High molecular weight glutenin subunits (HMW-GS) from three hexaploid wheat species (AABBDD, 2n=6x=42, Triticum aestivum L., T. spelta L., and T. compactum L.) were separated and identified by acidic ...capillary electrophoresis (A-CE) with phosphate-glycine buffer (pH 2.5) in uncoated fused-silica capillaries (50 micrometer, i.d. x 25.5 cm) at 12.5 kV and 40 degrees C. The rapid separations (<15 min) of HMW-GS with good repeatability (RSD < 2%) were obtained using a fast capillary rising protocol. All 17 HMW-GS analyzed could be well separated and their relative migration orders were ranked. In particular, the good quality subunit pair 5+10 could be differentiated from poor quality subunit pair 2+12. In addition, the other three allelic pairs of 13+16, 17+18, and 7+8 subunits that were considered to have positive effects on dough properties, as well as three pairs of novel subunits 13+22*, 13*+19*, and 6.1+22.1 detected from spelt and club wheat, can also be readily separated and identified. An additional protein subunit presented in Chinese bread wheat cultivar Jing 411 and club wheat TRI 4445/75, respectively, was detected by both A-CE and 2-D gel electrophoresis (A-PAGE x SDS-PAGE), for which further identification is needed.
Image quality assessment is an important and necessary task in the field of image processing. It can simulate human visual perception accurately and effectively to ensure the credibility of ...information. Although the existing IQA algorithm based on CNN has achieved excellent success, the generalization and robustness of the algorithm are limited due to the loss of image information during feature extraction. The research shows that the phase and amplitude of image frequency domain will change with the quality, so we proposes an image quality assessment algorithm based on dual domains fusion (DualD-IQA). Using the frequency domain and spatial domain as multiple inputs of convolutional neural network, we can complement each other to represent image quality related information. Moreover, the input of any scale can be accepted by adding bilinear pooling, so as to ensure the reliability and robustness of the quality evaluation results. Experimental results show that the algorithm in this paper achieves higher consistency and accuracy in two commonly used public databases, and has higher robustness in different distortion types and cross databases.
Face Quality Assessment Based on Local Gradient Lu, Yaxuan; Li, Weijun; Ning, Xin ...
2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS),
2020-March
Conference Proceeding
Face recognition system performance is affected by face image quality. In this paper, a face matching score, instead of a subjective perceptual score, is used as the image quality label to build a ...face image quality database; therefore, the ground truth quality achieved high accordance with the recognition performance. The database contains five common practical application distortion types for 19 people and three to five collection scenes for each. In addition, a face image quality algorithm based on a local gradient is proposed to judge the image quality. Making use of the fact that face landmarks can locate contour areas that have rich gradient information, a new mask based on human visual characteristics is designed to evaluate the image quality by using the local gradient information of landmark neighborhoods; this method was used to control for the influence of the image content and background. Our algorithm does not rely on a large amount of training data, and it has low computational complexity. The experimental results show that the algorithm is effective and efficient for evaluating image quality and improving the performance of face recognition systems.
Leaf area index (LAI) is an important structure parameter to illuminate the fractions of solar radiation absorbed, transmitted and reflected by the plant canopy, and also a useful reference for ...ecological and meteorological modeling. The GLAS full-waveform Lidar data of ICESat satellite are easily available and global coverage, which can also provide detailed forest canopy structure information in the GLAS footprint. In this study, we show a LAI estimation method from the GLAS waveform Lidar data at footprint level. Firstly, Gaussian decomposition method is used to process the raw GLAS waveform data to identify ground echo energy and canopy echo energy. In addition, the optical height threshold (HT) to separate the canopy and ground in the GLAS waveform has been discussed, and the result show that 3 m is the optical HT in our study area. Secondly, a reflectance correction method is used to calculate the laser penetration ratio (PC) of forest covered GLAS footprints based on the ground echo energy and canopy echo energy. Thirdly, the relationship between the between the field-measured LAIs and P C is constructed based on the Beer-Lambert law. The determination coefficient (R 2 ) is 0.69 and the root mean square error (RMSE) is 0.64. The performance of the GLAS-derived LAIs is also evaluated using the 20 field-measured LAIs. The result indicates that the GLAS-derived LAIs have a high accordance with the field measurements (R 2 =0.67, RMSE=0.52). The result suggests that the GLAS waveform data can be used to retrieval LAI for various ecological applications.
It has been a hot study field to extract forest structure parameter using Airborne LiDAR. Since footprints of Airborne LiDAR data are discontinuously distributed with small data coverage, therefore, ...it is impossible to obtain the forest structure information of continuous region using Airborne LiDAR data alone. The MODIS BRDF shape indicators contain the information regarding 3-D structure of forest and have the possibility to retrieve the structural parameters of forest. In this study, we select Howland Forest, Harvard Forest, La Selva Forest and Bartlett Forest as experimental areas, and aim to construct a canopy height estimation model from the airborne Laser Vegetation Imaging Sensor (LVIS) data and MODIS BRDF shape indicators. Firstly, H100 canopy height was extracted from the LVIS data and the MODIS BRDF shape indicators were calculated based on MODIS data. Secondly, using the Random Forest algorithm to develop a canopy height estimation model with H100 canopy height data and MODIS BRDF shape indicators. Finally, 10-fold cross-validation method is used to evaluate the accuracy of the model, and the validation results show that the MODIS BRDF shape indicators can be estimated forest canopy heights in high accuracy.
Cultivated emmer (Triticum dicoccum, 2n=4x=28, AABB) is closely related to bread wheat and possesses extensive allelic variations in high molecular weight glutenin subunit (HMW‐GS) composition. These ...alleles may be an important genetic resource for wheat quality improvement. To isolate and clone HMW‐GS genes from cultivated emmer, two pairs of allele‐specific (AS) PCR primers were designed to amplify the coding sequence of y‐type HMW‐GS genes and their upstream sequences, respectively. The results showed that single bands of strong amplification were obtained through AS‐PCR of genomic DNA from emmer. After cloning and sequencing the complete sequence of coding and 5′‐flanking regions of a y‐type subunit gene at Glu‐A1 locus was obtained. Nucleotide and deduced amino acid sequences analysis showed that this gene possessed a similar structure as the previously reported Ay gene from common wheat, and is hence designated as Ay1d. The distinct feature of the Ay1d gene is that its coding region contains four stop codons and its upstream region has a 85‐bp deletion in the same position of the Ay gene, which are probably responsible for the silencing of y‐type subunit genes at Glu‐A1 locus. Phylogenetic analysis of HMW glutenin subunit genes from different Triticum species and genomes were also carried out.
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