analysis (PCA) and hierarchical clustering analysis (HCA)) | Authenticity check | [191] |
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Country Exporting | Importing Countries | References |
---|---|---|
Ethiopia | 50% India, 8% Egypt, 6% Iraq, 5% Turkey, 5% Pakistan, 3% Malaysia, 2% Bangladesh, 1% Saudi Arabia, 1% Iran, <1% United States of America, <1% Kenya | [22] |
Djibouti | 88% India, 12% Malaysia | [23] |
Madagascar | 51% Germany, 49% France, <1% Italy, <1% Belgium, <1% Canada | [24] |
South Africa | 19% Zimbabwe, 12% Botswana, 8% Namibia, 7% Zambia, 4% Mozambique, 3% Australia, 1% Angola, 1% United Arab Emirates, <1% Ghana, <1% Congo, <1% Kenya | [25] |
Nigeria | 61% India, 33% United States of America, 6% Germany | [26] |
Cameroon | 100% France | [27] |
Adulterant | F in EMA HIR (n = 51) | F in RASFF (n = 27) | Total (%) (n = 78) |
---|---|---|---|
Lead chromate, lead | 34 | 12 | 46 (58.97) |
Metanil yellow | 31 | 0 | 31 (39.74) |
Starch (corn, rice, etc.) | 18 | 0 | 18 (23.08) |
Sudan dye (I-IV) | 9 | 13 | 22 (28.21) |
Other Curcuma spp. | 6 | 0 | 6 (7.69) |
Others (chalk, orange II, rhodamine, sawdust, etc.) | 7 | 2 | 9 (11.54) |
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Abia, W.A.; Haughey, S.A.; Radhika, R.; Taty, B.P.; Russell, H.; Carey, M.; Maestroni, B.M.; Petchkongkaew, A.; Elliott, C.T.; Williams, P.N. Africa, an Emerging Exporter of Turmeric: Combating Fraud with Rapid Detection Systems. Foods 2025, 14, 1590. https://doi.org/10.3390/foods14091590
Abia WA, Haughey SA, Radhika R, Taty BP, Russell H, Carey M, Maestroni BM, Petchkongkaew A, Elliott CT, Williams PN. Africa, an Emerging Exporter of Turmeric: Combating Fraud with Rapid Detection Systems. Foods. 2025; 14(9):1590. https://doi.org/10.3390/foods14091590
Chicago/Turabian StyleAbia, Wilfred Angie, Simon A. Haughey, Radhika Radhika, Brandy Perkwang Taty, Heidi Russell, Manus Carey, Britt Marianna Maestroni, Awanwee Petchkongkaew, Christopher T. Elliott, and Paul N. Williams. 2025. "Africa, an Emerging Exporter of Turmeric: Combating Fraud with Rapid Detection Systems" Foods 14, no. 9: 1590. https://doi.org/10.3390/foods14091590
APA StyleAbia, W. A., Haughey, S. A., Radhika, R., Taty, B. P., Russell, H., Carey, M., Maestroni, B. M., Petchkongkaew, A., Elliott, C. T., & Williams, P. N. (2025). Africa, an Emerging Exporter of Turmeric: Combating Fraud with Rapid Detection Systems. Foods, 14(9), 1590. https://doi.org/10.3390/foods14091590