Mapping and validation of a major QTL for primary root length of soybean seedlings grown in hydroponic conditions.

BACKGROUND: The root system provides nutrient absorption and is closely related to abiotic stress tolerance, but it is difficult to study the roots under field conditions. This study was conducted to identify quantitative trait loci (QTL) associated with primary root length (PRL) during soybean seedling growth in hydroponic conditions. A total of 103 F7 recombinant inbred lines (RILs) derived from a cross between K099 (short primary root) and Fendou 16 (long primary root) were used to identify QTL for PRL in soybean. The RIL population was genotyped with 223 simple sequence repeats markers covering 20 chromosomes. Phenotyping for primary root length was performed for 3-weeks plants grown in hydoponic conditions. The identified QTL was validated in near isogenic lines and in a separate RIL population. RESULTS: QTL analysis using inclusive composite interval mapping method identified a major QTL on Gm16 between SSR markers Sat_165 and Satt621, explaining 30.25 % of the total phenotypic variation. The identified QTL, qRL16.1, was further confirmed in a segregating population derived from a residual heterozygous line (RHLs-98). To validate qRL16.1 in a different genetic background, QTL analysis was performed in another F6 RIL population derived from a cross between Union (medium primary root) and Fendou 16, in which a major QTL was detected again in the same genomic region as qRL16.1, explaining 14 % of the total phenotypic variation for PRL. In addition, the effect of qRL16.1 was confirmed using two pair of near-isogenic lines (NILs). PRL was significantly higher in NILs possessing the qRL16.1 allele from Fendou 16 compared to allele from K099. CONCLUSIONS: The qRL16.1 is a novel QTL for primary root length in soybean which provides important information on the genetic control of root development. Identification of this major QTL will facilitate positional cloning and DNA marker-assisted selection for root traits in soybean.

Quantitative trait locus mapping under irrigated and drought treatments based on a novel genetic linkage map in mungbean (Vigna radiata L.).

KEY MESSAGE: A novel genetic linkage map was constructed using SSR markers and stable QTLs were identified for six drought tolerance related-traits using single-environment analysis under irrigation and drought treatments. Mungbean (Vigna radiata L.) is one of the most important leguminous food crops. However, mungbean production is seriously constrained by drought. Isolation of drought-responsive genetic elements and marker-assisted selection breeding will benefit from the detection of quantitative trait locus (QTLs) for traits related to drought tolerance. In this study, we developed a full-coverage genetic linkage map based on simple sequence repeat (SSR) markers using a recombinant inbred line (RIL) population derived from an intra-specific cross between two drought-resistant varieties. This novel map was anchored with 313 markers. The total map length was 1010.18 cM across 11 linkage groups, covering the entire genome of mungbean with a saturation of one marker every 3.23 cM. We subsequently detected 58 QTLs for plant height (PH), maximum leaf area (MLA), biomass (BM), relative water content, days to first flowering, and seed yield (Yield) and 5 for the drought tolerance index of 3 traits in irrigated and drought environments at 2 locations. Thirty-eight of these QTLs were consistently detected two or more times at similar linkage positions. Notably, qPH5A and qMLA2A were consistently identified in marker intervals from GMES5773 to MUS128 in LG05 and from Mchr11-34 to the HAAS_VR_1812 region in LG02 in four environments, contributing 6.40-20.06% and 6.97-7.94% of the observed phenotypic variation, respectively. None of these QTLs shared loci with previously identified drought-related loci from mungbean. The results of these analyses might facilitate the isolation of drought-related genes and help to clarify the mechanism of drought tolerance in mungbean.

A Novel Image Formation Model for Descattering.

In the field of image descattering, the image formation models employed for restoration approaches are often simplified. In these models, scattering distribution is uniform in homogeneous media when transmission is fixed. Through specifically designed experiments, we discover that scattering exhibits non-uniform characteristics even in homogeneous media. Neglecting non-uniform scattering in these models limits their accuracy in representing scattering distribution, resulting in existing image descattering approaches inadequate. To tackle these issues, this paper proposes a novel image formation model for image descattering, considering more physical parameters, such as zenith angle, azimuth angle, scattering phase function, and camera focal length. Our model describes the light transfer process in scattering media more accurately. For image descattering, we introduce corresponding algorithms for parameter estimation in our model and simultaneous restoration from degraded images. Experimental evaluations demonstrate the effectiveness of our proposed model in various tasks, including physical parameter estimation, pure-scattering removal, image dehazing, and underwater image restoration. In terms of calculating parameters, our results are close to the real values; in terms of underwater image restoration, our work outperforms the state-of-art methods; in terms of image dehazing, our work promotes the performance of existing methods by replacing previous models with our model.

QueryTrack: Joint-Modality Query Fusion Network for RGBT Tracking.

Existing RGB-Thermal trackers usually treat intra-modal feature extraction and inter-modal feature fusion as two separate processes, therefore the mutual promotion of extraction and fusion is neglected. Then, the complementary advantages of RGB-T fusion are not fully exploited, and the independent feature extraction is not adaptive to modal quality fluctuation during tracking. To address the limitations, we design a joint-modality query fusion network, in which the intra-modal feature extraction and the inter-modal fusion are coupled together and promote each other via joint-modality queries. The queries are initialized based on the multimodal features of the current frame, making the subsequent fusion adaptive to modal quality fluctuation during tracking. Then the joint-modality query fusion (JQF) utilizes the queries to interact with RGB-T features, allowing the intra-modal enhancement and the inter-modal interactions to be unified for mutual promotion. In this way, JQF can distinguish and enhance the complementary modality features, while filtering out redundant information. For real-time tracking, we propose regional cross-attention for cross-modal interactions to reduce computational cost. Our end-to-end tracker sets a new state-of-the-art performance on multiple RGBT tracking benchmarks including LasHeR, VTUAV, RGBT234 and GTOT, while running at a real-time speed.

Study on energy evolution and fractal characteristics of sandstone with different fracture dip angles under uniaxial compression.

In order to investigate the failure modes and instability mechanism of fractured rock. Uniaxial compression tests were conducted on sandstone specimens with different dip angles. Based on rock energy dissipation theory and fractal theory, the energy evolution characteristics and fragmentation fractal characteristics in the process of deformation and failure of specimens were analyzed. The results show that the peak strength and elastic modulus of fractured rock mass are lower than those of intact samples, and both show an exponential increase with the increase of fracture dip angle. The energy evolution laws of different fracture specimens are roughly similar and can be classified into four stages based on the stress-strain curve: pressure-tight, elastic, plastic, and post-destructive. The total strain energy, elastic strain energy, and dissipated strain energy of the specimen at the peak stress point increased exponentially with crack inclination, and the dissipated strain energy and compressive strength conformed to a power function growth relationship. The distribution of the fragments after the failure of the fracture sample has fractal characteristics, and the fractal dimension increases with the increase of the fracture dip angle. In addition, the higher the compressive strength of the specimen, the greater the energy dissipation, the more serious the degree of fragmentation, and the greater the fractal dimension. The data fitting further shows that there is a power function relationship between the dissipated strain energy and the fractal dimension. The research results can provide a theoretical basis for the stability of rock mass engineering and structural deformation control.

Performance of feeding black soldier fly (Hermetia illucens) larvae on shrimp carcasses: A green technology for aquaculture waste management and circular economy.

Over 944 thousand tonnes of shrimp carcasses are produced worldwide during the shrimp production cycle, and black soldier fly larvae (BSFL) are a potential solution for this shrimp carcass accumulation. In this study, we evaluated the performance of BSFL feeding on shrimp carcasses. Six combinations of wheat bran and shrimp carcass powder (with replacement increments of 20 %) and one whole shrimp carcasses treatment were tested. The bioconversion rate (27.15 ± 3.66 %; p = 0.001), crude protein (55.34 ± 1.27 %; p < 0.001), and crude lipid (14.37 ± 1.86 %; p = 0.007) values of BSFL reared on whole shrimp carcasses were significantly higher than those of BSFL reared on wheat bran. Increasing the shrimp carcass amount in the feeding media resulted in significant increases in BSFL docosahexaenoic acid (with the highest value occurring for BSFL reared on whole shrimp carcasses; 1.46 ± 0.09 %; p < 0.001). Conversely, BSFL docosahexaenoic acid was not detected for BSFL reared on wheat bran. The detected heavy metal concentrations in BSFL were below the limits of the published international guidelines for animal feed. In the obtained BSFL, Salmonella was not detected, and the mould count was <10 CFU/g. The total bacterial count (Lg transformation) of obtained BSFL ranged from 7.88 to 8.07 CFU/g, and no significant differences among all treatments (p = 0.424). Overall, this study demonstrates that BSFL-based bioconversion presents a resource recovery technology for converting shrimp carcasses into high-value nutritional biomass.

Study on strength characteristics and thickening characteristics of classified-fine cemented backfill in gold mine.

For some new mines, the utilization rate of tailings is not satisfactory when using unclassified tailings as backfill aggregate for cemented backfill. At the same time, with the progress of mineral processing technology, the tailings discharged by the concentrator gradually become finer. Therefore, cemented filling with fine-grained tailings as aggregate will become the development direction of filling technology in the future. In this paper, the feasibility of fine particle tailings backfill is studied by taking the particle tailings of-200 mesh as aggregate in Shaling gold mine. The calculation shows that the utilization rate of tailings is increased from 45.1% to 90.3% by using-200 mesh tailings as filling aggregate. The response surface central composite design method (RSM-CCD) was used to study the strength of backfill with alkali-activated cementitious material as binder by taking the mass concentration of backfill slurry and sand-binder ratio as input factors. The results show that the 28-day strength of the backfill with graded fine-grained tailings as filling aggregate can reach 5.41 MPa when the sand-binder ratio is 4, which can fully meet the needs of the mine for the strength of the backfill. The thickening test of-200 mesh fine particle tailings was carried out by static limit concentration test and dynamic thickening test. In the case of adding 35 g/t BASF 6920 non-ionic flocculant, the concentration of 64.74% tail mortar can reach 67.71% after 2 h of static thickening, and the concentration can reach 69.62% after 2 h of static thickening. The feeding speed of thickener should be controlled between 0.4 and 0.59 t/(m2 h). In this case, the underflow concentration of thickener is relatively high, which is 64.92-65.78%, and the solid content of overflow water is less than 164 ppm. The conventional full tailings thickening process was improved by using the design of high-efficiency deep cone thickener and vertical sand silo. The feasibility of fine-grained tailings as filling aggregate was demonstrated by combining the filling ratio test of fine-grained tailings, the data of thickening test and the improved thickening process. The research results can provide reference for other mines to use fine-grained tailings as filling aggregate to design filling system.

Dual Aligned Siamese Dense Regression Tracker.

Anchor or anchor-free based Siamese trackers have achieved the astonishing advancement. However, their parallel regression and classification branches lack the tracked target information link and interaction, and the corresponding independent optimization maybe lead to task-misalignment, such as the reliable classification prediction with imprecisely localization and vice versa. To address this problem, we develop a general Siamese dense regression tracker (SDRT) with both task and feature alignments. It consists of two cooperative and mutual-guidance core branches: dense local regression with RepPoint representation, the global and local multi-classifier fusion with aligned features. They complement and boost each other to constrain the results with well-localized followed to also be well-classified. Specifically, a dense local regression with RepPoint representation, directly estimates and averages multiple dense local bounding box offsets for accurate localization. And then, the refined bounding boxes can be used to learn the global and local affine alignment features for reliable multi-classifier fusion. The classified scores in turn guide the assigned positive bounding boxes for the regression task. The mutual guidance operations can bridge the connection between classification and regression substantially, since the assigned labels of one task depend on the prediction quality of the other task. The proposed tracking module is general, and it can boost both the anchor or anchor-free based Siamese trackers to some extent. The extensive tracking comparisons on six tracking benchmarks verify its favorable and competitive performance over states-of-the-arts tracking modules.

High-quality genome assembly and pan-genome studies facilitate genetic discovery in mung bean and its improvement.

Mung bean is an economically important legume crop species that is used as a food, consumed as a vegetable, and used as an ingredient and even as a medicine. To explore the genomic diversity of mung bean, we assembled a high-quality reference genome (Vrad_JL7) that was ∼479.35 Mb in size, with a contig N50 length of 10.34 Mb. A total of 40,125 protein-coding genes were annotated, representing ∼96.9% of the genetic region. We also sequenced 217 accessions, mainly landraces and cultivars from China, and identified 2,229,343 high-quality single-nucleotide polymorphisms (SNPs). Population structure revealed that the Chinese accessions diverged into two groups and were distinct from non-Chinese lines. Genetic diversity analysis based on genomic data from 750 accessions in 23 countries supported the hypothesis that mung bean was first domesticated in south Asia and introduced to east Asia probably through the Silk Road. We constructed the first pan-genome of mung bean germplasm and assembled 287.73 Mb of non-reference sequences. Among the genes, 83.1% were core genes and 16.9% were variable. Presence/absence variation (PAV) events of nine genes involved in the regulation of the photoperiodic flowering pathway were identified as being under selection during the adaptation process to promote early flowering in the spring. Genome-wide association studies (GWASs) revealed 2,912 SNPs and 259 gene PAV events associated with 33 agronomic traits, including a SNP in the coding region of the SWEET10 homolog (jg24043) involved in crude starch content and a PAV event in a large fragment containing 11 genes for color-related traits. This high-quality reference genome and pan-genome will provide insights into mung bean breeding.

Reliable Multi-kernel Subtask Graph Correlation Tracker.

Many astonishing correlation filter trackers pay limited concentration on the tracking reliability and locating accuracy. To solve the issues, we propose a reliable and accurate cross correlation particle filter tracker via graph regularized multi-kernel multi-subtask learning. Specifically, multiple non-linear kernels are assigned to multi-channel features with reliable feature selection. Each kernel space corresponds to one type of reliable and discriminative features. Then, we define the trace of each target subregion with one feature as a single view, and their multi-view cooperations and interdependencies are exploited to jointly learn multi-kernel subtask cross correlation particle filters, and make them complement and boost each other. The learned filters consist of two complementary parts: weighted combination of base kernels and reliable integration of base filters. The former is associated to feature reliability with importance map, and the weighted information reflects different tracking contribution to accurate location. The second part is to find the reliable target subtasks via the response map, to exclude the distractive subtasks or backgrounds. Besides, the proposed tracker constructs the Laplacian graph regularization via cross similarity of different subtasks, which not only exploits the intrinsic structure among subtasks, and preserves their spatial layout structure, but also maintains the temporal-spatial consistency of subtasks. Comprehensive experiments on five datasets demonstrate its remarkable and competitive performance against state-of-the-art methods.

Speedup 3-D Texture-Less Object Recognition Against Self-Occlusion for Intelligent Manufacturing.

Realtime 3-D object detection and 6-DOF pose estimation in clutter background is crucial for intelligent manufacturing, for example, robot feeding and assembly, where robustness and efficiency are the two most desirable goals. Especially for various metal parts with a textless surface, it is hard for most state of the arts to extract robust feature from the clutter background with various occlusions. To overcome this, in this paper, we propose an online 3-D object detection and pose estimation method to overcome self-occlusion for textureless objects. For feature representation, we only adopt the raw 3-D point clouds with normal cues to define our local reference frame and we automatically learn the compact 3-D feature from the simple local normal statistics via autoencoder. For a similarity search, a new basis buffer k-d tree method is designed without suffering branch divergence; therefore, ours can maximize the GPU parallel processing capabilities especially in practice. We then generate the hypothesis candidates via the hough voting, filter the false hypotheses, and refine the pose estimation via the iterative closest point strategy. For the experiments, we build a new 3-D dataset including industrial objects with heavy self-occlusions and conduct various comparisons with the state of the arts to justify the effectiveness and efficiency of our method.

A deep sequencing analysis of transcriptomes and the development of EST-SSR markers in mungbean (Vigna radiata).

Mungbean (Vigna radiata L. Wilczek) is one of the most important leguminous food crops in Asia. We employed Illumina paired-end sequencing to analyse transcriptomes of three different mungbean genotypes. A total of 38.3-39.8 million pairedend reads with 73 bp lengths were generated. The pooled reads from the three libraries were assembled into 56,471 transcripts. Following a cluster analysis, 43,293 unigenes were obtained with an average length of 739 bp and N50 length of 1176 bp. Of the unigenes, 34,903 (80.6%) had significant similarity to known proteins in the NCBI nonredundant protein database (Nr), while 21,450 (58.4%) had BLAST hits in the Swiss-Prot database (E-value<10⁻5). Further, 1245 differential expression genes were detected among three mungbean genotypes. In addition, we identified 3788 expressed sequence tag-simple sequence repeat (EST-SSR) motifs that could be used as potential molecular markers. Among 320 tested loci, 310 (96.5%) yielded amplification products, and 151 (47.0%) exhibited polymorphisms among six mungbean accessions. These transcriptome data and mungbean EST-SSRs could serve as a valuable resource for novel gene discovery and the marker-assisted selective breeding of this species.

Development of a high-density genetic linkage map and identification of flowering time QTLs in adzuki bean (Vigna angularis).

A high-density linkage map is crucial for the identification of quantitative trait loci (QTLs), positional cloning, and physical map assembly. Here, we report the development of a high-density linkage map based on specific length amplified fragment sequencing (SLAF-seq) for adzuki bean and the identification of flowering time-related QTLs. Through SLAF library construction and Illumina sequencing of a recombinant inbred line (RIL) population, a total of 4425 SLAF markers were developed and assigned to 11 linkage groups (LGs). After binning the SLAF markers that represented the same genotype, the final linkage map of 1628.15 cM contained 2032 markers, with an average marker density of 0.80 cM. Comparative analysis showed high collinearity with two adzuki bean physical maps and a high degree of synteny with the reference genome of common bean (Phaseolus vulgaris). Using this map, one major QTL on LG03 and two minor QTLs on LG05 associated with first flowering time (FLD) were consistently identified in tests over a two-year period. These results provide a foundation that will be useful for future genomic research, such as identifying QTLs for other important traits, positional cloning, and comparative mapping in legumes.