Research on Automatic Recognition of Dairy Cow Daily Behaviors Based on Deep Learning.

Dairy cow behavior carries important health information. Timely and accurate detection of behaviors such as drinking, feeding, lying, and standing is meaningful for monitoring individual cows and herd management. In this study, a model called Res-DenseYOLO is proposed for accurately detecting the individual behavior of dairy cows living in cowsheds. Specifically, a dense module was integrated into the backbone network of YOLOv5 to strengthen feature extraction for actual cowshed environments. A CoordAtt attention mechanism and SioU loss function were added to enhance feature learning and training convergence. Multi-scale detection heads were designed to improve small target detection. The model was trained and tested on 5516 images collected from monitoring videos of a dairy cowshed. The experimental results showed that the performance of Res-DenseYOLO proposed in this paper is better than that of Fast-RCNN, SSD, YOLOv4, YOLOv7, and other detection models in terms of precision, recall, and mAP metrics. Specifically, Res-DenseYOLO achieved 94.7% precision, 91.2% recall, and 96.3% mAP, outperforming the baseline YOLOv5 model by 0.7%, 4.2%, and 3.7%, respectively. This research developed a useful solution for real-time and accurate detection of dairy cow behaviors with video monitoring only, providing valuable behavioral data for animal welfare and production management.

[Genome survey and characteristic analysis of SSR in Callicarpa nudiflora].

Callicarpa nudiflora,which is a big brand of Li nationality medicine with Hainan characteristics,has the effects of dissolving stasis,hemostasis,anti-inflammatory and antibacterial. At present,there is a lack of information about the reference genome of C. nudiflora. The study of the genome size,heterozygosity rate and characteristics of SSR of C. nudiflora,can provide an effective basis for the formulation of the whole genome de novo sequencing strategy and development of SSR molecular markers of C. nudiflora. To realize this purpose,high throughput sequencing platform Illumina Hiseq was used to sequence the genome structure of C. nudiflora and K-mer analysis was applied to estimate genome size,repeat sequences and heterozygosity rate. Simple-sequence repeat( SSR) loci that are suitable as markers were identified by MISA software. The results showed the estimated genome size of C. nudiflora was 822. 43 Mb,with a 0. 85% heterozygosity rate and 71. 67% repeats,and the GC content of genome was about 49. 20%. Therefore,C. nudiflora belongs to a complex genome with high heterozygosity and repetition. SSR molecular genetic markers were analyzed in the genome sequence,and a total of 206 049 SSRs were identified,among which mono-nucleotide,di-nucleotide and tri-nucleotide repetitive motifs summed up to 198 993,accounting for 96. 57% of the total SSRs. Among the 2-6 nucleotide repeats,AT/AT,AAT/ATT,AGCC/CTGG,AAAAT/ATTTT and AGATAT/ATATCT have the largest number,respectively. This report represents the first genome-wide characterization of C. nudiflora,and provides a reference for the construction of the library for the fine sequencing of the genome,and a molecular basis for the development of SSR molecular markers as well as for the protection and utilization of gene resources.

Rapid Analysis of Corni fructus Using Paper Spray-Mass Spectrometry.

INTRODUCTION: Paper spray-mass spectrometry (PS-MS) is a kind of ambient MS technique for the rapid analysis of samples. Corni fructus has been widely used in traditional Chinese compound preparations and healthy food. However, a number of counterfeits of Corni fructus, such as Crataegi fructus, Lycii fructus, and grape skin are illegally sold in crude herb markets. Therefore, the development of a rapid and high-throughput quality evaluation method is important for ensuring the effectiveness and safety of the crude materials of Corni fructus. OBJECTIVE: To develop PS-MS chemical profiles and a semi-quantitative method of Corni fructus for quality assessment and control, and species distinction of Corni fructus. METHODOLOGY: Both positive and negative ion PS-MS chemical profiles were constructed for species distinction. The statistical analysis of the chemical profiles was accomplished by principal component analysis (PCA). Rapid semi-quantitative analysis of loganin and morroniside in the extracts of Corni fructus were accomplished by PS-MS. RESULTS: The profiles of the Corni fructus and Crataegi fructus samples were clearly clustered into two categories. The limit of quantification (LOQ) in the semi-quantitative analysis was 6 µg/mL and 5.6 µg/mL for loganin and morroniside, respectively. CONCLUSION: PS-MS is a simple, rapid, and high-throughput method for the quality control and species distinction of Corni fructus. Copyright © 2017 John Wiley & Sons, Ltd.

Rapid analysis of Aurantii Fructus Immaturus (Zhishi) using paper spray ionization mass spectrometry.

Paper spray-mass spectrometry (PS-MS) is a rapid, solvent-efficient, and high-throughput analytical method for analyzing complex samples. In this study, a PS-MS method was developed to obtain MS profiles of Aurantii Fructus Immaturus (aka Zhishi in Chinese) in positive and negative ion modes. In combination with multivariate analyses, including principal component analysis and cluster analysis, the PS-MS profiles of 25 batches of Zhishi were discriminated in 25 batches of Citri Reticulatae Pericarpium Viride (aka Qingpi in Chinese; an adulterant of Zhishi). Moreover, a rapid quantitative analysis of synephrine, a prescriptive quality control component of Zhishi listed in the Chinese Pharmacopoeia, was conducted with PS-MS using synephrine-d2 as an internal standard (IS). The linearity range was 1.68-16.8µg/mL (R2=0.9985), the limit of quantitation was 0.5µg/mL. Relative standard deviations in the intra- and inter-day precision of the MS were 4.87 and 4.90%, respectively. Compared with HPLC results, there was no significant difference in the quantitation of synephrine. This study demonstrated that the PS-MS method is useful for the rapid discrimination and quality control of Zhishi samples.

Rapid analysis of Callicarpa L. using direct spray ionization mass spectrometry.

Direct spray such as leaf spray and paper spray ionization mass spectrometry (MS) is a powerful type of ambient MS for phytochemical analysis. In this paper, direct spray MS methods to rapidly distinguish and analyze five species of Callicarpa L. have been developed. To distinguish species, leaf spray MS was employed to directly analyze leaves. A small triangular leaf sample was wetted with 15 µL of spray solvent and a high DC voltage was then simply applied to the wet leaf sample, which was positioned in front of the inlet of a mass spectrometer to produce electrospray ionization. The MS signals of phenylpropanoid glycosides, i.e. forsythiaside B, poliumoside, verbascoside in leaves could be sensitively detected. The content characteristics of the phenylpropanoid glycosides in five species including Callicarpae kwangtungensis Folium, Callicarpae macrophyllae Folium, Callicarpa nudiflora Folium, Callicarpae formosanae Folium, Callicarpa longissima Folium could be used to distinguish them, then the mass spectra of the Callicarpa L. samples were analyzed using principal component analysis(PCA) or partial least squares-discriminant analysis(PLS-DA). For the rapid semi-quantitative analysis, of phenylpropanoid glycosides in leaves, paper spray MS was employed to determine phenylpropanoid glycosides in the extracts of Callicarpa L. leaves. Ginsenoside Rg1 was selected as an internal standard (I.S.). The calibration curves were constructed through ratios of target ion abundance to I.S. ion abundance vs. concentration of targets. The linearity range was 8-250 µg/mL (R(2)=0.9947) for forsythiaside B, 9-280 µg/mL (R(2)=0.9939) for verbascoside, and 9-260 µg/mL (R(2)=0.9917) for poliumoside, respectively. The limit of detection (LOD) was 1 µg/mL, 0.5 µg/mL and 1 µg/mL for forsythiaside B, verbascoside, and poliumoside, respectively.

[Application of near infrared spectroscopy combined with particle swarm optimization based least square support vactor machine to rapid quantitative analysis of Corni Fructus].

A novel method was developed for the rapid determination of multi-indicators in corni fructus by means of near infrared (NIR) spectroscopy. Particle swarm optimization (PSO) based least squares support vector machine was investigated to increase the levels of quality control. The calibration models of moisture, extractum, morroniside and loganin were established using the PSO-LS-SVM algorithm. The performance of PSO-LS-SVM models was compared with partial least squares regression (PLSR) and back propagation artificial neural network (BP-ANN). The calibration and validation results of PSO-LS-SVM were superior to both PLS and BP-ANN. For PSO-LS-SVM models, the correlation coefficients (r) of calibrations were all above 0.942. The optimal prediction results were also achieved by PSO-LS-SVM models with the RMSEP (root mean square error of prediction) and RSEP (relative standard errors of prediction) less than 1.176 and 15.5% respectively. The results suggest that PSO-LS-SVM algorithm has a good model performance and high prediction accuracy. NIR has a potential value for rapid determination of multi-indicators in Corni Fructus.

Arginine vasopressin induces rat caudate nucleus releasing acetylcholine to participate in pain modulation.

A lot of studies have pointed that acetylcholine (Ach), a classic neurotransmitter can regulate pain process in the caudate nucleus (CdN). Our previous report has proven that arginine vasopressin (AVP) effects on pain modulation in the CdN. The communication was designed to investigate the interaction between AVP and Ach in the rat CdN during the pain process. AVP concentration was determined by radioimmunoassay (RIA) and Ach concentration by high performance liquid chromatography (HPLC). The results showed that pain stimulation increased both AVP and Ach concentrations in the CdN perfusion liquid; AVP increased Ach concentration in the CdN perfusion liquid, while AVP receptor antagonist including d(CH(2))(5)Tyr(Me)AVP (V(1) receptor antagonist) and d(CH(2))(5)[D-Ile(2), Ile(4), Ala-NH(2)(9)]AVP (V(2) receptor antagonist) decreased Ach concentration in the CdN perfusion liquid. The data indicated that the analgesic effect of AVP might be involved in the Ach system in the CdN.