Analisis Komposisi Kimia Beras dengan Metode Eksploratif Spektra NIR-Vis Sebagai Dasar Pengembangan Metode Analisis Non-Destruktif
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Abstract
Beras merupakan komoditas pangan utama dengan komposisi kimia meliputi kadar air, protein, lemak, karbohidrat, dan mineral (Ca, Fe, Mg, Zn) yang berpengaruh pada nilai gizi, rasa dan umur simpan beras. Penelitian ini bertujuan untuk menganalisis kesahihan metode spektroskopi NIR-Vis dalam analisis komposisi kimia beras sebagai dasar pengembangan metode analisis non-destruktif. Enam varietas beras (beras Cokelat, Merah, Hitam, Mentik Putih, Pandan Wangi, dan Porang) dipilih karena mewakili variasi warna, aroma, tekstur dan komposisi gizi beras. Metode penelitian ini terdiri dari uji proksimat yang dilakukan sesuai SNI 01-2891-1992 dan eksplorasi spektra NIR-Vis yang diukur pada panjang gelombang 400–1700 nm. Hasil menunjukkan bahwa kadar air tertinggi terdapat pada beras Mentik Putih (11,57±0,03%), kadar abu dan lemak tertinggi pada beras Hitam (2,55±0,01% dan 5,02±0,03%), kadar protein tertinggi pada beras Cokelat (10,68±0,67%), serta kadar karbohidrat tertinggi pada beras Porang (82,34±0,09%). Sedangkan, kadar mineral Ca tertinggi terdapat pada beras Hitam (0,72±0,04 mg/L), Fe dan Mg pada beras Merah (0,90±0,01 mg/L dan 1,04±0,01 mg/L), dan Zn pada beras Mentik Putih (1,31±0,01 mg/L). Analisis korelasi Pearson (r) menunjukkan kadar karbohidrat berkorelasi positif kuat (r→+1,0) pada 1300–1650 nm, kadar lemak dan protein menunjukkan korelasi negatif kuat (r→-0,9) pada 1000–1200 nm, sedangkan kadar air menunjukkan korelasi positif lemah (r→+0,3) di 600 nm. Analisis PCA menunjukkan efisiensi tinggi dengan PC 1 (53,8%) dan PC 2 (44,2%) secara kumulatif telah menangkap 98% total perbedaan antar sampel. Penelitian ini membuktikan bahwa kombinasi uji proksimat dan spektroskopi NIR-Vis efektif digunakan sebagai metode non-destruktif untuk analisis komposisi kimia beras.
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How to Cite
Widi, D. C., Prastika, D. Y., Santosa, E. D. A., Putri, L. S. S., Putra, M. M. P., & Rohman, M. S. (2026). Analisis Komposisi Kimia Beras dengan Metode Eksploratif Spektra NIR-Vis Sebagai Dasar Pengembangan Metode Analisis Non-Destruktif. Agroteknika, 9(2), 182-201. https://doi.org/10.55043/agroteknika.v9i2.609
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https://doi.org/10.12911/22998993/163308
Wuryandani, S., Ismoyowati, D., & Suwondo, E. (2021). Improving Pigmented Rice Farmers’ Marketing Activity for Sustainable Agroindustry: Consumers’ Voice to be Considered. E3S Web of Conferences, 232. https://doi.org/10.1051/e3sconf/202123202008
Xu, Y., Dong, Y., Liu, J., Wang, C., & Li, Z. (2025). Combination of near infrared spectroscopy with characteristic interval selection for rapid detection of rice protein content. Journal of Food Composition and Analysis, 137. https://doi.org/10.1016/j.jfca.2024.106995
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Bani, C., Cappa, C., Restani, P., Sala, M., Colombo, F., Mercogliano, F., & di Lorenzo, C. (2024). Physicochemical and nutritional quality of pigmented rice and bran: Influence of milling and cooking. LWT, 208. https://doi.org/10.1016/j.lwt.2024.116653
Barnaby, J. Y., Huggins, T. D., Lee, H., McClung, A. M., Pinson, S. R. M., Oh, M., & Edwards, J. D. (2020). Vis/NIR hyperspectral imaging distinguishes sub-population, production environment, and physicochemical grain properties in rice. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-65999-7
Burestan, N. F., Sayyah, A. H. A., & Taghinezhad, E. (2021). Prediction of some quality properties of rice and its flour by near-infrared spectroscopy (NIRS) analysis. Food Science and Nutrition, 9(2), 1099–1105. https://doi.org/10.1002/fsn3.2086
Chen, H., Tan, C., & Lin, Z. (2018). Authenticity detection of black rice by near-infrared spectroscopy and support vector data description. International Journal of Analytical Chemistry, 2018, 1–8. https://doi.org/10.1155/2018/8032831
Cheng, W., Xu, Z., Fan, S., Liu, B., Zhang, P., Xia, J., & Wu, Y. (2023). Rapid Evaluation Method of Eating Quality Based on Near-Infrared Spectroscopy for Composition and Physicochemical Properties Analysis of Rice Grains. Journal of Food Measurement and Characterization, 17(2), 1640–1650. https://doi.org/10.1007/s11694-022-01686-7
Colombo, F., Cappa, C., Bani, C., Magni, M., Biella, S., Restani, P., & di Lorenzo, C. (2023). Characterization of color, phenolic profile, and antioxidant activity of Italian pigmented rice varieties after different technological treatments. Food Bioscience, 53. https://doi.org/10.1016/j.fbio.2023.102674
Das, S., Kumari, T., Babu, S., C, N., Kumar, S., & Deka, S. C. (2025). Bioactive Compounds, Functional Properties, Health Benefits, and Food Applications of Black Rice: A Comprehensive Review. In Food Chemistry Advances, 7. https://doi.org/10.1016/j.focha.2025.101028
Eden, W. T., & Rumambarsari, C. O. (2020). Proximate Analysis of Soybean and Red Bean Cookies According to the Indonesian National Standard. Journal of Physics: Conference Series, 1567(2). https://doi.org/10.1088/1742-6596/1567/2/022033
Fahroji, Zulfia, V., Yuliasari, S., Pratama, D., & Swastika, S. (2025). Karakteristik Fisik dan Kimia Beras Lokal Sawah di Provinsi Riau. Pangan, 34(1). 13-22. https://www.jurnalpangan.com/index.php/pangan/article/view/697
Fitrawaty, Hermawan, W., Yusuf, M., & Maipita, I. (2023). A simulation of increasing rice price toward the disparity of income distribution: An evidence from Indonesia. Heliyon, 9(3). https://doi.org/10.1016/j.heliyon.2023.e13785
Folli, G. S., Santos, L. P., Santos, F. D., Cunha, P. H. P., Schaffel, I. F., Borghi, F. T., & Filgueiras, P. R. (2022). Food analysis by portable NIR spectrometer. Food Chemistry Advances, 1. https://doi.org/10.1016/j.focha.2022.100074
Gatti, R. F., de Santana, F. B., Poppi, R. J., & Ferreira, D. S. (2021). Portable NIR spectrometer for quick identification of fat bloom in chocolates. Food Chemistry, 342. https://doi.org/10.1016/j.foodchem.2020.128267
Hanas, D. F., Kriswiyanti, E., & Ketut Junitha, I. K. (2017). Karakter Morfologi Beras Sebagai Pembeda Varietas Padi. In Indonesian Journal of Legal and Forensic Sciences, (1). https://doi.org/10.24843/IJLFS.2017.v07.i01.p04
Handayani, D., Kusumastuty, I., Inayah, A. M., Retnaningtyas, E., Sulistyowati, E., Sasiarini, L., & Rudijanto, A. (2022). Substitution of local Indonesian varieties of brown rice on anthropometry and blood glucose level improvement in type 2 DM patients: A pilot project. In Journal of Public Health Research. 11. https://doi.org/10.4081/jphr.2021.2283
Hasnelly, H., Evi F., Shelvi P. A., & Hervelly H. (2020). Pengaruh Drajat Penyosohan terhadap Mutu Fisik dan Nilai Gizi Beberapa Jenis Beras. AgriTECH, 40(3). 182-189. http://doi.org/10.22146/agritech.47487
Hayati, R., Munawar, A. A., & Marliah, A. (2021). Rapid quantification of rice (Oryza sativa) qualities based on adaptive near infrared spectroscopy. IOP Conference Series: Earth and Environmental Science, 922(1). https://doi.org/10.1088/1755-1315/922/1/012020
Husnah, Y. A., Turhadi, T., Safitri, A., & Fatchiyah, F. (2024). Morphoagronomical Evaluation of Several Indonesian Pigmented Rice (Oryza sativa L.) Accessions from East Java and Central Java, Indonesia. Plant Breeding and Biotechnology, 12, 122–137. https://doi.org/10.9787/PBB.2024.12.122
Javed, M., Jawid, J., Zafar, S., Ahmad, A. M. R., Shah, S. H. B. U., Farooq, U., & Abid, J. (2025). Black rice as the emerging functional food: bioactive compounds, therapeutic potential and industrial applications. In Frontiers in Nutrition (Vol. 12). Frontiers Media SA. https://doi.org/10.3389/fnut.2025.1705983
Lu, B., Wang, X., Liu, N., Hu, C., Xu, H., Wu, K., & Tang, X. (2020). Quantitative NIR spectroscopy determination of coco-peat substrate moisture content: Effect of particle size and non-uniformity. Infrared Physics and Technology, 111. https://doi.org/10.1016/j.infrared.2020.103482
Mohan, V., Anjana, R. M., Gayathri, R., Bai, M. R., Lakshmipriya, N., Ruchi, V., & Sudha, V. (2019). Glycemic Index of a Novel High-Fiber White Rice Variety Developed in India - A Randomized Control Trial Study. Diabetes Technology and Therapeutics, 18(3), 164–170. https://doi.org/10.1089/dia.2015.0313
Mugalavai, V. K., Aduol, K. O., & Onkware, A. O. (2021). Nutritional Characteristics of Rice (Oryza sativa L.) Composite Flours Obtained by Food Fortification. European Journal of Agriculture and Food Sciences, 3(1), 79–83. https://doi.org/10.24018/ejfood.2021.3.1.224
Munarko, H., Sitanggang, A. B., Kusnandar, F., & Budijanto, S. (2020). Phytochemical, fatty acid and proximal composition of six selected Indonesian brown rice varieties. CYTA - Journal of Food, 18(1), 336–343. https://doi.org/10.1080/19476337.2020.1754295
Ndumuye, E., Langi, T. M., & Taroreh, M. I. R. (2022). Chemical Characteristic of Muate Flour (Pteridophyta filicinae) as Traditional Food for The Community of Kimmam Island. Applied Agroecotechnology Journal. 3(2), 261-268. https://doi.org/10.35791/jat.v3i2.44440
Purwaningsih, & Indrasari, S. D. (2019). The Paddy and Rice Quality of Three Varieties of Indonesian Local Aromatic Paddy. IOP Conference Series: Earth and Environmental Science, 309(1). https://doi.org/10.1088/1755-1315/309/1/012018
Quiroga-Mosquera, A., Santos-Rivera, M., Guzmán-Prada, D., Casas, J., Ishitani, M., & Selvaraj, M. G. (2025). Improving nitrogen use efficiency in rice by estimating leaf nitrogen content with near-infrared spectroscopy and chemometric modeling. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-27389-9
Rahman, A. N. F., Genisa, J., Dirpan, A., & Badani, A. A. (2018). Modification of Dry Grain Processing for Rice Nutrition Produced. IOP Conference Series: Earth and Environmental Science, 157(1). https://doi.org/10.1088/1755-1315/157/1/012036
Ramalho, F. M. G., Simetti, R., Arriel, T. G., Loureiro, B. A., & Hein, P. R. G. (2019). Influence of particles size on nir spectroscopic estimations of charcoal properties. Floresta e Ambiente, 26(1). https://doi.org/10.1590/2179-8087.039718
Rizwana, S., & Hazarika, M. K. (2020). Application of Near-Infrared Spectroscopy for Rice Characterization Using Machine Learning. Journal of The Institution of Engineers (India): Series A, 101(4), 579–587. https://doi.org/10.1007/s40030-020-00459-z
Sari, A. R., Martono, Y., & Rondonuwu, F. S. (2020). Identifikasi Kualitas Beras Putih (Oryza sativa L.) Berdasarkan Kandungan Amilosa dan Amilopektin di Pasar Tradisional dan “Selepan” Kota Salatiga. Titian Ilmu: Jurnal Ilmiah Multi Sciences, 12(1), 24–30. https://journal.unuha.ac.id/index.php/JTI/article/view/599
Susiyanti, Rusmana, Maryani, Y., Sjaifuddin, Krisdianto, N., & Syabana, M. A. (2020). The physicochemical properties of several Indonesian rice varieties. Biotropia, 27(1), 41–50. https://doi.org/10.11598/btb.2020.27.1.1030
Tahsin, M., Mahazabin, K. I., Nuha, M. B. R., Efad, A. R., Momo, M. R., Niloy, N. T., & Islam, R. U. (2025). Grain by grain: A microscopic image dataset of rice varieties from Bangladeshi rice markets. Data in Brief, 63. https://doi.org/10.1016/j.dib.2025.112058
Wahyuningsih, N. E., Setiawan, H., Nabiha, P. I., Kartasurya, M. I., & Azam, M. (2023). Heavy Metals Contamination of Local and Imported Rice in Semarang, Central Java, Indonesia. Journal of Ecological Engineering, 24(7), 49–60.
https://doi.org/10.12911/22998993/163308
Wuryandani, S., Ismoyowati, D., & Suwondo, E. (2021). Improving Pigmented Rice Farmers’ Marketing Activity for Sustainable Agroindustry: Consumers’ Voice to be Considered. E3S Web of Conferences, 232. https://doi.org/10.1051/e3sconf/202123202008
Xu, Y., Dong, Y., Liu, J., Wang, C., & Li, Z. (2025). Combination of near infrared spectroscopy with characteristic interval selection for rapid detection of rice protein content. Journal of Food Composition and Analysis, 137. https://doi.org/10.1016/j.jfca.2024.106995
Zaresani, H., Sayyah, A. H. A., Zareiforoush, H., Khorramifar, A., Gancarz, M., Tabor, S., & Karami, H. (2024). Vis/NIR and FTIR spectroscopy supported by machine learning techniques to distinguish pure from impure Iranian rice varieties. International Agrophysics, 38(2), 203–211. https://doi.org/10.31545/intagr/185392