Combining Different Transformations of Ground Hyperspectral Data with Unmanned Aerial Vehicle (UAV) Images for Anthocyanin Estimation in Tree Peony Leaves

To explore rapid anthocyanin (Anth) detection technology based on remote sensing (RS) in tree peony leaves, we considered 30 species of tree peonies located in Shaanxi Province, China. We used an SVC HR~1024i portable ground object spectrometer and mini-unmanned aerial vehicle (UAV)-borne RS systems to obtain hyperspectral (HS) reflectance and images of canopy leaves. First, we performed principal component analysis (PCA), first-order differential (FD), and continuum removal (CR) transformations on the original ground-based spectra; commonly used spectral parameters were implemented to estimate Anth content using multiple stepwise regression (MSR), partial least squares (PLS), back-propagation neural network (BPNN), and random forest (RF) models. The spectral transformation highlighted the characteristics of spectral curves and improved the relationship between spectral reflectance and Anth, and the RF model based on the FD spectrum portrayed the best estimation accuracy (R2c = 0.91; R2v = 0.51). Then, the RGB (red-green-blue) gray vegetation index (VI) and the texture parameters were constructed using UAV images, and an Anth estimation model was constructed using UAV parameters. Finally, the UAV image was fused with the ground spectral data, and a multisource RS model of Anth estimation was constructed, based on PCA + UAV, FD + UAV, and CR + UAV, using MSR, PLS, BPNN, and RF methods. The RF model based on FD+UAV portrayed the best modeling and verification effect (R2c = 0.93; R2v = 0.76); compared with the FD-RF model, R2c increased only slightly, but R2v increased greatly from 0.51 to 0.76, indicating improved modeling and testing accuracy. The optimal spectral transformation for the Anth estimation of tree peony leaves was obtained, and a high-precision Anth multisource RS model was constructed. Our results can be used for the selection of ground-based HS transformation in future plant Anth estimation, and as a theoretical basis for plant growth monitoring based on ground and UAV multisource RS

Combining Different Transformations of Ground Hyperspectral Data with Unmanned Aerial Vehicle (UAV) Images for Anthocyanin Estimation in Tree Peony Leaves

To explore rapid anthocyanin (Anth) detection technology based on remote sensing (RS) in tree peony leaves, we considered 30 species of tree peonies located in Shaanxi Province, China. We used an SVC HR~1024i portable ground object spectrometer and mini-unmanned aerial vehicle (UAV)-borne RS systems to obtain hyperspectral (HS) reflectance and images of canopy leaves. First, we performed principal component analysis (PCA), first-order differential (FD), and continuum removal (CR) transformations on the original ground-based spectra; commonly used spectral parameters were implemented to estimate Anth content using multiple stepwise regression (MSR), partial least squares (PLS), back-propagation neural network (BPNN), and random forest (RF) models. The spectral transformation highlighted the characteristics of spectral curves and improved the relationship between spectral reflectance and Anth, and the RF model based on the FD spectrum portrayed the best estimation accuracy (R2c = 0.91; R2v = 0.51). Then, the RGB (red-green-blue) gray vegetation index (VI) and the texture parameters were constructed using UAV images, and an Anth estimation model was constructed using UAV parameters. Finally, the UAV image was fused with the ground spectral data, and a multisource RS model of Anth estimation was constructed, based on PCA + UAV, FD + UAV, and CR + UAV, using MSR, PLS, BPNN, and RF methods. The RF model based on FD+UAV portrayed the best modeling and verification effect (R2c = 0.93; R2v = 0.76); compared with the FD-RF model, R2c increased only slightly, but R2v increased greatly from 0.51 to 0.76, indicating improved modeling and testing accuracy. The optimal spectral transformation for the Anth estimation of tree peony leaves was obtained, and a high-precision Anth multisource RS model was constructed. Our results can be used for the selection of ground-based HS transformation in future plant Anth estimation, and as a theoretical basis for plant growth monitoring based on ground and UAV multisource RS

Simultaneous efficient removal of oxyfluorfen with electricity generation in a microbial fuel cell and its microbial community analysis

The performance of a microbial fuel cell (MFC) to degrade oxyfluorfen was investigated. Approximately 77% of 50 mg/L oxyfluorfen was degraded within 24 h by anodic biofilm. The temperature, pH, and initial oxyfluorfen concentration had a significant effect on oxyfluorfen degrading, and a maximum degradation rate of 94.95% could theoretically be achieved at 31.96 degrees C, a pH of 7.65, and an initial oxyfluorfen concentration of 120.05 mg/L. Oxyfluorfen was further catabolized through various microbial metabolism pathways. Moreover, the anodic biofilm exhibited multiple catabolic capacities to 4-nitrophenol, chloramphenicol, pyraclostrobin, and sulfamethoxazole. Microbial community analysis indicated that functional bacteria Arcobacter, Acinetobacter, Azospirillum, Azonexus, and Comamonas were the predominant genera in the anodic biofilm. In terms of the efficient removal of various organic compounds and energy recovery, the MFC seemed to be a promising approach for the treatment of environmental contaminants

Applications and prospects of functional oligosaccharides in pig nutrition: A review

Oligosaccharides are low molecular weight carbohydrates between monosaccharides and polysaccharides, which consist of 2 to 20 monosaccharides linked by glycosidic bonds. They have the effects of promoting growth, regulating immunity, improving the structure of intestinal flora, and are anti-inflammatory and antioxidant. With the comprehensive implementation of the antibiotic prohibition policy in China, oligosaccharides as new green feed additive have been paid more attention. Oligosaccharides can be divided into the following 2 categories according to their digestive characteristics: one is easy to be absorbed by the intestine, called common oligosaccharides, such as sucrose and maltose oligosaccharide; the other is difficult to be absorbed by the intestine and has special physiological functions, called functional oligosaccharides. The common functional oligosaccharides include mannan oligosaccharides (MOS), fructo-oligosaccharides (FOS), chitosan oligosaccharides (COS), xylo-oligosaccharides (XOS) and so on. In this paper, we review the types and sources of functional oligosaccharides, their application in pig nutrition, and the factors limiting their efficacy in recent years. This review provides the theoretical basis for further research of functional oligosaccharides, and the future application of alternative antibiotics in pig industry

Larger tumors are associated with inferior progression‐free survival of first‐line EGFR‐tyrosine kinase inhibitors and a lower abundance of EGFR mutation in patients with advanced non‐small cell lung cancer

Background The impact of primary tumor size on the therapeutic outcomes of EGFR‐tyrosine kinase inhibitors (TKIs) in advanced non‐small cell lung cancer (NSCLC) with EGFR mutation remains unclear. Methods A total of 291 consecutive patients with advanced EGFR‐mutant NSCLC administered first‐line EGFR‐TKIs were enrolled. Computed tomography was used to assess primary tumor diameter. The amplification refractory mutation system plus was used to quantitatively evaluate the abundance of EGFR mutations. Associations between depth of response, abundance of EGFR mutations, and tumor size was investigated. Results Patients were divided into three groups according to T classification: ≤ 3 cm (n = 109), 3–5 cm (n = 121), and > 5 cm (n = 61). Median progression‐free survival (PFS) was significantly longer in the ≤ 3 cm and 3–5 cm groups compared to the > 5 cm group (10.8 vs. 10.5 vs. 7.1 months; P 5 cm) were marginally significantly less EGFR‐mutant abundant than smaller tumors (≤ 5 cm) (mean ± standard deviation 30.5 ± 29.5% vs. 45.8 ± 43.1%; P = 0.08). Conclusion Larger tumors (> 5 cm) were associated with inferior PFS of first‐line EGFR‐TKI therapy in advanced NSCLC patients with activating EGFR mutations. A potential explaination might be that EGFR mutations are less abundant in larger tumors