Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model
The dry matter (DM) content of feed is vital in cattle nutrition and is inversely correlated with moisture content. The established ranges of moisture content serve as a marker for factors such as safe storage limit and DM intake. Rapid changes in moisture content necessitate rapid measurements. A r...
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MDPI AG
2021-04-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/11/5/1299 |
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| author | Daniel Dooyum Uyeh Juntae Kim Santosh Lohumi Tusan Park Byoung-Kwan Cho Seungmin Woo Won Suk Lee Yushin Ha |
| author_facet | Daniel Dooyum Uyeh Juntae Kim Santosh Lohumi Tusan Park Byoung-Kwan Cho Seungmin Woo Won Suk Lee Yushin Ha |
| author_sort | Daniel Dooyum Uyeh |
| collection | DOAJ |
| description | The dry matter (DM) content of feed is vital in cattle nutrition and is inversely correlated with moisture content. The established ranges of moisture content serve as a marker for factors such as safe storage limit and DM intake. Rapid changes in moisture content necessitate rapid measurements. A rapid and non-destructive global model for the measurement of moisture content in total mixed ration feed and feed materials was developed. To achieve this, we varied and measured the moisture content in the feed and feed materials using standard methods and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 1000–2500 nm. The spectral data from the samples were extracted and preprocessed using seven techniques and were used to develop a global model using partial least squares regression (PLSR) analysis. The range preprocessing technique had the best prediction accuracy (R<sup>2</sup> = 0.98) and standard error of prediction (2.59%). Furthermore, the visual assessment of distribution in moisture content made possible by the generated PLSR-based moisture content mapped images could facilitate precise formulation. These applications of HSI, when used in commercial feed production, could help prevent feed spoilage and resultant health complications as well as underperformance of the animals from improper DM intake. |
| first_indexed | 2024-03-10T11:47:45Z |
| format | Article |
| id | doaj.art-f772b399d9cd43c4b815f7bda45de6dc |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-10T11:47:45Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-f772b399d9cd43c4b815f7bda45de6dc2023-11-21T18:01:06ZengMDPI AGAnimals2076-26152021-04-01115129910.3390/ani11051299Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral ModelDaniel Dooyum Uyeh0Juntae Kim1Santosh Lohumi2Tusan Park3Byoung-Kwan Cho4Seungmin Woo5Won Suk Lee6Yushin Ha7Department of Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu 41566, KoreaDepartment 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 Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu 41566, KoreaDepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, KoreaDepartment of Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu 41566, KoreaDepartment of Agricultural & Biological Engineering, University of Florida, Gainesville, FL 32611, USADepartment of Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu 41566, KoreaThe dry matter (DM) content of feed is vital in cattle nutrition and is inversely correlated with moisture content. The established ranges of moisture content serve as a marker for factors such as safe storage limit and DM intake. Rapid changes in moisture content necessitate rapid measurements. A rapid and non-destructive global model for the measurement of moisture content in total mixed ration feed and feed materials was developed. To achieve this, we varied and measured the moisture content in the feed and feed materials using standard methods and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 1000–2500 nm. The spectral data from the samples were extracted and preprocessed using seven techniques and were used to develop a global model using partial least squares regression (PLSR) analysis. The range preprocessing technique had the best prediction accuracy (R<sup>2</sup> = 0.98) and standard error of prediction (2.59%). Furthermore, the visual assessment of distribution in moisture content made possible by the generated PLSR-based moisture content mapped images could facilitate precise formulation. These applications of HSI, when used in commercial feed production, could help prevent feed spoilage and resultant health complications as well as underperformance of the animals from improper DM intake.https://www.mdpi.com/2076-2615/11/5/1299dairy cattledry matter intakefeed materialsmetabolic diseasesmultivariate analysesprecision feed formulation |
| spellingShingle | Daniel Dooyum Uyeh Juntae Kim Santosh Lohumi Tusan Park Byoung-Kwan Cho Seungmin Woo Won Suk Lee Yushin Ha Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model Animals dairy cattle dry matter intake feed materials metabolic diseases multivariate analyses precision feed formulation |
| title | Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model |
| title_full | Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model |
| title_fullStr | Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model |
| title_full_unstemmed | Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model |
| title_short | Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model |
| title_sort | rapid and non destructive monitoring of moisture content in livestock feed using a global hyperspectral model |
| topic | dairy cattle dry matter intake feed materials metabolic diseases multivariate analyses precision feed formulation |
| url | https://www.mdpi.com/2076-2615/11/5/1299 |
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