Abstract:Objective To estimate the genetic parameters of three economic traits in a long-term selection population, analyze their genetic progress, and investigate the factors including long-term selection affecting the genetic parameters in the practical breeding population.Method A total of 15 760 growth performance records of Duroc pigs were collected in a core breeding field from 2003 to 2018. Using DMUAI module and DMU4 module of DMU software, a multi-trait animal model was used to estimate the genetic parameters and breeding values of three important economic traits. We estimated the genetic parameters of annual accumulative population to evaluate the change of genetic parameters during the long-term selection.Result The estimates of heritability for three important economic traits including age, backfat thickness and loin muscle area at 100 kg body weight were 0.354, 0.477 and 0.479, respectively. All three traits had medium-high heritability. There were low correlations among three economic traits. The genetic and phenotypic correlations ranged from -0.110 to 0.039 and from -0.076 to 0.082, respectively. Among three traits, age at 100 kg body weight had relatively greater genetic progress in long-term selection, while backfat thickness at 100 kg body weight and loin muscle area at 100 kg body weight had relatively less genetic progress. Furthermore, the additive genetic variance changed in different degrees for three economic traits by estimating the genetic parameters of the annual accumulative population.Conclusion These traits of this Duroc pig population had the medium-high estimates of heritability and low correlations. Moreover, long-term selection and introduction could lead to the changing of genetic parameters. Therefore, genetic parameters should be estimated timely to obtain accurate genetic evaluation for accelerating the genetic improvement in breeding practice.

Abstract:Objective In mammalian cells, RAD51 and RAD18 are the key factors for regulating the relationship between non-homologous end joining and homology-directed repair. The purpose of this study was to explore the effects of these two factors on the knock-in (KI) efficiency in HEK293T cell lines by eSpCas9 system, and improve the KI efficiency.Method eSpCas9-RAD51, eSpCas9-RAD18 fusion proteins and RAD51, RAD18 overexpression vectors were constructed to compare their difference of KI efficiency.Result Only the eSpCas9-RAD18 system could significantly increase the KI efficiency of HEK293T cells, which was about 1.4~1.9 times that of the original eSpCas9 system (P<0.01). The eSpCas9-RAD51 system and overexpression of RAD51/RAD18 did not improve the KI efficiency.Conclusion The eSpCas9-RAD18 system constructed in this study can effectively improve the KI efficiency in HEK293T cells, and provides a novel auxiliary integration tool for gene editing, gene therapy and site-specific transgenesis.

Abstract:Objective To explore the function and molecular mechanism of circRIPK2 on the growth of chicken skeletal muscle.Method The convergent and divergent primers were designed according to the back-splicing site, and the circular structure of circRIPK2 was verified by Sanger sequencing. RT-PCR was used to explore the expression level of circRIPK2 at different developmental stages. The circRIPK2 overexpression vector was constructed. The effect of circRIPK2 on the proliferation and differentiation of chicken primary myoblasts were detected using EdU, flow cytometry and RT-PCR technology.Result The electrophoresis of PCR product and Sanger sequencing proved the existence of circRIPK2. RT-PCR result showed that comparing with control, overexpression of circRIPK2 up-regulated the mRNA expression of cell cycle-inhibiting gene p21 by 20%, down-regulated the mRNA expressions of cell cycle-promoting genes Cyclin B2, Cyclin D1, Cyclin D2 and PCNA by 39%, 22%, 29% and 45% respectively, and up-regulated the mRNA expressions of differentiation marker genes MyHC, MYOG and Myomaker by 39%, 56% and 25% respectively. The EdU assay and flow cytometry analysis also indicated that circRIPK2 inhibited cell proliferation.Conclusion CircRIPK2 may inhibit myoblast proliferation and promote myoblast differentiation, thus affecting the growth and development of chicken skeletal muscle.

Abstract:Objective To understand the immune status of chicken respiratory mucosa at different stages.Method The embryo of Hy-line white chickens (18- and 20-day-old), and the nose, larynx, trachea and lung of chickens at different day-age (1-, 4-, 7-, 14-, 21-, 35- and 56-day-old) were selected in this study. The occurrence, location, distribution and quantity change of IgA⁺ secreting cells were studied by immunohistochemical method.Result There was no IgA⁺ cell in the mucosa of each respiratory organ during the embryonic period. IgA⁺ cells were present in the nose and lung at 1-day-old age, laryngeal mucosa at 4-day-old age, and tracheal mucosa at 7-day-old age. The number of IgA⁺ cells in the respiratory mucosa of each organ increased gradually with the increase of age. The lymphoid aggregates were formed earlier in the nasal mucosa and the intersections of the primary and secondary bronchus in the lung at 4-day-old age, and formed in the laryngeal mucosa at 7-day-old age, in the tracheal mucosa at 35-day-old age. The IgA⁺ cells in these lymphoid aggregates were all mainly distributed on the periphery of the lymphoid aggregates. At 35-day-old age, there were more IgA⁺ cells in the mucosal lamina propria and the epithelium of the nose, larynx and trachea, and thus more effective and direct secretion of SIgA could be performed for mucosal immunity. At 56-day-old age, the number of IgA⁺ cells in the respiratory mucosa of the four organs reached a peak and germinal centers were formed at the mucosal bottom, which was the characteristic of mucosal associated lymphoid tissue, thus more effectively performed mucosal immune function.Conclusion The distribution and number of IgA⁺ cells in the respiratory mucosa of chickens show age-related changes, and the number and distribution of IgA⁺ cells in the nose, larynx, trachea and lung all reach a certain scale at 35-day-old, which can provide immune protection for the respiratory mucosa.

Abstract:Objective To establish a rapid detection method of African swine fever virus (ASFV) DNA based on enzymatic recombinase amplification (ERA) technology.Method Specific ERA probes and primers were designed according to the conserved sequences of B646L and EP402R genes, and MGF360/505 gene which was one of the ASFV multigene family members. Through optimizing reaction conditions, the ERA method for detecting ASFV DNA was finally established under the isothermal condition of 42 ℃.Result The detection results of three methods of ERA-ASFV-B646L, ERA-ASFV-EP402R and ERA-ASFV-MGF could be obtained within 16, 7 and 13 min respectively. The copy number detection limitation of positive sample was all 10² μL⁻¹. The coincidence rate was 100% compared with the common method in the technical standard of ASFV diagnosis in China.Conclusion The established ERA method can be used for rapid detection of ASFV, and provides an effective rapid detection method for epidemiological investigation and field detection.

Abstract:Objective The objective was to obtain water and nitrogen management mode for methane (CH₄) emission reduction, and reveal the effects of soil organic carbon fraction and methane oxidizing bacteria on CH₄ emission flux from rice fields treated by different irrigation methods and nitrogen application.Method Through field experiment, CH₄ emission fluxes, soil organic carbon fraction contents and methane oxidizing bacteria numbers at different growth stages of double-cropping rice were determined under three irrigation methods (conventional irrigation, “thin-shallow-wet-dry” irrigation and alternate drying and wetting irrigation) and three nitrogen application methods (N1: 120 kg·hm^-2 nitrogen, 20% basal fertilizer and 80% topdressing; N2: 120 kg·hm^-2 nitrogen, 50% basal fertilizer and 50% topdressing; N3: 90 kg·hm^-2 nitrogen, 50% basal fertilizer and 50% topdressing). The correlation relationships of CH₄ emission fluxes with soil organic carbon fractions and methane oxidizing bacteria were analyzed.Result The treatment of alternate drying and wetting irrigation combining with N3 had the lowest CH₄ emission flux from rice fields, and CH₄ emission flux at the tillering stage of late rice decreased by 70.5% compared with the treatment of conventional irrigation combining with N1. Under the alternate drying and wetting irrigation, the soil microbial biomass carbon content at the booting stage of early rice in N2 treatment increased by 23.5% compared with both N1 and N3 treatments, and the soil soluble organic carbon content at the tillering stage of late rice in N3 treatment increased by 12.0% and 12.9% compared with N1 and N2 treatments, respectively. Under the N3 treatment, conventional irrigation increased the soil readily oxidizable organic carbon content by 38.8% and 40.9% compared to “thin-shallow-wet-dry” irrigation and alternate drying and wetting irrigation at the booting stage of early rice, respectively. CH₄ emission flux from double-cropping rice fields was significantly positively correlated only with soil soluble organic carbon content (r=0.55, P<0.01).Conclusion Soil soluble organic carbon content significantly affects CH₄ emission fluxes from double-cropping rice fields, and alternate drying and wetting irrigation combining with N3 treatment had lower CH₄ emission flux from rice fields.

Abstract:Objective To mine the sequence information of the β-amylase gene family of Ipomoea batatas genome, and analyze the structure and function of genes.Method Based on the whole genome sequence data of I. batatas cultivar ‘Taizhong 6’, the bioinformatic methods were applied to analyze the identified 12 members of the β-amylase gene family and conduct the domain conservation analysis, chromosomal localization, screening of potential duplication genes, conservative motif analysis, phylogenetic tree construction. The gene expression under low temperature stress was analyzed using the transcriptomics data.Result Twelve β-amylase genes were located on chromosomes No. 2, 4, 5, 6, 11, 12, 13 and 14 of I. batatas, and eight pairs showed potential duplication relationship. Multiple sequence alignment and functional domain search indicated that there were three highly conserved domains and 10 conservative motifs in the amino acid sequences of I. batatas β-amylase family. Phylogenetic trees of β-amylase proteins in I. batatas and other species showed that 62 β-amylase family members were divided into seven subgroups of S1-S7. The β-amylases of I. batatas were mainly distributed in the subgroups of S2, S4, S5, S6 and S7, most of which belonged to the same branches with Arabidopsis thaliana, Solanum tuberosum and S. lycopersicum. The results of transcriptomics data showed that six β-amylase genes expressed differentially during the low temperature storage period, of which two were up-regulated and four were down-regulated in ‘Xushu 15-1’, while only two genes were down-regulated in ‘Xushu 15-4’.Conclusion The β-amylases are a key class of starch hydrolyzing enzymes that play important roles in the degradation of starch into reducing sugars during the process of I. batatas growth, development and tuber storage stages. The sequences of the identified 12 sweet potato β-amylase genes provide data reference for further study on the biological functions of I. batatas β-amylase gene family.

Abstract:Objective To obtain the full-length sequences of CsinCSPs genes of five chemosensory proteins (CSP) from Conopomorpha sinensis, and analyze the effect of diflubenzuron on CsinCSP gene expression.Method Total RNA was extracted from C. sinensis eggs. The full-length cDNA of five CsinCSP genes were cloned by transcriptome sequencing results and rapid amplification of cDNA ends(RACE). The putative amino acid sequences of CsinCSPs were analyzed by bioinformatics software. The three-dimensional (3D) structure of CsinCSPs were predicted using the Phyre² online software. The binding capacities of CsinCSPs to pesticides were studied by AutoDock software. The changes of CsinCSP gene expressions after treating the C. sinensis eggs with diflubenzuron were analyzed by qRT-PCR.Result Full-length sequences of five CsinCSP genes were cloned from C. sinensis eggs. Sequence analysis results indicated these five genes encode proteins with typical characteristics of insect chemosensory proteins. The putative cysteines pattern of five CsinCSPs was C1-X₆-C2-X₁₈-C3-X₂-C4. The five CsinCSPs could be classified to clades with five α-helix and six α-helix. Based on analysis of model template, the 3D structures of five CsinCSPs were found to consist of α-helix, β-strand and loop, and were most similar to the 3D structure of Mamestra brassicae CSP2. The molecular docking results revealed that the five CsinCSPs had the highest binding affinities with two pyrethroids, while the lowest binding affinity with diflubenzuron. The expressions of CsinCSP3 and CsinCSP5 were up-regulated by more than 40 times at 6 and 24 h after diflubenzuron treatment at sublethal dose to C. sinensis eggs, and decreased at 48 h after treatment.Conclusion The chemosensory protein CsinCSPs may be involved in the detoxification process after pesticide treatment in C. sinensis eggs.

Abstract:Objective The metabolite pretreatment technology was optimized based on GC-MS to establish a rapid, accurate sample preparation protocol for metabolomics analysis in Metarhizium.Method Several sample preparation steps, including cell quenching, metabolite extraction, derivatization and detection were optimized, and the stability of this method was also determined.Result The quenching effect of 40% cold ethanol was better than that of other quenching solutions, and the recoveries of nucleic acid and protein of Metarhizium were 9.63% and 11.61% respectively. Total 109 metabolites were obtained by cold methanol, more than those by other methods. The longer derivation time was, the more metabolites could be obtained, and 1.5 h was the best. Too high initial temperature of gas chromatography was not conducive to acquisition of metabolites, and 50 ℃ was the best. The optimal sample preparation conditions were as follows: After quenching with 40% cold ethanol, the supernatant was extracted with 2 mL cold methanol. After centrifugation, the supernatant was dried with N₂, and then added with 80 μL 20 mg/mL methoxylamine hydrochloride pyridine solution. After severe oscillation for 30 s, the supernatant was reacted at 37 ℃ for 90 min, and cooled to room temperature. Then 80 μL BSTFA derivatization agent with 1%(φ) TMCS was added, the derivatization reaction continued for 1.5 h at 70 ℃, and solution cooled to room temperature.Conclusion The method is simple, convenient and reproducible, it is conducive to carry out more in depth studies on metabolic mechanisms, and provides references for related studies on metabolic groups of pathogenic microorganisms in agriculture and forestry.

Abstract:Objective To compare and analyze the distribution characteristics of endophytic bacteria in wild and cultivated Dendrobium officinale, and screen active strains with strong colonization ability. To lay the foundation for improving the domestication of wild D. officinale and the quality of medicinal materials.Method The endophytic bacteria were isolated from the root, stem, leaf of D. officinale by tissue block separation method, and 16S rDNA sequence and phylogenetic tree were used to identify the isolated strains. The probioticactive bacterial strains with the abilities of phosphate-solubilizing, potassium-dissolving, nitrogen-fixing, siderophore-synthesizing, IAA-producting and antagonistic activity of pathogen were screened in vitro. The colonization dynamics of endophytic bacteria in tissue culture seedlings were observed after backgrafting and separation.Result A total of 285 endophytic bacteria strains were isolated from D. officinale, among which 217 were isolated from wild D. officinale, which were classified into three phylums and nine genera. Bacillus and Acinetobacter strains accounted for 79.26% and 8.76% of the total isolated strains respectively, and were the dominant bacteria. Only 68 endophytic bacteria strains were isolated from the cultivated D.officinale, which were classified into one phylum three genera, Burkholderia and Escherichia accounted for 54.41% and 30.88% of the total isolated strains respectively, and were the dominant bacteria. Only Pantoea was distributed in both wild and cultivated D. officinale. The number of endophytic species (9) and diversity index (0.85) of wild D. officinale were obviously higher than those of cultivated D. officinale (3 and 0.61 respectively). A total of 38 strains were obtained by active screening, accounting for 45% of the screened strains and three of four strains of endophytic bacteria from wild D. officinale showed good colonization in artificial tissue culture seedlings.Conclusion The biodiversity and community structure of endophytic bacteria of wild and artificially cultivated D. officinale are obviously different and the endophytic bacteria contains abundant potential of growth promotion.

Abstract:Objective To study the effects of UV-C treatment on chilling injury and flavor changes of pepino (Solanum muricatum) fruit during storage, and provide a new technique and theoretical basis for postharvest storage and chilling injury prevention of pepino fruit.Method Pepino fruits were stored at different temperatures (0, 5, 10, 15, 20 ℃) for 15 days, and the changes in chilling injury index, sensory quality, respiration intensity, and ethylene production during storage were measured to verify pepino fruits would have chilling injury when stored at 5 ℃ and below. Further pepino fruits were treated with UV-C at doses of 0.25, 0.50 and 1.00 kJ·m^-2 respectively, and stored at 5 ℃ for 15 days. The changes in chilling injury and flavor quality during storage were measured, combining with measurement of the changes of flavor substances using the electronic nose.Result Under 5 ℃ cold stress, the different doses of UV-C treatment effectively maintained the flavor quality, alleviated the symptoms of chilling injury and inhibited the respiration intensity and ethylene production at low temperature of pepino fruits. The ethylene production of 1.00 kJ·m^-2 UV-C treatment was 46% lower than that of the control group on the 15th day of storage, and the chilling injury index of 1.00, 0.50 and 0.25 kJ·m^-2 UV-C treatments were 30%, 70% and 67% respectively, which were significantly lower than that of the control group (81%). The 1.00 kJ·m^-2 UV-C treatment could significantly delay the onset of chilling injury for six days. Through linear discriminant analysis and radar analysis, it was found that the different doses of UV-C treatment kept the volatile aroma components of pepino fruits well.Conclusion Under cold stress, the different doses of UV-C treatment could significantly decrease the symptoms of chilling injury, maintain the flavor quality during storage to varying degrees, and delay the senescence of pepino fruits. Compared with other treatments, pepino fruits treated with 1.00 kJ·m^-2 UV-C have lower chilling injury index during storage and the treatment effect is the best.

Abstract:Objective In order to improve the automation and information levels of rice seedling transplanting manipulator, a set of monitoring system for rice seedling transplanting manipulator was designed.Method According to the working principle of rice seedling transplanting manipulator, the programmable logic controller (PLC) was used as the main control unit, and the hardware circuit and software program of the system were designed. The human-machine interaction monitoring interface of rice seedling transplanting manipulator was designed with a touch screen and the configuration software. The mobile APP for remotely monitoring system was designed with the GRM530 communication module, cloud server, Android mobile phone, and Android Studio software. When the monitoring system was working, the GRM530 communication module read the specified memory data in the PLC and uploaded the data to the cloud server through 4G network or WIFI. Then the Android mobile APP could directly access and download the data in the cloud server. Finally, the data was presented visually in the APP.Result The monitoring system was stable and reliable. The packet loss rates of remote communication for 10 repeated tests all were 0 and the average time delay was 25 ms, which showed that the Android mobile APP client and the rice seedling transplanting manipulator could realize stable and reliable two-way communication. The data transmission of the system was bidirectional. The human-machine interaction function was normal, and the touch screen and Android mobile APP could accurately feedback the working status and data. The user could send the control instructions to PLC through the Android mobile APP to realize the monitoring and controlling integration of the whole system. The response delay of remote control command was low, and the maximum response delay was no more than 0.63 s.Conclusion The monitoring system of rice seedling transplanting manipulator can remotely monitor the working status and data of the manipulator in real-time. It has a good human-machine interaction interface and has a certain guiding significance for promoting the deep integration of informatization and agricultural machinery.

Abstract:Objective To conduct structured storage of complex and heterogeneous data information in the field of rice diseases and pests using knowledge graphs, establish semantic relationships between diseases and pests, and provide a theoretical basis for rice diseases and pests association retrieval and intelligent diagnosis.Method Firstly, a method of constructing a knowledge graph for rice diseases and pests was proposed. At the same time, a series of graph-based retrieval algorithms for rice diseases and pests were proposed for information mining, through introducing solar terms entities to achieve early warning of rice diseases and pests. Secondly, a knowledge reasoning method based on the combination of certainty factor (CF) model and knowledge graph was proposed to realize the intelligent diagnosis of rice diseases and pests by combining CF with the symptom of diseased plant.Result The accuracy rates of named entity recognition model were 0.92, 0.90, and 0.87 in disease and pest name and hazard symptom entities. Further, a knowledge graph of rice disease and pest domain including 1 972 entities and 5 226 entity relationships was constructed. Through the self-developed intelligent diagnosis system, case analysis was conducted and the test showed that the correct rate of the diagnosis algorithm reached 86.25%.Conclusion This study effectively solves the complexity and uncertainty of knowledge in data retrieval, early warning and diagnosis in the field of rice diseases and pests, and has a strong practical value and extension prospects.

Abstract:Objective Brassica chinensis var. parachinensis was used as the experimental object to study the change rule of water stress during growth process based on canopy temperature, and the machine learning method was used for predicting the photosynthetic rate based on crop water stress index (CWSI) and photosynthetically active radiation.Method During the test, the experiment adopted different field capacities for B. chinensis var. parachinensis at the vegetative growth stage (V stage) and reproductive growth stage (R stage), collected the canopy temperature, air temperature and humidity data, established non-transpiration-baseline (upper limit equation), non-water-stress-baseline (lower limit equation), and calculated CWSI by empirical formulation. Cluster method of density-based spatial clustering of application with noise and air temperature were used to study the upper limit distribution of canopy temperature minus air temperature of B. chinensis var. parachinensis, and the fixed values were selected as the upper limit. Based on the CWSI empirical formulation, CWSI was calculated using the non-transpiration-baselines with different temperature fixed values to verify the clustering effect. In order to obtain the photosynthetic rate more easily, four machine learning methods of k-nearest neighbor (KNN), support vector regression (SVR), extreme gradient boosting (XGBoost) and random forest (RF) were used for prediction, and the prediction effects were compared.Result Under different field capacities, CWSI could better monitor the water stress status of B. chinensis var. parachinensis. Through cluster analysis, the upper limit of canopy temperature minus air temperature at V stage and R stage was classified into two clusters, and the cluster centers were 3.4 and 4.2 ℃, respectively, which were significantly correlated with the values calculated by the empirical formula of CWSI, indicating that it was feasible to use a fixed value as the upper limit of canopy temperature minus air temperature in B. chinensis var. parachinensis. The prediction models of KNN, SVM, XGBoost and RF all achieved good results, and the correlation coefficients were 0.873, 0.877, 0.887 and 0.863, respectively.Conclusion Machine learning can be used for predicting the photosynthetic rate of B. chinensis var. parachinensis, avoid the use of large and cumbersome instruments, reduce the damage to the leaves of B. chinensis var. parachinensis, and reduce the measurement time.

Abstract:Objective The study was aimed to improve the intelligent management level of citrus orchards, quickly and non-destructively evaluate the spraying quality on citrus canopy, and solve the overfitting problem of the spraying quality classification model caused by small-scale data set.Method We proposed a classification model of spraying quality on citrus canopy based on convolutional neural network: Visual geometry group citrus model (VGG_C model). The model was constructed based on the core idea of the VGG model. Through optimization of the cross-entropy loss function, the iterative process of probability distribution and true distribution was accelerated. The uncertainty measurement calculation was introduced at the output end and the Droupout method was inserted in the downsampling module to reduce the probability of overfitting due to small amount of data.Result The loss value of VGG_C model for the training set was 0.44%, which was 87% and 91% lower than that of ResNet and VGG respectively. The accuracy of VGG_C model for the training set was 95.3%, which was 5% and 10% higher than that of ResNet and VGG respectively. The average accuracy of the verification set was 96.4%.Conclusion VGG_ C model can effectively extract the features of citrus canopy thermal infrared image through multi-layer convolution model and improve the training and testing superiority of citrus canopy application classification model in small data set by optimizing the output structure. VGG_ C model can provide an effective reference for the intelligent judgment of pesticide application on citrus trees.