来自近红外光谱（NIRS）对单双壳类物种模型中储能成分（蛋白质、脂质、糖原）进行定量建模的带宽选择数据。
Band width selection data from Near Infra-red Spectral (NIRS) quantitative modelling of energy storage components (protein, lipid, glycogen) for single and multi-bivalve species models.
作者信息
Bartlett Jill K, Maher William A, Purss Matthew B J
机构信息
Ecochemistry Laboratory, Institute for Applied Ecology, University of Canberra, Bruce, ACT, Australia.
Pangaea Innovations Pty. Ltd., Canberra, ACT, Australia.
出版信息
Data Brief. 2018 Apr 22;18:1509-1512. doi: 10.1016/j.dib.2018.04.054. eCollection 2018 Jun.
Data presented in this article are related to the research article entitled "Near Infra-red spectroscopy quantitative modelling of bivalve protein, lipid and glycogen composition using single-species versus multi-species calibration and validation sets" [1]. Band width selections were determined using a data-driven approach to modelling Near Infra-red Spectra (NIRS) of protein, lipid and glycogen content in bivalves. Models were produced for single species and combined species of and . Band width selection was undertaken using Fourier wavelet transformation coupled with a genetic algorithm (GA) to aggregate adjacent wavelet bands to select the minimum number of IR bands that were consistently identified in the majority of individual spectra.
本文所呈现的数据与题为《使用单物种与多物种校准及验证集对双壳贝类蛋白质、脂质和糖原成分进行近红外光谱定量建模》的研究文章[1]相关。带宽选择是通过一种数据驱动方法来确定的，该双该方法用于对双壳贝类中蛋白质、脂质和糖原含量的近红外光谱（NIRS）进行建模。针对 和 的单物种及组合物种建立了模型。使用傅里叶小波变换结合遗传算法（GA）进行带宽选择，以聚合相邻小波带，从而选择在大多数个体光谱中一致识别出的最少红外波段数量。
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