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用于分析家畜日粮质量的近红外光谱法:一项系统综述。

Near-infrared spectroscopy for analysing livestock diet quality: A systematic review.

作者信息

Hossain Md Ekramul, Kabir Muhammad Ashad, Zheng Lihong, Swain David L, McGrath Shawn, Medway Jonathan

机构信息

School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.

Food Agility CRC Ltd, Sydney, NSW 2000, Australia.

出版信息

Heliyon. 2024 Nov 7;10(22):e40016. doi: 10.1016/j.heliyon.2024.e40016. eCollection 2024 Nov 30.

Abstract

Near-infrared spectroscopy (NIRS) is a non-invasive and fast technology that has been increasingly used to analyse livestock diet quality. The objective of this study was to conduct a systematic review of the literature to examine the utilisation of NIRS technology for analysing livestock diet quality, with a focus on identifying trends, methodologies, and challenges in recent research. We conducted a systematic search of the literature on five electronic databases and retrieved 718 studies that have been published on the subject. Fifty-four studies were subsequently selected and investigated in depth. These studies were categorised into two groups, namely benchtop and portable, based on the types of NIRS devices utilised, with a majority employing the reflectance spectra mode. Our analysis found that standard normal variate (SNV), detrend (DT), and multiplicative scatter correction (MSC) are the most commonly used spectral data processing methods. The findings indicate that NIRS technology can provide accurate and reliable measurements of key livestock diet quality parameters such as crude protein, fibre, and moisture content. Additionally, we discuss the challenges associated with NIRS technology and provide recommendations for future research directions to further advance the use of NIRS technology in the livestock industry.

摘要

近红外光谱(NIRS)是一种非侵入性的快速技术,已越来越多地用于分析家畜日粮质量。本研究的目的是对文献进行系统综述,以考察NIRS技术在分析家畜日粮质量方面的应用,重点是识别近期研究中的趋势、方法和挑战。我们在五个电子数据库中对文献进行了系统检索,检索到718篇关于该主题的已发表研究。随后选取了54项研究进行深入调查。根据所使用的NIRS设备类型,这些研究分为两组,即台式和便携式,大多数采用反射光谱模式。我们的分析发现,标准正态变量变换(SNV)、去趋势(DT)和多元散射校正(MSC)是最常用的光谱数据处理方法。研究结果表明,NIRS技术可以对家畜日粮质量的关键参数,如粗蛋白、纤维和水分含量,提供准确可靠的测量。此外,我们讨论了与NIRS技术相关的挑战,并为未来的研究方向提供建议,以进一步推动NIRS技术在家畜行业的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72bc/11609248/868b9f8f2e14/gr001.jpg

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