Tracking hydrological processes during the formation of Marinoan cap dolostone; insight from reordered clumped isotopes

Widespread dolomite precipitates, known as cap dolostone, were deposited in the aftermath of the Neoproterozoic Marinoan glaciation, and are thought to reflect dramatic perturbations of seawater chemistry in the aftermath of the glaciation. However, controversy still remains on the nature and the hydrodynamic process of fluids that produced these dolomites. In this study, we present clumped isotope values (Delta (sub 47) ) of Neoproterozoic Marinoan cap carbonates from five sections in Namibia and South China and examine the spatial variation of the post-glacial hydrodynamics across the two carbonate platforms. The Delta (sub 47) -temperatures show the mineral-specific variation in dolostone and limestone, a feature that can be attributed to the solid-state reordering driven by short-term hydrothermal events. Based on the results of theoretical calculations and laboratory experiments, we present a framework that enables the utilization of the reordered clumped isotopes to trace the dolomitization process. Under such a framework, we find the reordering patterns determined by clumped isotopes are indistinguishable from the inner to outer platforms as well as between the dolostone and limestone, which suggests the mixture of meltwater and seawater as the source of dolomitizing fluids. Our findings demonstrate the clumped isotope can be used to trace hydrological processes for deep-time successions, and offer insight into the enigmatic origin of cap carbonates

Estimation of Garden Chrysanthemum Crown Diameter Using Unmanned Aerial Vehicle (UAV)-Based RGB Imagery

Crown diameter is one of the crucial indicators for evaluating the adaptability, growth quality, and ornamental value of garden chrysanthemums. To accurately obtain crown diameter, this study employed an unmanned aerial vehicle (UAV) equipped with a RGB camera to capture orthorectified canopy images of 64 varieties of garden chrysanthemums at different growth stages. Three methods, namely RGB color space, hue-saturation-value (HSV) color space, and the mask region-based convolutional neural network (Mask R-CNN), were employed to estimate the crown diameter of garden chrysanthemums. The results revealed that the Mask R-CNN exhibited the best performance in crown diameter estimation (sample number = 2409, R2 = 0.9629, RMSE = 2.2949 cm). Following closely, the HSV color space-based model exhibited strong performance (sample number = 2409, R2 = 0.9465, RMSE = 3.4073 cm). Both of the first two methods were efficient in estimating crown diameter throughout the entire growth stage. In contrast, the RGB color space-based model exhibited slightly lower performance (sample number = 1065, R2 = 0.9011, RMSE = 3.3418 cm) and was only applicable during periods when the entire plant was predominantly green. These findings provide theoretical and technical support for utilizing UAV-based imagery to estimate the crown diameter of garden chrysanthemums