Spring frost damage (SFD), defined as the disaster during the period of newly formed tea buds in spring caused by lower temperature and frost damage, is a particular challenge for tea plants (Camellia sinensis), whose capacity to adapt to extreme weather and climate impacts is limited. In this paper, the region of the Middle and Lower Reaches of the Yangtze River (MLRYR) in China was selected as the major tea plantation study area, and the study period was focused on the concentrated occurrence of SFD, i.e., from March to April. By employing the standard lapse rate of air temperature with elevation, a minimum temperature (Tmin) estimation model that had been previously established was used based on reconstructed MYD11A1 nighttime LST values for 3 × 3 pixel windows and digital elevation model data. Combined with satellite-based Tmin estimates and ground-based Tmin observations, the spatiotemporal characteristics of SFD for tea plants were systematically analyzed from 2003 to 2020 in the MLRYR. The SFD risks at three scales (temporal, spatial, and terrain) were then evaluated for tea plants over the MLRYR. The results show that both SFD days at the annual scale and SFD areas at the daily scale exhibited a decreasing trend at a rate of 2.7 days/decade and 2.45 × 10⁴ ha/day, respectively (significant rates at the 0.05 and 0.01 levels, respectively). The period with the highest SFD risk appeared mainly in the first twenty days of March. However, more attention should be given to the mid-to-late April time period due to the occurrence of late SFD from time to time. Spatially, areas with relatively higher SFD days and SFD risks were predominantly concentrated in the higher altitude areas of northwestern parts of MLRYR for both multi-year averages and individual years. Fortunately, in regions with a higher risk of SFD, the distribution of tea plants was relatively scattered and the area was small. These findings will provide helpful guidance for all kinds of people, including government agencies, agricultural insurance agencies, and tea farmers, in order that reasonable and effective strategies to reduce losses caused by spring frost damage to tea plants may be recommended and implemented.

The implementation of real-time dynamic monitoring of disaster formation and severity is essential for the timely adoption of disaster prevention and mitigation measures, which in turn minimizes disaster-related losses and safeguards agricultural production safety. This study establishes a low-temperature disaster (LTD) monitoring system based on machine learning algorithms, which primarily consists of a module for identifying types of disasters and a module for simulating the evolution of LTDs. This study firstly employed the KNN model combined with a piecewise function to determine the daily dynamic minimum critical temperature for low-temperature stress (LTS) experienced by winter wheat in the Huang-Huai-Hai (HHH) region after regreening, with the fitting model’s R², RMSE, MAE, NRMSE, and MBE values being 0.95, 0.79, 0.53, 0.13, and 1.716 × 10⁻¹¹, respectively. This model serves as the foundation for determining the process by which winter wheat is subjected to LTS. Subsequently, using the XGBoost algorithm to analyze the differences between spring frost and cold damage patterns, a model for identifying types of spring LTDs was developed. The validation accuracy of the model reached 86.67%. In the development of the module simulating the evolution of LTDs, the XGBoost algorithm was initially employed to construct the Low-Temperature Disaster Index (LTDI), facilitating the daily identification of LTD occurrences. Subsequently, the Low-Temperature Disaster Process Accumulation Index (LDPI) is utilized to quantify the severity of the disaster. Validation results indicate that 79.81% of the test set samples exhibit a severity level consistent with historical records. An analysis of the environmental stress-mitigation mechanisms of LTDs reveals that cooling induced by cold air passage and ground radiation are the primary stress mechanisms in the formation of LTDs. In contrast, the release of latent heat from water vapor upon cooling and the transfer of sensible heat from soil moisture serve as the principal mitigation mechanisms. In summary, the developed monitoring framework for LTDs, based on environmental patterns of LTD formation, demonstrates strong generalization capabilities in the HHH region, enabling daily dynamic assessments of the evolution and severity of LTDs.

Low-temperature stress during the jointing stage severely disrupts the coordination of the source–flow–sink system in winter wheat. To elucidate the underlying mechanism, three wheat cultivars with different winter habits (Zhenmai 12, Jimai 22, and Shannong 38) were selected and subjected to six temperature levels (−6 °C to 8 °C) and three stress durations (2–6 days). The effects of vascular bundle traits on the transport of photosynthetic products, dry matter distribution, and yield formation were analyzed. The results showed that Zhenmai 12 and Jimai 22 completely ceased photosynthesis under 0 °C and −3 °C, respectively. The leaf vascular bundle area continuously decreased with increasing low-temperature stress, while the proportion of xylem and phloem initially increased by approximately 15% and 10%, respectively, before rapidly decreasing to 65% of the control value. In the stem, the three vascular bundle parameters initially increased by 20%, 25%, and 20%, respectively, before quickly decreasing to 50%. Changes in the vascular bundle structure weakened the transport capacity of assimilates, with dry matter in leaves and stems decreasing by 15–20% and 10%, respectively, while the root dry matter increased by 20–30%. Correlation analysis revealed highly significant relationships (p < 0.001) between vascular bundle parameters and yield components. Principal component and cluster analyses indicate that the area of leaf and stem vascular bundles, maximum net photosynthetic rate, and water use efficiency may be key indicators in explaining the variation in yield. Radar plots further validated this finding, showing that Zhenmai 12 and Jimai 22 are more sensitive to changes in the maximum net photosynthetic rate, while Shannong 38 exhibits a greater sensitivity to changes in water use efficiency. Based on existing research on photosynthetic pathways and dry matter distribution, this study innovatively investigates the potential relationship between material transport and yield formation under low-temperature stress during the jointing stage from the perspective of anatomical structure and functional coupling. The findings provide new insights into understanding the structural impact of low-temperature stress on crop yield formation and offer theoretical support for identifying the structural basis of limited material transport under stress and for developing disaster diagnostic models driven by structural parameters.

Frost stress is a major environmental factor that limits apricot growth in the warm temperate zone (WTZ) of China, and is always triggered by extreme low temperature weather processes. In this study, the characteristics of the apricot frost processes f(D,Tcum), which were identified from historical disaster representation, were analyzed and apricot frost evaluation indicators were developed, thus facilitating the process-based assessment and spatiotemporal analysis of apricot frost processes. Periods of low temperature that persist for 1~2, 3 and ≥4 days (i.e., duration days, D) provide the initial identification indicator for light, moderate and severe apricot frost. The threshold ranges for Tcum are 0~3.9, 9.2~12.0 and >16.2 for D values of 1~2, 3 and ≥4, respectively. The northwest of the WTZ is dominated by apricot frost, with approximately 80% of apricot frost being light, followed by moderate and severe. Regional apricot frost exhibited a significant decreasing trend over the last four decades. A total of 29.65% of stations, which were mainly located in the northwest and middle parts of the study region, detected an increasing trend in apricot frost. The results provide technical support for targeted apricot frost level detection, and the process-based spatiotemporal characteristics of apricot frost can provide basic information for the prevention and mitigation of apricot frost.

Drought stress is one of the major environmental limiting factors for grape growth in the Bohai Rim Region (BRR) in China. Investigation of process-based meteorological evaluation indicators is of particular interest to precisely understand the spatiotemporal characteristics of grape drought processes, providing substantial support for grape drought monitoring, prevention, and mitigation. In this study, a daily index grape drought index (GDI) was constructed based on the rolling calculation of water profit and deficit. Characteristics of GDI in historical drought disaster samples were analyzed, and drought evaluation level indicators were constructed, facilitating the assessment of process-based grape drought risk. The results showed that duration days with GDI<-0.4 identified can be used as drought level indicators, and the threshold of grape drought in germination-new shoot (P1), flowering-fruit setting (P2), fruit expansion (P3), and coloring-mature (P4) were 14, 13, 12, and 13 days with GDI<-0.4, respectively. Identification results calculated by grape drought indicators were basically consistent with historic occurrence levels of grape drought, with 76.9% of historical records completely consistent with the grape level assessment, and 15.4% within one level. The process-based grape drought risk gradually decreased with the advancement of grape growth process, with grape drought risk in the order of P1 > P2 > P3 > P4. Beijing, Tianjin, Hebei and west of Liaoning were detected with the higher drought risk.