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Reactive oxygen species (ROS) are produced as undesirable by‐products of metabolism in various cellular compartments, especially in response to unfavorable environmental conditions, throughout the life cycle of plants. Stress‐induced ROS production disrupts normal cellular function and leads to oxidative damage. To cope with excessive ROS, plants are equipped with a sophisticated antioxidative defense system consisting of enzymatic and non‐enzymatic components that scavenge ROS or inhibit their harmful effects on biomolecules. Nonetheless, when maintained at relatively low levels, ROS act as signaling molecules that regulate plant growth, development, and adaptation to adverse conditions. Here, we provide an overview of current approaches for detecting ROS. We also discuss recent advances in understanding ROS signaling, ROS metabolism, and the roles of ROS in plant growth and responses to various abiotic stresses. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is a crucial macronutrient for plant growth, development, and reproduction. The effects of low P (LP) stress on leaf senescence and the role of PHR1 in LP‐induced leaf senescence are still unknown. Here, we report that PHR1 plays a crucial role in LP‐induced leaf senescence, showing delayed leaf senescence in phr1 mutant and accelerated leaf senescence in 35S:PHR1 transgenic Arabidopsis under LP stress. The transcriptional profiles indicate that 763 differentially expressed SAGs (DE‐SAGs) were upregulated and 134 DE‐SAGs were downregulated by LP stress. Of the 405 DE‐SAGs regulated by PHR1, 27 DE‐SAGs were involved in P metabolism and transport. PHR1 could bind to the promoters of six DE‐SAGs (RNS1, PAP17, SAG113, NPC5, PLDζ2, and Pht1;5), and modulate them in LP‐induced senescing leaves. The analysis of RNA content, phospholipase activity, acid phosphatase activity, total P and phosphate content also revealed that PHR1 promotes P liberation from senescing leaves and transport to young tissues under LP stress. Our results indicated that PHR1 is one of the crucial modulators for P recycling and redistribution under LP stress, and the drastic decline of P level is at least one of the causes of early senescence in P‐deficient leaves. Summary Statement: In Arabidopsis, PHR1 is the crucial regulator in low phosphate‐induced leaf senescence by modulating P recycling and redistribution. [ABSTRACT FROM AUTHOR]

The accurate measurement of river velocity is essential due to its multifaceted significance. In response to this demand, remote measurement techniques have emerged, including large-scale particle image velocimetry (LSPIV), which can be implemented through cameras or unmanned aerial vehicles (UAVs). This study conducted water surface velocity measurements in the Xihu River, situated in Miaoli County, Taiwan. These measurements were subjected to analysis using five distinct algorithms (PIVlab, Fudaa-LSPIV, OpenPIV, KLT-IV, and STIV) and were compared with surface velocity radar (SVR) results. In the quest for identifying the optimal parameter configuration, it was found that an IA size of 32 pixels × 32 pixels, an image acquisition frequency of 12 frames per second (fps), and a pixel size of 20.5 mm/pixel consistently yielded the lowest values for mean error (ME) and root mean squared error (RMSE) in the performance of Fudaa-LSPIV. Among these algorithms, Fudaa-LSPIV consistently demonstrated the lowest mean error (ME) and root mean squared error (RMSE) values. Additionally, it exhibited the highest coefficient of determination (R2 = 0.8053). Subsequent investigations employing Fudaa-LSPIV delved into the impact of various water surface velocity calculation parameters. These experiments revealed that alterations in the size of the interrogation area (IA), image acquisition frequency, and pixel size significantly influenced water surface velocity. This parameter set was subsequently employed in an experiment exploring the incorporation of artificial particles in image velocimetry analysis. The results indicated that the introduction of artificial particles had a discernible impact on the calculation of surface water velocity. Inclusion of these artificial particles enhanced the capability of Fudaa-LSPIV to detect patterns on the water surface. [ABSTRACT FROM AUTHOR]