Spring Frost Damage to Tea Plants Can Be Identified with Daily Minimum Air Temperatures Estimated by MODIS Land Surface Temperature Products

Abstract

Tea (Camellia sinensis) is one of the most dominant economic plants in China and plays an important role in agricultural economic benefits. Spring tea is the most popular drink due to Chinese drinking habits. Although the global temperature is generally warming, spring frost damage (SFD) to tea plants still occurs from time to time, and severely restricts the production and quality of spring tea. Therefore, monitoring and evaluating the impact of SFD to tea plants in a timely and precise manner is a significant and urgent task for scientists and tea producers in China. The region designated as the Middle and Lower Reaches of the Yangtze River (MLRYR) in China is a major tea plantation area producing small tea leaves and low shrubs. This region was selected to study SFD to tea plants using meteorological observations and remotely sensed products. Comparative analysis between minimum air temperature (Tmin) and two MODIS nighttime land surface temperature (LST) products at six pixel-window scales was used to determine the best suitable product and spatial scale. Results showed that the LST nighttime product derived from MYD11A1 data at the 3 × 3 pixel window resolution was the best proxy for daily minimum air temperature. A Tmin estimation model was established using this dataset and digital elevation model (DEM) data, employing the standard lapse rate of air temperature with elevation. Model validation with 145,210 ground-based Tmin observations showed that the accuracy of estimated Tmin was acceptable with a relatively high coefficient of determination (R2 = 0.841), low root mean square error (RMSE = 2.15 °C) and mean absolute error (MAE = 1.66 °C), and reasonable normalized RMSE (NRMSE = 25.4%) and Nash–Sutcliffe model efficiency (EF = 0.12), with significantly improved consistency of LST and Tmin estimation. Based on the Tmin estimation model, three major cooling episodes recorded in the "Yearbook of Meteorological Disasters in China" in spring 2006 were accurately identified, and several highlighted regions in the first two cooling episodes were also precisely captured. This study confirmed that estimating Tmin based on MYD11A1 nighttime products and DEM is a useful method for monitoring and evaluating SFD to tea plants in the MLRYR. Furthermore, this method precisely identified the spatial characteristics and distribution of SFD and will therefore be helpful for taking effective preventative measures to mitigate the economic losses resulting from frost damage.

Review of the application of in-situ sensing techniques to address the tea growth characteristics from leaf to field

“…Kotikot et al [92] utilized MODIS-derived LST to detect frost occurrences in tea plantations, and further employed MODIS and risk factors associated with topography and land surface temperature [109] . Wu et al [110] put forth a real-time forecasting system for evaluating frost damage degrees by using a small weather station to validate parameters, resulting in accurate prediction of the frost damage. Wang et al [111] monitored and assessed spring frost in tea plants in China through MODIS data and established a minimum temperature (Tmin) elevation model based on reconstructed MYD11A1 nighttime LST values for 3×3 pixel windows and digital elevation model data [112] .…”

Light Intensity Regulates Low-Temperature Adaptability of Tea Plant through ROS Stress and Developmental Programs

“…Tea plants suffer from frost damage manifested as cell injury, browning, and even bud scorch [ 15 , 19 ]. These tea plants grown at high latitudes or high altitudes are faced with a higher risk of frost damage [ 20 , 21 ]. A number of satellite remote sensing techniques have recently been developed for assessing the risk of frost damage and economic loss to tea plants [ 20 , 21 , 22 , 23 ].…”

“…These tea plants grown at high latitudes or high altitudes are faced with a higher risk of frost damage [ 20 , 21 ]. A number of satellite remote sensing techniques have recently been developed for assessing the risk of frost damage and economic loss to tea plants [ 20 , 21 , 22 , 23 ]. However, how to improve the low-temperature adaptation of tea plants and reduce the damage risk is still a difficult task.…”

Exploring the Potential Use of Sentinel-1 and 2 Satellite Imagery for Monitoring Winter Wheat Growth under Agricultural Drought Conditions in North-Western Poland

“…Satellite imagery used for agricultural applications allows the phenomena under study to be observed either temporally or spatially, depending on the image resolution, from global to field scale, i.e., drought monitoring [1], plant freezing [2], crop overwintering assessment [3], yield forecasting [4], crop identification [5], plant disease and pest detection [6,7], precision agriculture [8,9]. However, so far, these studies have been expensive.…”