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能否使用变换近红外光谱法定量分析草原化学质量?

Can Grassland Chemical Quality Be Quantified Using Transform Near-Infrared Spectroscopy?

作者信息

Parrini Silvia, Staglianò Nicolina, Bozzi Riccardo, Argenti Giovanni

机构信息

Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, 50144 Florence, Italy.

出版信息

Animals (Basel). 2021 Dec 31;12(1):86. doi: 10.3390/ani12010086.

Abstract

Near-infrared spectroscopy (NIRS) and closed spectroscopy methods have been applied to analyse the quality of forage and animal feed. However, grasslands are linked to variability factors (e.g., site, year, occurring species, etc.) which restrict the prediction capacity of the NIRS. The aim of this study is to test the Fourier transform NIRS application in order to determine the chemical characteristics of fresh, undried and unground samples of grassland located in north-central Apennine. The results indicated the success of FT-NIRS models for dry matter (DM), crude protein (CP), acid detergent fibre (ADF), neutral detergent fibre (NDF) and acid detergent lignin (ADL) on fresh grassland samples (R2 > 0.90, in validation). The model can be used to quantitatively determine CP and ADF (residual prediction deviation-RPD > 3 and range error ratio- RER > 10), followed by DM and NDF that maintain a RER > 10, and are sufficient for screening for the lignin fraction (RPD = 2.4 and RER = 8.8). On the contrary, models for both lipid and ash seem not to be usable at a practical level. The success of FT-NIRS quantification for the main chemical parameters is promising from the practical point of view considering both the absence of samples preparation and the importance of these parameters for diet formulation.

摘要

近红外光谱法(NIRS)和近红外封闭光谱法已被用于分析草料和动物饲料的质量。然而,草地与多种可变因素(如地点、年份、出现的物种等)相关联,这些因素限制了NIRS的预测能力。本研究的目的是测试傅里叶变换近红外光谱法(FT-NIRS)的应用,以确定位于亚平宁山脉中北部的新鲜、未干燥且未研磨的草地样本的化学特性。结果表明,FT-NIRS模型在新鲜草地样本上对干物质(DM)、粗蛋白(CP)、酸性洗涤纤维(ADF)、中性洗涤纤维(NDF)和酸性洗涤木质素(ADL)的预测取得成功(验证时R2>0.90)。该模型可用于定量测定CP和ADF(剩余预测偏差-RPD>3且范围误差率-RER>10),其次是DM和NDF,其RER>10,足以筛选木质素部分(RPD=2.4且RER=8.8)。相反,脂质和灰分的模型在实际应用中似乎不可用。从实际角度来看,考虑到无需样品制备以及这些参数对日粮配方的重要性,FT-NIRS对主要化学参数的定量成功是很有前景的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a63/8749596/52e5ff0535a1/animals-12-00086-g001.jpg

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