Insulin-like growth factor 1 receptor (IGF-1R) gene is the main effector of insulin-like growth factor (IGF), which plays an important role in growth, development and reproduction of the animal ...organism. This study aimed to investigate the association of IGF-1R gene single nucleotide polymorphisms (SNPs) with egg quality and carcass traits of quail by direct sequencing. In this study, genomic DNA was extracted from quail blood samples of 46 Chinese yellow (CY) quail, 49 Beijing white (BW) quail and 48 Korean (KO) quail strains. Egg quality and carcass traits were measured and used for IGF-1R gene analysis in 3 quail strains. The results showed that 2 SNPs (A57G and A72T) of the IGF-1R gene were detected in 3 quail strains. The A57G was significantly associated with yolk width (YWI) in BW strain (P < 0.05). Whereas A72T was significantly associated with egg shell thickness (EST) in BW strain (P < 0.05), and significantly associated with egg weight (EW), egg long (EL), and egg short (ES) in KO strain (P < 0.05). Haplotypes based on 2 SNPs showed significant effect on EST in 3 quail strains (P < 0.05), it also has a significant effect on EW in KO strain (P < 0.05). Meanwhile, A72T was significantly associated with liver weight (LW) and dressing percentage (DP) in 3 strains (P < 0.05). Haplotypes showed significant effect on LW (P < 0.05). Therefore, the IGF-1R gene may be a molecular genetic marker to improve egg quality and carcass traits in quails.
This study aimed to identify polymorphisms of gonadotropin-releasing hormone (GnRH) gene and their association with growth traits in quail by PCR and direct sequencing. Genomic DNA was extracted from ...quail blood samples of 36 from Savimalt (SV) and 49 from French Giant (FG). Growth traits were measured and used for candidate gene analysis, as body weight (BW), shank length (SL), chest width (CW), chest depth (CD), breastbone length (BBL), body length (BL), and shank circumference (SC). The results showed that a total of 20 SNPs were detected in GnRH gene, whereas 8 SNPs were significantly associated with growth traits (P < 0.05). The T215C, G279A, C458T, A520G, and C547G were significantly associated with SL at 3 wk of age in the FG strain, whereas A583T was significantly related to BBL and BL, and C591T was significantly related to SL, BBL, and BL, whereas A592G was significantly correlated with SL, CW, CD, BBL, and BL (P < 0.05). The 8 SNPs were significantly related to CW, CD, and BBL at 3 wk of age in the SV strain, whereas A583T, C591T, and A592G were significantly associated with BW (P < 0.05). The G279A showed significant correlations with SL at 5 wk of age in FG, whereas A583T showed significant associations with SC in FG, and C591T was significantly associated with BW and SC in FG, whereas A592T was significantly related to BW, SL, and CD in FG (P < 0.05). The T215C, G279A, C458T, A520G, and C547G were significantly correlated with BW, CW, BBL, and BL at 5 wk of age in SV, whereas A583T, C591T, and A592G were significantly related to BW, SL, CW, BBL, and BL (P < 0.05). Haplotypes based on 8 SNPs showed significant correlation with BW, SL, CW, CD, BBL, BL, and SC in FG (P < 0.05). In conclusion, the GnRH gene could be used as a molecular genetic marker to provide theoretical foundation to improve growth traits in quail.
This study aimed to identify InDels from the FTO and PLIN1 genes and to analyze their association with morphometric traits in Hu sheep (HS), Dupor sheep (DS), and Small Tail Han sheep (STHS). The FTO ...and PLIN1 genes were genotyped using the insertion/deletion (InDel) method. A one-way ANOVA with SPSS 26.0 software (IBM Corp, Armonk, NY, USA) was used to assess the effect of the InDel FTO and PLIN1 genes on morphometric traits. The results revealed significant associations between certain InDels and the morphometric traits in different breeds of sheep. Specifically, FTO-2 was significantly associated with cannon circumference (CaC) in HS rams and body height (BoH) in HS ewes (p < 0.05). FTO-2 was also significantly associated with chest width (ChW), CaC, head length (HeL), and coccyx length (CoL) in the STHS breed (p < 0.05). FTO-3 showed significant associations with BoH in HS rams and BoH, back height (BaH), ChW, and chest depth (ChD) in HS ewes (p < 0.05). FTO-3 was also significantly associated with ChW in the DS and STHS breeds (p < 0.05). FTO-5 was significantly associated with body weight (BoW) in the DS breed and BoH in the STHS breed (p < 0.05). Furthermore, PLIN1 was significantly related to BoW in the DS breed and was significantly associated with CoL and forehead width (FoW) in the STHS breed (p < 0.05). In conclusion, the study suggested that InDels in the FTO and PLIN1 genes could provide practical information to improve morphometric traits in sheep breeding.
Fat mass and obesity-associated (FTO) and perilipin1 (PLIN1) genes have been associated with fat mass deposition. These genes have also been found to regulate economic traits (e.g., morphometric ...traits) in animals. In this study, the researchers analyzed insertion–deletion (InDel) variations in the FTO and PLIN1 genes and their association with morphometric traits in three sheep breeds (Hu sheep, Dupor sheep, and Small Tail Han sheep). A total of six InDels (FTO-2, FTO-3, FTO-4, FTO-5, FTO-6, and PLIN1) were identified in the FTO and PLIN1 genes in the three breeds of sheep. Genetic variations of these InDels were evaluated on the basis of their polymorphism information content (PIC). The FTO-6 and PLIN1 genes showed low levels of polymorphism (0 < PIC < 0.25), while the other four InDels were moderately polymorphic (0.25 < PIC < 0.50) in the three breeds of sheep. The results of the association analysis revealed that four InDels from the FTO and PLIN1 genes were significantly associated with the morphometric traits in the three sheep breeds, such as body weight, body height, chest width, chest depth, cannon circumference, head length, coccyx length, forehead width, and back height. Based on these findings, the FTO and PLIN1 genes can serve as genetic markers to select sheep with desirable morphometric traits. This study aimed to identify InDels from the FTO and PLIN1 genes and to analyze their association with morphometric traits in Hu sheep (HS), Dupor sheep (DS), and Small Tail Han sheep (STHS). The FTO and PLIN1 genes were genotyped using the insertion/deletion (InDel) method. A one-way ANOVA with SPSS 26.0 software (IBM Corp, Armonk, NY, USA) was used to assess the effect of the InDel FTO and PLIN1 genes on morphometric traits. The results revealed significant associations between certain InDels and the morphometric traits in different breeds of sheep. Specifically, FTO-2 was significantly associated with cannon circumference (CaC) in HS rams and body height (BoH) in HS ewes (p < 0.05). FTO-2 was also significantly associated with chest width (ChW), CaC, head length (HeL), and coccyx length (CoL) in the STHS breed (p < 0.05). FTO-3 showed significant associations with BoH in HS rams and BoH, back height (BaH), ChW, and chest depth (ChD) in HS ewes (p < 0.05). FTO-3 was also significantly associated with ChW in the DS and STHS breeds (p < 0.05). FTO-5 was significantly associated with body weight (BoW) in the DS breed and BoH in the STHS breed (p < 0.05). Furthermore, PLIN1 was significantly related to BoW in the DS breed and was significantly associated with CoL and forehead width (FoW) in the STHS breed (p < 0.05). In conclusion, the study suggested that InDels in the FTO and PLIN1 genes could provide practical information to improve morphometric traits in sheep breeding.
Spatiotemporal data fusion provides an efficacious strategy for addressing data gaps within time series datasets. This approach significantly enhances the feasibility of large-scale remote sensing ...applications by, for example, enabling the creation of seamless data cubes (SDCs). Nevertheless, strict data input requirements and the low computational efficiency of current methods severely limit the practicality of large-scale SDC production. In this study, we propose an efficient spatiotemporal data fusion method, the Fast Variation-based Spatiotemporal Data Fusion (FastVSDF) method. FastVSDF consists of three steps, i.e., unmixing, distributing global residuals, and distributing local residuals. In the unmixing process, FastVSDF introduces the fast abundant variation classification (FAVC) to mitigate sample imbalance and expedite the unsupervised classification. Then, the in-class Gaussian weight function is introduced to accelerate the distribution of local residuals by considering the classification to introduce the information on spectral similarity. Besides, FastVSDF employs the fast-guided filter to combat the "block artifacts" of global residuals efficiently. Results show that FastVSDF demonstrated superior performance over regression model fitting, spatial filtering and residual compensation (Fit-FC), spatial and temporal adaptive reflectance fusion (STARFM), reliable and adaptive spatiotemporal data fusion (RASDF), and flexible spatiotemporal data fusion (FSDAF). More importantly, FastVSDF yields a remarkable improvement in computational efficiency, reducing predicting time by 43-573 times. As a practical application, we generated the Sentinel-2 SDC for the Yangtze River Basin, China. The fusion process for a single period's Yangtze River Basin dataset was accomplished within 20 min, with an average of 3.85 s for each Sentinel-2 scene. Comprehensively considering the efficiency, accuracy, feasibility, and universality, FastVSDF demonstrates the practical potential for constructing large-scale and long-term SDC. Our code will be publicly available at https://github.com/ChenXuAxel/FastVSDF .
Personnel and boat detection in unmanned aerial vehicles (UAVs) imagery plays a crucial role in open water search and rescue missions. The diverse perspectives and altitudes of UAV images often ...result in significant variations in the imagery's appearance and dimensions of personnel and boats, and the false detections arising from water surface flares are acknowledged as a great challenge as well. The existing deep learning-based detection methods employ convolutional blocks with fixed kernel sizes to extract features from the imagery at a fixed spatial scale, which will lead to missed and false detections and severely affect detection accuracy when there are substantial differences in the appearance and size of the target objects. In this article, a spatial scale adaptive real-time object detection neural network, namely YoloOW, was proposed to tackle the challenge of personnel and boat detection amid the diverse UAV imagery, which comprises a feature extractor, a feature enhancer, and a postprocessor. The OaohRep convolutional block was proposed as a pivotal component in constructing the YoloOW and applied to the feature extractor and the feature enhancer. Compared with general convolution blocks, the OaohRep convolution block can extract image features across a wide range of spatial scales, show better scale adaptability, and achieve faster detection speed due to its unique merged convolution layer design. OaohRepBi-path aggregation network (PAN) was proposed in the feature enhancer, which imitated the architecture of the classic algorithm scale invariant feature transform (SIFT) and was successfully applied to deep learning models, showing better scale adaptability. A novel UAV detection box filter (UDBF) module was proposed in the postprocessor, which can effectively remove false detections caused by water surface flares. Experimental results demonstrate that our YoloOW model achieves 37.18% mean averaged precision (mAP) on the SeaDronesSee dataset, surpassing the baseline by 8.43%. This notable improvement positions our model at the first of the leaderboard. The code will be available at https://github.com/Xjh-UCAS/YoloOW .
Existing research indicates that detecting near-surface methane point sources using Sentinel-2 satellite imagery can offer crucial data support for mitigating climate change. However, current ...retrieval methods necessitate the identification of reference images unaffected by methane, which presents certain limitations. This study introduces the use of a matched filter, developing a novel methane detection algorithm for Sentinel-2 imagery. Compared to existing algorithms, this algorithm does not require selecting methane-free images from historical imagery in methane-sensitive bands, but estimates the background spectral information across the entire scene to extract methane gas signals. We tested the algorithm using simulated Sentinel-2 datasets. The results indicated that the newly proposed algorithm effectively reduced artifacts and noise. It was then validated in a known methane emission point source event and a controlled release experiment for its ability to quantify point source emission rates. The average estimated difference between the new algorithm and other algorithms was about 34%. Compared to the actual measured values in the controlled release experiment, the average estimated values ranged from −48% to 42% of the measurements. These estimates had a detection limit ranging from approximately 1.4 to 1.7 t/h and an average error percentage of 19%, with no instances of false positives reported. Finally, in a real case scenario, we demonstrated the algorithm’s ability to precisely locate the source position and identify, as well as quantify, methane point source emissions.
The Universal Thermal Climate Index (UTCI) is a crucial temperature index for describing human thermal comfort. With the continuous advancement of earth observation technologies, it has become ...feasible to monitor hourly global UTCI at kilometer-level resolution. However, the computational efficiency of UTCI calculations limits the production and application of UTCI, particularly time-series UTCI application at fine resolution. To address the abovementioned issue, this letter proposes a CUDA UTCI (CUTCI) method based on the graphics processing unit (GPU). CUTCI leverages the parallel computing capabilities of GPUs and kernel fusion techniques to improve parallelization and mitigate overhead during calculation. Experimental results demonstrated that, in comparison to operational UTCI and Thermofeel UTCI, CUTCI significantly improved computational efficiency by over 250 times and 17 times, respectively. Production of a single-period global UTCI at 0.1° resolution consumed less than 0.2 seconds. Experimental results revealed that CUTCI holds practical value in supporting real-time UTCI analysis and historical big data analysis over long time series.
•Two new hydrophilic-hydrophobic and acid-base balance silica were prepared.•Vinyl pyridine was copolymerized with undecylenic acid and oleic acid, respectively.•The stationary phase has mixed-mode ...performance with high column efficiency.•PAHs, phenols, aromatic acids, aromatic amines and oxazolidinones were separated.
Two new hydrophilic-hydrophobic and acid-base balanced liquid chromatographic stationary phases were obtained by using two long-chain monomers including undecylenic acid (UA) and oleic acid (OA) combined with short-chain 4-vinyl pyridine (Py) in-situ polymerized on silica microspheres surfaces, respectively. These two stationary phases can be used for reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) modes. Hydrophilic, hydrophobic, acidic and basic analytes can be separated on two new stationary phases in RPLC or HILIC mode. Compared with commercial hydrophobic C18 columns and other HILIC columns, two new stationary phases have excellent selectivity and separation performance in the separation of 9 polycyclic aromatic hydrocarbons, 10 aromatic acids, 10 anilines and 5 oxazolidinones, respectively. This novel polymer-functionalized silica design strategy has opened up new ideas for the future of mixed-mode stationary phases with multiple functions and specificity.
•Three new RPLC stationary phases were prepared by copolymerization on silica surface.•n-Vinylpyrrolidone (NVP), 1-Vinylimidazole (VIm) and 4-vinylpyridine (VPy) were co-grafted with 1-octadecene, ...respectively.•New stationary phases were evaluated in RPLC mode and two commercial C18 columns were compared.•VIm and VPy have smaller peak broadening than NVP at these separations.
Three reversed-phase liquid chromatography (RPLC) stationary phases were obtained by using long-chain 1-octadecene (OD) co-grafted with three short-chain monomers, including N-vinylpyrrolidone (NVP), 1-vinylimidazole (VIm) and 4-vinylpyridine (VPy), respectively (noted as Sil@ODNVP, Sil@ODVIm and Sil@ODVPy). Peak broadening phenomenon in RPLC mode which resulted by short-chain was examined carefully. Compared with Sil@ODNVP, both of Sil@ODVIm and Sil@ODVPy had smaller peak width and higher column efficiency in the separation of 10 polycyclic aromatic hydrocarbons (PAHs), 7 alkyl benzenes, 7 aromatic acids, 7 aromatic esters and 9 phenols. In addition, VPy has the strongest ion exchange capacity than other two short-chains. In this case, we can see that VPy and VIm maybe more suitable to be used as functional monomeric modifiers of new chromatographic stationary phases.
