Quantitative Assessment of Cold Injury in Tea Plants by Terahertz Spectroscopy Method

Abstract

Cold injury (CI) causes irreversible damage to tea plants, which results in decline in the quality of famous teas and huge economic loss. A new, quick, non-destructive method is provided to assess the CI of tea leaf based on terahertz (THz) spectroscopy. Absorbance of the samples was measured with THz spectroscopy in frequency bands from 0.1 to 1.6 THz under low temperature treatments of 4.0, 0, −2.5, −5.0, −7.5, and −10.0 °C. Fast Fourier transformation was explored to decompose the endpoint signal to improve the ratio of signal to air and convert the time-domain spectra to the corresponding frequency-domain spectra. To improve the separation of overlap signals caused by substantial scattering of injured cells in the leaf, two-dimensional correlation spectroscopy (2DCOS) and average intensity (AI) were introduced into the partial least squares regression (PLSR) to build 2DCOS–PLSR and AI–PLSR models. Quantitative assessments of the 2DCOS–PLSR and AI–PLSR models were conducted to evaluate the three models. The assessment results showed that the correlation coefficients of the 2DCOS–PLSR model (R2D) were 0.7873, 0.8305, and 0.9103, respectively. The root mean square errors of the 2DCOS–PLSR model (RMSE2D) were 0.6032, 0.5763, and 0.5221, respectively. For the AI–PLSR model, RAI values were 0.7477, 0.7691, and 0.8974, respectively. RMSEAI values were 0.6038, 0.5962, and 0.5797. The combination of THz spectroscopy with the 2DCOS–PLSR model provided a better benchmark for the input interval selection and improved the accuracy of cold-injury detection results.