Accurate and rapid detection of tea shoots within the tea canopy is essential for achieving the automatic picking of famous tea. The current detection models suffer from two main issues: low inference speed and difficulty in deployment on movable platforms, which constrain the development of intelligent tea picking equipment. Furthermore, the detection of tea canopy shoots is currently limited to natural daylight conditions, with no reported studies on detecting tea shoots under artificial light during the nighttime. Developing an all-day tea picking platform would significantly improve the efficiency of tea picking. In view of these problems, the research objective was to propose an all-day lightweight detection model for tea canopy shoots (TS-YOLO) based on YOLOv4. Firstly, image datasets of tea canopy shoots sample were collected under low light (6:30–7:30 and 18:30–19:30), medium light (8:00–9:00 and 17:00–18:00), high light (11:00–15:00), and artificial light at night. Then, the feature extraction network of YOLOv4 and the standard convolution of the entire network were replaced with the lightweight neural network MobilenetV3 and the depth-wise separable convolution. Finally, to compensate for the lack of feature extraction ability in the lightweight neural network, a deformable convolutional layer and coordinate attention modules were added to the network. The results showed that the improved model size was 11.78 M, 18.30% of that of YOLOv4, and the detection speed was improved by 11.68 FPS. The detection accuracy, recall, and AP of tea canopy shoots under different light conditions were 85.35%, 78.42%, and 82.12%, respectively, which were 1.08%, 12.52%, and 8.20% higher than MobileNetV3-YOLOv4, respectively. The developed lightweight model could effectively and rapidly detect tea canopy shoots under all-day light conditions, which provides the potential to develop an all-day intelligent tea picking platform.

Severe frost usually has adverse impacts on agricultural production, resulting in crop freeze injury, poor crop yield, and crop quality reduction. Timely and accurate detection of frost plays an important role in cold damage warnings, prevention, and control. Current frost detection methods mostly use physical properties such as light, electricity, and heat, or the judge and quantify using environmental factors such as temperature and wind speed. However, it is difficult to detect and accurately identify the frosting phenomenon in real time during field trials because of the complex environment, different plant types, and interference by many factors during observation. To provide an overview of the analytical tools for scientists, researchers, and product developers, a review and comparative analysis of the available literature on frost mechanisms, correlations, and characteristics are presented in this study. First, the mechanisms of the frost formation process, frost level, and the significance of detection, are introduced. Then, the methods and techniques used to measure frost on plant surfaces are synthetically classified and further compared. Moreover, the key points and difficulties are summarized and discussed. Finally, some constructive methods of frost detection are proposed to improve the frost detection process.

Sprinkler irrigation is an effective method for protecting economic crops from frost damage; however, current research on its impacts is insufficient and lacks comprehensive evaluation. This research investigated the effects of sprinkler irrigation for frost protection on the air, soil, and tea plants in the tea garden. Sprinkler frost protection experiments were conducted in the tea garden, where temperature sensors measured the air and soil temperatures, and Monitoring-PAM was used to measure the chlorophyll fluorescence parameters (Fv/Fm) of the tea plants. The results indicated that lower initial ambient temperatures or smaller droplet sizes accelerate the rate of air temperature increase and slow the cooling rate. Under conditions of heavy frost, ice formation from irrigation water acts as an insulating layer, protecting the inter-row soil. Additionally, the Fv/Fm values of tea leaves protected by sprinkler irrigation ranged from 0.6 to 0.7, and were significantly higher than those of leaves exposed to frost damage. The results also showed that air and soil temperature and tea Fv/Fm can be used to perform a comprehensive assessment of sprinkler frost protection effectiveness.

Climatic changes have caused seasonal drought to occur frequently in tea fields of low-mountain and hill regions over the past decades. This leads to huge losses in the quality and yields of famous tea, which restricts the economic development of the tea industry. It is crucial to implement suitable irrigation scheduling. The crop water stress index (CWSI) is the main index to assess the water status of the crop. When the crop suffers irreversible drought stress, its critical water status cannot be easily evaluated using the CWSI. The change from stomatal limitations (SLs) to non-stomatal limitations (NSLs) of photosynthesis is vital for accurately recognizing crop drought stress. Thus, the objective of this research is to determine the critical crop water stress index of tea based on intercellular CO₂ concentration (C_i) dynamic responses to drought stress. During two sensitive periods of water stress (famous tea harvest season and summer drought season, which are from March to April and July to August, respectively), the dynamic changes in the CWSI in tea were calculated and analyzed based on the CWSI theoretical model. The upper and lower baselines were determined on a daily basis and during a certain period. A critical value of the CWSI represents irreversible drought damage. This was determined by the characteristic response of the C_i of tea leaves during extreme drought stress. The results showed the following: (1) during the famous tea harvest season and summer drought season, the daily variation in CWSI was similar. During a certain period, the former maintained a stable fluctuation, while the latter increased in fluctuation. (2) The C_i showed a trend of fluctuating downward to a low point and then upward during extreme drought stress. After reaching the low point, it quickly increased in the former and stabilized for a day in the latter. When the C_i reached the low point, the upper benchmark of this critical point was 13.9 μmol·mol⁻¹, the lower benchmark was 3.4, and the CWSI was 0.27. This critical CWSI could be used as an irrigation threshold point to ensure normal production for tea fields.

Wind machines based on the air disturbance method are progressively employed to mitigate frost damage within the agricultural machinery frost protection. These devices are utilized during radiative frost nights to disrupt near-surface thermal inversion through air mixing. Despite this application, the fundamental mechanisms underlying these mixing processes are not well comprehended. In this research, numerical simulations were conducted using COMSOL Multiphysics software version 6.0 to simulate the flow and heat transfer processes between the thermal airflow and both the tea canopy and stems. The results indicated that due to obstruction from the canopy cross-section, the airflow velocity on the contact surface rapidly increased. As the airflow further progressed, the high-speed region of the airflow gradually approached the canopy surface. Turbulent kinetic energy increased initially on the windward side of the canopy cross-section and near the top interface. On the windward side of the canopy, due to the initial impact of the thermal airflow, rapid heating occurred, resulting in a noticeable temperature difference between the windward and leeward sides within a short period. In the interaction between airflow and stems, with increasing airflow velocity, fluctuations and the shedding of wake occurred on the leeward side of the stems. The maximum sensible heat flux at the windward vertex of the stem increased significantly with airflow velocity. At an airflow velocity of 2.0 m/s, the maximum heat flux value was 2.37 times that of an airflow velocity of 1.0 m/s. This research utilized simulation methods to study the interaction between airflow and tea canopy and stems in frost protection, laying the foundation for further research on the energy distribution in tea ecosystem under the disturbance of airflow for frost protection.