Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Application of near-infrared spectroscopy for hay evaluation at different degrees of sample preparation

  • Eun Chan Jeong (Graduate School of International Agricultural Technology, Seoul National University) ;
  • Kun Jun Han (School of Plant, Environmental, and Soil Sciences, Louisiana State University, Agricultural Center) ;
  • Farhad Ahmadi (Research Institute of Eco-friendly Livestock Science, Institute of GreenBio Science Technology, Seoul National University) ;
  • Yan Fen Li (Graduate School of International Agricultural Technology, Seoul National University) ;
  • Li Li Wang (Graduate School of International Agricultural Technology, Seoul National University) ;
  • Young Sang Yu (Graduate School of International Agricultural Technology, Seoul National University) ;
  • Jong Geun Kim (Graduate School of International Agricultural Technology, Seoul National University)
  • Received : 2023.11.06
  • Accepted : 2024.01.08
  • Published : 2024.07.01
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Abstract

Objective: A study was conducted to quantify the performance differences of the near-infrared spectroscopy (NIRS) calibration models developed with different degrees of hay sample preparations. Methods: A total of 227 imported alfalfa (Medicago sativa L.) and another 360 imported timothy (Phleum pratense L.) hay samples were used to develop calibration models for nutrient value parameters such as moisture, neutral detergent fiber, acid detergent fiber, crude protein, and in vitro dry matter digestibility. Spectral data of hay samples prepared by milling into 1-mm particle size or unground were separately regressed against the wet chemistry results of the abovementioned parameters. Results: The performance of the developed NIRS calibration models was evaluated based on R2, standard error, and ratio percentage deviation (RPD). The models developed with ground hay were more robust and accurate than those with unground hay based on calibration model performance indexes such as R2 (coefficient of determination), standard error, and RPD. Although the R2 of calibration models was mainly greater than 0.90 across the feed value indexes, the R2 of cross-validations was much lower. The R2 of cross-validation varies depending on feed value indexes, which ranged from 0.61 to 0.81 in alfalfa, and from 0.62 to 0.95 in timothy. Estimation of feed values in imported hay can be achievable by the calibrated NIRS. However, the NIRS calibration models must be improved by including a broader range of imported hay samples in the modeling. Conclusion: Although the analysis accuracy of NIRS was substantially higher when calibration models were developed with ground samples, less sample preparation will be more advantageous for achieving rapid delivery of hay sample analysis results. Therefore, further research warrants investigating the level of sample preparations compromising analysis accuracy by NIRS.

Keywords

Acknowledgement

This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, and Forestry (IPET) through (the Livestock Industrialization Technology Development Program), funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) (No. 121036-02-1-SB010). Also, the calibration model development was partially supported by the Hatch project fund (LAB 94398).

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