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Wheat authentication:An overview on different techniques and chemometric methods

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  • Abbas, O., M. Zadravec, V. Baeten, T. Mikus, T. Lesic, A. Vulic, J. Prpic, L. Jemersic, and J. Pleadin. 2018. Analytical methods used for the authentication of food of animal origin. Food Chemistry 246:6–17. doi: 10.1016/j.foodchem.2017.11.007.
  • Abdi, H. 2007. Partial least square regression PLS-Regression. In Encyclopedia of measurement and statistics, ed. Neil Salki, 1–13. ThousandOaks, CA: Sage.
  • Amir, R. M., F. M. Anjum, M. I. Khan, M. R. Khan, I. Pasha, and M. Nadeem. 2013. Application of fourier transform infrared (FTIR) spectroscopy for the identification of wheat varieties. Journal of Food Science and Technology 50 (5):1018–23. doi: 10.1007/s13197-011-0424-y.
  • Arslan, F. N., and F. Çağlar. 2019. Attenuated total reflectance-fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics for rapid determination of cold-pressed wheat germ oil adulteration. Food Analytical Methods 12 (2):355–70. doi: 10.1007/s12161-018-1368-x.
  • Bai, S. L., L. Xu, Y. Wang, X. L. Yang, F. C. Zhu, Y. Chen, Y. Hu, F. Bao, Y. K. He, and Y. C. Zhang. 2013. A simple and reliable qualitative detection of six foodstuff powders using optical thin-film biosensor chips. European Food Research and Technology 236 (5):899–904. doi: 10.1007/s00217-013-1940-y.
  • Banerjee, R., B. Tudu, R. Bandyopadhyay, and N. Bhattacharyya. 2016. A review on combined odor and taste sensor systems. Journal of Food Engineering 190:10–21. doi: 10.1016/j.jfoodeng.2016.06.001.
  • Barreto, A., J. P. Cruz-Tirado, R. Siche, and R. Quevedo. 2018. Determination of starch content in adulterated fresh cheese using hyperspectral imaging. Food Bioscience 21:14–9. doi: 10.1016/j.fbio.2017.10.009.
  • Bateman, A. S., S. D. Kelly, and T. D. Jickells. 2005. Nitrogen isotope relationships between crops and fertilizer: Implications for using nitrogen isotope analysis as an indicator of agricultural regime. Journal of Agricultural and Food Chemistry 53 (14):5760–5. doi: 10.1021/jf050374h.
  • Bateman, A. S., S. D. Kelly, and M. Woolfe. 2007. Nitrogen isotope composition of organically and conventionally grown crops. Journal of Agricultural and Food Chemistry 55 (7):2664–70. doi: 10.1021/jf0627726.
  • Bonte, A., H. Neuweger, A. Goesmann, C. Thonar, P. MaDer, G. Langenkamper, and K. Niehaus. 2014. Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems. Journal of the Science of Food and Agriculture 94 (13):2605–12. doi: 10.1002/jsfa.6566.
  • Brigante, F. I., A. L. Mas, N. B. Pigni, D. A. Wunderlin, and M. V. Baroni. 2020. Targeted metabolomics to assess the authenticity of bakery products containing chia, sesame and flax seeds. Food Chemistry 312:126059. doi: 10.1016/j.foodchem.2019.126059.
  • Campiglia, E., R. Mancinelli, E. De Stefanis, S. Pucciarmati, and E. Radicetti. 2015. The long-term effects of conventional and organic cropping systems, tillage managements and weather conditions on yield and grain quality of durum wheat (Triticum durum Desf.) in the mediterranean environment of central Italy. Field Crops Research 176:34–44. doi: 10.1016/j.fcr.2015.02.021.
  • Capuano, E., J. Rademaker, H. Bijgaart, and S. Ruth. 2014. Verification of fresh grass feeding, pasture grazing and organic farming by FTIR spectroscopy analysis of bovine milk. Food Research International 60:59–65. doi: 10.1016/j.foodres.2013.12.024.
  • Carloni, E., G. Amagliani, E. Omiccioli, V. Ceppetelli, M. Del Mastro, L. Rotundo, G. Brandi, and M. Magnani. 2017. Validation and application of a quantitative real-time PCR assay to detect common wheat adulteration of durum wheat for pasta production. Food Chemistry 224:86–91. doi: 10.1016/j.foodchem.2016.12.053.
  • Casazza, A. P., C. Morcia, E. Ponzoni, F. Gavazzi, S. Benedettell, and D. Breviario. 2012. A reliable assay for the detection of soft wheat adulteration in Italian pasta is based on the use of new DNA molecular markers capable of discriminating between Triticum aestivum and Triticum durum. Journal of Cereal Science 56 (3):733–40. doi: 10.1016/j.jcs.2012.08.015.k.
  • Cavanna, D., C. Loffi, C. Dall'Asta, and M. Suman. 2020. A non-targeted high-resolution mass spectrometry approach for the assessment of the geographical origin of durum wheat. Food Chemistry 317:126366. doi: 10.1016/j.foodchem.2020.126366.
  • Ciolek, A., E. Makarska, M. Wesolowski, and R. Cierpiala. 2012. Content of selected nutrients in wheat, barley and oat grain from organic and conventional farming. Journal of Elementology 17 (2):181–9. doi: 10.5601/jelem.2012.17.2.02.
  • Cooper, J., R. Sanderson, I. Cakmak, L. Ozturk, P. Shotton, A. Carmichael, R. S. Haghighi, C. Tetard-Jones, N. Volakakis, M. Eyre, et al. 2011. Effect of organic and conventional crop rotation, fertilization, and crop protection practices on metal contents in wheat (Triticum aestivum). Journal of Agricultural and Food Chemistry 59 (9):4715–24. doi: 10.1021/jf104389m.
  • Creydt, M., and M. Fischer. 2018. Omics approaches for food authentication. Electrophoresis 39 (13):1569–81. doi: 10.1002/elps.201800004.
  • Creydt, M., D. Hudzik, M. Rurik, O. Kohlbacher, and M. Fischer. 2018. Food Authentication: Small-Molecule Profiling as a tool for the geographic discrimination of german white asparagus. Journal of Agricultural and Food Chemistry 66 (50):13328–39. doi: 10.1021/acs.jafc.8b05791.
  • Danezis, G. P., A. S. Tsagkaris, F. Camin, V. Brusic, and C. A. Georgiou. 2016. Food authentication: Techniques, trends & emerging approaches. TrAC Trends in Analytical Chemistry 85:123–32. doi: 10.1016/j.trac.2016.02.026.
  • De Girolamo, A., M. C. Arroyo, S. Cervellieri, M. Cortese, M. Pascale, A. F. Logrieco, and V. Lippolis. 2020a. Detection of durum wheat pasta adulteration with common wheat by infrared spectroscopy and chemometrics: A case study. LWT-Food Science and Technology 127:109368. doi: 10.1016/j.lwt.2020.109368.
  • De Girolamo, A., M. C. Arroyo, V. Lippolis, S. Cervellieri, M. Cortese, M. Pascale, A. F. Logrieco, and C. von Holst. 2020b. A simple design for the validation of a FT-NIR screening method: Application to the detection of durum wheat pasta adulteration . Food Chemistry 333:127449. doi: 10.1016/j.foodchem.2020.127449.
  • Del Coco, L., B. Laddomada, D. Migoni, G. Mita, R. Simeone, and F. P. Fanizzi. 2019. Variability and site dependence of grain mineral contents in tetraploid wheats. Sustainability 11 (3):736. doi: 10.3390/su11030736.
  • Di Anibal, C. V., I. Ruisánchez, M. Fernández, R. Forteza, V. Cerdà, and M. Pilar Callao. 2012. Standardization of UV-visible data in a food adulteration classification problem. Food Chemistry 134 (4):2326–31. doi: 10.1016/j.foodchem.2012.03.100.
  • Di Rosa, A. R., F. Leone, F. Cheli, and V. Chiofalo. 2017. Fusion of electronic nose, electronic tongue and computer vision for animal source food authentication and quality assessment – A review. Journal of Food Engineering 210:62–75. doi: 10.1016/j.jfoodeng.2017.04.024.
  • Dong, G., J. Guo, C. Wang, Z. L. Chen, L. Zheng, and D. Z. Zhu. 2015. The classification of wheat varieties based on near infrared hyperspectral imaging and information fusion. Guang pu Xue yu Guang pu Fen xi = Guang pu 35 (12):3369–74. doi: 10.3964/j.issn.1000-0593(2015)12-3369-06.
  • Drivelos, S. A., and C. A. Georgiou. 2012. Multi-element and multi-isotope-ratio analysis to determine the geographical origin of foods in the European Union. TrAC Trends in Analytical Chemistry 40:38–51. doi: 10.1016/j.trac.2012.08.003.
  • Esteki, M., J. Simal-Gandara, Z. Shahsavari, S. Zandbaaf, E. Dashtaki, and Y. Vander Heyden. 2018. A review on the application of chromatographic methods, coupled to chemometrics, for food authentication. Food Control 93:165–82. doi: 10.1016/j.foodcont.2018.06.015.
  • Frigerio, J., R. Pellesi, V. Mezzasalma, F. De Mattia, A. Galimberti, F. Lambertini, M. Suman, S. Zanardi, A. Leporati, and M. Labra. 2019. Development of a DNA barcoding-like approach to detect mustard allergens in wheat flours. Genes 10 (3):234. doi: 10.3390/genes10030234.
  • Fritz, J., M. Athmann, T. Kautz, and U. Kopke. 2011. Grouping and classification of wheat from organic and conventional production systems by combining three image forming methods. Biological Agriculture & Horticulture 27 (3-4):320–36. doi: 10.1080/01448765.2011.648918.
  • Fu, X., J. Chen, F. Fu, and C. Wu. 2020. Discrimination of talcum powder and benzoyl peroxide in wheat flour by near-infrared hyperspectral imaging. Biosystems Engineering 190:120–30. doi: 10.1016/j.biosystemseng.2019.12.006.
  • Ghisoni, S., L. Lucini, F. Angilletta, G. Rocchetti, D. Farinelli, S. Tombesi, and M. Trevisan. 2019. Discrimination of extra-virgin-olive oils from different cultivars and geographical origins by untargeted metabolomics. Food Research International (Ottawa, ON) 121:746–53. doi: 10.1016/j.foodres.2018.12.052.
  • Goitom Asfaha, D., C. R. Quétel, F. Thomas, M. Horacek, B. Wimmer, G. Heiss, C. Dekant, P. Deters-Itzelsberger, S. Hoelzl, S. Rummel, et al. 2011. Combining isotopic signatures of n(87Sr)/n(86Sr) and light stable elements (C, N, O, S) with multi-elemental profiling for the authentication of provenance of European cereal samples. Journal of Cereal Science 53 (2):170–7. doi: 10.1016/j.jcs.2010.11.004.
  • Gonzalez-Martin, M. I., G. W. Moncada, C. Gonzalez-Perez, N. Z. San Martin, F. Lopez-Gonzalez, I. L. Ortega, and J. M. Hernandez-Hierro. 2014. Chilean flour and wheat grain: Tracing their origin using near infrared spectroscopy and chemometrics. Food Chemistry 145:802–6. doi: 10.1016/j.foodchem.2013.08.103.
  • Helfenstein, J., I. Muller, R. Gruter, G. Bhullar, L. Mandloi, A. Papritz, M. Siegrist, R. Schulin, and E. Frossard. 2016. Organic wheat farming improves grain zinc concentration. Plos One 11 (8):e0160729. doi: 10.1371/journal.pone.0160729.
  • Ishida, Y., K. Nakamura, K. Ariyama, and A. Kawasaki. 2014. Identification of geographic origin of wheat grain using trace-element concentrations and heavy element isotopic ratios. Bunseki Kagaku 63 (3):255–61. doi: 10.2116/bunsekikagaku.63.255.
  • Kahl, J., N. Busscher, G. Mergardt, P. Mader, T. Torp, and A. Ploeger. 2015. Differentiation of organic and non-organic winter wheat cultivars from a controlled field trial by crystallization patterns. Journal of the Science of Food and Agriculture 95 (1):53–8. doi: 10.1002/jsfa.6818.
  • Kamal, M., and R. Karoui. 2015. Analytical methods coupled with chemometric tools for determining the authenticity and detecting the adulteration of dairy products: A review. Trends in Food Science & Technology 46 (1):27–48. doi: 10.1016/j.tifs.2015.07.007.
  • Khorshidi, A. S., N. Ames, R. Cuthbert, E. Sopiwnyk, and S. J. Thandapilly. 2019. Application of low-intensity ultrasound as a rapid, cost-effective tool to wheat screening: Discrimination of Canadian varieties at 10 MHz. Journal of Cereal Science 88:9–15. doi: 10.1016/j.jcs.2019.05.001.
  • Lakshmi, V. 2012. Food adulterations. International Journal of Science Invention Today 1 (2):106–13.
  • Lamanna, R., L. Cattivelli, M. L. Miglietta, and A. Troccoli. 2011. Geographical origin of durum wheat studied by 1H-NMR profiling. Magnetic Resonance in Chemistry: MRC 49 (1):1–5. doi: 10.1002/mrc.2695.
  • Laursen, K. H., A. Mihailova, S. D. Kelly, N. Epo, S. Bérail, J. K. Schjoerring, O. F. X. Donard, E. H. Larsen, N. Pedentchouk, A. D. Marca-Bell, et al. 2013. Is it really organic?-multi-isotopic analysis as a tool to discriminate between organic and conventional plants . Food Chemistry 141 (3):2812–20. doi: 10.1016/j.foodchem.2013.05.068.
  • Laursen, K. H., J. K. Schjoerring, S. D. Kelly, and S. Husted. 2014. Authentication of organically grown plants – advantages and limitations of atomic spectroscopy for multi-element and stable isotope analysis. Trac Trends in Analytical Chemistry 59:73–82. doi: 10.1016/j.trac.2014.04.008.
  • Laursen, K. H., J. K. Schjoerring, J. E. Olesen, M. Askegaard, U. Halekoh, and S. Husted. 2011. Multielemental fingerprinting as a tool for authentication of organic wheat, barley, faba bean, and potato. Journal of Agricultural and Food Chemistry 59 (9):4385–96. doi: 10.1021/jf104928r.
  • Levandi, T., T. Pussa, M. Vaher, A. Ingver, R. Koppel, and M. Kaljurand. 2014. Principal component analysis of HPLC-MS/MS patterns of wheat (Triticum aestivum) varieties. Proceedings of the Estonian Academy of Sciences 63 (1):86–92. doi: 10.3176/proc.2014.1.11.
  • Liang, K., S. Liang, L. Lu, D. Zhu, and L. Cheng. 2018. Geographical origin traceability of foxtail millet based on the combination of multi-element and chemical composition analysis. International Journal of Food Properties 21 (1):1769–77. doi: 10.1080/10942912.2018.1506479.
  • Li, Q., L. Chen, Q. Ding, and G. Lin. 2013. The stable isotope signatures of blackcurrant (Ribes nigrum L.) in main cultivation regions of China: Implications for tracing geographic origin. European Food Research and Technology 237 (2):109–16. doi: 10.1007/s00217-013-1967-0.
  • Li, C., H. Dong, D. Luo, Y. Xian, and X. Fu. 2016. Recent developments in application of stable isotope and multi-element analysis on geographical origin traceability of cereal grains. Food Analytical Methods 9 (6):1512–9. doi: 10.1007/s12161-015-0328-y.
  • Liu, H., B. Guo, Y. Wei, S. Wei, Y. Ma, and W. Zhang. 2015. Effects of region, genotype, harvest year and their interactions on δ13C, δ15N and δD in wheat kernels. Food Chemistry 171:56–61. doi: 10.1016/j.foodchem.2014.08.111.
  • Liu, H., B. Guo, B. Zhang, Y. Zhang, S. Wei, M. Li, S. Wadood, and Y. Wei. 2018. Characterizations of stable carbon and nitrogen isotopic ratios in wheat fractions and their feasibility for geographical traceability: A preliminary study. Journal of Food Composition and Analysis 69:149–55. doi: 10.1016/j.jfca.2018.01.009.
  • Liu, H., Y. Wei, H. Lu, S. Wei, T. Jiang, Y. Zhang, J. Ban, and B. Guo. 2017b. The determination and application of (87) Sr/(86) Sr ratio in verifying geographical origin of wheat. Journal of Mass Spectrometry: JMS 52 (4):248–53. doi: 10.1002/jms.3930.
  • Liu, H., Y. Wei, H. Lu, S. Wei, T. Jiang, Y. Zhang, and B. Guo. 2016. Combination of the (87)Sr/(86)Sr ratio and light stable isotopic values (δ(13)C, δ(15)N and δD) for identifying the geographical origin of winter wheat in China. Food Chemistry 212:367–73. doi: 10.1016/j.foodchem.2016.06.002.
  • Liu, H., Y. Wei, S. Wei, T. Jiang, S. Zhang, and B. Guo. 2017a. δ2H of wheat and soil water in different growth stages and their application potentialities as fingerprints of geographical origin. Food Chemistry 226:135–40. doi: 10.1016/j.foodchem.2017.01.029.
  • Liu, H., Y. Wei, Y. Zhang, S. Wei, S. Zhang, and B. Guo. 2017c. The effectiveness of multi-element fingerprints for identifying the geographical origin of wheat. International Journal of Food Science & Technology 52 (4):1018–25. doi: 10.1111/ijfs.13366.
  • Lohumi, S., S. Lee, H. Lee, and B.-K. Cho. 2015. A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration. Trends in Food Science & Technology 46 (1):85–98. doi: 10.1016/j.tifs.2015.08.003.
  • Luo, D., H. Dong, H. Luo, Y. Xian, J. Wan, X. Guo, and Y. Wu. 2015. The application of stable isotope ratio analysis to determine the geographical origin of wheat. Food Chemistry 174:197–201. doi: 10.1016/j.foodchem.2014.11.006.
  • Luykx, D. M. A. M., and S. M. van Ruth. 2008. An overview of analytical methods for determining the geographical origin of food products. Food Chemistry 107 (2):897–911. doi: 10.1016/j.foodchem.2007.09.038.
  • Ma, H. L., J. W. Wang, Y. J. Chen, J. L. Cheng, and Z. T. Lai. 2017. Rapid authentication of starch adulterations in ultrafine granular powder of Shanyao by near-infrared spectroscopy coupled with chemometric methods. Food Chemistry 215:108–15. doi: 10.1016/j.foodchem.2016.07.156.
  • Maione, C., and R. M. Barbosa. 2019. Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review. Critical Reviews in Food Science and Nutrition 59 (12):1868–79. doi: 10.1080/10408398.2018.1431763.
  • Márquez, C., M. I. López, I. Ruisánchez, and M. P. Callao. 2016. FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud. Talanta 161:80–6. doi: 10.1016/j.talanta.2016.08.003.
  • Mayer, J., L. Gunst, P. Mader, M. F. Samson, M. Carcea, V. Narducci, I. K. Thomsen, and D. Dubois. 2015. Productivity, quality and sustainability of winter wheat under long-term conventional and organic management in Switzerland. European Journal of Agronomy 65:27–39. doi: 10.1016/j.eja.2015.01.002.
  • McGrath, T. F., S. A. Haughey, J. Patterson, C. Fauhl-Hassek, J. Donarski, M. Alewijn, S. van Ruth, and C. T. Elliott. 2018. What are the scientific challenges in moving from targeted to non-targeted methods for food fraud testing and how can they be addressed? – Spectroscopy case study. Trends in Food Science & Technology 76:38–55. doi: 10.1016/j.tifs.2018.04.001.
  • Miano, B., L. Righetti, R. Piro, C. Dall'Asta, S. Folloni, G. Galaverna, and M. Suman. 2018. Direct analysis real-time-high-resolution mass spectrometry for Triticum species authentication. Food Additives & Contaminants. Part A, Chemistry, Analysis, Control, Exposure & Risk Assessment 35 (12):2291–7. doi: 10.1080/19440049.2018.1520398.
  • Neacsu, A., G. ŞErban, C. TuţA˘, and I. Toncea, 2010. Baking quality of wheat cultivars, grown in organic, conventional and low input agricultural systems. Romanian Agricultural Research 27:35–42.
  • Oliveira, M. M., J. P. Cruz‐Tirado, and D. F. Barbin. 2019. Nontargeted analytical methods as a powerful tool for the authentication of spices and herbs: A review. Comprehensive Reviews in Food Science and Food Safety 18 (3):670–89. doi: 10.1111/1541-4337.12436.
  • Otaka, A., A. Hokura, and I. Nakai. 2014. Determination of trace elements in soybean by X-ray fluorescence analysis and its application to identification of their production areas. Food Chemistry 147:318–26. doi: 10.1016/j.foodchem.2013.09.142.
  • Otaka, A., Y. Yanada, A. Hokura, K. Matsuda, and I. Nakai. 2009. Determination of trace elements in wheat flour by x-ray fluorescence analysis and its application to identification of their production area. Bunseki Kagaku 58 (12):1011–22. doi: 10.2116/bunsekikagaku.58.1011.
  • Paolini, M., L. Ziller, K. H. Laursen, S. Husted, and F. Camin. 2015. Compound-specific δ15N and δ13C analyses of amino acids for potential discrimination between organically and conventionally grown wheat. Journal of Agricultural and Food Chemistry 63 (25):5841–50. doi: 10.1021/acs.jafc.5b00662.
  • Pastor, K., M. Acanski, D. Vujic, G. Bekavac, S. Milovac, and S. Kravic. 2016a. Rapid method for small grain and corn flour authentication using GC/EI-MS and multivariate analysis. Food Analytical Methods 9 (2):443–50. doi: 10.1007/s12161-015-0215-6.
  • Pastor, K., M. Acanski, D. Vujic, D. Jovanovic, and S. Wienkoop. 2016b. Authentication of cereal flours by multivariate analysis of GC-MS Data. Chromatographia 79 (19-20):1387–93. doi: 10.1007/s10337-016-3142-9.
  • Pastor, K., M. Acanski, D. Vujic, and P. Kojic. 2019. A rapid dicrimination of wheat, walnut and hazelnut flour samples using chemometric algorithms on GC/MS data. Journal of Food Measurement and Characterization 13 (4):2961–9. doi: 10.1007/s11694-019-00216-2.
  • Pauli, E. D., F. Barbieri, P. S. Garcia, T. B. Madeira, V. R. Acquaro, I. S. Scarminio, C. A. P. da Camara, and S. L. Nixdorf. 2014. Detection of ground roasted coffee adulteration with roasted soybean and wheat. Food Research International 61:112–9. doi: 10.1016/j.foodres.2014.02.032.
  • Pazoki, A., and Z. Pazoki. 2011. Classification system for rain fed wheat grain cultivars using artificial neural network. African Journal of Biotechnology 10 (41):8031–8. doi: 10.5897/AJB11.488.
  • Pegels, N., I. Gonzalez, T. Garcia, and R. Martin. 2015. Authenticity testing of wheat, barley, rye and oats in food and feed market samples by real-time PCR assays. LWT - Food Science and Technology 60 (2):867–75. doi: 10.1016/j.lwt.2014.10.049.
  • Perry, D. J., and S. J. Lee. 2015. Identification of Canadian wheat varieties using OpenArray genotyping technology. Journal of Cereal Science 65:267–76. doi: 10.1016/j.jcs.2015.08.002.
  • Podio, N. S., M. V. Baroni, R. G. Badini, M. Inga, H. A. Ostera, M. Cagnoni, E. A. Gautier, P. P. García, J. Hoogewerff, and D. A. Wunderlin. 2013. Elemental and isotopic fingerprint of Argentinean wheat. matching soil, water, and crop composition to differentiate provenance. Journal of Agricultural and Food Chemistry 61 (16):3763–73. doi: 10.1021/jf305258r.
  • Rachmawati Rohaeti, E., and M. Rafi. 2017. Combination of near infrared spectroscopy and chemometrics for authentication of taro flour from wheat and sago flour. Journal of Physics Conference 835:012011. doi: 10.1088/1742-6596/835/1/012011.
  • Rascio, A., E. Carlino, G. D. Santis, and N. D. Fonzo. 2013. A discriminant analysis to categorize durum wheat varieties in drought-tolerance classes on the basis of rheological and physiological traits. Cereal Research Communications 41 (1):88–96. doi: 10.1556/CRC.2012.0016.
  • Rashmi, D., P. Shree, and D. K. Singh. 2017. Stable isotope ratio analysis in determining the geographical traceability of Indian wheat. Food Control 79:169–76. doi: 10.1016/j.foodcont.2017.03.025.
  • Righetti, L., J. Rubert, G. Galaverna, K. Hurkova, C. Dall'Asta, J. Hajslova, and M. Stranska-Zachariasova. 2018. A novel approach based on untargeted lipidomics reveals differences in the lipid pattern among durum and common wheat. Food Chemistry 240:775–83. doi: 10.1016/j.foodchem.2017.08.020.
  • Rocha, L. D. O., G. M. Reis, V. N. D. Silva, R. Braghini, M. M. G. Teixeira, and B. Correa. 2011. Molecular characterization and fumonisin production by Fusarium verticillioides isolated from corn grains of different geographical origins in Brazil. International Journal of Food Microbiology 145 (1):9–21. doi: 10.1016/j.ijfoodmicro.2010.11.001.
  • Rodríguez Silvio, D., R. Guido, and B. M. Pilar. 2019. Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods. Food Chemistry 274:392–401. doi: 10.1016/j.foodchem.2018.08.140.
  • Russo, R.,. E. Cusano, A. Perissi, F. Ferron, V. Severino, A. Parente, and A. Chambery. 2014. Ultra-high performance liquid chromatography tandem mass spectrometry for the detection of durum wheat contamination or adulteration. Journal of Mass Spectrometry: JMS 49 (12):1239–46. doi: 10.1002/jms.3451.
  • Sezer, B., H. Apaydin, G. Bilge, and I. H. Boyaci. 2018. Coffee arabica adulteration: Detection of wheat, corn and chickpea. Food Chemistry 264:142–8. doi: 10.1016/j.foodchem.2018.05.037.
  • Silletti, S., L. Morello, F. Gavazzi, S. Giani, L. Braglia, and D. Breviario. 2019. Untargeted DNA-based methods for the authentication of wheat species and related cereals in food products. Food Chemistry 271:410–8. doi: 10.1016/j.foodchem.2018.07.178.
  • Sonnante, G., C. Montemurro, A. Morgese, W. Sabetta, A. Blanco, and A. Pasqualone. 2009. DNA microsatellite region for a reliable quantification of soft wheat adulteration in durum wheat-based foodstuffs by real-time PCR. Journal of Agricultural and Food Chemistry 57 (21):10199–204. doi: 10.1021/jf902624z.
  • Spink, J., and D. C. Moyer. 2011. Defining the public health threat of food fraud. Journal of Food Science 76 (9):R157–163. doi: 10.1111/j.1750-3841.2011.02417.x.
  • Stark, T. D., P. Weiss, L. Friedrich, and T. Hofmann. 2020. The wheat species profiling by non-targeted UPLC–ESI–TOF-MS analysis. European Food Research and Technology 246 (8):1617–26. doi: 10.1007/s00217-020-03517-9.
  • Stolz, P., and J. Strube. 2010. Determination of the physiological amino acid status for identification of the culture system of wheat and carrots—method and validation. Biological Agriculture & Horticulture 27 (1):107–27. doi: 10.1080/01448765.2010.10510433.
  • Stracke, B. A., J. Eitel, B. Watzl, P. Mader, and C. E. Rufer. 2009. Influence of the production method on phytochemical concentrations in whole wheat (Triticum aestivum L.): A comparative study. Journal of Agricultural and Food Chemistry 57 (21):10116–21. doi: 10.1021/jf901267z.
  • Su, W. H., and D. W. Sun. 2017. Evaluation of spectral imaging for inspection of adulterants in terms of common wheat flour, cassava flour and corn flour in organic Avatar wheat (Triticum spp.) flour. Journal of Food Engineering 200:59–69. doi: 10.1016/j.jfoodeng.2016.12.014.
  • Szulc, M., J. Kahl, N. Busscher, G. Mergardt, P. Doesburg, and A. Ploeger. 2010. Discrimination between organically and conventionally grown winter wheat farm pair samples using the copper chloride crystallisation method in combination with computerised image analysis. Computers and Electronics in Agriculture 74 (2):218–22. doi: 10.1016/j.compag.2010.08.001.
  • Turmel, M. S., M. H. Entz, K. C. Bamford, and J. R. Thiessen Martens. 2009. The influence of crop rotation on the mineral nutrient content of organic vs. conventionally produced wheat grain: Preliminary results from a long-term field study. Canadian Journal of Plant Science 89 (5):915–9. doi: 10.4141/CJPS09006.
  • Van Stappen, F., A. Loriers, M. Mathot, V. Planchon, D. Stilmant, and D. Frédéric. 2015. Organic versus conventional farming: The case of wheat production in wallonia (Belgium). Agriculture and Agricultural Science Procedia 7:272–9. doi: 10.1016/j.aaspro.2015.12.047.
  • Vemireddy, L. R., V. V. Satyavathi, E. A. Siddiq, and J. Nagaraju. 2015. Review of methods for the detection and quantification of adulteration of rice: Basmati as a case study. Journal of Food Science and Technology 52 (6):3187–202. doi: 10.1080/10408398.2018.1431763.
  • Verdu, S., F. Vasquez, R. Grau, E. Ivorra, A. J. Sanchez, and J. M. Barat. 2016. Detection of adulterations with different grains in wheat products based on the hyperspectral image technique: The specific cases of flour and bread. Food Control 62:373–80. doi: 10.1016/j.foodcont.2015.11.002.
  • Vlachos, A., and I. S. Arvanitoyannis. 2008. A review of rice authenticity/adulteration methods and results. Critical Reviews in Food Science and Nutrition 48 (6):553–98. doi: 10.1080/10408390701558175.
  • Vrček, I. V., D. V. Čepo, D. Rašić, M. Peraica, I. Žuntar, M. Bojić, G. Mendaš, and M. Medić-Šarić. 2014. A comparison of the nutritional value and food safety of organically and conventionally produced wheat flours. Food Chemistry 143:522–9. doi: 10.1016/j.foodchem.2013.08.022.
  • Vrcek, V., and I. V. Vrcek. 2012. Metals in organic and conventional wheat flours determined by an optimised and validated ICP-MS method. International Journal of Food Science and Technology 47 (8):1777–83. doi: 10.1111/j.1365-2621.2012.03034.x.
  • Wadood, S. A., B. Guo, H. Liu, S. Wei, X. Bao, and Y. Wei. 2018. Study on the variation of stable isotopic fingerprints of wheat kernel along with milling processing. Food Control 91:427–33. doi: 10.1016/j.foodcont.2018.03.045.
  • Wadood, S. A., B. Guo, and Y. Wei. 2019a. Geographical traceability of wheat and its products using multielement light stable isotopes coupled with chemometrics. Journal of Mass Spectrometry: JMS 54 (2):178–88. doi: 10.1002/jms.4312.
  • Wadood, S. A., B. Guo, X. Zhang, I. Hussain, and Y. Wei. 2020a. Recent development in the application of analytical techniques for the traceability and authenticity of food of plant origin. Microchemical Journal 152:104295. doi: 10.1016/j.microc.2019.104295.
  • Wadood, S. A., B. Guo, X. Zhang, A. Raza, and Y. Wei. 2020b. Geographical discrimination of Chinese winter wheat using volatile compound analysis by HS-SPME/GC-MS coupled with multivariate statistical analysis. Journal of Mass Spectrometry: JMS 55 (1):e4453. doi: 10.1002/jms.4453.
  • Wadood, S. A., B. Guo, X. Zhang, and Y. Wei. 2019b. Geographical origin discrimination of wheat kernel and white flour using near‐infrared reflectance spectroscopy fingerprinting coupled with chemometrics. International Journal of Food Science & Technology 54 (6):2045–54. doi: 10.1111/ijfs.14105.
  • Wang, F., H. Y. Zhao, C. Yu, J. Tang, W. Wu, and Q. Yang. 2020. Determination of the geographical origin of Maize (Zea mays L.) using mineral element fingerprints. Journal of the Science of Food and Agriculture 100 (3):1294–300. doi: 10.1002/jsfa.10144.
  • Weesepoel, Y., S. Heenan, R. Boerrigter-Eenling, T. Venderink, M. Blokland, and S. Van Ruth. 2016. Protocatechuic acid levels discriminate between organic and conventional wheat from Denmark. CHIMIA International Journal for Chemistry 70 (5):360–3. doi: 10.2533/chimia.2016.360.
  • Wilkes, T., G. Nixon, C. Bushell, A. Waltho, A. Alroichdi, and M. Burns. 2016. Feasibility study for applying spectral imaging for wheat grain authenticity testing in pasta. Food and Nutrition Sciences 7 (5):355–61. doi: 10.4236/fns.2016.75037.
  • Wu, Y., D. Luo, H. Dong, J. Wan, H. Luo, Y. Xian, X. Guo, F. Qin, W. Han, L. Wang, et al. 2015. Geographical origin of cereal grains based on element analyser-stable isotope ratio mass spectrometry (EA-IRMS). Food Chemistry 174:553–7. doi: 10.1016/j.foodchem.2014.11.096.
  • Yilmaz, R., C. Bayrac, A. Basman, and H. Koksel. 2019. Development of SYBR green-based real time PCR assays for detection and quantification of adulteration in wheat-based composite breads and their in-house validation. Journal of Cereal Science 85:91–7. doi: 10.1016/j.jcs.2018.11.020.
  • Zapotoczny, P. 2011a. Discrimination of wheat grain varieties using image analysis: Morphological features. European Food Research and Technology 233 (5):769–79. doi: 10.1007/s00217-011-1573-y.
  • Zapotoczny, P. 2011b. Discrimination of wheat grain varieties using image analysis and neural networks. Part I. Single kernel texture. Journal of Cereal Science 54 (1):60–8. doi: 10.1016/j.jcs.2011.02.012.
  • Zapotoczny, P. 2014. Discrimination of wheat grain varieties using image analysis and multidimensional analysis texture of grain mass. International Journal of Food Properties 17 (1):139–51. doi: 10.1080/10942912.2011.615085.
  • Zhai, Y. F., Q. Su, W. J. Wu, Z. T. He, Z. Y. Zhang, J. S. An, J. Dong, X. Deng, C. G. Han, J. L. Yu, et al. 2010. Fast discrimination of varieties of transgene wheat based on biomimetic pattern recognition and near infrared spectra. Guang pu Xue yu Guang pu Fen xi = Guang pu 30 (4):924–8. doi: 10.3964/j.issn.1000-0593(2010)04-0924-05.
  • Zhao, H., B. Guo, Y. Wei, and B. Zhang. 2012. Effects of wheat origin, genotype, and their interaction on multielement fingerprints for geographical traceability. Journal of Agricultural and Food Chemistry 60 (44):10957–62. doi: 10.1021/jf3021283.
  • Zhao, H., B. Guo, Y. Wei, and B. Zhang. 2013a. Multi-element composition of wheat grain and provenance soil and their potentialities as fingerprints of geographical origin. Journal of Cereal Science 57 (3):391–7. doi: 10.1016/j.jcs.2013.01.008.
  • Zhao, H., B. Guo, Y. Wei, and B. Zhang. 2013b. Near infrared reflectance spectroscopy for determination of the geographical origin of wheat. Food Chemistry 138 (2-3):1902–7. doi: 10.1016/j.foodchem.2012.11.037.
  • Zhao, H., B. Guo, Y. Wei, and B. Zhang. 2014. Effects of grown origin, genotype, harvest year, and their interactions of wheat kernels on near infrared spectral fingerprints for geographical traceability. Food Chemistry 152:316–22. doi: 10.1016/j.foodchem.2013.11.122.
  • Zhao, H., B. Guo, Y. Wei, B. Zhang, S. Sun, L. Zhang, and J. H. Yan. 2011. Determining the geographic origin of wheat using multielement analysis and multivariate statistics. Journal of Agricultural and Food Chemistry 59 (9):4397–402. doi: 10.1021/jf200108d.
  • Zhou, B., J. Wang, and J. F. Qi. 2012. Identification of different wheat seeds by electronic nose. International Agrophysics 26 (4):413–8. doi: 10.2478/v10247-012-0058-y.
  • Zhu, Y. F., J. Hu, R. Han, Y. Wang, and S. J. Zhu. 2011. Fingerprinting and identification of closely related wheat (Triticum aestivum L.) cultivars using ISSR and fluorescence-labeled TP-M13-SSR markers. Australian Journal of Crop Science 5 (7):846–50. doi: 10.1002/ps.2124.
  • Ziegler, J. U., M. Leitenberger, C. F. H. Longin, T. Wurschum, R. Carle, and R. M. Schweiggert. 2016. Near-infrared reflectance spectroscopy for the rapid discrimination of kernels and flours of different wheat species. Journal of Food Composition and Analysis 51:30–6. doi: 10.1016/j.jfca.2016.06.005.
  • Zorb, C., G. Langenkamper, T. Betsche, K. Niehaus, and A. Barsch. 2006. Metabolite profiling of wheat grains (Triticum aestivum L.) from organic and conventional agriculture. Journal of Agricultural and Food Chemistry 54 (21):8301–6. doi: 10.1021/jf802923r.
  • Zorb, C., K. Niehaus, A. Barsch, T. Betsche, and G. Langenkamper. 2009. Levels of compounds and metabolites in wheat ears and grains in organic and conventional agriculture. Journal of Agricultural and Food Chemistry 57 (20):9555–62. doi: 10.1021/jf9019739.
  • Zuchowski, J., K. Jonczyk, L. Pecio, and W. Oleszek. 2011. Phenolic acid concentrations in organically and conventionally cultivated spring and winter wheat. Journal of the Science of Food and Agriculture 91 (6):1089–95. doi:10.1002/jsfa.4288. PMID:21308690
  • Żuchowski, J., I. Kapusta, B. Szajwaj, K. Jończyk, and W. Oleszek. 2009. Phenolic acid content of organic and conventionally grown winter wheat. Cereal Research Communications 37 (2):189–97. doi:10.1556/CRC.37.2009.2.5.

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