EVALUASI MUTU BIJI MELINJO (Gnetum gnemon L.) MENGGUNAKAN PENGOLAHAN CITRA DIGITAL

Authors

  • Slamet Widodo Department of Mechanical and Biosystem Engineering, Bogor Agricultural University
  • Muhammad Kalili Departemen Teknik Mesin dan Biosistem, Fakultas Teknologi Pertanian Institut Pertanian Bogor

DOI:

https://doi.org/10.23960/jtep-l.v7i2.106-114

Abstract

Some studies show that melinjo (Gnetum gnemon L.) seed extract contains various active ingredients that are beneficial to human health; even it has been commercialized as a health supplement product. Quality of seeds as raw material becomes one of key factors that determine the quality of product derived from melinjo seed extract. Therefore sorting becomes a critical process. However the sorting of good quality and broken seeds (moldy, chalky and perforated/infected insects) is still done manually with visual observations that tend to be inaccurate and inconsistent. This study aims to develop a new method for evaluation of quality of melinjo seeds based on digital image processing. The image is taken using two lighting systems i.e. frontlight and backlight. The results show that using color features (RGB and HSV) and certain threshold values, good quality and broken seeds can be distinguished by 92.5% and 100% accuracy using frontlight and backlight image respectively. It indicates that digital image processing can be used as an alternative for quality evaluation of melinjo seed.

References

Bhat, R., dan Yahya, N.B.. 2014. Evaluating belinjau (Gnetum gnemon L.) seed flour quality as a base for development of novel food products and food formulations. Food Chemistry 156, pp. 42–49

Cubero, S., Aleixos, N., Moltó, E., Gómez-Sanchis, J., Blasco, J. 2011. Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables. Food Bioprocess Technol. 4(4), pp. 487-504

Du, C.J. dan Sun, D.W. 2004. Recent developments in the applications of image processing techniques for food quality evaluation.Trends in Food Science & Technology. 15(5), pp. 230-249

Gong, Z.Y., Cheng, F., Liu, Z.H., Yang, X.L., Zhai, B.J., You, Z.H. 2015. Recent Developments of Seeds Quality Inspection and Grading Based on Machine Vision . 2015 ASABE Annual International Meeting, New Orleans, Louisiana 26 – 29 July 2015, Paper Number: 152188378

Hosoda Company. 2013. Melinjo Resveratrol launching in markets outside Japan. Tersedia online di https://www.nutraingredients-usa.com/Article/2013/08/13/Melinjo-Resveratrol-launching-in-markets-outside-Japan. [diakses pada 17 Juni 2018]

Kato, E., Tokunaga, Y., Sakan, F. 2009. Stilbenoids isolated from the seeds of melinjo (Gnetum gnemon L.) and their biological activity. J. Agric. Food Chem. 57(6), pp. 2544-2549

Momin, M.A. , Rahman, M.T., Sultana, M.S., Igathinathane, C., Ziauddin, A.T.M., Grift, T.E. 2017. Geometry-based mass grading of mango fruits using image processing. Information Processing in Agriculture 4, pp.150–160

Payne, A., dan Walsh, K. 2014. Machine vision in estimation of crop yield. In: Plant image analysis: fundamentals and applications. CRC Press, pp. 341–57

Shapiro, L.G. dan Stockman, G.C. 2001. Computer Vision. USA, New Jersey, Prentice-Hall. pp 279-325.

Siswoyo, T.A., Mardiana, E., Lee, K.O., Hoshokawa, K. 2011. Isolation and characterization of antioxidant protein fractions from melinjo (Gnetum gnemon) seeds. Journal of Agricultural and Food Chemistry. 59(10), pp. 5648-5656

Ikuta, T., Saito, S., Tani, H., Tatefuji, T., Hashimoto, K. 2015. Resveratrol derivative-rich melinjo (Gnetum gnemon L.) seed extract improves obesity and survival of C57BL/6 mice fed a high-fat diet. Bioscience, Biotechnology, and Biochemistry 79(12), pp. 2044-2049

Terkeltaub R. 2010. Update on gout: new therapeutic strategies and options. Nat. Rev. Rheumatol. 6, pp. 30-38

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Published

2018-08-30

Issue

Vol. 7 No. 2 (2018): Agustus

Section

Articles

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