RESUMEN
Image-based root phenotyping technologies, including the minirhizotron (MR), have expanded our understanding of the in situ root responses to changing environmental conditions. The conventional manual methods used to analyze MR images are time-consuming, limiting their implementation. This study presents an adaptation of our previously developed convolutional neural network-based models to estimate the total (cumulative) root length (TRL) per MR image without requiring segmentation. Training data were derived from manual annotations in Rootfly, commonly used software for MR image analysis. We compared TRL estimation with 2 models, a regression-based model and a detection-based model that detects the annotated points along the roots. Notably, the detection-based model can assist in examining human annotations by providing a visual inspection of roots in MR images. The models were trained and tested with 4,015 images acquired using 2 MR system types (manual and automated) and from 4 crop species (corn, pepper, melon, and tomato) grown under various abiotic stresses. These datasets are made publicly available as part of this publication. The coefficients of determination (R2), between the measurements made using Rootfly and the suggested TRL estimation models were 0.929 to 0.986 for the main datasets, demonstrating that this tool is accurate and robust. Additional analyses were conducted to examine the effects of (a) the data acquisition system and thus the image quality on the models' performance, (b) automated differentiation between images with and without roots, and (c) the use of the transfer learning technique. These approaches can support precision agriculture by providing real-time root growth information.
RESUMEN
Xiaozhong Zhitong tincture (XZZTT), a prominent Traditional Chinese Medicine (TCM) formulation comprising 21 intricate herbal components, poses a challenge in terms of quality control due to its complex composition and the interplay of diverse chemical constituents. To address this issue, a comprehensive assessment strategy was devised by integrating chromatographic and electrochemical techniques to construct a multidimensional fingerprint for XZZTT samples. This study encompassed the evaluation of 42 XZZTT samples through a systematic quantitative fingerprinting method (SQFM), while also quantifying the concentrations of four specific compounds-Geniposide, Palmatine hydrochloride, Paeonol, and Chlorogenic acid. The experimental approach encompassed the establishment of fingerprints using High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), and GC-HPLC tandem fingerprints methods. Furthermore, electrochemical fingerprints (ECFP) were established using the B-Z oscillation system, and eight characteristic parameters in the oscillation system were recorded and compared among samples. Hierarchical Clustering Analysis (HCA) was subsequently employed to classify the distinct fingerprints and compare outcomes from one-dimensional spectroscopy, GC-HPLC tandem chromatography, and the fusion fingerprints. Finally, Grey Relation Analysis (GRA) was harnessed to unravel the relationship between ECFP outcomes and peak areas in fusion fingerprints, facilitating predictions regarding the substances' reducing potency. In conclusion, the rational combination of multidimensional fingerprinting and multidimensional analysis provides a reliable and comprehensive method for the evaluation of XZZTT and its related products.
RESUMEN
High resolution spectra and luminescent lifetimes of 6 europium(III)-cinnamic acid complex {[Eu2L6(DMF)(H2O)]·nDMF·H2O}m (L=cinnamic acid I, 4-methyl-cinnamic acid II, 4-chloro-cinnamic acid III, 4-methoxy-cinnamic acid IV, 4-hydroxy-cinnamic acid V, 4-nitro-cinnamic acid VI; DMF=N, N-dimethylformamide, C3H7NO) were recorded from 8 K to room temperature. The energy levels of Eu(3+) in these 6 complexes are obtained from the spectra analysis. It is found that the energy levels of the central Eu(3+) ions are influenced by the nephelauxetic effect, while the triplet state of ligand is lowered by the p-π conjugation effect of the para-substituted functional groups. The best energy matching between the ligand triplet state and the central ion excited state is found in complex I. While the other complexes show poorer matching because the gap of (5)D0 and triplet state contracts.
RESUMEN
A series of LiY(0.95-x)Eu(0.05)Sm(x)(MoO4)2 red light emitting phosphors were synthesized by sol-gel technique. The phase impurity and spectroscopic properties were characterized by X-ray Diffraction (XRD), Photo-Luminescence (PL) and Photo-Luminescence Excitation (PLE) spectra, respectively. It is found that the PLE spectra of the Eu3+, Sm3+ co-doped nanoparticles are enhanced and broadened as compared with the solely doped samples, which will make the co-doped phosphors match better with blue and/or UV GaN based LED chips. The red emission intensity of Eu3+ is largely enhanced by the energy transfer from Sm3+. The mechanism of the enhancement is clearly proven to be the increase in the quantum efficiency of 5D0 state of Eu3+ rather than the increase in the absorption of Eu3+. Meanwhile, the characteristic f-f transitions of Sm3+ are greatly reduced, resulting in little influence in the color purity of the co-doped phosphors. The present material is an amendatory promising red light emitting phosphor for white LEDs.
