Abstract:Objective To explore the phototransformation of a synthetic progestin, dydrogesterone (DYD), under simulated sunlight, and identify its potential transformation pathways. Method Photoreactor was used to test the phototransformation process of DYD under simulated sunlight. Experiments were also conducted to explore different pH (5, 7, and 9), temperature (15, 25, and 35 ℃), and natural organic matter (NOM) concentration (0, 5, and 20 mg·L^-1) on DYD phototransformation rate. Ultra-high performance liquid chromatography-time of flight mass spectrometer (UHPLC-QTOF-MS) was used to identify the potential photoproducts of DYD, and the potential transformation pathways were speculated. Result The concentration of DYD decreased over time under simulated sunlight, indicating that phototransformation occurred in the system. DYD transformation rate was not obviously affected by the initial solution pH, and the first-order phototransformation kinetic rate constant (k) was 0.015−0.019 h^-1. DYD transformation rate was facilitated by high temperature and low concentration of NOM (k increased from 0.019 h^-1 to 0.027 and 0.028 h^-1, respectively), but was inhibited by high concentration of NOM. UHPLC-QTOF-MS analysis showed that 19 photoproducts were generated during transformation, via hydroxylation, hydrogenation, polycondensation, and photoisomerization with subsequent ring-opening reactions. Conclusion Phototransformation will occur for DYD in surface water, and temperature and NOM play important roles in DYD phototransformation. A total of 19 photoproducts detected in this study remain the basic molecular skeleton of DYD, indicating that these products would exhibit potential endocrine disruption to aquatic systems.

Abstract:Objective To explore the effects of different addition amounts of litter biochar on growth, heavy metal absorption and accumulation of Ruellia simplex planted in the sludge + soil mixed matrix, and provide a reference for the resource utilization of municipal sludge and garden waste.Method A pot experiment was conducted to analyze the effects of adding 0 (CK), 1.5% (F_1.5), 3.0% (F_3.0) and 4.5% (F_4.5) of litter biochar on growth, root morphology, physiology, nutrient and heavy metal uptake and accumulation of Ruellia simplex.Result Compared with CK, F_1.5 significantly increased plant height, root biomass, shoot biomass and whole plant biomass. The plant biomass decreased gradually with the increase of biochar addition. The biomass of F_4.5 was significantly lower than that of CK, showing the characteristic of “low promotion and high inhibition”. Total root length, root surface area, average diameter and root volume of Ruellia simplex reached the maximum in F_1.5 treatment, and all of them gradually decreased with the increase of biochar addition. Among all treatments, the contents of soluble protein and malondialdehyde (MDA) in roots of F_1.5 were the lowest, and the activity of superoxide dismutase (SOD) was the highest. The SOD activity of roots showed a downward trend with the increase of biochar addition, while the change trends of soluble protein and MDA contents were opposite. Compared with CK, all treatments increased the uptakes of N, P and K of R. simplex shoots and roots to different degrees, reduced the contents of Cd and Cu in R. simplex plant to different degrees, and increased the contents of Pb and Ni. The accumulative amounts of N, P, K, Cd, Cu, and Pb in R. simplex plant showed a downward trend with the increase of biochar addition, and the accumulative amounts of N, P, K, Cd, Cu, Pb and Ni of F_1.5 were significantly higher than those of CK.Conclusion The addition of 1.5% litter biochar significantly promoted R. simplex growth, absorption and accumulation of Pb, Cu, Cd and Ni, but excessive addition would inhibit plant growth and affect the repair effect of substrate. Therefore, the applied amount of biochar should be controlled reasonably in the practical application process.

Abstract:Objective This study aimed to analyze the effect of sewage sludge (SS) surface and mixed application on Schefflera arboricola root growth and heavy metals uptake, to deeply understand the effect of SS application on landscape plant root growth, and to provide a reference for the safe use of SS in the landscape.Method We conducted a root box experiment without SS (no SS) and with the surface application (surface SS) or the mixed application (mixed SS) of 10% SS, to analyze the dynamic changes of S. arboricola root morphology, soil pH, and conductivity in different soil layers. Root tissue density, root density, and heavy metal contents of plant were also analyzed. The relationships between soil pH, soil conductivity, root heavy metal contents, and root length were further established by the linear regression analysis. Result Compared with no SS, mixed SS treatment obviously inhibited the increment of root length, root surface area, and root density. Surface SS treatment significantly increased total root length, root volume, and root density in the 0-20 cm soil layer. After 240 days of treatment, total root length in 0-20 cm and 20-40 cm layers in mixed SS treatment were 66.37% and 51.51% of no SS, respectively. Those for surface SS treatment were 115.43% and 98.66% of no SS, respectively. The maximum root total length, root volume, and root density occurred in the 0-20 cm soil layer in surface SS treatment, while the maximum root dry weight and tissue density occurred in the SS layer in surface SS treatment. Mixed SS treatment significantly increased soil pH, soil conductivity, and heavy metal contents of S. arboricola. The contents of Cd, Zn, Cu, and Ni in roots of different soil layers in mixed SS treatment were 2.32 to 11.70 times higher than those in no SS treatment. The linear regression analysis showed that the in-situ scanning total root length of S. arboricola in 0-20 cm soil layers was significantly positively correlated with in-situ measured soil pH in no SS and surface SS treatment (P<0.001). Total root length of S. arboricola was significantly negatively correlated with the contents of Cd, Zn, Cu, and Ni in roots (P<0.001). Conclusion Surface application of 10% SS increases soil pH and promotes S. arboricola root growth. Mixed application of 10% SS significantly increases root heavy metal uptake in different soil layers and inhibits root growth of S. arboricola.

Abstract:Objective Dehong Prefecture in Yunnan Province is the only Camellia oleifera growing area in the northern tropical margin of China. We conducted the study on soil and leaf nutrient content and ecological stoichiometric characteristics of C. oleifera in this area to provide a theoretical basis for scientific fertilization and accurate management of C. oleifera. Method We determined and analyzed the contents of carbon, nitrogen, phosphorus and potassium in soil and leaves of C. oleifera by ecological stoichiometry. Result The contents of organic carbon, total nitrogen, total phosphorus and total potassium in C. oleifera forest soil were 47.77, 2.56, 0.69 and 5.28 g·kg^-1 respectively, while the contents of available phosphorus and available potassium were 3.69 and 26.05 mg·kg^-1 respectively. The changes of organic carbon, total nitrogen and total phosphorus in soil were synergistic; The contents of available potassium and available phosphorus in soil directly depended on the contents of total potassium and total phosphorus. The cotents of carbon, nitrogen, phosphorus and potassium in C. oleifera leaves were 422.09, 13.51, 0.97 and 4.92 g·kg^-1 respectively. Nitrogen and phosphorus changed synergistically, and were both regulated by soil phosphorus. The growth and development of C. oleifera was limited by nitrogen and phosphorus, of which phosphorus was the main limiting element. The P and P∶K in leaves showed homeostasis, H_p was 5.08 and H_P:K was 3.26, while the other elements and stoichiometric ratios did not show homeostasis. Conclusion In order to ensure the health and sustainable production of C. oleifera forest, the input of phosphorus should be continuously strengthened, and the input of nitrogen and potassium should be balanced.

Abstract:Objective The alien invasive plant Alternanthera philoxeroides is often sympatric with native congener A. sessilis, but occupies an ecological advantage over A. sessilis in China. This study aimed to explore the relationship between clonal integration and the strong competitiveness of A. philoxeroides.Method In a common garden experiment, the stolon connection between the apical and the basal ramets of A. philoxeroides and A. sessilis were left intact (clonal integration) or disconnected (without clonal integration), and the growth, photosynthesis, and biomass distribution of the apical ramets, the basal ramets, and the whole fragments of the two plants under different clonal integration treatments were examined to compare the clonal integration abilities of the two plants.Result The stem length of the apical ramets, the number of leaves of the basal ramets as well as the leaf number and the stem length of the whole fragment of A. philoxeroides all significantly increased under clonal integration treatment. Moreover, the number of fine roots, total roots, and some photosynthetic indicators (such as light compensation point, stomatal conductivity, etc.) of A. philoxeroides all significantly increased under clonal integration treatment. Similarly, the aboveground/belowground biomass, the total biomass, the number of coarse/fine roots, and total number of roots of the apical ramets, the basal ramets, and the whole fragment of A. sessilis also significantly increased under clonal integration treatment. However, the aboveground/belowground biomass, the total biomass, and some photosynthetic indicators (such as net photosynthetic rate, transpiration rate, and stomatal conductance) of the apical ramets, the basal ramets, and the whole fragment of A. philoxeroides were significantly higher than those of A. sessilis under clonal integration treatment.Conclusion Both A. philoxeroides and A. sessilis can partly benefit from clonal integration, and A. philoxeroides has a stronger clonal integration ability than A. sessilis. A. philoxeroides might occupy the spatial niche through clonal integration, thus forming competitive advantage in natural habitats.

Abstract:Objective The aim of this study was to investigate the effects of several commercial herbicides and the botanical herbicidal compound berberine and its analogues on the redox potential of Arabidopsis thaliana root tip cells.Method A. thaliana transgenic plants marked with mitochondria targeted redox-sensitive green fluorescent protein were used as plant materials. The changes of cell redox potential in root cap, proximal meristem, transition zone and elongation zone were measured after being treated with different mass concentrations of herbicides for different time.Result The redox potential of the proximal meristematic zone of A. thaliana root cells treated with commercial herbicides was the lowest. From the meristematic zone to the elongation zone, the redox potential gradually increased, showing a trend of being gradually oxidized. Among the tested commercial herbicides, the change rule of redox potential of photosystem II inhibitors (atrazine and hexazinone) was the most obvious, indicating that mt-roGFP1 fluorescent probe could respond better to photosystem II inhibitors. The effect of glyphosate, an amino acid biosynthesis inhibitor, on the redox potential of A. thaliana root tip cells showed an obvious dose-response manner. With the increase of mass concentration, the change of the redox potential also gradually increased, showing a positive correlation with R²=0.9956. After the treatment of berberine and its analogues, the redox potential of A. thaliana root tip cells in most treatment groups reached the maximum reduction value in the proximal meristematic zone, and was gradually oxidized from the meristematic zone.Conclusion These results provide a basis for applying roGFP fluorescence probe technology to studying the mechanism of herbicidal compounds acting on root cell mitochondria.

Abstract:Objective In recent years, outbreak of an epidemic disease with significant ulcers on the pond-farmed largemouth bass (Micropterus salmoides) happen in winter and spring. This study aims to identify the underlying etiology. Method To clarify its etiology, disease fish samples from Dongpo and Hongya District, Meishan were collected and analyzed using pathogenesis, pathology and molecular biology methods. Result A large number of long filamentous and less-branched mycelia with 10−30 μm diameter were observed in the ulcerated tissues. Pathologically, we observed necrosis or lysed muscle fibers, inflammatory cell infiltration in the muscle tissue, and distribution of numerous fungal granulomas consisting of epithelioid cells, fibroblasts, and central located mycelia in the lesion tissues. By using periodic acid-silver metheramine (PASM) staining, the mycelia in the fungal granulomas center displayed black colour. We confirmed the infection of Aphanomyces invadans in the lesion muscle tissues by PCR using species-specific primers that target the ITS gene of A. invadans. The A. invadans (BW1 and BW3) pure cultures were isolated by glucose and peotone (GP) agar and then incubated in sterilized pond water. Prosporangium formation was observed in the culture after 12 h incubation period, which was consistent with the characteristics of Aphanomyces. Based on ITS gene sequencing of BW1 and BW3, their ITS genes were found to have 99.64% and 99.46% sequence similarities with A. invadans, and the two strains clustered with A. invadans in the phylogenetic tree.Conclusion The ulcer disease of largemouth bass in winter and spring has been caused by A. invadans.

Abstract:Objective To analyze the molecular characteristics of structural maintenance of chromosome (SMC) protein in Nosema ceranae, identify conserved motifs and structural domains within SMC in N. ceranae and other species followed by phyletic evolution analysis, thus enriching basic information about N. ceranae SMC and offering a basis for further functional study. Method Related software on Expasy website were utilized to predict and analyze physical and chemical property, signal peptide, phosphorylation site, secondary structure and tertiary structure of SMC. MEME software was employed to identify conserved motifs within SMC in N. ceranae and other species. TBtools software was used to identify structural domains within SMC. Based on SMC in N. ceranae and other species, phylogenetic tree was constructed with neighbor-joining method by Mega 11.0 software.Result SMC contained 1 102 amino acids, the molecular formula was C₅₇₈₇H₉₄₁₈N₁₅₂₆O₁₇₇₁S₄₁, the relative molecular weight was approximately 130 020, the lipid solubility coefficient was 93.49, the isoelectric point was 8.28, the average hydrophilic coefficient was −0.740, the number of hydrophilic amino acids was more than that of hydrophobic amino acids, and there was no typical signal peptide. SMC contained 50 serine phosphorylation sites, 26 tyrosine phosphorylation sites and 28 threonine phosphorylation sites. It as well included 787 α-helix, 106 β-sheet, 49 β-turn, and 160 random coil. SMC were simultaneously localized in nucleus, cytoplasm and mitochondria. Furthermore, SMC in N. ceranae, Encephalitozoon hellem, Hamiltosporidium magnivora, Nosema granulosis, Thelohania contejeani, Piromyces finnis, Trichophyton interdigitale, Trichophyton violaceum, Trichophyton tonsurans and Aspergillus melleus all contained nine same conserved motifs and two structural domains such as SMC_N and SMC_hinge. Further investigation indicated that the similarity of amino acid sequences of SMC between N. ceranae and P. finnis was the highest (61.96%), while that between N. ceranae and T. contejeani was the lowest (34.73%); SMC in N. ceranae and N. granulosis were clustered into a branch with the confidence of 99%, and their evolutionary distance was the closest. Conclusion The results define the molecular characteristics of N. ceranae SMC and enrich basic information about SMC, disclose that SMC in N. ceranae and other microsporidia are highly consevative, and provide a basis for further functional study.

Abstract:Objective Banana (Musa spp.) is one of the important economic crops in China. However, banana fusarium wilt caused by Fusarium oxysporum f. sp. cubense (Foc) seriously devastates the development of banana industry in China due to the rapid spread and difficult control of this disease. It is important to explore the spatial and temporal distribution of Foc in Brazilian (Musa acuminate L. AAA group, cv. Brazilian) plant and rhizosphere soil, which are directly related to infection and pathogenicity of Foc.Method Brazilian seedlings were inoculated with race 1 (Foc1) or race 4 (Foc4) by wounding roots in greenhouse, the amount and spatial distribution of Foc in different tissues at different times and in different rhizosphere soil of banana seedlings were analyzed using real-time quantitative PCR.Result From 2 to 21 days after inoculation, the contents of Foc1 and Foc4 in Brazilian roots and rhizomes increased with time, and the contents of Foc4 were significantly higher than those of Foc1. The contents of Foc1 and Foc4 in Brazilian rhizomes reached the highest at 21 and 14 days after inoculation, respectively. In the field, Foc1 and Foc4 were the most abundant in soil at the ground radius (r) of 5 cm from Brazilian plant and the depth of 25 to 30 cm under the ground at 30 days after inoculation. When the r values were 15 and 30 cm, the contents of Foc in soil at the depth of 10~15 cm were higher than those of 0~5 cm and 25~30 cm. In Brazilian rhizosphere soil at the same r value and soil depth, the contents of Foc4 were higher than those of Foc1 in most cases.Conclusion Foc1 and Foc4 have a significantly different spatial and temporal distribution in Brazilian plant and rhizosphere soil, and the content of Foc4 is higher than that of Foc1 in the same space, which provides a theoretical guidance for the epidemic, prediction and prevention and control of banana fusarium wilt.

Abstract:Objective To investigate the biological characteristics of Colletotrichum fioriniae on Rhododendron delavayi in Baili Azalea Nature Reserve of Guizhou Province, and to screen effective fungicides for disease control.Method The mycelial growth rate method was applied to explore the biological characteristics of C. fioriniae on R. delavayi. The indoor toxicity of pathogen was determined using 10 fungicides, including trifloxystrobin·tebuconazole, pyraclostrobin, difenoconazole, propiconazole, bromothalonil, dithianon, tetramycin, ethylicin, cnidiadin and ningnanmycin. Combined toxicity of two fungicides with high antifungal activities and different toxicological mechanisms to C. fioriniae was assessed in different mixture ratio. Result The pathogenic fungi could grow under 5-35 ℃ and pH 5-11. The optimum temperature was 25 ℃ and the optimum pH was 8. The best carbon sources were glucose and soluble starch. Peptone was the best nitrogen source for the pathogen growth and the growth rate reached the maximum on PSA medium. The results of the indoor toxicity test indicated that all of the 10 fungicides inhibited the mycelial growth of the pathogen to some extent. Among 10 fungicides, trifloxystrobin·tebuconazole, pyraclostrobin, tetramycin, difenoconazole, and propiconazole had better inhibitory effect with EC₅₀ of 0.102, 0.118, 1.107, 1.202 and 2.101 mg/L, respectively, followed by cnidiadin with EC₅₀ of 6.803 mg/L. The combination of tetramycin and difenoconazole with different mixture ratio showed synergistic inhibiting effect on the pathogen compared with single fungicide. The optimal mixture ratio was 7∶3 with co-toxicity coefficient (CTC) of 584.56, which was obviously higher than those of other mixture ratios. Both the mixture ratio of 6∶4 and 8∶2 had CTC above 500, being next to the best ratio. Conclusion The growth of C. fioriniae is significantly affected by temperature, pH, culture medium, carbon and nitrogen sources. The combination of tetramycin and difenoconazole in different mixture ratios has obvious synergistic toxicity, and the 7∶3 mixture ratio can be selected for field control experiments.

Abstract:Objective In order to achieve accurate application of micro flow liquid fertilizer near rice root, an electromechanical flow regulating valve was designed and integrated with the developed pneumatic ejector fertilizer applicator to construct a variable application regulation system of liquid fertilizer. Method The theoretical model of system mass flow rate was calibrated through experiments, and the transfer function model of control system was established. The structure, rules and initial parameters of the PID controller based on fuzzy reasoning (fuzzy PID control) were designed. The regulatory response capabilities of PID control and fuzzy PID control were compared through simulation experiment. Result The simulation experimental results showed that the overshoot, adjustment time, and steady-state error of step signal response for fuzzy PID control were 0.12%, 2.51 s, and 0.007 respectively, which were lower than 42.9%, 4.44 s, and 0.010 of PID control, and suggested fuzzy PID control had better dynamic adjustment and stability. Under interference of pulse signal with amplitude of 0.5 and duration of 0.1 s, the adjustment time of fuzzy PID control was 0.61 s, which was less than 1.67 s of PID control, and had stronger anti-interference ability. The performance test showed that under ten-target mass flow rate condition, the absolute error of mass flow rate of fuzzy PID control was lower than that of PID control, with a control accuracy of 93.93% to 96.88%, which was higher than 90.00% to 95.21% accuracy of PID control. When the fertilizer amount changed, the average overshoot was 12.2%, and rise time, adjustment time and peak time of fuzzy PID control were 1.5, 10.7 and 1.7 s respectively, which were lower than 17.4%, 2.1 s, 13.3 s and 2.3 s of PID control.Conclusion The variable rate application and regulation system for liquid fertilizer in rice based on fuzzy PID control has higher quality flow rate control accuracy and tracking performance, laying a foundation for the development of variable rate fertilizer equipment for liquid fertilizer in rice field.

Abstract:Objective In order to explore the effects of different biomass additions and amounts on soil infiltration characteristics and nutrient transport in fertilizer irrigation, so as to provide a theoretical basis for improving fertilizer irrigation efficiency. Method Biochar (BC), coffee grounds (CF) and bagasse (SC) were used as biomass additives, and four levels of addition were set including T₁ (0.5%), T₂ (1.0%), T₃ (1.5%), and T₄ (2.0%). The transport characteristics of fertilizer solution in different biomass-added soils and their nutrient distributions were measured. The effects of different biomass additions on soil structure were evaluated.Result The inhibitory effects of three kinds of biomass on wetting front migration and soil cumulative infiltration were SC>CF>BC, and the inhibitory effects in each treatment group increased with increasing biomass addition. Compared with the CK group, the wetting front migration distances of SCT₄, CFT₄ and BCT₄ decreased by 38.33%, 37.00% and 34.00% respectively. The cumulative soil infiltration amounts of SCT₄, CFT₄ and BCT₄ decreased by 31.01%, 30.00% and 26.60% respectively. Compared with the CK group, the three kinds of biomass additions under the fertilizer irrigation improved the contents of three main inorganic nutrients in soil, and the soil fertility was improved with increasing biomass addition. The overall performance of soil nitrate nitrogen retention by the three kinds of biomass was BC>CF>SC. Among them, the soil nitrate nitrogen contents of BCT₄, CFT₄ and SCT₄ increased by 74.32%, 56.00% and 51.00% respectively. The overall performance of soil available phosphorus retention by the three kinds of biomass was CF>SC>BC. Among them, the soil available phosphorus contents of CFT₄, SCT₄ and BCT₄ increased by 140.70%, 139.20% and 30.25% respectively. The overall performance of soil available potassium retention by the three kinds of biomass was CF>BC>SC. Among them, CFT₄, BCT₄ and SCT₄ increased the soil available potassium contents by 143.87%, 126.85% and 104.03% respectively.Conclusion All three kinds of biomass have inhibitory effects on the infiltration of fertilizer solution with biochar being the best. The three kinds of biomass all have interception effects on fertility, meanwhile, biochar has the best interception effect on nitrate nitrogen, and coffee grounds have the best interception effect on available phosphorus and available potassium.

Abstract:Objective To identify crop diseases accurately and quickly, reduce the cost of artificial diagnosis, and reduce the impacts of crop diseases on crop yield and quality. Method Based on the analysis of the characteristics of crop diseases and spots, an improved YOLOX-Nano intelligent detection and recognition model based on convolution attention mechanism was proposed. The model employed CSPDarkNet as the backbone network, added convolutional attention module CBAM to the feature pyramid network (FPN) of the YOLOX-Nano network structure, and then introduced the mixup data enhancement method in the training. At the same time, the classification loss function was replaced by the binary cross entropy loss function (BCE Loss) with the focus loss function, the regression loss function of GIOU Loss was replaced by the CenterIOU Loss function designed in this paper, and a transfer learning strategy was also used to train the modified YOLOX-Nano model so as to improve the accuracy of crop disease detection. Result The improved YOLOX-Nano model had parameters of 0.98×10⁶, and the detection time of a single sheet was about 0.187 s at the mobile end, with a mean average precision of 99.56%. The practical results of introducing this method into mobile terminal deployment showed that it could quickly and effectively identify common diseases of crops such as apples, corns, grapes, strawberries, potatoes and tomatoes, and achieve the balance of accuracy and speed.Conclusion The improved model not only has higher accuracy and detection speed for crop leaf disease identification, but also has less parameters and calculation amount. The model was easy to be deployed on mobile devices such as mobile phones. In addition, the model achieves accurate positioning and identification of a variety of crop diseases in complex field environment, which is of great practical significance to guide the prevention and control of early crop diseases.

Abstract:Objective In order to improve the grade classification accuracy of damage degree by wheat stripe rust, the automatic, accurate and rapid identification method of damage degree by wheat stripe rust was studied.Method Under complex field conditions, images were taken by mobile phones, and data sets of wheat leaves with different grades of stripe rust were constructed. The combination of GrabCut and YOLOv5s was used to automatically segment wheat leaves from complex background. The Inception module was added to enhance the ability of ResNet50 in extracting phenotypic features. The disease grades of wheat stripe rust were identified according to the classified disease grade standards of wheat stripe rust. The performance of the improved ResNet50 model (B-ResNet50) on the data set was analyzed using evaluation indexes such as accuracy, recall and precision. Result Wheat leaf images were segmented automatically, accurately and quickly by the combination of GrabCut and YOLOv5s under complex background in the field. The recognition rate of B-ResNet50 on the data set of wheat stripe rust leaves was 97.3%, which was obviously higher than that of InceptionV3 (87.8%), DenseNet121 (87.6%) and ResNet50 (88.3%). The accuracy rate was greatly improved, and nine percentage points more than that of the original model(ResNet50). Conclusion Using deep learning to identify the disease grade of wheat stripe rust is of great significance to applying accurate pesticide for its control, and provides technical support for the control of wheat stripe rust under complex field conditions.

Abstract:Objective With the rapid development of big data technology and artificial intelligence, aiming at the problems of low accuracy, too large prediction area, too long model optimization time of the current rice yield prediction model, etc., a whale optimization algorithm-backpropagation (WOA-BP) rice yield prediction method based on Spark was proposed.Method This paper took rice yield and weather data of counties/cities/districts in the western region of Guangdong Province as the research object, used WOA to optimize the weights and bias values of BP neural network, and constructed a rice yield prediction model to improve the prediction accuracy. In addition, the WOA-BP algorithm was parallelized in the Spark framework to reduce the algorithm time overhead.Result In terms of model accuracy, by comparing the prediction results after inverse normalization, the mean absolute percentage error of the BP neural network model optimized by WOA decreased from 8.354% to 7.068%, and the mean absolute error decreased from 31.320 kg to 26.982 kg, the root mean square error dropped from 41.008 kg to 33.546 kg. In terms of run time, 3-node Spark cluster reduced runtime by 11 742 s over non-Spark mode, reducing time overhead by 44%. Conclusion The WOA-BP rice yield prediction method based on Spark can better predict rice yield in western Guangdong counties/cities/districts, and at the same time can well reflect the influence of weather factors on rice yield in western Guangdong Province, which is a reference for studying the rice yield situation in western Guangdong counties/cities/districts and even the whole Guangdong.

Abstract:Objective To address the issues of edge jitter in chicken point clouds, feather redundancy and challenging feature point extraction in chicken body size estimation using depth cameras, this paper proposes a method combining point cloud edge smoothing and biometric-based feature point extraction for mult-position estimation of chicken body size. Method Firstly, the point cloud was preprocessed by direct filtering, statistical filtering and other methods to reduce the impact of background and noise on the target. Secondly, the edge was constrained by the spatial change of point cloud, and the edge was smoothed by continuous multi-frame sequence changes, so as to reduce the interference of edge jitter on the extraction of body measurement points. Thirdly, the biological characteristics of the processed point cloud were analyzed. Combined with the edge algorithm based on neighborhood analysis, the RGB image was fused and the feature points were extracted by Canny edge detection, Hough transform and other methods. Finally, the chest width, semi diving length and tibial length were estimated according to the feature points.Result The test results showed that the average error of estimated chest width was 6.64%, the average error of tibial length was 5.93%, and the average error of semi diving length was 3.34%. The average calculation time of body size per frame image was 8.8 s. Conclusion The algorithm of this paper can provide a technical reference for chicken body size measurement.

Abstract:Objective A low-cost 3D light detecting and ranging (LiDAR) point cloud information processing and plant row estimation method for environment perception in agricultural robot navigation is proposed for the areas where the satellite signal is seriously occluded in the forest or under the canopy.Method First, the pass through filter was used to filter out the target irrelevant points outside the area of interest. Secondly, the methods of mean shift clustering and scanning area adaptation were proposed to segment the trunk of each plant, and the vertical projection of the trunk point cloud was used to estimate the center point. Finally, the plant rows were estimated by determing the trunk centers with the least square fitting method. The simulation experiment and field experiment were carried out in the simulated orchard and metasequoia forest in the open field. The angle between the plant row vector and the due east was used as the index. The angle error between the plant row information identified by the proposed method and the true value of the plant row measured by GNSS satellite antenna positioning was calculated.Result Using the proposed method of 3D LiDAR point cloud information processing and plant row estimation, the average errors of plant row identification in simulation experiment and field experiment were 0.79° and 1.48°, the minimum errors were 0.12° and 0.88°, and the maximum errors were 1.49° and 2.33°, respectively.Conclusion The vehicle-mounted 3D LiDAR can effectively estimate the plant rows of metasequoia. This research enriches the ideas and methods of crop identification, and provides a theoretical basis for the map-free navigation of agricultural robots in areas without satellite signal coverage.

Abstract:Objective Water pollution monitoring is a prerequisite for water pollution prevention and control in watersheds. In order to achieve high accuracy of surface water quality monitoring and water body rating judgement, we designed a water quality monitoring and rating system based on IGWOPSO-SVM (Improved grey wolf optimizer particle swarm optimization-support vector machine) model. Method We selected sensor group, STM32F103 microcontroller, ESP8266WIFI wireless communication module to build a water quality monitoring system data processing module. The WIFI wireless communication transmitted the water quality data collected by data processing module to the server. We designed water quality monitoring system server interactive end, while developing water quality monitoring applet for real-time monitoring of water quality grade. Based on the improved particle swarm optimization (IPSO) and grey wolf optimizer (GWO), the IGWOPSO algorithm was proposed to optimize SVM algorithm, according to which the IGWOPSO-SVM water quality rating algorithm was proposed. The water quality rating effect of this system was verified by experiment based on 135 groups water quality data of Nanjing Xuanwu Lake, Jinchuan River and Jiangpu water source. Result Compared with SVM, the total sample classification accuracy of IGWOPSO-SVM water quality rating algorithm increased from 86.67% to 100.00%, with an increase of 13.33 percent. Compared with particle swarm optimization (PSO), the best adaptation degree of IGWOPSO algorithm increased from 86.80 to 99.20, with an increase of 14.29%. Conclusion This study solves the problems of low efficiency and low accuracy of traditional water body rating methods, and provides a method reference for accurate monitoring of surface water quality.