All-solid-state potentiometric salicylic acid sensor for in-situ measurement of plant.

Using PEDOT as the conductive polymer, an innovative small-scale sensor for directly measuring salicylate ions in plants was developed, which avoided the complicated sample pretreatment of traditional analytical methods and realized the rapid detection of salicylic acid. The results demonstrate that this all-solid-state potentiometric salicylic acid sensor is easy to miniaturize, has a longer lifetime (≥1 month), is more robust, and can be directly used for the detection of salicylate ions in real samples without any additional pretreatment. The developed sensor has a good Nernst slope (63.6 ± 0.7 mV/decade), the linear range is 10-2 ~ 10-6 M, and the detection limit can reach (2.8 × 10-7 M). The selectivity, reproducibility, and stability of the sensor were evaluated. The sensor can perform stable, sensitive, and accurate in situ measurement of salicylic acid in plants, and it is an excellent tool for determining salicylic acid ions in plants in vivo.

Remote sensing estimation of the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions.

The flood storage of lakes and reservoirs plays an important role in flood regulation and control in floodplains. However, the flood storage capacity of lakes and reservoirs is ineffectively quantified at the basin scale due to the limited access to in-situ data and poor quality of optical satellite images in flooding seasons. To address this, taking a typical floodplain basin (the Poyang Lake basin) in the Yangtze as a study case, radar satellite data combined with measured bathymetry and digital elevation model data were utilized to reconstruct the time series of the water inundation area and water storage change of all lakes and reservoirs larger than 1 km2 during the once-in-a-generation flood event that occurred in 2020 (termed as the 2020 flood event hereafter). Results show that the flood storage capacity of Poyang Lake can reach the maximum at 12.18 Gt, and that for other lakes and reservoirs within the basin is approximately 2.95 Gt. It indicates a total flood-storage capacity of 15.13 Gt for the basin-scale lakes and reservoirs, approximately accounting for 45.02% of the terrestrial water storage change of the basin. The storage capacity of Poyang Lake was approximately four times larger than the entirety of other lakes and reservoirs in the basin despite that its maximum water inundation area is in the proportion of 2.58 times other water bodies. This finding indicates that the Poyang Lake provided the dominant contribution to flood storage among all the lakes and reservoirs in the basin. This study introduced a remote sensing approach to quantify the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions during the flood event, which could fill the insufficiently-quantified knowledge about dynamics of lakes and reservoirs in areas lacking full-covered in-situ data records. This study also helps to offer a quantitative basis to improve flood forecasting and control for the public authority, stakeholders, and decision-makers.

Satellite and UAV-based remote sensing for assessing the flooding risk from Tibetan lake expansion and optimizing the village relocation site.

Climate change in recent decades led to the remarkable expansions for most lakes in endorheic basins of the Tibetan Plateau (TP). Enlarged lake inundation areas may pose adverse effects and potential threats on the local human living environment, especially for high-risk villages adjacent to rapidly expanding lakes. Taking a rapidly expanding lake, Angzi Co in the central TP as a study case, we investigated the flooding risk of lake growth on the local living environment and proposed an optimized solution of village relocation selection on the basis of satellite and unmanned aerial vehicle (UAV) remote sensing. The detection of spatiotemporal variations of Angzi Co using optical and altimetric satellite observations revealed a significant area and water level increase by 81.28 km2 and 5.78 m, respectively, from 2000 to 2020. We also assessed the vertical accuracy of multi-source digital elevation model (DEM) products using Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) altimetry data and further examined the flooding risk and potential influences of lake expansion on adjacent settlements (Guozha Village). Results indicated that UAV-DEM achieves excellent advantages in depicting details of lake shoreline variations and simulating potential submergence regions, followed by Advanced Land Observing Satellite World 3D DEM (AW3D DEM). Moreover, assuming that Angzi Co maintains the water level at a growth rate of 0.29 m/a (the average change rate during 2000-2020), the village will be submerged in approximate 10 years based on our assessment. Furthermore, we designed an optimal relocation site southwest of Guozha Village and approximately 3 km away based on the GIS-MVDA method and field investigations. An initial remote sensing-based approach for assessing the flooding risk from dramatic lake expansions in the TP and optimizing the village relocation site was proposed in this study to provide an essential scientific reference for formulating risk mitigation solutions under future climate change scenarios.

Plant electrical signals: A multidisciplinary challenge.

Plant electrical signals, an early event in the plant-stimulus interaction, rapidly transmit information generated by the stimulus to other organs, and even the whole plant, to promote the corresponding response and trigger a regulatory cascade. In recent years, many promising state-of-the-art technologies applicable to study plant electrophysiology have emerged. Research focused on expression of genes associated with electrical signals has also proliferated. We propose that it is appropriate for plant electrical signals to be considered in the form of a "plant electrophysiological phenotype". This review synthesizes research on plant electrical signals from a novel, interdisciplinary perspective, which is needed to improve the efficient aggregation and use of plant electrical signal data and to expedite interpretation of plant electrical signals.

Illumination/Darkness-Induced Changes in Leaf Surface Potential Linked With Kinetics of Ion Fluxes.

A highly reproducible plant electrical signal-light-induced bioelectrogenesis (LIB) was obtained by means of periodic illumination/darkness stimulation of broad bean (Vicia faba L.) leaves. By stimulating the same position of the same leaf with different concentrations of NaCl, we observed that the amplitude and waveform of the LIB was correlated with the intensity of stimulation. This method allowed us to link dynamic ion fluxes induced by periodic illumination/darkness to salt stress. The self-referencing ion electrode technique was used to explore the ionic mechanisms of the LIB. Fluxes of H+, Ca2+, K+, and Cl- showed periodic changes under periodic illumination/darkness before and after 50 mM NaCl stimulation. Gray relational analysis was used to analyze correlations between each of these ions and LIB. The results showed that different ions are involved in surface potential changes at different stages under periodic illumination/darkness. The gray relational grade reflected the contribution of each ion to the change in surface potential at a certain time period. The ion fluxes data obtained under periodic illumination/darkness stimulation will contribute to the future development of a dynamic model for interpretation of electrophysiological events in plant cells.