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Preliminary study of estradiol and progesterone detection based on terahertz spectroscopy

文献类型： 外文期刊

作者： Liu, Lirong 1 ; Li, Bin 1 ; Zhu, Jun 1 ; Wang, Haifeng 1 ; Zhao, Wenwen 1 ; Jia, Nan 1 ; Sun, Wen 1 ; Zhang, Yuxuan 1 ; Jiang, Lin 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing 100097, Peoples R China

关键词： Terahertz time-domain spectroscopy; Estradiol; Progesterone; Density functional theory; Qualitative; Quantitative

期刊名称：VIBRATIONAL SPECTROSCOPY （ 影响因子：2.5； 五年影响因子：2.5 ）

ISSN： 0924-2031

年卷期： 2023 年 126 卷

页码：

收录情况： SCI

摘要： Estradiol (E2) and progesterone (PROG) are the two typical reproductive hormones in cows. The concentrations of E2 and PROG in milk are highly correlated with the estrus in cows. In the present work, the feasibility of qualitative and quantitative detection of E2 and PROG by terahertz time-domain spectroscopy (THz-TDS) is preliminarily investigated. 522 sample tablets of E2, PROG, powdered milk, estradiol-powdered milk (E2-PM), progesterone-powdered milk (PROG-PM) and estradiol-progesterone-powdered milk (E2-PROG-PM) are pre-pared, and the time-domain spectral, frequency-domain spectral and absorption coefficients are collected and analyzed. The density functional theory (DFT) is used to simulate the molecular dynamics of E2 and PROG. The four preprocessing methods, including first order derivative (FD), standard normal variant (SNV), multiple scatter correction (MSC) and Savitzky-Golay (S-G) along with different modeling methods, including support vector regression (SVR), partial least squares regression (PLSR) and convolutional neural network (CNN) are used for quantitative model building and predictions. The prediction set correlation coefficient (Rp) having value 0.9843 for the E2 concentration in the E2-PM, 0.9935 Rp of the PROG concentration in PROG-PM, and 0.9830 Rp for E2 and PROG concentrations in E2-PROG-PM are achieved by using the combination of None & CNN model, None & CNN model and S-G & CNN model respectively. Our study indicates that the use of terahertz technology to determine hormone content has great potential applications in the field of identification of estrus in dairy cows.

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