Sains Malaysiana 51(10)(2022): 3321-3332

http://doi.org/10.17576/jsm-2022-5110-17

Estimation of Proximate, Fatty Acid, Mineral Content and Proline Level in Amaranth using Near Infrared Reflectance Spectroscopy

(Anggaran Proksimat, Asid Lemak, Kandungan Mineral dan Tahap Prolin dalam Amaranth menggunakan Spektroskopi Pemantulan Inframerah Dekat)

AYLIN CELILE OLUK^*

Eastern Mediterranean Agricultural Research Institute, Yüregir, Adana, Turkey

Received: 8 October 2021/Accepted: 18 May 2022

Abstract

For successful development of new amaranth varieties, it is important to find inexpensive and rapid analysis methods for the measurement of proximate, fatty acid, mineral content, and proline level in seeds. In this study, calibration equations in NIR spectroscopy were developed to estimate for the fatty acid, mineral content and proline level of amaranth using the modified partial least squares (MPLS) regression method. The calibrations estimated by NIR spectroscopy were consistent with the correlations between reference values at external validation. The equations developed were evaluated based on the relative estimate determination results for external validation (RPDv). The equations for total protein (RPDv = 2.967), fat (RPDv = 4.396), Zn (RPDv = 3.668), proline (RPDv = 6.692), oleic acid (RPDv = 3.366) and linoleic acid (RPDv = 2.086) showed high accuracy, while the equations for ash (RPDv = 1.675) and Fe (RPDv = 1.565) showed relatively high accuracy. When calculated with the same validation factors, the level of Ca (RPDv = 0.268), palmitic acid (RPDv = 1.434), stearic acid (RPDv = 0.949), linolenic acid (RPDv = 1.244) and arachidic acid (RPDv = 0.402) were lower than the estimated value. Protein, oil, ash, Fe, Zn, proline, oleic acid and linoleic acid can be used as reliable users, while equations developed for Ca, palmitic acid, stearic acid, linolenic acid and arachidic acid can be reliably used to screen samples for amaranth breeding programmes.

Keywords: Calibration; fatty acids; minerals; near-ınfrared reflectance spectroscopy; proline

AbstraK

Bagi mencapai kejayaan pembangunan varieti amaranth baru, adalah penting untuk mencari kaedah analisis yang murah dan pantas untuk pengukuran proksimat, asid lemak, kandungan mineral dan tahap prolin dalam benih. Dalam kajian ini, persamaan penentukuran spektroskopi NIR telah dibangunkan untuk menganggar asid lemak, kandungan mineral dan tahap prolin amaranth menggunakan kaedah regresi separa terkecil (MPLS) yang terubah suai. Penentukuran yang dianggarkan oleh spektroskopi NIR adalah tekal dengan korelasi antara nilai rujukan pada pengesahan luaran. Persamaan yang dibangunkan telah dinilai berdasarkan keputusan penentuan anggaran relatif untuk pengesahan luaran (RPDv). Persamaan untuk jumlah protein (RPDv = 2.967), lemak (RPDv = 4.396), Zn (RPDv = 3.668), prolin (RPDv = 6.692), asid oleik (RPDv = 3.366) dan asid linoleik (RPDv = 2.086) menunjukkan ketepatan yang tinggi manakala persamaan untuk abu (RPDv = 1.675) dan Fe (RPDv = 1.565) menunjukkan ketepatan yang agak tinggi. Apabila dihitung dengan faktor pengesahan yang sama, paras Ca (RPDv = 0.268), asid palmitik (RPDv = 1.434), asid stearik (RPDv = 0.949), asid linolenik (RPDv = 1.244) dan asid arakidik (RPDv = 0.402) adalah lebih rendah daripada nilai anggaran. Protein, minyak, abu, Fe, Zn, prolin, asid oleik dan asid linoleik boleh digunakan sebagai pengguna yang boleh dipercayai, manakala persamaan yang dibangunkan untuk Ca, asid palmitik, asid stearik, asid linolenik dan asid arakidik boleh digunakan dengan pasti untuk menyaring sampel untuk program pembiakan amaranth.

Kata kunci: Asid lemak; mineral; penentukuran; prolin; spektroskopi pemantulan inframerah dekat

REFERENCES

Acosta, J.J., Castillo, M.S. & Hodge, G.R. 2020. Comparison of benchtop and handheld near-infrared spectroscopy devices to determine forage nutritive value. Crop Science 60(6): 3410-3422.

Aditya, K., Saputro, A.H. & Handayani, W. 2018. Enhancement of visible-NIR imaging prediction system using genetic algorithm: Prediction of carotenoid content in Amaranthus sp. leaf. 2018 International Conference on Electrical Engineering and Informatics (ICELTICs). pp. 106-110. doi: 10.1109/ICELTICS.2018.8548868.

AOAC 2005. Official Methods of Analysis of the AOAC. 18^th ed. Methods 990.03;942.05; 922.02; 975.03. Association of Official Analytical Chemists. Arlington, VA, USA.

AOCS 2005. Method Ce 1-62. Fatty Acid Composition by Gas Chromatography. AOCS Methods American Oil Chemists Society.

Barba de la Rosa, A.P., Fomsgaard, I.S., Laursen, B., Mortensen, A.G., Olvera-Martınez, L., Silva-Sanchez, C., Mendoza-Herrera, A., Gonzalez Casta~neda, J. & De Leon-Rodrıguez A. 2009. Amaranth (Amaranthus hypochondriacus) as an alternative crop for sustainable food production: phenolic acids and flavonoids with potential impact on its nutraceutical quality. Journal of Cereal Science 49(1): 117-121.

Barnes, R.J., Dhanoa, M.S. & Lester, S.J. 1989. Standard normal variate transformation and detrending for near infrared diffuse reflectance spectra. Applied Spectroscopy 43(5): 772-777.

Barickman, T.C., Simpson, C.R. & Sams, C.E. 2019. Waterlogging causes early modification in the physiological performance, carotenoids, chlorophylls, proline, and soluble sugars of cucumber plants. Plants 8(6): 160-175.

Becker, R., Wheeler, E.L., Lorenz, K., Stafford, A.E., Grosjean, O.K., Betschart, A. & Saunders, R.M. 1981. A composition study of amaranth grain. Journal of Food Science 46(4): 1175-1180.

Brenner, D.M., Baltensperger, D.D., Kulakow, P.A., Lehmann, J.W., Myers, R.L., Slabbert, M.M. & Sleugh, B.B. 2010. Genetic resources and breeding of Amaranthus. In Plant Breeding Reviews, Vol. 19, edited by Janick, J. New York: John Wiley & Sons, Inc. pp. 227-285.

Cai, Y.Z. & Cork, H. 2001. Effect of postharvest treatments on Amaranthus betacyanin degradation evaluated by visible/near-infrared spectroscopy. Journal of Food Science: Food Chemistry and Toxicology 66(8): 1112-1118.

Conzen, J.P. 2006. Multivariate Calibration. A Practical Guide for Developing Methods in the Quantitative Analytical Chemistry. 2nd English ed. Ettlingen, Germany: Bruker Optics. p. 127.

Delauney, A.J., Hu, C.A.A., Kishor, P.B.K. & Verma, D.P.S. 1993. Cloning of ornithine deltaaminotransferase cdna from vigna-aconitifolia by transcomplementation in Escherichia-coli and regulation of proline biosynthesis. Journal of Biological Chemistry 268(25): 18673-18678.

Ejieji, C.J. & Adeniran, K.A. 2010. Effects of water and fertilizer stress on the yield, fresh and dry matter production of grain Amaranth (Amaranthus cruentus). Australian Journal of Agricultural Engineering 1(1): 18-24.

Font, R., del Río-Celestino, M., Luna, D., Gil, J. & de Haro-Bailón, A. 2021. Rapid and cost-effective assessment of the neutral and acid detergent fiber fractions of chickpea (Cicer arietinum L.) by combining modified PLS and visible with near-infrared spectroscopy. Agronomy 11(4): 666-678.

Font, R., Del Rı́o Vélez, D., Montoro, R. & De Daro, A. 2004. Use of near-infrared spectroscopy for determining the total arsenic content in prostrate amaranth. Science of The Total Environment 327(1-3): 93-104.

Garcia, A.A., Damian Huato, M.A., Huerta Lara, M., Saenzde-Cabezon, F.J., Perez-Moreno, I., Marco-Mancebon, V. & Lopez-Olguın, J.F. 2011. Insect occurrence and losses due to phytophagous species in the amaranth Amaranthus hypocondriacus L. crop in Puebla, Mexico. African Journal of Agricultural Research6(27): 5924-5929.

Gregorova, Z., Kovacik, J., Klejdus, B., Maglovski, M., Kuna, R., Hauptvogel, P. & Matusikova, I. 2015. Drought-induced responses of physiology, metabolites and PR proteins in Triticum aestivum. Journal of Agricultural and Food Chemistry 63(37): 8125-8133.

Guo, Y., Ni, Y.N. & Kokot, S. 2016. Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 153: 79-86.

Han, S.I., Chae, J.H., Bilyeu, K., Shannon, J.G. & Lee, J.D. 2014. Non-destructive determination of high oleic acid content in single soybean seeds by near ınfrared reflectance spectroscopy. Journal of the American Oil Chemists Society 91(2): 229-234.

Hasegawa, P.M., Bressan, R.A., Zhu, J.K. & Bohnert, H.J. 2000. Plant cellular and molecular responses to high salinity. Annual Review of Plant Physiology and Plant Molecular Biology 51: 463-499.

Herold, B., Kawano, S., Sumpf, B., Tillmann, P. & Walsh, K.B. 2009. VIS/NIR spectroscopy. In Optical Monitoring of Fresh and Processed Agricultural Crops, edited by Zude, M. Boca Raton: CRC Press. pp. 141-249.

Kamboj, U., Guha, P. & Mishra, S. 2017. Characterization of chickpea flour by near infrared spectroscopy and chemometrics. Analytical Letters 50(11): 1754-1766.

Li, X., Zhang, L., Zhang, Y., Wang, D., Wang, X., Yu, L., Zhang, W. & Li, P. 2020. Review of NIR spectroscopy methods for nondestructive quality analysis of oilseeds and edible oils. Trends in Food Science & Technology 101: 172-181.

Mailer, R.J. 2004. Rapid evaluation of olive oil quality by NIR reflectance spectroscopy. Journal of the American Chemical Society 81: 823-827.

Maritim, T.K., Kamunya, S.M., Mireji, P., Mwendia, C., Muoki, R.C., Cheruiyot, E.K. & Wachira, F.N. 2015. Physiological and biochemical response of tea [Camellia sinensis (L.) O. Kuntze] to water-deficit stress. Journal of Horticultural Science & Biotechnology 90(4): 395-400.

Montesinos-Pereira, D., Barrameda-Medina, Y., Romero, L., Ruiz, J.M. & Sanchez-Rodriguez, E. 2014. Genotype differences in the metabolism of proline and polyamines under moderate drought in tomato plants. Plant Biology 16(6): 1050-1057.

Muscolo, A., Junker, A., Klukas, C., Weigelt-Fischer, K., Riewe, D. & Altmann, T. 2015. Phenotypic and metabolic responses to drought and salinity of four contrasting lentil accessions. Journal of Experimental Botany 66(18): 5467-5480.

Nasirpour-Tabrizi, P., Azadmard-Damirchi, S., Hesari, J. & Piravi-Vanak, Z. 2020. Amaranth seed oil composition. In Nutritional Value of Amaranth, edited by Waisundara, V.Y. Intechopen. pp. 131-164. DOI: 10.5772/intechopen.91381.

Olaniyi, J.O., Adelasoye, K.A. & Jegede, C.O. 2008. Influence of nitrogen fertilizer on the growth, yield and quality of grain amaranth varieties. World Journal of Agricultural Sciences 4(4): 506-513.

Patil, A.G., Oak, M.D., Taware, S.P., Tamhankar, S.A. & Rao, V.S. 2010. Nondestructive estimation of fatty acid composition in soybean [Glycine max (L.) Merrill] seeds using near-infrared transmittance spectroscopy. Food Chemistry 120(4): 1210-1217.

Porep, J.U., Kammerer, D.R. & Reinhold, C. 2015. On-line application of near infrared (NIR) spectroscopy in food production. Trends in Food Science & Technology 46(2A): 211-230.

Qu, J.H., Liu, D., Cheng, J.H., Sun, D.W., Ma, J., Pu, H.B. & Zeng, X.A. 2015. Applications of near-infrared spectroscopy in food safety evaluation and control: A review of recent research advances. Critical Reviews in Food Science and Nutrition 55(13): 1939-1954.

Quampah, A., Huang, Z.R., Wu, J.G., Liu, H.Y., Li, J.R., Zhu, S.J. & Shi, C.H. 2012. Estimation of oil content and fatty acid composition in cottonseed kernel powder using near infrared reflectance spectroscopy. Journal of American Oil Chemists’ Society 89: 567-575.

Repo-Carrasco-Valencia, R., Pe~na, J., Kallio, H. & Salminen, S. 2009. Dietary fiber and other functional components in two varieties of crude and extruded kiwicha (Amaranthus caudatus). Journal of Cereal Science 49(2): 219-224.

Reta Alemayehu, F., Bendevis, M.A. & Jacobsen, S.E. 2015. The potential for utilizing the seed crop amaranth (Amaranthus spp.) in East Africa as an alternative crop to support food security and climate change mitigation. Journal of Agronomy and Crop Science 201(5): 321-329.

Savary, S., Willocquet, L., Pethybridge, S.J., Esker, P., McRoberts, N. & Nelson, A. 2019. The global burden of pathogens and pests on major food crops. Nature Ecology & Evolution 3: 430-439.

Shenk, J.S., Workman, Jr. J.J. & Westerhaus, M.O. 2008. Application of NIR spectroscopy to agricultural products. In Handbook of Near Infrared Analysis Third Edition, edited by Burns, D.A. & Ciurczak, E.W. Boca Raton: CRC Press. pp. 348-382.

Siesler, H.W. 2008. Basic principles of near-infrared spectroscopy. In Handbook of Near-Infrared Analysis, edited by Burns, D.A. & Ciurczak, E.W. Boca Raton: CRC Press. pp 7-19.

Uddin, M., Okazaki, E., Fukushima, H., Turza, S., Yumiko, Y. & Fukuda, Y. 2006. Nondestructive determination of water and protein in surimi by near-infrared spectroscopy. Food Chemistry 96(3): 491-495.

Valcarcel-Yamani, B. & Lannes, S. 2012. Applications of quinoa (Chenopodium Quinoa Willd.) and amaranth (Amaranthus Spp.) and their influence in the nutritional value of cereal based foods. Food and Public Health 2(6): 265-275.

Williams, P.C. & Norris, K. 2000. Near-Infrared Technology in the Agricultural and Food Industries. St. Paul: American Association of Cereal Chemists. p. 312.

Wutipraditkul, N., Wongwean, P. & Buaboocha, T. 2015. Alleviation of salt-induced oxidative stress in rice seedlings by proline and/or glycinebetaine. Biologia Plantarum 59: 547-553.

^*Corresponding author; email: celileaylin.oluk@tarimorman.gov.tr