Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques
The demand for rapid and nondestructive methods to determine chemical components in food and agricultural products is proliferating due to being beneficial for screening food quality. This research investigates the feasibility of Fourier transform near-infrared (FT-NIR) and Fourier transform infrare...
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MDPI AG
2022-01-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/11/2/232 |
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| author | Hanim Z. Amanah Salma Sultana Tunny Rudiati Evi Masithoh Myoung-Gun Choung Kyung-Hwan Kim Moon S. Kim Insuck Baek Wang-Hee Lee Byoung-Kwan Cho |
| author_facet | Hanim Z. Amanah Salma Sultana Tunny Rudiati Evi Masithoh Myoung-Gun Choung Kyung-Hwan Kim Moon S. Kim Insuck Baek Wang-Hee Lee Byoung-Kwan Cho |
| author_sort | Hanim Z. Amanah |
| collection | DOAJ |
| description | The demand for rapid and nondestructive methods to determine chemical components in food and agricultural products is proliferating due to being beneficial for screening food quality. This research investigates the feasibility of Fourier transform near-infrared (FT-NIR) and Fourier transform infrared spectroscopy (FT-IR) to predict total as well as an individual type of isoflavones and oligosaccharides using intact soybean samples. A partial least square regression method was performed to develop models based on the spectral data of 310 soybean samples, which were synchronized to the reference values evaluated using a conventional assay. Furthermore, the obtained models were tested using soybean varieties not initially involved in the model construction. As a result, the best prediction models of FT-NIR were allowed to predict total isoflavones and oligosaccharides using intact seeds with acceptable performance (<i>R<i><sup>2</sup></i><sub>p</sub></i>: 0.80 and 0.72), which were slightly better than the model obtained based on FT-IR data (<i>R<i><sup>2</sup></i><sub>p</sub></i>: 0.73 and 0.70). The results also demonstrate the possibility of using FT-NIR to predict individual types of evaluated components, denoted by acceptable performance values of prediction model (<i>R<i><sup>2</sup></i><sub>p</sub></i>) of over 0.70. In addition, the result of the testing model proved the model’s performance by obtaining a similar <i>R<i><sup>2</sup></i></i> and error to the calibration model. |
| first_indexed | 2024-03-10T01:29:13Z |
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| language | English |
| last_indexed | 2024-03-10T01:29:13Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-eaf94ec2384a4692b9ed817c50c7ca602023-11-23T13:45:54ZengMDPI AGFoods2304-81582022-01-0111223210.3390/foods11020232Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic TechniquesHanim Z. Amanah0Salma Sultana Tunny1Rudiati Evi Masithoh2Myoung-Gun Choung3Kyung-Hwan Kim4Moon S. Kim5Insuck Baek6Wang-Hee Lee7Byoung-Kwan Cho8Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, KoreaDepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, KoreaDepartment of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Gadjah Mada University, Yogyakarta 55281, IndonesiaDepartment of Herbal Medicine Resource, Dogye Campus, Kangwon National University, Samcheok 25949, KoreaDepartment of Gene Engineering, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, KoreaEnvironmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Powder Mill Road, BARC-East, Bldg 303, Beltsville, MD 20705, USAEnvironmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Powder Mill Road, BARC-East, Bldg 303, Beltsville, MD 20705, USADepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, KoreaDepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, KoreaThe demand for rapid and nondestructive methods to determine chemical components in food and agricultural products is proliferating due to being beneficial for screening food quality. This research investigates the feasibility of Fourier transform near-infrared (FT-NIR) and Fourier transform infrared spectroscopy (FT-IR) to predict total as well as an individual type of isoflavones and oligosaccharides using intact soybean samples. A partial least square regression method was performed to develop models based on the spectral data of 310 soybean samples, which were synchronized to the reference values evaluated using a conventional assay. Furthermore, the obtained models were tested using soybean varieties not initially involved in the model construction. As a result, the best prediction models of FT-NIR were allowed to predict total isoflavones and oligosaccharides using intact seeds with acceptable performance (<i>R<i><sup>2</sup></i><sub>p</sub></i>: 0.80 and 0.72), which were slightly better than the model obtained based on FT-IR data (<i>R<i><sup>2</sup></i><sub>p</sub></i>: 0.73 and 0.70). The results also demonstrate the possibility of using FT-NIR to predict individual types of evaluated components, denoted by acceptable performance values of prediction model (<i>R<i><sup>2</sup></i><sub>p</sub></i>) of over 0.70. In addition, the result of the testing model proved the model’s performance by obtaining a similar <i>R<i><sup>2</sup></i></i> and error to the calibration model.https://www.mdpi.com/2304-8158/11/2/232isoflavonesoligosaccharidessoybean seedspectroscopic techniques |
| spellingShingle | Hanim Z. Amanah Salma Sultana Tunny Rudiati Evi Masithoh Myoung-Gun Choung Kyung-Hwan Kim Moon S. Kim Insuck Baek Wang-Hee Lee Byoung-Kwan Cho Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques Foods isoflavones oligosaccharides soybean seed spectroscopic techniques |
| title | Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques |
| title_full | Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques |
| title_fullStr | Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques |
| title_full_unstemmed | Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques |
| title_short | Nondestructive Prediction of Isoflavones and Oligosaccharides in Intact Soybean Seed Using Fourier Transform Near-Infrared (FT-NIR) and Fourier Transform Infrared (FT-IR) Spectroscopic Techniques |
| title_sort | nondestructive prediction of isoflavones and oligosaccharides in intact soybean seed using fourier transform near infrared ft nir and fourier transform infrared ft ir spectroscopic techniques |
| topic | isoflavones oligosaccharides soybean seed spectroscopic techniques |
| url | https://www.mdpi.com/2304-8158/11/2/232 |
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