https://doi.org/10.4081/jae.2023.1535
Hyperspectral imaging system to online monitoring the soy flour content in a functional pasta
Published: 4 August 2023
Abstract Views: 1054
PDF: 271
HTML: 22
HTML: 22
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Pasta enriched with soy flour can be considered as a functional food, due to its content in nutraceutical compounds such as isoflavones, carotenoids, and other antioxidants. The quantification of the amount of a functional ingredient is an important step in food authenticity. The availability of non-destructive techniques for quantitative and qualitative analyses of food is therefore desirable. This research aimed to investigate the feasibility of hyperspectral imaging in reflectance mode for the evaluation of the soy flour content, also to investigate the possibility of implementing a feed-back control system to precisely dose the soy flour during the industrial production of pasta. Samples of pasta in shape of spaghetti were produced with durum wheat semolina and soy flour at increasing percentages (0, to 50%, steps of 5%). A feature selection algorithm was used to predict the amount of soy flour. The most influent wavelengths were selected, and a six-term Gauss function was trained, validated, and tested. The identified transfer function was able to predict the percentage of soy flour with high accuracy, with an R2adj value of 0.98 and a Root Mean Square Error of 1.31. The developed system could represent a feasible tool to control the process in a continuous mode.
Altieri, G., Rashvand, M., Mammadov, O., Matera, A., Genovese, F., & Di Renzo, G. C. (2022). Use of wavelength interaction terms to improve near infrared spectroscopy models of donkey milk properties. Journal of Near Infrared Spectroscopy, 30(4), 219-226. doi:10.1177/09670335221097004
DOI: https://doi.org/10.1177/09670335221097004
Baiano, A., Lamacchia, C., Fares, C., Terracone, C., La Notte, E., 2011. Cooking behaviour and acceptability of composite pasta made of semolina and toasted or partially defatted soy flour. LWT - Food Sci. Technol. 44, 1226-1232. https://doi: 10.1016/j.lwt.2010.11.029
DOI: https://doi.org/10.1016/j.lwt.2010.11.029
Beghi, R., Giovenzana, V., Civelli, R., Cini, E. and Guidetti, R. (2013) “Characterisation of olive fruit for the milling process by using visible/near infrared spectroscopy”, Journal of Agricultural Engineering, 44(2), p. e8. doi: 10.4081/jae.2013.e8
DOI: https://doi.org/10.4081/jae.2013.202
Benelli, A., Cevoli, C., Fabbri, A. and Ragni, L. (2022) “Hyperspectral imaging to measure apricot attributes during storage”, Journal of Agricultural Engineering, 53(2). doi: 10.4081/jae.2022.1311.
DOI: https://doi.org/10.4081/jae.2022.1311
Ding, C., and H. Peng., 2005. "Minimum redundancy feature selection from microarray gene expression data." Journal of Bioinformatics and Computational Biology, 3(2), 185–205. doi: 10.1142/s0219720005001004
DOI: https://doi.org/10.1142/S0219720005001004
Darbellay, G. A., and I. Vajda. "Estimation of the information by an adaptive partitioning of the observation space." IEEE Transactions on Information Theory. Vol. 45, Number 4, 1999, pp. 1315–1321. doi: 10.1109/18.761290
DOI: https://doi.org/10.1109/18.761290
Di Monaco, R., Caella, S., Di Marzo, S., Masi, P., 2004. The effect of expectations generated by brand name on the acceptability of dried semolina pasta. Food Qual. Prefer. 15, 429-437. https://doi.org/10.1016/j.foodqual.2003.07.003
DOI: https://doi.org/10.1016/j.foodqual.2003.07.003
Elmasry, G., Wang, N., Elsayed, A. Ngadi, N., 2007. Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry. J. Food Eng. 81, 98–107. https://doi.org/10.1016/j.jfoodeng.2006.10.016
DOI: https://doi.org/10.1016/j.jfoodeng.2006.10.016
Fares, C., Menga, V., Martina, A., Pellegrini, N., Scazzina, F., Torriani, S., 2015. Nutritional profile and cooking quality of a new functional pasta naturally enriched in phenolic acids, added with β-glucan and Bacillus coagulans GBI-30, 6086. J. Cereal Sci. 65, 260-266. https://doi.org/10.1016/j.jcs.2015.07.017
DOI: https://doi.org/10.1016/j.jcs.2015.07.017
Fuad, T., Prabhasankar, P., 2010. Role of ingredients in pasta product quality: a review on recent developments. Crit. Rev. Food Sci. Nutr. 50, 787–798. https://doi: 10.1080/10408390903001693
DOI: https://doi.org/10.1080/10408390903001693
Gowen, A.A., O’Donnell, C.P., Cullen, P.J., Downey, G., Frias, J.M., 2011. Hyperspectral imaging - an emerging process analytical tool for food quality and safety control. Trends Food Sci. Technol. 18, 590-598. https://doi: 10.1016/j.tifs.2007.06.001
DOI: https://doi.org/10.1016/j.tifs.2007.06.001
Lin, C., Popescu, S.C., Huang, S.C., Chang, P.T., Wen, H.L., 2015. A novel reflectance-based model for evaluating chlorophyll concentrations of fresh and water-stressed leaves. Biogeosciences, 12, 49–66. https://doi: doi:10.5194/bg-12-49-2015
DOI: https://doi.org/10.5194/bg-12-49-2015
International Pasta Organization, 2013. The world pasta industry status report. http://www.internationalpasta.org/resources/World%20Pasta%20Industry%20Survey/IPOstatreport2013.pdf. Accessed 23 March 2020
Liu, Y., Pu, H., Sun, D.W., 2017. Hyperspectral imaging technique for evaluating food quality and safety during various processes: A review of recent applications. Trends Food Sci. Technol. 69, 25-35. https://doi.org/10.1016/j.tifs.2017.08.013
DOI: https://doi.org/10.1016/j.tifs.2017.08.013
Matera, A., Altieri, G., Genovese, F., & Di Renzo, G. C. (2021). Improved spectrophotometric models and methods for the non-destructive and effective foodstuff parameters forecastingdoi:10.17660/ActaHortic.2021.1311.50
DOI: https://doi.org/10.17660/ActaHortic.2021.1311.50
Messina, M., 2003. Soyfoods and disease prevention: pt. 1—coronary heart disease. Agro Food Industry Hi. Tech. 14, 7–10.
Omeire, G.C., Umeji, O.F., Obasi, N.E., 2014. Acceptability of noodles produced from blends of wheat, acha and soybean composite flours. Niger. Food J. 32, 31–37. https://doi: 10.1016/S0189-7241(15)30093-X
DOI: https://doi.org/10.1016/S0189-7241(15)30093-X
Pasqualone, A., Gambacorta, G., Summo, C., Caponio, F., Di Miceli, G., Flagella, Z., Marrese, P.P., Piro, G., Perrotta, C., De Bellis, L., Lenucci, M.S., 2016. Functional, textural and sensory properties of dry pasta supplemented with lyophilized tomato matrix or with durum wheat bran extracts produced by supercritical carbon dioxide or ultrasound. Food Chem. 15, 213:545-553. https://doi: 10.1016/j.foodchem.2016.07.006
DOI: https://doi.org/10.1016/j.foodchem.2016.07.006
Piazzolla, F., Amodio, M. L., & Colelli, G. (2017). Spectra evolution over on-vine holding of italia table grapes: Prediction of maturity and discrimination for harvest times using a vis-NIR hyperspectral device. Journal of Agricultural Engineering, 48(2), 109-116. doi:10.4081/jae.2017.639.
DOI: https://doi.org/10.4081/jae.2017.639
Stein, A.J., Rodríguez-Cerezo, E., 2008. Functional Foods in the European Union. European Commission Joint Research Centre Institute for Prospective Technological Studies. Luxembourg: Office for Official Publications of the European Communities. https://publications.jrc.ec.europa.eu/repository/bitstream/JRC43851/jrc43851.pdf. Accessed 23 March 2020
Tripathi, M.K., Mangaraj, S., 2011. Soy food in demand: a present and future perspective. In: (J.E.Maxwell ed.) Soybeans: Cultivation, uses and nutrition. Nova Science Publishers, New York, USA.
Wietrzyk, J., Grynkiewicz, G., Opolski, A., 2005. Phytoestrogens in cancer prevention and therapy — mechanism of their biological activity. Anticancer Res. 25, 2357–2366.
Wilkes, T., Nixon, G., Bushell, C., Waltho, A., Alroichdi, A., Burns, M., 2016. Feasibility study for applying spectral imaging for wheat grain authenticity testing in pasta. Food Nutr. Sci. 7, 355-361. http://dx.doi.org/10.4236/fns.2016.75037
DOI: https://doi.org/10.4236/fns.2016.75037
Workman, J.J., 2016. Concise handbook of analytical spectroscopy, the: theory, applications, and reference materials (in 5 volumes). World Scientific Publishing Co. Pte. Ltd., Singapore.
DOI: https://doi.org/10.1142/8800-vol3
Rafael C. Castro, David S.M. Ribeiro, João L.M. Santos, Ricardo N.M.J. Páscoa, Authentication/discrimination, identification and quantification of cinnamon adulterants using NIR spectroscopy and different chemometric tools: A tutorial to deal with counterfeit samples, Food Control, Volume 147, 2023, 109619, ISSN 0956-7135, https://doi.org/10.1016/j.foodcont.2023.109619.
DOI: https://doi.org/10.1016/j.foodcont.2023.109619
Masithoh, E.R., Pahlawan, M.F.R., Saputri, D.A.S., Abadi, F.R. (2023). Visible-near-infrared spectroscopy and chemometrics for authentication detection of organic soybean flour. Pertanika J. Sci. & Technol. 31 (2): 671 – 688
DOI: https://doi.org/10.47836/pjst.31.2.03
Pahlawan, M.F.R., Murti, B.M.A., Masithoh, R.E. (2022). The potency of Vis/NIR spectroscopy for classification of soybean based of colour. IOP Conf. Series: Earth and Environmental Science, 1018, 012015. doi:10.1088/1755-1315/1018/1/012015
DOI: https://doi.org/10.1088/1755-1315/1018/1/012015
Bianchi, F., Tolve, R., Rainero, G., Bordiga, M., Brennan, C.S., Simonato, B. (2021). Technological, nutritional and sensory properties of pasta fortified with agro-industrial by-products: a review. International Journal of Food Science and Technology, 56, 4356–4366.
DOI: https://doi.org/10.1111/ijfs.15168
IPO. (2021). International Pasta Organization. Annual Report. Available at: https://internationalpasta.org/annual-report/. Accessed: 12 April 2023.
Duda A,, Adamczak J,, Chełmiinska P,, Juszkiewicz J,, Kowalczewski P. (2019). Quality and nutritional/textural properties of durum wheat pasta enriched with cricket powder. Foods, 8:46
DOI: https://doi.org/10.3390/foods8020046
Nilusha, R.A.T., Jayasinghe, J.M.J.K., Perera, O.D.A.N., Perera, P.I.P. (2019). Development of pasta products with nonconventional ingredients and their effect on selected quality characteristics: a brief overview. Int J Food Sci 2019:1-10.
DOI: https://doi.org/10.1155/2019/6750726
Romano, A., Ferranti, P., Gallo, V., Masi, P. (2021). New ingredients and alternatives to durum wheat semolina for a high quality dried pasta. Current Opinion in Food Science, 41:249–259.
DOI: https://doi.org/10.1016/j.cofs.2021.07.005
Nishinari, K., Fang, Y., Guo, S., and Phillips, G.O. (2014). Soy proteins: A review on composition, aggregation and emulsification. Food Hydrocolloids, 39, 301-318. https://doi.org/10.1016/j.foodhyd.2014.01.013
DOI: https://doi.org/10.1016/j.foodhyd.2014.01.013
Wietrzyk, J., Grynkiewicz, G. and Opolski, A. (2005). Phytoestrogens in cancer prevention and therapy - Mechanisms of their biological activity. Anticancer Research, 25(3c), 2357-2366.
Dulger Altiner, D. and Hallac, S. (2020). The effect of soy flour and carob flour addition on the physicochemical, quality, and sensory properties of pasta formulations. Int. J. Agric. Environ. Food Sci., 4(4), 406-417. https://doi.org/10.31015/jaefs.2020.4.3
DOI: https://doi.org/10.31015/jaefs.2020.4.3
Wang, J., Brennan, M.A., Serventi, L., Brennan, C.S. (2021). Impact of functional vegetable ingredients on the technical and nutritional quality of pasta, Critical Reviews in Food Science and Nutrition, DOI: 10.1080/10408398.2021.1895712
DOI: https://doi.org/10.1080/10408398.2021.1895712
Kamble, D.B.; Singh, R.; Rani, S.; Pratap, D. Physicochemical properties, in vitro digestibility and structural attributes of okara-enriched functional pasta. J. Food Process Preserv. 2019, 43, e14232.
DOI: https://doi.org/10.1111/jfpp.14232
Giannetti, V.; Mariani, M.B.; Marini, F.; Biancolillo, A. Effects of thermal treatments on durum wheat pasta flavour during production process: A modelling approach to provide added-value to pasta dried at low temperatures. Talanta 2021, 225, 121955.
DOI: https://doi.org/10.1016/j.talanta.2020.121955
Bogue, J., Collins, O., Troy, A.J. (2017). Chapter 2 - Market analysis and concept development of functional foods. In (Eds Debasis Bagchi, Sreejayan Nair) Developing New Functional Food and Nutraceutical Products. Academic Press, pp.29-45. https://doi.org/10.1016/B978-0-12-802780-6.00002-X.
DOI: https://doi.org/10.1016/B978-0-12-802780-6.00002-X
How to Cite
Romaniello, R. (2023) “Hyperspectral imaging system to online monitoring the soy flour content in a functional pasta”, Journal of Agricultural Engineering, 54(4). doi: 10.4081/jae.2023.1535.
Copyright (c) 2023 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Simona Rainis, Franco Sulli, Sirio Rossano Secondo Cividino, Eliana Cossio, The impact on the landscape, environment and society of new productive chains in a mountain area: strategies, analysis and future perspectives , Journal of Agricultural Engineering: Vol. 43 No. 1 (2012)
- Bhola Paudel, Jayanta Kumar Basak, Seong Woo Jeon, Nibas Chandra Deb, Sijan Karki, Hyeon Tae Kim, Development and field testing of biodegradable seedling plug-tray cutting mechanism for automated vegetable transplanter , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
- Aldo Calcante, Roberto Oberti, Francesco M. Tangorra, Definition of linear regression models to calculate the technical parameters of Italian agricultural tractors , Journal of Agricultural Engineering: Vol. 54 No. 4 (2023)
- Raffaele Cavalli, Stefano Grigolato, Marco Pellegrini, DETERMINATION OF THE FOREST ROAD NETWORK INFLUENCE ON THE SUPPLY CHAIN FOR FIREWOOD PRODUCTION BY DISCRETE EVENT SIMULATION , Journal of Agricultural Engineering: Vol. 42 No. 4 (2011)
- Andrea Setti, Giulio Castelli, Lorenzo Villani, Roberto Ferrise, Elena Bresci, Modelling the impacts of water harvesting and climate change on rainfed maize yields in Senegal , Journal of Agricultural Engineering: Vol. 54 No. 3 (2023)
- Lingxin Bu, Qianwen Kou, Adilet Sugirbay, Jun Chen, Yu Chen, An air-assisted mechanical hill-seeding device for foxtail millet (Setaria italica) , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
- Daniele Duca, Giovanni Riva, Ester Foppa Pedretti, Giuseppe Toscano, Chiara Mengarelli, Giorgio Rossini, Solid biofuels production from agricultural residues and processing by-products by means of torrefaction treatment: the case of sunflower chain , Journal of Agricultural Engineering: Vol. 45 No. 3 (2014)
- Bhola Paudel, Jayanta Kumar Basak, Seong Woo Jeon, Gun Ho Lee, Nibas Chandra Deb, Sijan Karki, Hyeon Tae Kim, Working speed optimization of the fully automated vegetable seedling transplanter , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
- Fabiana Convertino, Ileana Blanco, Evelia Schettini, Giuliano Vox, A nature-based system for improving Mediterranean buildings’ performance: contribution to energy saving by heat transfer reduction and influence of climatic parameters , Journal of Agricultural Engineering: Vol. 54 No. 3 (2023)
- Mario Pirastru, Marcello Niedda, Mirko Castellini, Effects of maquis clearing on the properties of the soil and on the near-surface hydrological processes in a semi-arid Mediterranean environment , Journal of Agricultural Engineering: Vol. 45 No. 4 (2014)
<< < 11 12 13 14 15 16 17 18 19 20 > >>
You may also start an advanced similarity search for this article.
