Large-scale Breeding Research Articles

Effect of Host Pupae Cryogenic, Anesthesia, Parasitoid-to-Host Ratios to Scleroderma sichuanensis the Percentage Parasitism and Numbers of Output.

Biological control is one of the effective means of controlling forestry burrowing pests in a low-cost and efficient way. Scleroderma sichuanensis, an ectoparasitic wasp, exhibits significant potential in managing burrowing pests. Currently, the mealworm Tenebrio molitor pupae are mainly used to many insects large-scale indoor breeding of diet. Therefore, this study focused on the effects of cryogenically treated the mealworm T. molitor pupae for different times and anesthesia treatment on the percentage parasitism and the number of emergence of S. sichuanensis, optimum parasitism and emergence were achieved in the wasp with a parasitoid-to-host ratio of 2:1, anesthesia treatment of T. molitor pupae with ethyl ether fumigation for 1.5 h, and cold treatment of them at a temperature of -10°C. As a result, various methods of treating T. molitor pupae indoors were explored, and optimal conditions for indoor rearing were explored for the expansion of S. sichuanensis.

Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning.

Liaoning Cashmere Goats are a high-quality dual-purpose breed valued for both their cashmere and meat. They are also a key national genetic resource for the protection of livestock and poultry in China, with their intensive farming model currently taking shape. Leveraging new productivity advantages and reducing labor costs are urgent issues for intensive breeding. Recognizing goatbehavior in large-scale intelligent breeding not only improves health monitoring and saves labor, but also improves welfare standards by providing management insights. Traditional methods of goat behavior detection are inefficient and prone to cause stress in goats. Therefore, the development of a convenient and rapid detection method is crucial for the efficiency and quality improvement of the industry. This study introduces a deep learning-based behavior recognition and online detection system for Liaoning Cashmere Goats. We compared the convergence speed and detection accuracy of the two-stage algorithm Faster R-CNN and the one-stage algorithm YOLO in behavior recognition tasks. YOLOv8n demonstrated superior performance, converging within 50 epochs with an average accuracy of 95.31%, making it a baseline for further improvements. We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. Our improved model achieved the highest detection accuracy of 98.11% compared to other state-of-the-art (SOTA) target detection algorithms. The Liaoning Cashmere Goat Online Behavior Detection System demonstrated real-time detection capabilities, with a relatively low error rate compared to manual video review, and can effectively replace manual labor for online behavior detection. This study introduces detection algorithms and develops the Liaoning Cashmere Goat Online Behavior Detection System, offering an effective solution for intelligent goat management.

Oropharyngeal swab sampling for PRRSV detection in large-scale pig farms: a convenient and reliable method for mass sampling

BackgroundPorcine reproductive and respiratory syndrome virus (PRRSV) has significant productivity and economic impacts in swine herds. Accurately determining the PRRSV status at the herd level is crucial for producers and veterinarians to implement strategies to control and eliminate the virus from infected herds. This study collected oropharyngeal swabs (OSs), nasal swabs (NSs), oral fluid swabs (OFs), rectal swabs (RSs), and serum samples continuously from PRRSV challenged pigs under experimental conditions and growing pigs under field conditions. Additionally, OSs and serum samples were collected from individual sows from 50 large-scale breeding farms, and the collection of OSs does not require the sows to be restrained. Ct values of PRRSV were detected in all samples using real-time reverse transcriptase-polymerase chain reaction (RT-qPCR).ResultsIn PRRSV challenged pigs, OSs showed a higher PRRSV-positive rate until the end of the observation period. The Ct values of OSs were significantly lower than those of NSs, OFs, and RSs at 2, 8, 12, 14 and 20 days post-challenge (DPC) (P < 0.05). For growing pigs, the positivity rate of PRRSV in OSs was higher than that in other sample types at 30, 70, and 110 days of age. In sows, 24,718 OSs and 6259 serum samples were collected, with PRRSV-positive rate in OSs (9.4%) being significantly higher than in serum (4.1%) (P < 0.05). However, the Ct values of PRRSV RNA in serum were significantly lower than those in OSs (P < 0.001).ConclusionsThe OSs sample type yielded higher PRRSV-positive rates for longer periods compared to NSs, RSs, OFs and serum samples for PRRSV detection in infected pigs. Therefore, OSs has a good potential to be a convenient, practical, and reliable sample type for implementing mass sampling and testing of PRRSV in large-scale pig farms.

Metabolite and Transcriptomic Changes Reveal the Cold Stratification Process in Sinopodophyllum hexandrum Seeds.

Sinopodophyllum hexandrum (Royle) Ying, an endangered perennial medicinal herb, exhibits morpho-physiological dormancy in its seeds, requiring cold stratification for germination. However, the precise molecular mechanisms underlying this transition from dormancy to germination remain unclear. This study integrates transcriptome and plant hormone-targeted metabolomics techniques to unravel these intricate molecular regulatory mechanisms during cold stratification in S. hexandrum seeds. Significant alterations in the physicochemical properties (starch, soluble sugars, soluble proteins) and enzyme activities (PK, SDH, G-6-PDH) within the seeds occur during stratification. To characterize and monitor the formation and transformation of plant hormones throughout this process, extracts from S. hexandrum seeds at five stratification stages of 0 days (S0), 30 days (S1), 60 days (S2), 90 days (S3), and 120 days (S4) were analyzed using UPLC-MS/MS, revealing a total of 37 differential metabolites belonging to seven major classes of plant hormones. To investigate the biosynthetic and conversion processes of plant hormones related to seed dormancy and germination, the transcriptome of S. hexandrum seeds was monitored via RNA-seq, revealing 65,372 differentially expressed genes associated with plant hormone synthesis and signaling. Notably, cytokinins (CKs) and gibberellins (GAs) exhibited synergistic effects, while abscisic acid (ABA) displayed antagonistic effects. Furthermore, key hub genes were identified through integrated network analysis. In this rigorous scientific study, we systematically elucidate the intricate dynamic molecular regulatory mechanisms that govern the transition from dormancy to germination in S. hexandrum seeds during stratification. By meticulously examining these mechanisms, we establish a solid foundation of knowledge that serves as a scientific basis for facilitating large-scale breeding programs and advancing the artificial cultivation of this highly valued medicinal plant.

The selection traits of mite non-reproduction (MNR) and Varroa sensitive hygiene (VSH) show high variance in subsequent generations and require intensive time investment to evaluate

The honey bee ectoparasite Varroa destructor is the main cause of honey bee colony losses worldwide. Over the last decades, several projects have focused on improving the robustness of Apis mellifera against this parasitic mite. Selection traits, such as mite non-reproduction (MNR) and Varroa sensitive hygiene (VSH), are favored selection factors in Varroa resistance projects. VSH is a trait where adult honey bees remove the Varroa-infested brood. During this process, the female mites are arrested in their reproductive cycle leading to a reduction of the Varroa population within the bee colony. From 2019 to 2022, 1402 queens were instrumentally inseminated with single or multiple drones in a breeding program. Colonies headed by these queens were established annually, and the MNR and VSH levels were analyzed. VSH was evaluated in response to cells artificially infested with Varroa, and colonies with high VSH values were used to generate our selected VSH stock. Despite crossing high VSH drones and queens, we measured a remarkable heterogeneity of MNR and VSH in the next generation(s), most likely due to the well-described, high recombination rate in the honey bee genome. When assessed multiple times in the same colony, great variance between measurements was observed. Detailed evaluations of daughter colonies are thus required if selection programs want to breed colonies with reliable VSH traits. This constant need to evaluate all offspring to ensure the desirable resistance traits are present results in high workloads and great expenses in selection programs. Furthermore, such large-scale breeding programs are inefficient due to high fluctuations between measurements and generations, indicating we need to develop new approaches and improved methods for assessing Varroa resistance.

Integrated microRNA study and pathological analysis provides new insights into the immune response of Ruditapes philippinarum under Vibrio anguillarum challenge

Manila clam (Ruditapes philippenarum) is an important shellfish aquaculture product. The large-scale breeding of clams is often affected by V. anguillarum and causes large-scale death. However, the pathogenesis, immune response and metabolic pathway of V. anguillarum are still unclear. In this study, we found that the bacterial load in the hepatopancreas of R. philippinarum peaked at 48 h after V. anguillarum infection, and then gradually decreased, while the activity of lysozyme reached the peak at 12 h. Tissue section observation reveals that the infected hepatopancreas cells lost normal structure or necrosis. Additionally, six small RNA libraries were constructed using hepatopancreas of clams. A total of 15 differentially expressed (DE) microRNA (miRNA) were identified at 48 h after V. anguillarum infection, including 8 upregulated and 7 downregulated miRNAs. GO and KEGG enrichment results indicated the prediction of 48 known miRNAs and 127 new miRNAs, with functional annotation suggests that endocytosis pathway and bacterial recognition proteins may play key roles in immune response. The sequencing results were basically consistent with the qRT-PCR validation, indicating the accuracy of the data. This study provides a new idea to explore the immune regulation mechanism of shellfish after V. anguillarum infection, which brings important reference significance for modern immunological research.

Research on an Identification and Grasping Device for Dead Yellow-Feather Broilers in Flat Houses Based on Deep Learning

The existence of dead broilers in flat broiler houses poses significant challenges to large-scale and welfare-oriented broiler breeding. To ensure the timely identification and removal of dead broilers, a mobile device based on visual technology for grasping them was meticulously designed in this study. Among the multiple recognition models explored, the YOLOv6 model was selected due to its exceptional performance, attaining an impressive 86.1% accuracy in identification. This model, when integrated with a specially designed robotic arm, forms a potent combination for effectively handling the task of grasping dead broilers. Extensive experiments were conducted to validate the efficacy of the device. The results reveal that the device achieved an average grasping rate of dead broilers of 81.3%. These findings indicate that the proposed device holds great potential for practical field deployment, offering a reliable solution for the prompt identification and grasping of dead broilers, thereby enhancing the overall management and welfare of broiler populations.

Visual Navigation of Caged Chicken Coop Inspection Robot Based on Road Features.

The speed and accuracy of navigation road extraction and driving stability affect the inspection accuracy of cage chicken coop inspection robots. In this paper, a new grayscale factor (4B-3R-2G) was proposed to achieve fast and accurate road extraction, and a navigation line fitting algorithm based on the road boundary features was proposed to improve the stability of the algorithm. The proposed grayscale factor achieved 92.918% segmentation accuracy, and the speed was six times faster than the deep learning model. The experimental results showed that at the speed of 0.348 m/s, the maximum deviation of the visual navigation was 4 cm, the average deviation was 1.561 cm, the maximum acceleration was 1.122 m/s2, and the average acceleration was 0.292 m/s2, with the detection number and accuracy increased by 21.125% and 1.228%, respectively. Compared with inertial navigation, visual navigation can significantly improve the navigation accuracy and stability of the inspection robot and lead to better inspection effects. The visual navigation system proposed in this paper has better driving stability, higher inspection efficiency, better inspection effect, and lower operating costs, which is of great significance to promote the automation process of large-scale cage chicken breeding and realize rapid and accurate monitoring.

Characteristic of epicotyl dormancy and its hormonal regulation in Chinese cork oak (Quercus variabilis)

Emergence heterogeneity caused by epicotyl dormancy contributes to variations in seedling quality during large-scale breeding. However, the mechanism of epicotyl dormancy release remains obscure. We first categorized the emergence stages of Chinese cork oak (Quercus variabilis) using the BBCH-scale. Subsequently, we identified the key stage of the epicotyl dormancy process. Our findings indicated that cold stratification significantly released epicotyl dormancy by increasing the levels of gibberellic acid 3 (GA3) and GA4. Genes associated with GA biosynthesis and signaling also exhibited altered expression patterns. Inhibition of GA biosynthesis by paclobutrazol (PAC) treatment severely inhibited emergence, with no effect on seed germination. Different concentrations (50 μM, 100 μM, and 200 μM) of GA3 and GA4+7 treatments of germinated seeds demonstrated that both can promote the emergence, with GA4 exhibiting a more pronounced effect. In conclusion, this study provides valuable insights into the characterization of epicotyl dormancy in Chinese cork oak and highlights the critical role of GA biosynthesis in seedling emergence. These findings serve as a basis for further investigations on epicotyl dormancy and advancing large-scale breeding techniques.

Development of DNA Insertion-specific Markers Based on the Intron Region of Oplegnathus punctatus itih4b for Genetic Sex Identification.

Spotted knifejaw (Oplegnathus punctatus) is a significant marine fish species that exhibits pronounced sexual dimorphism, with males generally exhibiting greater weight and growth rates than females. Therefore, the farming of O. punctatus with a high proportion of males is beneficial for improving the quality and efficiency of the O. punctatus aquaculture industry. Furthermore, the development of a rapid technique in sexing O. punctatus fry will facilitate the selection and breeding of superior male varieties of O. punctatus. In this study, genome-wide scanning, comparative genomics, and structural variation analysis methods were employed to identify and extract the homologous region of the inter-alpha-trypsin inhibitor heavy chain 4 (itih4b) gene on the X and Y chromosomes from the complete genome sequence of O. punctatus. This analysis revealed the presence of a large segment of DNA insertion markers on the Y chromosome in the region. Itih4b plays an important role in the mechanisms that regulate inflammatory and immune responses in multicellular organisms. The method described here involved the design of a pair of primers to amplify two bands of 532bp and 333bp in males (individuals with DNA insertion variants in the intron of the itih4b gene). In females (individuals without DNA insertion), only one band of 333bp could be distinguished by agarose gel electrophoresis. This method shortened the time required to accurately characterize intronic DNA insertion variants and genetic sexes in O. punctatus, thereby improving detection efficiency. This study has significant value for the large-scale breeding of O. punctatus all-male seedlings and provides a reference point for the study of intron variation regulation and RNA shearing in the itih4b gene.

Soluble expression and immunogenicity analysis of capsid proteins of porcine circoviruses types 2, 3, and 4

Porcine circoviruses (PCVs) contain four types: PCV1, PCV2, PCV3, and PCV4, all of which can infect pigs. Among them, PCV1 is non-pathogenic, and PCV2 can cause porcine circovirus diseases (PCVD) or porcine circovirus-associated diseases (PCVAD). Although the pathogenicity of PCV3 and PCV4 is still controversial, increasing evidence shows that PCV3 and PCV4 can cause PCV-related disease. However, mixed infection of PCV2, PCV3, and PCV4 with other pathogens often occurs in large-scale pig breeding, bringing severe economic losses to the global pig industry. In this study, the soluble recombinant proteins of PCV2, PCV3, and PCV4 Cap were expressed by the prokaryotic expression system and biotinylated to combine with the Streptavidin magnetic beads, followed by immunogenicity evaluation of the recombinant proteins. Furthermore, we also assessed the efficacy and immunogenicity of trivalent recombinant proteins conjugated with different adjuvants in mice. The results showed that the highly effective anti-PCV serum was successfully prepared, and the recombinant proteins conjugated with different adjuvants produced various degrees of humoral and cellular immunity in mice. Three recombinant proteins are effective immunogens, and the trivalent proteins coupled with the aluminum adjuvant or GM-CSF-CpG for two-dose immunization can stimulate prominent humoral and cellular immunity against PCVs in vivo. The soluble recombinant proteins are the most promising candidate for developing a trivalent vaccine against PCVs (PCV2, PCV3, and PCV4) infection simultaneously.

Activated Carbons for Removing Ammonia from Piggery Vent Air: A Promising Tool for Mitigating the Environmental Impact of Large-Scale Pig Breeding

Unsustainable pig breeding is a great threat to the environment. Ammonia is one of the main pollutants emitted in piggery vent air. This work is a comparative survey that presents the findings on the effectiveness of ammonia adsorption from air using various activated carbons (ACs). Detailed consideration is given to the effects of (i) type of raw material (wood char, wood pellet, and commercial lignite-based char), (ii) preparation method (CO2, steam, and KOH activation), and (iii) activation conditions (temperature and KOH/char ratio), on the porous structure of ACs and their ammonia sorption capacity and reversibility. Response surface methodology and genetic algorithm were used to find optimum KOH activation conditions. Economic analyses of AC production were performed using process modeling in Aspen software. It was found that ACs obtained from wood char in KOH activation show a maximum ammonia capacity of 397 g/kg, which is at least 2.5-fold higher than that reached on ACs from physical activation. A lower activation temperature (&lt;750 °C) and a higher KOH/char ratio (&gt;3) were preferred for effective adsorption, regardless of the type of feedstock. High sorption reversibility was achieved (87–96%). This makes the obtained sorbents promising sorbents for ammonia removal from piggery vent air with potential subsequent application as nitrogen-enriched biochar for crop fertilization. Thus, it facilitates sustainable pig breeding.

A method to rapidly construct 3D canopy scenes for maize and their spectral response evaluation

Three-dimensional (3D) scenes of a maize canopy can be utilized to depict its vertical structure and serve as the foundation for a 3D radiative transfer model. Given the inherent heterogeneity of canopy structures, evaluating their spectral response is crucial for remote-sensing inversion algorithms. Yet existing methods to model 3D canopy scenes of crops lack the high efficiency required for large-scale breeding applications. Hence, this study aims to develop a method to rapidly construct 3D canopy scenes of maize based on key structural parameters—namely, leaf area, base angle, and inclination angle—across multiple cultivars and growth stages. The accuracy of this canopy scenes modeling method was validated by comparison with a fine-scale 3D model and a multi-growth stage reflectance dataset. The root mean square error (RMSE) and normalized root mean square error (NRMSE) between the fine-scale 3D model and the constructed 3D model were less than 0.021 and 6.4%, respectively. Moreover, the RMSE and NRMSE between the simulated reflectance and measured reflectance were less than 0.042 and 11.1%, respectively. Next, we integrated the 3D radiative transfer model with 3D scenes to analyze the spectral response of maize canopy structure. The findings revealed that the near-infrared band was affected more by leaf area than leaf base angle, while the opposite is observed for the red-edge band. Furthermore, the middle layer contributed more to the canopy reflectance than either the upper or lower layers. Notably, two maize scenes where two structural parameters simultaneously change could elicit the same canopy spectra. The proposed method thus offers the dual advantages of rapid modeling and high efficiency, making it highly applicable for maize and other similar crops.

Effects of different dietary fats on biological characteristics of Coccinella septempunctata L

The study aims to provide a basis for the large-scale artificial breeding of Coccinella septempunctata, the composition of an artificial diet for the ladybird was optimised by adding different fats to the diet. The effects of different dietary fats on the biology of ladybirds were evaluated by supplementing artificial diets with fats. The results show that the coconut, palm, perilla, linseed, lard and sesame oils should not be added to the artificial diet of ladybird larvae because of deleterious effects on ladybirds. The addition of 6 g olive oil (3 % of diet weight) improved larvae survival rate, and the addition of 4 g beef tallow (2 % of diet weight) increased ladybird pupation and emergence rates. In adult stage, the addition of 4 g coconut oil (2 % of diet weight) improved survival rates. Whereas 2–4 g olive oil (1–2 % of diet weight), 2–6 g lard (1–3 % of diet weight) and 6 g beef tallow oil (3 % of diet weight) improved oviposition and hatchability. In conclusion, the demand for fats is different in the larval and adult stages of the C. septempunctata. The findings of this study provide a valuable reference for the addition of exogenous fats to the ladybird artificial diet.

Arsenic uptake and biotransformation mechanisms in Dunaliella salina: Insights into physiological and molecular responses

The biomass and premium extracts derived from D. salina possess diverse applications in industries like food, feed, health products, nutrition, pharmaceuticals, and cosmetics. However, D. salina's capacity to absorb and transform heavy metals, notably arsenic, can result in elevated arsenic concentrations in its products. This poses a challenge to large-scale D. salina breeding and introduces potential health risks. The impact of arsenic on D. salina product quality and the specific arsenic forms within its cells remain insufficiently understood. This study explores arsenic uptake and biotransformation mechanisms in D. salina exposed to arsenate (AsV) and arsenite (AsIII). Our findings highlight D. salina's preference for AsV, causing a significant rise in intracellular arsenic compared to AsIII exposure. Lower AsV concentrations facilitate arsenic methylation and organic transformation, influencing compound ratios. AsV triggers differential gene expression, upregulating metabolic pathways, arsenic transporters, and antioxidative defenses. Our results suggest that D. salina efficiently detoxifies arsenic by converting it into organoarsenicals, specifically arsenosugars and arsenicbetaine. This research offers valuable insights into microalgae's physiological and molecular responses to arsenic exposure, providing a foundation for understanding arsenic biotransformation mechanisms and potential applications in the large-scale breeding industry of D. salina.

Multi-Target Feeding-Behavior Recognition Method for Cows Based on Improved RefineMask.

Within the current process of large-scale dairy-cattle breeding, to address the problems of low recognition-accuracy and significant recognition-error associated with existing visual methods, we propose a method for recognizing the feeding behavior of dairy cows, one based on an improved RefineMask instance-segmentation model, and using high-quality detection and segmentation results to realize the recognition of the feeding behavior of dairy cows. Firstly, the input features are better extracted by incorporating the convolutional block attention module into the residual module of the feature extraction network. Secondly, an efficient channel attention module is incorporated into the neck design to achieve efficient integration of feature extraction while avoiding the surge of parameter volume computation. Subsequently, the GIoU loss function is used to increase the area of the prediction frame to optimize the convergence speed of the loss function, thus improving the regression accuracy. Finally, the logic of using mask information to recognize foraging behavior was designed, and the accurate recognition of foraging behavior was achieved according to the segmentation results of the model. We constructed, trained, and tested a cow dataset consisting of 1000 images from 50 different individual cows at peak feeding times. The method's effectiveness, robustness, and accuracy were verified by comparing it with example segmentation algorithms such as MSRCNN, Point_Rend, Cascade_Mask, and ConvNet_V2. The experimental results show that the accuracy of the improved RefineMask algorithm in recognizing the bounding box and accurately determining the segmentation mask is 98.3%, which is higher than that of the benchmark model by 0.7 percentage points; for this, the model parameter count size was 49.96 M, which meets the practical needs of local deployment. In addition, the technologies under study performed well in a variety of scenarios and adapted to various light environments; this research can provide technical support for the analysis of the relationship between cow feeding behavior and feed intake during peak feeding periods.

A delayed and unsynchronized ovary development as revealed by transcriptome of brain and pituitary of Coilia nasus.

Coilia nasus is an anadromous fish that has been successfully domesticated in the last decade due to its high economic value. The fish exhibits a delayed ovary development during the reproductive season, despite breeding and selection for five to six offspring. The molecular mechanism of the delayed ovary development is still unknown, so the obstacles have not been removed in the large-scale breeding program. This study aims to investigate the key genes regulating ovarian development by comparing the transcriptomes of ovarian-stage IV and stage II brain/pituitary of Coilia nasus. Ovarian stages were validated by histological sections. A total of 75,097,641 and 66,735,592 high-quality reads were obtained from brain and pituitary transcriptomes, respectively, and alternatively spliced transcripts associated with gonadal development were detected. Compared to ovarian Ⅱ- brain, 515 differentially expressed genes (DEGs) were upregulated and 535 DEGs were downregulated in ovarian Ⅳ- brain, whereas 470 DEGs were upregulated and 483 DEGs were downregulated in ovarian Ⅳ- pituitary compared to ovarian Ⅱ- pituitary. DEGs involved in hormone synthesis and secretion and in the GnRH signaling pathway were screened. Weighted gene co-expression network analysis identified gene co-expression modules that were positively correlated with ovarian phenotypic traits. The hub genes Smad4 and TRPC4 in the modules were co-expressed with DEGs including Kiss1 receptor and JUNB, suggesting that ovarian development is controlled by a hypothalamic-pituitary-gonadal axis. Our results have provided new insights that advance our understanding of the molecular mechanism of C. nasus reproductive functions and will be useful for future breeding.

Alternating Low and High Temperatures Increases the Hatching Rate of Eupolyphaga sinensis (Blattaria: Polyphagidae) Eggs

The hatching rates and developmental durations of Eupolyphaga sinensis Walker eggs were studied under variable combinations of low temperatures (5 °C and 10 °C) and high temperatures (25 °C and 30 °C). Our findings were intended to provide new evidence on the effect of temperature on the hatching of insect eggs. The results showed that both low temperatures and high temperatures significantly affected the hatching rate and time of E. sinensis eggs. Further analysis revealed a significant interactive effect between low temperatures and high temperatures. The 5 °C + 30 °C treatment achieved the highest egg hatching rate (77.33%) and the shortest hatching time (44.11 ± 1.55 d), which was significant compared with three other temperature treatments. The effects of high temperatures treatments on the hatching rate and the hatching time were more significant than that in the low temperature treatments. Hatching began earlier at 5 °C + 30 °C and 10 °C+30 °C temperatures, and single-day hatching first increased rapidly before declining afterwards within a short period. Comparatively, the hatching of eggs under the (5 °C+25 °C) and (10 °C+25 °C) temperatures was initially significantly delayed, including the peak single-day hatching rate. Under these treatments, the hatching rate tended to be gradual in terms of the temporal dynamics without showing any prominent peak. These results showed that low and high temperatures significantly affect the hatching rates of E. sinensis eggs. This study provided basis for the large-scale breeding of E. sinensis.

SCS-YOLOv5s: A cattle detection and counting method for complex breeding environment

Cattle detection and counting is one of the most important topics in the development of modern agriculture and animal husbandry. The traditional manual monitoring methods are inefficient and constrained by factors such as site. To solve the above problems, a SCS-YOLOv5 cattle detection and counting model for complex breeding scenarios is proposed. The original SPPF module is replaced in the YOLOv5 backbone network with a CSP structured SPPFCSPC. A CA (Coordinate Attention) mechanism is added to the neck network, as well as the SC (Standard Convolution) of the Neck network is replaced with a light convolution GSConv and Slim Neck is introduced, and training strategies such as multi-scale training are also employed. The experimental results show that the proposed method enhances the feature extraction ability and feature fusion ability, balances the localization accuracy and detection speed, and improves the use effect in real farming scenarios. The Precision of the improved network model is improved from 93.2% to 95.5%, mAP@0.5 is improved from 94.5% to 95.2%, the RMSE is reduced by about 0.03, and the FPS reaches 88. Compared with other mainstream algorithms, the comprehensive performance of SCS-YOLOv5 s is in a leading position, with fewer missed and false detections, and the strong robustness and generalization ability of this model are proved on multi-category public datasets. Applying the improvement ideas in this paper to YOLOv8 s also yields an increase in accuracy. The improved method in this study can greatly improve the accuracy of cattle detection and counting in complex environments, and has good real-time performance, so as to provide technical support for large-scale cattle breeding.

Comparison of the effects of chlorogenic acid isomers and their compounds on alleviating oxidative stress injury in broilers

The development of large-scale and intensive breeding models has led to increasingly prominent oxidative stress issues in animal husbandry production. Chlorogenic acid (CGA) is an important extract with a variety of biological activities. It is an effective antioxidant drug and shows different antioxidant capacities due to its different chemical structures. Therefore, it is a new research target to determine the proportion of chlorogenic acid isomers with high antioxidant activity to resist the damage caused by oxidative stress. In this experiment, the antioxidant activities of the chlorogenic acid monomer and its compounds were compared by a series of in vitro antioxidant indexes. Based on the above experiments, it was found that LB and LC have superior antioxidant abilities (P < 0.05). Subsequently, 300 healthy 1-day-old Arbor Acres (AA) male broilers with no significant difference in body weight (about 44g) were randomly selected and randomly divided into five groups with 6 replicates in each group and 10 chickens in each replicate. One group was the control group, one group was the model group, and the remaining three groups were the experimental groups. At 37 days of age, animals in the control group were injected with normal saline, and animals in the other four groups were injected with 1 ml/kg 5% hydrogen peroxide (H2O2) through the chest muscle before the supplementation. The control group (control) and the model group (PC) were fed a standard diet. The remaining three groups included the chlorogenic acid (CGA) group, LB group (CIB) and LC group (CIC). In these groups, 50 g/t chlorogenic acid, LB compound or LC compound were added to the basal diet, respectively, and the other feeding conditions remained consistent. The addition of the LB complex to the diet could significantly improve the growth performance and antioxidant performance of broilers (P < 0.05), upregulate the expression of Nuclear factor erythroid 2-related factor 2 (Nrf2) pathway related genes in liver and jejunum (P < 0.05), regulate the disordered intestinal flora, and alleviate the damage caused by oxidative stress. These results suggested for the first time that the LB complex exhibited superior effects in vitro and vivo.