DataSheet_1_WeedNet-R: a sugar beet field weed detection algorithm based on enhanced RetinaNet and context semantic fusion.pdf

Accurate and dependable weed detection technology is a prerequisite for weed control robots to do autonomous weeding. Due to the complexity of the farmland environment and the resemblance between crops and weeds, detecting weeds in the field under natural settings is a difficult task. Existing deep learning-based weed detection approaches often suffer from issues such as monotonous detection scene, lack of picture samples and location information for detected items, low detection accuracy, etc. as compared to conventional weed detection methods. To address these issues, WeedNet-R, a vision-based network for weed identification and localization in sugar beet fields, is proposed. WeedNet-R adds numerous context modules to RetinaNet’s neck in order to combine context information from many feature maps and so expand the effective receptive fields of the entire network. During model training, meantime, a learning rate adjustment method combining an untuned exponential warmup schedule and cosine annealing technique is implemented. As a result, the suggested method for weed detection is more accurate without requiring a considerable increase in model parameters. The WeedNet-R was trained and assessed using the OD-SugarBeets dataset, which is enhanced by manually adding the bounding box labels based on the publicly available agricultural dataset, i.e. SugarBeet2016. Compared to the original RetinaNet, the mAP of the proposed WeedNet-R increased in the weed detection job in sugar beet fields by 4.65% to 92.30%. WeedNet-R’s average precision for weed and sugar beet is 85.70% and 98.89%, respectively. WeedNet-R outperforms other sophisticated object detection algorithms in terms of detection accuracy while matching other single-stage detectors in terms of detection speed.</p

Physiochemical characterizations of nanoemulsions.

<p>H/C: Six heating-cooling cycles. Cent.: centrifugation at 3,000 rpm for 30min. Freeze-Thaw: Three freeze-thaw cycles. All data were analyzed by Duncan’s multiple range test using SAS software package. The different letters indicate a statistically significant difference (p ≤ 0.01).</p><p>Physiochemical characterizations of nanoemulsions.</p

HLB-affected citrus treated by nano-formulations.

<p>(<b>A</b>): Amp (left) vs. tap water (CK) (right); (<b>B</b>): Nano-1-Amp+Brij 35 (left) vs. tap water (CK) (right); (<b>C</b>): Nano-2-Amp+Brij 35 (left) vs. tap water (CK) (right).</p

Additional file 2 of Genome-wide analysis of R2R3-MYB transcription factors family in the autopolyploid Saccharum spontaneum: an exploration of dominance expression and stress response

Additional file 2: Table S2. The classification of the SsR2R3-MYB family by phylogenetic tree. The 15 subgroups of the SsR2R3-MYB family by phylogenetic classification with rice

Deciphering the Bacterial Microbiome of Citrus Plants in Response to ‘<i>Candidatus</i> Liberibacter asiaticus’-Infection and Antibiotic Treatments

<div><p>The bacterial microbiomes of citrus plants were characterized in response to ‘<i>Candidatus</i> Liberibacter asiaticus’ (Las)-infection and treatments with ampicillin (Amp) and gentamicin (Gm) by Phylochip-based metagenomics. The results revealed that 7,407 of over 50,000 known Operational Taxonomic Units (OTUs) in 53 phyla were detected in citrus leaf midribs using the PhyloChip™ G3 array, of which five phyla were dominant, <i>Proteobacteria</i> (38.7%), <i>Firmicutes</i> (29.0%), <i>Actinobacteria</i> (16.1%), <i>Bacteroidetes</i> (6.2%) and <i>Cyanobacteria</i> (2.3%). The OTU62806, representing ‘<i>Candidatus</i> Liberibacter’, was present with a high titer in the plants graft-inoculated with Las-infected scions treated with Gm at 100 mg/L and in the water-treated control (CK₁). However, the Las bacterium was not detected in the plants graft-inoculated with Las-infected scions treated with Amp at 1.0 g/L or in plants graft-inoculated with Las-free scions (CK₂). The PhyloChip array demonstrated that more OTUs, at a higher abundance, were detected in the Gm-treated plants than in the other treatment and the controls. Pairwise comparisons indicated that 23 OTUs from the <i>Achromobacter</i> spp. and 12 OTUs from the <i>Methylobacterium</i> spp. were more abundant in CK₂ and CK₁, respectively. Ten abundant OTUs from the <i>Stenotrophomonas</i> spp. were detected only in the Amp-treatment. These results provide new insights into microbial communities that may be associated with the progression of citrus huanglongbing (HLB) and the potential effects of antibiotics on the disease and microbial ecology.</p></div

Additional file 8 of Genome-wide analysis of R2R3-MYB transcription factors family in the autopolyploid Saccharum spontaneum: an exploration of dominance expression and stress response

Additional file 8: Table S8. SsMYB and SbMYB sequences

Bacterial community of leaf midribs of scions.

<p><b>A</b>) Composition and <b>B</b>) relative abundance of the bacterial Operational Taxonomic Units (OTUs) present in leaf midribs of scions from grapefruit rootstocks grafted with HLB-affected lemon scions treated with ampicillin (Amp), gentamicin (Gm) and water (disease control; CK₁). The healthy plants were grafted using Las-free lemon scions (healthy control; CK₂).</p

Ct value detected by qPCR in HLB-affected citrus after foliar spraying by nano-formulations.

<p>Ct value detected by qPCR in HLB-affected citrus after foliar spraying by nano-formulations.</p

Additional file 3 of Genome-wide analysis of R2R3-MYB transcription factors family in the autopolyploid Saccharum spontaneum: an exploration of dominance expression and stress response

Additional file 3: Table S3. Members of identified MYB family in Sorghum

Additional file 13 of Genome-wide analysis of R2R3-MYB transcription factors family in the autopolyploid Saccharum spontaneum: an exploration of dominance expression and stress response

Additional file 13: Figure S4. Relative expression level quantified by RT-qPCR. High transcripts of MYB gene in prophase of stem formation (A) and whole stem development period (B)