Application of Taguchi design of experiments in the food industry: a systematic literature review

References

• Abrunhosa, L., Venâncio, A., & Teixeira, J.A. (2011). Optimisation of process parameters for the production of an OTA-hydrolyzing enzyme from Aspergillus niger under solid-state fermentation. Journal of Bioscience and Bioengineering, 112(4), 351–355. https://doi.org/10.1016/j.jbiosc.2011.06.016
   PubMed Web of Science ®Google Scholar
• Ahangari, H., King, J.W., Ehsani, A., & Yousefi, M. (2021). Supercritical fluid extraction of seed oils – A short review of current trends. Trends in Food Science & Technology, 111, 249–260. https://doi.org/10.1016/j.tifs.2021.02.066
   Web of Science ®Google Scholar
• Ansaripoor, A., Sedghi, M., Sadeghi-Sefidmazgi, A., & Pilevar, M. (2020). Optimisation of growth performance responses of Japanese quail with different concentrations of metabolisable energy, lysine, and sulfur amino acids using Taguchi method. Livestock Science, 241, 104234. https://doi.org/10.1016/j.livsci.2020.104234
   Web of Science ®Google Scholar
• Antony, J. (2001). Improving the manufacturing process quality using design of experiments: A case study. International Journal of Operations & Production Management, 21(5/6), 812–822. https://doi.org/10.1108/01443570110390499
   Web of Science ®Google Scholar
• Antony, J. (2014). Design of experiments for engineers and scientists. Elsevier.
   Google Scholar
• Antony, J., & Kaye, M. (1997). Design of experiments for improving the product and process integrity. Total Quality Management, 8(2–3), 75–78. https://doi.org/10.1080/0954412979730
   Web of Science ®Google Scholar
• Antony, J., & Kaye, M. (2000). Experimental quality: A strategic approach to achieve and improve quality. Kluwer Academic.
   Google Scholar
• Besseris, G.J. (2009). Multi-response unreplicated-saturated Taguchi designs and super-ranking in food formulation improvement. International Journal of Quality & Reliability Management, 26(4), 341–368. https://doi.org/10.1108/02656710910950342
   Google Scholar
• Besseris, G.J. (2018). Taguchi-generalized regression neural network micro-screening. Heliyon, 4(3), e00551. https://doi.org/10.1016/j.heliyon.2018.e00551
   PubMedGoogle Scholar
• Bhat, V.S., Bhat, S., & Gijo, E.V. (2020). Robust design of proportional integral controllers: A Taguchi-grey approach. International Journal of Modelling, Identification and Control, 35(4), 363–375. https://doi.org/10.1504/IJMIC.2020.114791
   Web of Science ®Google Scholar
• Bhat, V.S., Bhat, S., & Gijo, E.V. (2021). Simulation-based lean six sigma for Industry 4.0: An action research in the process industry. International Journal of Quality and Reliability Management, 38(5), 1215–1245. https://doi.org/10.1108/IJQRM-05-2020-0167
   Web of Science ®Google Scholar
• Blackhall, R.B., Ritchie, J.M., Baxter, L.F., & Black, I. (2006). The novel combination of Taguchi methods and texture profile analysis applied to the optimisation of laboratory-based biscuit manufacturing. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 220(2), 273–293. https://doi.org/10.1243/095440506X78174
   Web of Science ®Google Scholar
• Booth, A., Sutton, A., & Papaioannou, D. (2016). Systematic approaches to a successful literature review (2nd ed.). SAGE Publications.
   Google Scholar
• Bouranta, N., Psomas, E., & Antony, J. (2022). Human factors involved in lean management: A systematic literature review. Total Quality Management & Business Excellence, 33(9–10), 1113–1145. https://doi.org/10.1080/14783363.2021.1936481
   Web of Science ®Google Scholar
• Box, G., Bisgaard, S., & Fung, C. (1988). An explanation and critique of Taguchi’s contributions to quality engineering. Quality and Reliability Engineering International, 4(2), 123–131. https://doi.org/10.1002/qre.4680040207
   Google Scholar
• Burgess, K., Singh, P.J., & Koroglu, R. (2006). Supply chain management: A structured literature review and implications for future research. International Journal of Operations & Production Management, 26(7), 703–729. https://doi.org/10.1108/01443570610672202
   Web of Science ®Google Scholar
• Chakraborty, S., & Shrivastava, C. (2019). Comparison between multiresponse-robust process design and numerical optimisation: A case study on baking of fermented chickpea flour-based wheat bread. Journal of Food Process Engineering, 42(3), e13008. https://doi.org/10.1111/jfpe.13008
   Web of Science ®Google Scholar
• Chen, W., Lin, Y., Liu, H., & Baroutian, S. (2020). Optimisation of food waste hydrothermal liquefaction by a two-step process in association with a double analysis. Energy, 199, 117438. https://doi.org/10.1016/j.energy.2020.117438
   Web of Science ®Google Scholar
• Chen, X., Ding, J., Ji, D., He, S., & Ma, H. (2020). Optimisation of ultrasonic-assisted extraction conditions for bioactive components from coffee leaves using the Taguchi design and response surface methodology. Journal of Food Science, 85(6), 1742–1751. https://doi.org/10.1111/1750-3841.15111
   PubMed Web of Science ®Google Scholar
• Chung, P.L., Liaw, E.T., Gavahian, M., & Chen, H.H. (2020). Development and optimisation of Djulis sourdough bread using Taguchi Grey relational analysis. Foods (Basel, Switzerland), 9(9), 1–9. https://doi.org/10.3390/foods9091149
   Web of Science ®Google Scholar
• Costa, L.B.M., Filho, M.G., Fredendall, L.D., & Paredes, P.J.G. (2018). Lean, six sigma and lean six sigma in the food industry: A systematic literature review. Trends in Food Science & Technology, 82, 122–133. https://doi.org/10.1016/j.tifs.2018.10.002
   Web of Science ®Google Scholar
• Das, S., & Chatterjee, S.S. (2018). Cabell's blacklist: A new way to tackle predatory journals. Indian Journal of Psychological Medicine, 40(2), 197–198. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6008990.
   PubMedGoogle Scholar
• Davis, R., & John, P. (2018). Application of Taguchi-based design of experiments for industrial chemical processes. Statistical approaches with emphasis on design of experiments applied to chemical processes. In Statistical approaches with emphasis on design of experiments applied to chemical processes. IntechOpen. https://doi.org/10.5772/intechopen.69501
   Google Scholar
• Dimou, M., Marnasidis, S., Antoniadou, I., Pliatsika, M., & Besseris, G.J. (2009). The application of Taguchi method to determine the optimum blend of unifloral honeys to most closely match thyme honey quality. International Journal of Food Science & Technology, 44(10), 1877–1886. https://doi.org/10.1111/j.1365-2621.2008.01899.x
   Web of Science ®Google Scholar
• Doering, C. (2017). 6 of the worst product failures in the food and beverage industry’s history. Food Dive. Retrieved June 5, 2022, from https://www.fooddive.com/news/6-of-the-worst-product-failures-in-the-food-and-beverage-industrys-history/444783/.
   Google Scholar
• Estevão, S.T., Silva, J.B.A., & Lourenço, F.R. (2021). Development and optimization of beer containing malted and non-malted substitutes using quality by design (QbD) approach. Journal of Food Engineering, 289, 110182. https://doi.org/10.1016/j.jfoodeng.2020.110182
   Web of Science ®Google Scholar
• Garza-Reyes, J.A. (2015). Lean and green: A systematic review of the state of the art literature. Journal of Cleaner Production, 102, 18–29. https://doi.org/10.1016/j.jclepro.2015.04.064
   Web of Science ®Google Scholar
• Ghasemian, S., Rezaei, K., Abedini, R., Poorazarang, H., & Ghaziani, F. (2014). Investigation of different parameters on acrylamide production in the fried beef burger using Taguchi experimental design. Journal of Food Science and Technology, 51(3), 440–448. https://doi.org/10.1007/s13197-011-0514-x
   PubMed Web of Science ®Google Scholar
• Ghosh, S., Gillis, A., Levkov, K., Vitkin, E., & Golberg, A. (2020). Saving energy on meat air convection drying with pulsed electric field coupled to mechanical press water removal. Innovative Food Science & Emerging Technologies, 66(9), 102509. https://doi.org/10.1016/j.ifset.2020.102509
   Google Scholar
• Guerra-Zubiaga, D.A., Mamun, A.A., & Gonzalez-Badillo, G. (2018). An energy consumption approach in a manufacturing process using design of experiments. International Journal of Computer Integrated Manufacturing, 31(11), 1067–1077. https://doi.org/10.1080/0951192X.2018.1493234
   Web of Science ®Google Scholar
• Hersleth, M., Bjørn-Helge, M., Naes, T., & Jean-Xavier, G. (2003). Effect of contextual factors on liking for wine - Use of robust design methodology. Food Quality and Preference, 14(7), 615–622. https://doi.org/10.1016/S0950-3293(02)00190-8
   Web of Science ®Google Scholar
• Hoshmand, R. (2018). Design of experiments for agriculture and the natural sciences. Chapman and Hall/CRC.
   Google Scholar
• Hsia, S.-Y., & Yang, S.-K. (2015). Enhancing algal growth by stimulation with LED lighting and ultrasound. Journal of Nanomaterials, 2015(1), 1–11. https://doi.org/10.1155/2015/531352
   Google Scholar
• Ilzarbe, L., Álvarez, M.J., Viles, E., & Tanco, M. (2008). Practical applications of design of experiments in the field of engineering: A bibliographical review. Quality and Reliability Engineering International, 24(4), 417–428. https://doi.org/10.1002/qre.909
   Web of Science ®Google Scholar
• Jafari, S.M., Vakili, S., & Dehnad, D. (2018). Production of a functional yogurt powder fortified with nanoliposomal vitamin D through spray drying. Food and Bioprocess Technology, 12(7), 1220–1231. https://doi.org/10.1007/s11947-019-02289-9
   Web of Science ®Google Scholar
• Jameel, N.J. (2020). Solvent extraction optimisation of chlorophyll dye from conocarpus lancifolius leaves. Journal of Engineering & Technological Sciences, 52(1), 14–27. https://doi.org/10.5614/j.eng.technol.sci.2020.52.1.2
   Web of Science ®Google Scholar
• Javadikia, H., Sabzi, S., & Arribas, J.I. (2018). An automatic and non-intrusive hybrid computer vision system for the estimation of peel thickness in Thomson orange. Spanish Journal of Agricultural Research, 16(4), 1–15. https://doi.org/10.5424/sjar/2018164-11185
   Web of Science ®Google Scholar
• Kasahara, I., Osorio, F., Moyano, P., Pizarro, G., & Beltran, J. (2002). Study of texture and glass transition of French fried potatoes pretreated with soaking solutions. Journal of Food Processing and Preservation, 26(4), 237–257. https://doi.org/10.1111/j.1745-4549.2002.tb00482.x
   Web of Science ®Google Scholar
• Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009). Systematic literature reviews in software engineering – A systematic literature review. Information and Software Technology, 51(1), 7–15. https://doi.org/10.1016/j.infsof.2008.09.009
   Web of Science ®Google Scholar
• Lim, S.A.H., Antony, J., & Albliwi, S. (2014). Statistical process control (SPC) in the food industry – A systematic review and future research agenda. Trends in Food Science & Technology, 37(2), 137–151. https://doi.org/10.1016/j.tifs.2014.03.010
   Web of Science ®Google Scholar
• Lim, S.A.H., Antony, J., Arshed, N., & Albliwi, S. (2017). A systematic review of statistical process control implementation in the food manufacturing industry. Total Quality Management & Business Excellence, 28(1–2), 176–189. https://doi.org/10.1080/14783363.2015.1050181
   Web of Science ®Google Scholar
• Liu, X., Bourvellec, C.L., Yu, J., Zhao, L., Wang, K., Tao, Y., Renard, C.M.G.C., & Hu, Z. (2022). Trends and challenges on fruit and vegetable processing: Insights into sustainable, traceable, precise, healthy, intelligent, personalized and local innovative food products. Trends in Food Science & Technology, 125, 12–25. https://doi.org/10.1016/j.tifs.2022.04.016
   Web of Science ®Google Scholar
• Lochner, R.H. (1991). Pros and cons of Taguchi. Quality Engineering, 3(4), 537–549. https://doi.org/10.1080/08982119108918882
   Google Scholar
• Lokesh, K.N., Channarayappa, & Venkatarangan, V. (2015). Exemplified screening standardisation of potent antioxidant nutraceuticals by principles of design of experiments. Journal of Functional Foods, 17, 260–270. https://doi.org/10.1016/j.jff.2015.05.023
   Web of Science ®Google Scholar
• Lopes, M., Miranda, S.M., Alves, J.M., Pereira, A.S., & Belo, I. (2019). Waste cooking oils as feedstock for lipase and lipid-rich biomass production. European Journal of Lipid Science and Technology, 121(1), 1800188. https://doi.org/10.1002/ejlt.201800188
   Web of Science ®Google Scholar
• Lundkvist, P., Bergquist, B., & Vanhatalo, E. (2020). Statistical methods – Still ignored? The testimony of Swedish alumni. Total Quality Management & Business Excellence, 31(3–4), 245–262. https://doi.org/10.1080/14783363.2018.1426449
   Web of Science ®Google Scholar
• Macedo, I.S.M., Gallagher, M.J.S., Oliveira, J.C., & Byrne, E.P. (2011). Shelf-life aspects of toasted breakfast cereal with and without fruit. Italian Journal of Food Science, 23, 178–181.
   Web of Science ®Google Scholar
• Maghsoodloo, S., Ozdemir, G., Jordan, V., & Huang, C. (2004). Strengths and limitations of Taguchi’s contributions to quality, manufacturing, and process engineering. Journal of Manufacturing Systems, 23(2), 73–126. https://doi.org/10.1016/S0278-6125(05)00004-X
   Web of Science ®Google Scholar
• Marina, J.P., & George, J.B. (2013). Robust screening of cake product characteristics by the Taguchi method. International Journal of Industrial and Systems Engineering, 14(2), 207–229. https://doi.org/10.1504/IJISE.2013.053737
   Google Scholar
• Mashhadi, A.F., Alänge, S., Gustafsson, G., & Roos, L. (2016). The Volvo robust engineering system: How to make robust design work in an industrial context. Total Quality Management & Business Excellence, 27(5-6), 647–665. https://doi.org/10.1080/14783363.2015.1039938
   Web of Science ®Google Scholar
• May, N.S., & Chappell, P. (2002). Finding critical variables for food heating. International Journal of Food Science and Technology, 37(5), 503–513. https://doi.org/10.1046/j.1365-2621.2002.00607.x
   Web of Science ®Google Scholar
• Minitab. (2018). Example of analyze Taguchi design (dynamic). Retrieved from June 5, 2022, from https://support.minitab.com/en-us/minitab/18/help-and-how-to/modeling-statistics/doe/how-to/taguchi/analyze-taguchi-design/before-you-start/example-of-analyzing-a-dynamic-design/.
   Google Scholar
• Moghadam, M.R.S., Safari, H., & Yousefi, N. (2021). Clustering quality management models and methods: Systematic literature review and text-mining analysis approach. Total Quality Management & Business Excellence, 32(3–4), 241–264. https://doi.org/10.1080/14783363.2018.1540927
   Web of Science ®Google Scholar
• Montgomery, D.C. (1984). Design and analysis of experiments. Wiley.
   Google Scholar
• NOS. (2022). Apply Design of Experiments (DOE) improvement techniques in food operations, IMPQI257. https://www.ukstandards.org.uk/PublishedNos-old/IMPQI257.pdf.
   Google Scholar
• Oztop, M.H., Sahin, S., & Sumnu, G. (2007). Optimisation of microwave frying of potato slices by using Taguchi technique. Journal of Food Engineering, 79(1), 83–91. https://doi.org/10.1016/j.jfoodeng.2006.01.031
   Web of Science ®Google Scholar
• Parameswaran, U.D., Ozawa-Kirk, J.L., & Latendresse, G. (2020). To live (code) or to not: A new method for coding in qualitative research. Qualitative Social Work, 19(4), 630–644. https://doi.org/10.1177/1473325019840394
   Web of Science ®Google Scholar
• Petticrew, M. (2001). Systematic reviews from astronomy to zoology: Myths and misconceptions. BMJ (Clinical Research Ed.), 322(7278), 98–101. https://doi.org/10.1136/bmj.322.7278.98
   PubMed Web of Science ®Google Scholar
• Politis, S.N., Colombo, P., Colombo, G., & Rekkas, D.M. (2017). Design of experiments (DoE) in pharmaceutical development. Drug Development and Industrial Pharmacy, 43(6), 889–901. https://doi.org/10.1080/03639045.2017.1291672
   PubMed Web of Science ®Google Scholar
• Popay, J., Roberts, H., Sowden, A., Petticrew, M., Arai, L., Rodgers, M., & Britten, N. (2006). Guidance on the conduct of narrative synthesis in systematic reviews. University of Lancaster. Retrieved June 11, 2021, from https://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/fhm/dhr/chir/NSsynthesisguidanceVersion1-April2006.pdf.
   Google Scholar
• Rojas-Lema, X., Alfaro-Saiz, J., Rodríguez-Rodríguez, R., & Verdecho, M. (2021). Performance measurement in SMEs: Systematic literature review and research directions. Total Quality Management & Business Excellence, 32(15–16), 1803–1828. https://doi.org/10.1080/14783363.2020.1774357
   Web of Science ®Google Scholar
• Roy, R.K. (2010). A primer on the Taguchi method. Dearborn Society of Manufacturing Engineers.
   Google Scholar
• Saguy, I.S., Singh, R.P., Johnson, T., Fryer, P.J., & Sastry, S.K. (2013). Challenges facing food engineering. Journal of Food Engineering, 119(2), 332–342. https://doi.org/10.1016/j.jfoodeng.2013.05.031
   Web of Science ®Google Scholar
• Salacheep, S., Kasemsiri, P., Pongsa, U., Okhawilai, M., Chindaprasirt, P., & Hiziroglu, S. (2020). Optimisation of ultrasound-assisted extraction of anthocyanins and bioactive compounds from butterfly pea petals using Taguchi method and Grey relational analysis. Journal of Food Science and Technology, 57(10), 3720–3730. https://doi.org/10.1007/s13197-020-04404-7
   PubMed Web of Science ®Google Scholar
• Samanta, A., Goswami, S., & Roy, P.C. (2020). Producing biodiesel and optimized by Taguchi design against palm oil as sustainable alternative fuels in Bangladesh. International Energy Journal, 20(3A), 411–420.
   Google Scholar
• Savelli, E., Murmura, F., Liberatore, L., Casolani, N., & Bravi, L. (2019). Consumer attitude and behaviour towards food quality among the young ones: Empirical evidence from a survey. Total Quality Management & Business Excellence, 30(1-2), 169–183. https://doi.org/10.1080/14783363.2017.1300055
   Web of Science ®Google Scholar
• Scimago Journal and Country Rank. (2020). Scimago Institutional Rank. Retrieved June 11, 2021, from https://www.scimagojr.com/journalrank.php.
   Google Scholar
• Secundo, G., Schena, R., Russo, A., Schiavone, F., & Shams, R. (2022). The impact of digital technologies on the achievement of the sustainable development goals: Evidence from the agri-food sector. Total Quality Management & Business Excellence. Ahead-of-print. https://doi.org/10.1080/14783363.2022.2065981
   Web of Science ®Google Scholar
• Sedghi, M., Golian, A., Esmaeilipour, O., & Van Krimpen, M.M. (2014). Application of the Taguchi method in poultry science: Estimation of the in vitro optimum intrinsic phytase activity of rye, wheat and barley. British Poultry Science, 55(2), 246–252. https://doi.org/10.1080/00071668.2014.883460
   PubMed Web of Science ®Google Scholar
• Siddh, M., Kumar, S., Soni, G., Jain, V., Chandra, C., Jain, R., Sharma, M.K., & Kazancoglu, Y. (2022). Impact of agri-fresh food supply chain quality practices on organizational sustainability. Operations Management Research, 15(1–2), 146–165. https://doi.org/10.1007/s12063-021-00196-x
   Web of Science ®Google Scholar
• Siddh, M.M., Soni, G., Jain, R., & Sharma, M.K. (2018). Structural model of perishable food supply chain quality (PFSCQ) to improve sustainable organizational performance. Benchmarking: An International Journal, 25(7), 2272–2317. https://doi.org/10.1108/BIJ-01-2017-0003
   Web of Science ®Google Scholar
• Siddh, M.M., Soni, G., Jain, R., Sharma, M.K., & Yadav, V. (2017). Agri-fresh food supply chain quality (AFSCQ): A literature review. Industrial Management & Data Systems, 117(9), 2015–2044. https://doi.org/10.1108/IMDS-10-2016-0427
   Web of Science ®Google Scholar
• Siddh, M.M., Soni, G., Jain, R., Sharma, M.K., & Yadav, V. (2021). A framework for managing the agri-fresh food supply chain quality in Indian industry. Management of Environmental Quality, 32(2), 436–451. https://doi.org/10.1108/MEQ-05-2020-0085
   Web of Science ®Google Scholar
• Şimşek, S.T. (2019). Vacuum-combined baking to enhance quality properties of gluten-free cake: Multi-response optimisation study. LWT - Food Science and Technology, 116, 108557. https://doi.org/10.1016/j.lwt.2019.108557
   Web of Science ®Google Scholar
• Singh, A., & Kumar, P. (2019). Storage stability determination of calorie deficit gluten-free biscuit: Taguchi concern. Journal of Food Processing and Preservation, 43(5), e13927. https://doi.org/10.1111/jfpp.13927
   Web of Science ®Google Scholar
• Taguchi, G., & Yokoyama, Y. (1993). Taguchi methods: Design of experiments. ASI Press.
   Google Scholar
• Taran, M., Mohamadian, E., Asadi, S., & Bakhtiyari, S. (2013). Surface active agent production from olive oil in high salt conditions and its process optimisation. Polish Journal of Chemical Technology, 14(4), 30–34. https://doi.org/10.2478/v10026-012-0098-x
   Web of Science ®Google Scholar
• Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375
   Web of Science ®Google Scholar
• Tsang, Y.P., Choy, K.L., Wu, C.H., Ho, G.T.S., Lam, H.Y., & Tang, V. (2018). An intelligent model for assuring food quality in managing a multitemperature food distribution centre. Food Control, 90, 81–97. https://doi.org/10.1016/j.foodcont.2018.02.030
   Web of Science ®Google Scholar
• United Nations. (2018). Food security and nutrition and sustainable agriculture - Sustainable Development Goals Knowledge Platform. Retrieved June 5, 2022, from https://sustainabledevelopment.un.org/topics/foodagriculture.
   Google Scholar
• Xu, C., Siegrist, M., & Hartmann, C. (2021). The application of virtual reality in food consumer behavior research: A systematic review. Trends in Food Science & Technology, 116, 533–544. https://doi.org/10.1016/j.tifs.2021.07.015
   Web of Science ®Google Scholar
• Yang, E.C.L., Khoo-Lattimore, C., & Arcodia, C. (2017). A systematic literature review of risk and gender research in tourism. Tourism Management, 58(C), 89–100. https://doi.org/10.1016/j.tourman.2016.10.011
   Google Scholar