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Boosting protein yield from mustard (Brassica juncea) meal via microwave-assisted extraction and advanced optimization methods

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Abstract

In this study, we used microwave-assisted extraction to extract mustard protein isolates from defatted mustard meal, highlighting the importance of mustard as a versatile crop and the value addition potential of mustard protein isolates. We examined the effects of microwave power (425, 625, 800 W), treatment time (60, 90, 120 s), pH (8, 9.5, 11), and particle size (150, 375, 600 μm). A support vector regression–based model was developed and combined with a genetic algorithm for optimization. The maximum yield of 46.73% was achieved at microwave power 800 W, treatment time 120 s, pH 11, and particle size 150 μm. The functional properties of the protein isolates obtained under optimized conditions were analyzed. The protein isolates exhibited water absorption capacity of 2.48 g/g, oil absorption capacity of 0.66 g/g, emulsifying stability of 57.89%, foaming capacity of 83%, and stability of 91.6%. Microwave treatment did not affect the protein bands observed in SDS-PAGE analysis. The extracted protein showed a semi-crystalline and semi-amorphous nature, with a crystallinity index of 51.891%.

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Data will be available on request from the corresponding author.

References

  1. Mitrović PM, Stamenković OS, Banković-Ilić I et al (2020) White Mustard (Sinapis alba L.) Oil in biodiesel production: a review. Front. Plant Sci 11. https://doi.org/10.3389/FPLS.2020.00299

  2. Sharma S, Raghuwanshi J, Jaulkar A, Srivastava SC (2019) Constraints in production, marketing and processing in rapeseed-mustard cultivation and suitable measures to overcome these constraints. Int J Curr Microbiol Appl Sci 8:1–9

    Google Scholar 

  3. Tian Y, Deng F (2020) Phytochemistry and biological activity of mustard (Brassica juncea): a review. http://mc.manuscriptcentral.com/tcyt 18:704–718. https://doi.org/10.1080/19476337.2020.1833988

  4. Arrutia F, Binner E, Williams P, Waldron KW (2020) Oilseeds beyond oil: press cakes and meals supplying global protein requirements. Trends Food Sci Technol 100:88–102. https://doi.org/10.1016/j.tifs.2020.03.044

    Article  Google Scholar 

  5. Puris E, Gynther M, Auriola S, Huttunen KM (2020) L-Type amino acid transporter 1 as a target for drug delivery. Pharm Res 37. https://doi.org/10.1007/s11095-020-02826-8

  6. Kumari PV, Sangeetha N (2017) Nutritional significance of cereals and legumes based food mix-A review.  Int J Agric Life Sci  3:115–122. https://doi.org/10.22573/spg.ijals.017.s12200075

  7. Jahan K, Ashfaq A, Islam RU et al (2022) Optimization of ultrasound-assisted protein extraction from defatted mustard meal and determination of its physical, structural, and functional properties. J Food Process Preserv. https://doi.org/10.1111/jfpp.16764

  8. Yousuf O, Singh A, Shahi NC et al (2019) Microwave assisted extraction: a technological alternative for valorization of orange peel for pectin extraction. Int Res J Pure Appl Chem 17:1–10. https://doi.org/10.9734/irjpac/2018/46089

    Article  Google Scholar 

  9. Bedin S, Netto FM, Bragagnolo N, Taranto OP (2020) Reduction of the process time in the achieve of rice bran protein through ultrasound-assisted extraction and microwave-assisted extraction. Sep Sci Technol (Philadelphia) 55:300–312. https://doi.org/10.1080/01496395.2019.1577449

    Article  Google Scholar 

  10. Varghese T, Pare A (2019) Effect of microwave assisted extraction on yield and protein characteristics of soymilk. J Food Eng 262:92–99. https://doi.org/10.1016/j.jfoodeng.2019.05.020

    Article  Google Scholar 

  11. Osama K, Pallavi S, Pandey AK, Mishra BN (2013) Modelling of nutrient mist reactor for hairy root growth using artificial neural network. Eur J Sci Res 97:516–526

    Google Scholar 

  12. Younis K, Ahmad S, Osama K, Malik MA (2019) Optimization of de-bittering process of mosambi (Citrus limetta) peel: artificial neural network, Gaussian process regression and support vector machine modeling approach. J Food Process Eng 42. https://doi.org/10.1111/jfpe.13185

  13. Chaurasia P, Younis K, Qadri OS et al (2019) Comparison of Gaussian process regression, artificial neural network, and response surface methodology modeling approaches for predicting drying time of mosambi (Citrus limetta) peel. J Food Process Eng 42. https://doi.org/10.1111/jfpe.12966

  14. Qadri OS, Osama K, Srivastava AK (2020) Foam mat drying of papaya using microwaves: machine learning modeling. J Food Process Eng. https://doi.org/10.1111/jfpe.13394

  15. Abdel-Sattar M, Aboukarima AM, Alnahdi BM (2021) Application of artificial neural network and support vector regression in predicting mass of ber fruits (Ziziphus mauritiana Lamk.) based on fruit axial dimensions. PLoS One 16:e0245228. https://doi.org/10.1371/JOURNAL.PONE.0245228

    Article  Google Scholar 

  16. Wang Y, Yang Y, Jiao J et al (2018) Support vector regression approach to predict the design space for the extraction process of Pueraria lobata. Molecules 23:2405. https://doi.org/10.3390/MOLECULES23102405

    Article  Google Scholar 

  17. Tao Y, Wang P, Wang J et al (2017) Combining various wall materials for encapsulation of blueberry anthocyanin extracts: optimization by artificial neural network and genetic algorithm and a comprehensive analysis of anthocyanin powder properties. Powder Technol 311:77–87. https://doi.org/10.1016/J.POWTEC.2017.01.078

    Article  Google Scholar 

  18. Ciaburro G, Puyana-Romero V, Iannace G, Jaramillo-Cevallos WA (2021) Characterization and modeling of corn stalk fibers tied with clay using support vector regression algorithms. https://doi.org/10.1080/15440478.2021.1944427

  19. Khursheed N, Osama K, Eldesoky GE et al (2022) Ultrasound-assisted protein extraction from mosambi peel support vector regression and genetic algorithm-based modeling and optimization. J Food Process Preserv:e16979. https://doi.org/10.1111/JFPP.16979

  20. AOAC (2006) Official methods of analysis, vol 15. Association of Official Analytical Chemists. Washington, D. C., pp 71–74

  21. Ochoa-Rivas A, Nava-Valdez Y, Serna-Saldívar SO, Chuck-Hernández C (1947) Microwave and ultrasound to enhance protein extraction from peanut flour under alkaline conditions: effects in yield and functional properties of protein isolates. Food Bioprocess Technol. https://doi.org/10.1007/s11947-016-1838-3

  22. Abdullah S, Pradhan RC, Pradhan D, Mishra S (2021) Modeling and optimization of pectinase-assisted low-temperature extraction of cashew apple juice using artificial neural network coupled with genetic algorithm. Food Chem 339. https://doi.org/10.1016/j.foodchem.2020.127862

  23. Çelik M, Güzel M, Yildirim M (2019) Effect of pH on protein extraction from sour cherry kernels and functional properties of resulting protein concentrate. J Food Sci Technol 56:3023–3032. https://doi.org/10.1007/s13197-019-03785-8

    Article  Google Scholar 

  24. Phongthai S, Lim ST, Rawdkuen S (2016) Optimization of microwave-assisted extraction of rice bran protein and its hydrolysates properties. J Cereal Sci 70:146–154. https://doi.org/10.1016/j.jcs.2016.06.001

    Article  Google Scholar 

  25. Sarker AK, Saha D, Begum H et al (2015) Comparison of cake compositions, pepsin digestibility and amino acids concentration of proteins isolated from black mustard and yellow mustard cakes. AMB Express 5:1–6. https://doi.org/10.1186/S13568-015-0110-Y/TABLES/3

    Article  Google Scholar 

  26. Sharma HK, Ingle S, Singh C et al (2012) Effect of various process treatment conditions on the allyl isothiocyanate extraction rate from mustard meal. J Food Sci Technol 49:368–372. https://doi.org/10.1007/S13197-011-0282-7/TABLES/3

    Article  Google Scholar 

  27. Ulloa JA, Rosas-Ulloa P, Ulloa-Rangel BE (2011) Physicochemical and functional properties of a protein isolate produced from safflower (Carthamus tinctorius L.) meal by ultrafiltration. J Sci Food Agric 91:572–577. https://doi.org/10.1002/JSFA.4227

    Article  Google Scholar 

  28. Jahan K, Ashfaq A, Islam RU et al (2022) Optimization of ultrasound-assisted protein extraction from defatted mustard meal and determination of its physical, structural, and functional properties. J Food Process Preserv:e16764. https://doi.org/10.1111/JFPP.16764

  29. Sadeghi A, Bhagya S (2009) Effect of recovery method on different property of mustard protein. World J Dairy Food Sci 4:100–106

  30. Ma M, Ren Y, Xie W et al (2018) Physicochemical and functional properties of protein isolate obtained from cottonseed meal. Food Chem 240:856–862. https://doi.org/10.1016/J.FOODCHEM.2017.08.030

    Article  Google Scholar 

  31. Wang S, Xu X, Wang S et al (2022) Effects of microwave treatment on structure, functional properties and antioxidant activities of germinated tartary buckwheat protein. Foods 11:1373. https://doi.org/10.3390/FOODS11101373

    Article  Google Scholar 

  32. Singh A, Sharma S, Singh B (2017) Effect of germination time and temperature on the functionality and protein solubility of sorghum flour. J Cereal Sci 76:131–139. https://doi.org/10.1016/J.JCS.2017.06.003

    Article  Google Scholar 

  33. Ma KK, Greis M, Lu J et al (2022) Functional performance of plant proteins. Foods 11. https://doi.org/10.3390/FOODS11040594

  34. Ivanova P, Chalova V, Koleva L (2014) Functional properties of proteins isolated from industrially produced sunflower meal. Int J Food Stud 3:203–212. https://doi.org/10.7455/IJFS/3.2.2014.A6

    Article  Google Scholar 

  35. Wang XB, Chi YJ (2012) Microwave-assisted phosphorylation of soybean protein isolates and their physicochemical properties. Czech J Food Sci 30:99–107. https://doi.org/10.17221/91/2011-CJFS

    Article  Google Scholar 

  36. Damodaran S (2007) Amino acids, peptides, and proteins. In: Fennema’s Food Chemistry, 4th edn. CRC Press, pp 229–342

    Google Scholar 

  37. Li P, Sun Z, Ma M et al (2018) Effect of microwave-assisted phosphorylation modification on the structural and foaming properties of egg white powder. LWT 97:151–156. https://doi.org/10.1016/J.LWT.2018.06.055

    Article  Google Scholar 

  38. Ashraf S, Saeed SMG, Sayeed SA, Ali AR (2012) Impact of microwave treatment on the functionality of cereals and legumes. Int J Agric Biol 14(356–370):39

    Google Scholar 

  39. Lin H, Bean SR, Tilley M et al (2021) Qualitative and quantitative analysis of sorghum grain composition including protein and tannins using ATR-FTIR spectroscopy. Food Anal Methods 14:268–279. https://doi.org/10.1007/S12161-020-01874-5/FIGURES/9

    Article  Google Scholar 

  40. Matheus S, Friess W, Mahler HC (2006) FTIR and nDSC as analytical tools for high-concentration protein formulations. Pharm Res 23:1350–1363. https://doi.org/10.1007/S11095-006-0142-8/TABLES/6

    Article  Google Scholar 

Download references

Acknowledgements

The authors are thankful to the DST-FIST-developed Central Instrumentation Facility, Integral University, for providing the analytical facilities. They are also thankful to Integral University for providing the manuscript number (IU/R&D/2023-MCN0002016) of this paper.

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Kausar Jahan and Samra Fatima: Conceptualization; methodology; writing—original draft and editing. Khwaja Usama and Kaiser Younis: Visualization; writing—review and methodology. Owais Yousuf: supervision and validation.

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Correspondence to Owais Yousuf.

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Jahan, K., Fatima, S., Osama, K. et al. Boosting protein yield from mustard (Brassica juncea) meal via microwave-assisted extraction and advanced optimization methods. Biomass Conv. Bioref. 13, 16241–16251 (2023). https://doi.org/10.1007/s13399-023-04662-3

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