High-resolution satellite imagery enables decametric-scale quasi-circular vegetation patch (QVP) mapping, which greatly aids the monitoring of vegetation restoration projects and the development of theories in pattern evolution and maintenance research. This study analyzed the potential of employing five seasonal fused 5 m spatial resolution CBERS-04 satellite images to map QVPs in the Yellow River Delta, China, using the Random Forest (RF) classifier. The classification accuracies corresponding to individual and multi-season combined images were compared to understand the seasonal effect and the importance of optimal image timing and acquisition frequency for QVP mapping. For classification based on single season imagery, the early spring March imagery, with an overall accuracy (OA) of 98.1%, was proven to be more adequate than the other four individual seasonal images. The early spring (March) and winter (December) combined dataset produced the most accurate QVP detection results, with a precision rate of 66.3%, a recall rate of 43.9%, and an F measure of 0.528. For larger study areas, the gain in accuracy should be balanced against the increase in processing time and space when including the derived spectral indices in the RF classification model. Future research should focus on applying higher resolution imagery to QVP mapping.
Freezing tolerance is a significant trait in plants that grow in cold environments and survive through the winter. Apple (Malus domestica Borkh.) is a cold-tolerant fruit tree, and the cold tolerance of its bark is important for its survival at low temperatures. However, little is known about the gene activity related to its freezing tolerance. To better understand the gene expression and regulation properties of freezing tolerance in dormant apple trees, we analyzed the transcriptomic divergences in the bark from 1-year-old branches of two apple cultivars, “Golden Delicious” (G) and “Jinhong” (H), which have different levels of cold resistance, under chilling and freezing treatments. “H” can safely overwinter below −30 °C in extremely low-temperature regions, whereas “G” experiences severe freezing damage and death in similar environments. Based on 28 bark transcriptomes (from the epidermis, phloem, and cambium) from 1-year-old branches under seven temperature treatments (from 4 to −29 °C), we identified 4173 and 7734 differentially expressed genes (DEGs) in “G” and “H”, respectively, between the chilling and freezing treatments. A gene coexpression network was constructed according to this expression information using weighted gene correlation network analysis (WGCNA), and seven biologically meaningful coexpression modules were identified from the network. The expression profiles of the genes from these modules suggested the gene regulatory pathways that are responsible for the chilling and freezing stress responses of “G” and/or “H.” Module 7 was probably related to freezing acclimation and freezing damage in “H” at the lower temperatures. This module contained more interconnected hub transcription factors (TFs) and cold-responsive genes (CORs). Modules 6 and 7 contained C-repeat binding factor (CBF) TFs, and many CBF-dependent homologs were identified as hub genes. We also found that some hub TFs had higher intramodular connectivity (KME) and gene significance (GS) than CBFs. Specifically, most hub TFs in modules 6 and 7 were activated at the beginning of the early freezing stress phase and maintained upregulated expression during the whole freezing stress period in “G” and “H”. The upregulation of DEGs related to methionine and carbohydrate biosynthetic processes in “H” under more severe freezing stress supported the maintenance of homeostasis in the cellular membrane. This study improves our understanding of the transcriptional regulation patterns underlying freezing tolerance in the bark of apple branches.
We apply the film bulk acoustic resonator for the detection of nerve gas. The resonator is consisted of a ZnO piezoelectric stack and a W/SiO2 Bragg reflector. Poly(vinylidene fluoride) (PVDF) is used as the sensing coating to adsorb the analyte under test. The testing results show that our proposed sensor can yield a sensitive, reversible and reproducible response to nerve gas. The relationship between the frequency shifts and the concentrations of the nerve gas exhibits a perfect linear correlation in the range of 10–50 ppm. The gas sensitivity of the proposed sensor is 718 kHz ppm−1, which is several orders of magnitude higher than that of a quartz crystal microbalance with the same sensitive coating. This study proves that it is feasible to use the PVDF-coated thin film bulk acoustic resonator for the detection of the traced nerve gas.
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