细磨处理对植物叶片养分含量中红外光谱分析的影响。

Effects of fine grinding on mid-infrared spectroscopic analysis of plant leaf nutrient content.

机构信息

Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, 39762, USA.

Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS, 39762, USA.

出版信息

Sci Rep. 2023 Apr 18;13(1):6314. doi: 10.1038/s41598-023-33558-5.

DOI:10.1038/s41598-023-33558-5

PMID:37072478

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10113243/

Abstract

Fourier transform mid infrared (FT-MIR) spectroscopy combined with modeling techniques has been studied as a useful tool for multivariate chemical analysis in agricultural research. A drawback of this method is the sample preparation requirement, in which samples must be dried and fine ground for accurate model calibrations. For research involving large sample sets, this may dramatically increase the time and cost of analysis. This study investigates the effect of fine grinding on model performance using leaf tissue from a variety of crop species. Dried leaf samples (N = 300) from various environmental conditions were obtained with data on 11 nutrients measured using chemical methods. The samples were scanned with attenuated total reflectance (ATR) and diffuse reflectance (DRIFT) FT-MIR techniques. Scanning was repeated after fine grinding for 2, 5, and 10 min. The spectra were analyzed for the 11 nutrients using partial least squares regression with a 75%/25% split for calibration and validation and repeated for 50 iterations. All analytes except for boron, iron, and zinc were well-modeled (average R > 0.7), with higher R values on ATR spectra. The 5 min level of fine grinding was found to be most optimal considering overall model performance and sample preparation time.

摘要

傅里叶变换中红外（FT-MIR）光谱结合建模技术已被研究作为农业研究中多元化学分析的有用工具。这种方法的一个缺点是样品制备要求，其中样品必须干燥并精细研磨以进行准确的模型校准。对于涉及大量样本集的研究，这可能会极大地增加分析的时间和成本。本研究通过对来自各种作物的叶片组织进行研究，探讨了精细研磨对模型性能的影响。从各种环境条件下获得了干燥的叶片样本（N=300），并用化学方法测量了 11 种营养素的数据。使用衰减全反射（ATR）和漫反射（DRIFT）FT-MIR 技术对样本进行扫描。在精细研磨 2、5 和 10 分钟后重复扫描。使用偏最小二乘回归（PLSR）对光谱进行了 11 种营养素的分析，校准和验证的比例为 75%/25%，重复了 50 次迭代。除硼、铁和锌外，所有分析物的模型拟合度都很好（平均 R>0.7），ATR 光谱的 R 值更高。考虑到整体模型性能和样品制备时间，5 分钟的精细研磨水平被认为是最理想的。