This work provides the experimental and theoretical fundamentals for detecting the molecular fingerprints of six kinds of pesticides by using terahertz (THz) time-domain spectroscopy (THz-TDS). The spectra of absorption coefficient and refractive index of the pesticides, chlorpyrifos, fipronil, carbofuran, dimethoate, methomyl, and thidiazuron are obtained in frequencies of 0.1–3.5 THz. To accurately describe the THz spectral characteristics of pesticides, the wavelet threshold de-noising (WTD) method with db 5 wavelet fucntion, 5-layer decomposition, and soft-threshold de-noising was used to eliminate the spectral noise. The spectral baseline correction (SBC) method based on asymmetric least squares smoothing was used to remove the baseline drift. Spectral results show that chlorpyrifo had three characteristic absorption peaks at 1.47, 1.93, and 2.73 THz. Fipronil showed three peaks at 0.76, 1.23, and 2.31 THz. Carbofuran showed two peaks at 2.72 and 3.06 THz. Dimethoate showed three peaks at 1.05, 1.89, and 2.92 THz. Methomyl showed five peaks at 1.01, 1.65, 1.91, 2.72, and 3.20 THz. Thidiazuron showed four peaks at 0.99, 1.57, 2.17, and 2.66 THz. The density functional theory (DFT) of B3LYP/6-31G+(d,p) was applied to simulate the molecular dynamics for peak analyzing of the pesticides based on isolated molecules. The theoretical spectra are in good agreement with the experimental spectra processed by WTD + SBC, which implies the validity of WTD + SBC spectral processing methods and the accuracy of DFT spectral peak analysis. These results support that the combination of THz-TDS and DFT is an effective tool for pesticide fingerprint analysis and the molecular dynamics simulations.

The feasibility of near-infrared spectroscopy (NIR) to detect chlorogenic acid, luteoloside and 3,5-O-dicaffeoylquinic acid in Chrysanthemum was investigated. An NIR spectroradiometer was applied for data acquisition. The reference values of chlorogenic acid, luteoloside, and 3,5-O-dicaffeoylquinic acid of the samples were determined by high-performance liquid chromatography (HPLC) and were used for model calibration. The results of six preprocessing methods were compared. To reduce input variables and collinearity problems, three methods for variable selection were compared, including successive projections algorithm (SPA), genetic algorithm-partial least squares regression (GA-PLS), and competitive adaptive reweighted sampling (CARS). The selected variables were employed as the inputs of partial least square (PLS), back propagation-artificial neural networks (BP-ANN), and extreme learning machine (ELM) models. The best performance was achieved by BP-ANN models based on variables selected by CARS for all three chemical constituents. The values of r_p² (correlation coefficient of prediction) were 0.924, 0.927, 0.933, the values of RMSEP were 0.033, 0.018, 0.064 and the values of RPD were 3.667, 3.667, 2.891 for chlorogenic acid, luteoloside, and 3,5-O-dicaffeoylquinic acid, respectively. The results indicated that NIR spectroscopy combined with variables selection and multivariate calibration methods could be considered as a useful tool for rapid determination of chlorogenic acid, luteoloside, and 3,5-O-dicaffeoylquinic acid in Chrysanthemum.

Terahertz (THz), as an advanced spectral technology, has unique absorption characteristics for most biological macromolecules. In this work, the theoretical fundamentals for the application of THz time-domain spectroscopy (THz-TDS) to molecular characterization and fingerprint peak detection of three plant growth regulators (PGRs), including 2,4-Dichlorophenoxyacetic acid (2,4-D), forchlorfenuron (CPPU) and indole-3-acetic acid (IAA) were researched. Meanwhile, the effects of eight types of window functions on THz spectra were studied when converting time-domain spectra into frequency-domain spectra by Fourier transform. Based on the optimal window function, the THz absorption coefficient and refractive index of PGRs in frequencies of 0.2–3 THz were extracted. The molecule structure and vibration mode of three PGR samples were simulated by using density functional theory (DFT). The results showed that the three PGRs had different fingerprint peaks. Characteristic absorption and anomalous dispersion of 2,4-D were found at 1.35, 1.57 and 2.67 THz, those of CPPU were found at 1.77 and 2.44 THz, and the absorption peak of IAA was located at 2.5 THz. The absorption peaks obtained from THz spectra were identified according to the theoretical calculation results of DFT. These fingerprint peaks in THz spectra were generated by the interior stretching vibration and external deformation vibration of molecular groups. The experimental results revealed the feasibility of identifying PGRs species and detecting residues using THz-TDS.

2,4-Dichlorophenoxyacetic acid (2,4-D) is a common plant growth regulator, which can remain in food and, with long-term consumption, threaten human health. Therefore, it is necessary to propose an effective detection method. Terahertz time-domain spectroscopy technique (THz-TDS) has good advantages in the quantitative and qualitative analysis of most biomolecules due to its rich fingerprint characteristics. In this paper, density functional theory (DFT) was applied to geometry optimization and frequency vibration calculation of 2,4-D, and THz-TDS was used to quantitatively detect 2,4-D in Zizania latifolia. The results showed that there were three characteristic absorption peaks of 2,4-D at 1.36, 1.60, and 2.38 THz, respectively, and the theoretical spectra were in good consistency with experimental spectra, with slight discrepancies. Additionally, the absorption peak at 1.36 THz had the best absorption characteristics and was chosen as the main peak for 2,4-D quantitative analysis. It was demonstrated that the limits of detection (LOD) of 2,4-D in Zizania latifolia were found to be as low as 5%, the absorbance intensity at 1.36 THz showed a good linear relationship (R² = 0.9854) with 2,4-D concentration from 5% to 30%, and the recovery was 93.29%–98.75%. Overall, this work enriched the fingerprint database of pesticide molecules on the basis of terahertz spectroscopy and could provide a technical support for the detection of 2,4-D in food by terahertz spectroscopy.

The water content in vegetative leaves is an important indicator to plant science. It reveals the physiological status of plants and provides valuable information in irrigation management. Terahertz (THz) as a state-of-the-art technology shows great potential in measuring and monitoring the water status in plant leaves. This paper reviewed the theoretical models for calculating water content in the plant leaves, the methods for eliminating the scattering loss caused by the surface roughness of leaf, the applications of THz spectroscopy and THz imaging for monitoring leaf water content and describing leaf water distribution. The survey of the researches presents the considerable advantages of this emerging and promising THz technology in agriculture. Keywords: terahertz (THz) spectroscopy, terahertz imaging, leaf water content, leaf water distribution, theoretical models, eliminating scattering loss, agriculture DOI: 10.25165/j.ijabe.20181105.3952 Citation: Qu F F, Nie P C, Lin L, Cai C Y, He Y. Review of theoretical methods and research aspects for detecting leaf water content using terahertz spectroscopy and imaging. Int J Agric & Biol Eng, 2018; 11(5): 27–34.