Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)

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Non-Destructive Evaluation of Moisture Content in Single Soybean Seed Using Vis-NIR Spectroscopy

Authors
Muhammad Fahri Reza Pahlawan1, Devi Alicia Surya Saputri1, Rudiati Evi Masithoh1, *
1Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Jl. Flora No. 1 Bulaksumur, Yogyakarta, 55281, Indonesia
*Corresponding author. Email: evi@ugm.ac.id
Corresponding Author
Rudiati Evi Masithoh
Available Online 28 December 2022.
DOI
10.2991/978-94-6463-086-2_52How to use a DOI?
Keywords
Moisture content; Soybean seed; Spectroscopy; Vis-NIR
Abstract

In this study, moisture content of soybean was evaluated using visible near infrared (Vis-NIR) spectroscopy. Soybean were dried at 60˚C for up to 10 hours to get moisture variation. A total of 200 soybean were used in this study which made a total of 600 reflectance spectra scanned with Vis-NIR spectrometer at 400-1000 nm. All samples were randomly divided into calibration set (2/3 samples) and prediction set (1/3 samples). Partial least square regression (PLSR) was used for developing calibration model for determining moisture content of soybean seed. Original and several pre-processed spectra such as area normalization, standard normal variate (SNV), multiple scatter correction (MSC), Savitzky-Golay smoothing, and Savitzky-Golay derivative were used in PLSR. The best PLSR model was obtained using 2nd Savitzky-Golay derivative with determination coefficient of calibration (R2C) of 0.93 and root mean square error of calibration (RMSEC) of 0.004%. The PLSR model was then applied to prediction data set which resulted in determination coefficient of prediction (R2P) of 0.82 and root mean square error of prediction (RMSEP) of 0.006%. The result showed the potency of Vis-NIR spectroscopy to predict moisture content in soybean seed.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
Series
Advances in Biological Sciences Research
Publication Date
28 December 2022
ISBN
978-94-6463-086-2
ISSN
2468-5747
DOI
10.2991/978-94-6463-086-2_52How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Muhammad Fahri Reza Pahlawan
AU  - Devi Alicia Surya Saputri
AU  - Rudiati Evi Masithoh
PY  - 2022
DA  - 2022/12/28
TI  - Non-Destructive Evaluation of Moisture Content in Single Soybean Seed Using Vis-NIR Spectroscopy
BT  - Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
PB  - Atlantis Press
SP  - 396
EP  - 400
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-086-2_52
DO  - 10.2991/978-94-6463-086-2_52
ID  - Pahlawan2022
ER  -