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Topic

Technologies and technical equipment for agriculture and food industry

Volume

Volume 73 / No. 2 / 2024

Pages : 406-415

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DEVELOPMENT OF MATHEMATICAL MODEL FOR ESTIMATING THE RICE MILLING DEGREE BASED ON FLUORESCENCE IMAGE

PENGEMBANGAN MODEL MATEMATIKA UNTUK MENDUGA DERAJAT SOSOH BERAS BERDASARKAN CITRA FLUORESENSI

DOI : https://doi.org/10.35633/inmateh-73-34

Authors

(*) Zakky MOCHAMAD

Agricultural and Biosystem Engineering Study Program, IPB University, Indonesia

Ahmad USMAN

Department of Mechanical and Biosystem Engineering, Faculty of Agricultural Engineering and Technology, IPB University, Indonesia

Subrata I DEWA MADE

Department of Mechanical and Biosystem Engineering, Faculty of Agricultural Engineering and Technology, IPB University, Indonesia

Suhil MARDISON

Indonesian Agricultural Engineering Polytechnic, Tangerang, Indonesia

(*) Corresponding authors:

[email protected] |

Zakky MOCHAMAD

Abstract

This research aims to develop a mathematical model for estimating the milling degree of milled rice based on fluorescent imaging. The materials used were the Ciherang, IR64 and Mekongga varieties which are widely grown and consumed by Indonesian people. The experiment was conducted by varying the polishing time starting from 0 seconds to 34 seconds with 1 second intervals. Six grains of polished rice were taken to record their images using a camera with 365 nm UV fluorescent ring light. The data collected in this research were milling degree obtained by gravimetric method, milling degree obtained using a milling meter and color values of fluorescent images of milled rice by image processing. The results showed that prediction of milling degree using the RGB color model has the coefficient of determination between 0.8001 – 0.8652, which is considered as potential to be used as a model for estimating the degree of milled rice based on fluorescence images. The RGB color model shows that the image red signal has the highest coefficient of determination compared to green and blue signals. For all of the three varieties in this study, the Ciherang variety has a predictive model equation for the image red signal y = 3.9027x - 429.61, the IR64 variety has a predictive model equation for the image red signal y = 3.7344x - 415.01, and the Mekongga variety has a predictive model equation for the image red signal y = 3.5627x - 388.86.

Abstract in Indonesian

Penelitian ini bertujuan untuk mengembangkan model matematika untuk menduga derajat sosoh beras giling berdasarkan pencitraan fluoresen. Bahan yang digunakan adalah varietas Ciherang, IR64 dan Mekongga yang banyak ditanam dan dikonsumsi oleh masyarakat Indonesia. Percobaan dilakukan dengan memvariasikan waktu pemolesan mulai dari 0 detik hingga 34 detik dengan interval 1 detik. Enam butir beras yang telah disosoh diambil untuk direkam gambarnya dengan menggunakan kamera dengan lampu cincin fluoresen UV 365 nm. Data yang dikumpulkan dalam penelitian ini adalah derajat sosoh yang diperoleh dengan metode gravimetri, derajat sosoh yang diperoleh dengan menggunakan alat ukur milling meter dan nilai warna citra fluoresen beras giling dengan pengolahan citra. Hasil penelitian menunjukkan bahwa prediksi derajat sosoh menggunakan model warna RGB memiliki nilai koefisien determinasi antara 0.8001 - 0.8652, sehingga model ini berpotensi untuk digunakan sebagai model penduga derajat sosoh beras giling berdasarkan citra fluoresensi. Model warna RGB menunjukkan bahwa sinyal warna merah pada citra memiliki nilai koefisien determinasi yang paling tinggi dibandingkan dengan sinyal warna hijau dan biru. Untuk ketiga varietas dalam penelitian ini, varietas Ciherang memiliki persamaan model prediksi untuk sinyal merah citra y = 3.9027x - 429.61, varietas IR64 memiliki persamaan model prediksi untuk sinyal merah citra y = 3.7344x - 415.01, dan varietas Mekongga memiliki persamaan model prediksi untuk sinyal merah citra y = 3.5627x - 388.86.

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