20368 results about "Zoology" patented technology

The invention, which belongs to the technical field of intelligent breeding equipment, discloses an underwater bionic robotic fish school cooperative breeding environment dynamic monitoring and regulation system comprising a bionic robotic fish body core module, a group cooperative control core module and an intelligent regulation core module. The bionic robotic fish module simulates a real fish swimming mode and carries various water quality sensors to autonomously cruise, so that interference to cultured fishes is reduced; the group cooperation module utilizes a cluster intelligent algorithm and an underwater acoustic communication technology to realize coordinated movement of multiple robotic fishes and full coverage of a monitoring area; the intelligent adjusting module is based on an abnormal detection algorithm, and integrates a miniature oxygenation device, a pH adjusting device and the like to achieve precise regulation and control of the local environment. By the adoption of the system, dynamic sensing and active regulation and control of the culture environment are achieved, a bionic monitoring regulation and control solution is provided for modern aquaculture through intelligent cooperation of the robot fish school and the management system, and the system has the important value of improving the culture efficiency and improving the growth environment.

A fishing line guide mountable to a fishing rod body to guide a fishing line, the fishing line guide includes a foam portion made of foamed resin, and a reinforced resin portion made of fiber-reinforced resin and covering a part of the foam portion.

The invention relates to the technical field of intelligent aquaculture and automatic processing, in particular to an appearance characteristic-based hippocampus intelligent grading and pond-dividing culture method and system, and the method comprises the following steps: S1, collecting sparse visual data and multi-source physiological data of hippocampus; s2, generating a three-dimensional digital twinborn model based on the sparse visual data; calculating a growth state grading index based on the three-dimensional digital twinborn model; s3, calculating a physiological stress index based on the multi-source physiological data; s4, comparing the physiological stress index calculated in real time with a preset safety stress threshold value and a critical stress threshold value, and generating a hierarchical adaptive correction strategy; s5, according to a grading self-adaptive correction strategy, controlling a flexible mechanical arm to execute fishing and pond separation operation; according to the method, the appearance and physiological data of the hippocampus are synchronously collected in a non-contact mode, the technical problems that the real condition of the hippocampus cannot be evaluated and damage is possibly caused due to target stress response caused by traditional physical intervention are solved, and the authenticity and effectiveness of original data are guaranteed.

The invention discloses an intelligent fishery environment sensing and self-adaptive intelligent adjustment method and system, and belongs to the technical field of intelligent fishery and intelligent environment regulation and control. The method comprises the following steps: acquiring multi-dimensional data such as water quality, weather and fish school behaviors through an environment sensing module, processing the multi-dimensional data through a data standardization and treatment module, extracting key features by using an environment-behavior feature engineering module, and performing state assessment and trend prediction through a coupling modeling and risk assessment module; a regulation and control strategy is generated and executed in combination with a multi-objective optimization and execution arrangement module, and finally, through feedback and optimization of a closed-loop evaluation and adaptive learning module, accurate sensing, dynamic prediction and intelligent adjustment of a fishery environment and a fish school state are realized, the stability of a breeding environment and the health level of a fish school are effectively improved, and environmental risks are reduced.

The invention discloses a shrimp health state early warning method and system based on water quality monitoring, and aims to improve the disease prevention and control efficiency in a shrimp culture process. The method comprises the following steps: collecting historical breeding disease data and water quality change data of a target shrimp breeding water area, and constructing a water quality pathopoiesis knowledge graph; then water quality change data in a preset monitoring time period is obtained, space-time tracing is carried out by using the water quality change prediction model, and a water quality anomaly propagation path diagram is generated; formulating a water quality monitoring strategy based on the propagation path diagram, and optimizing the layout and frequency of monitoring points; and finally, monitoring the water quality in real time according to the established monitoring strategy, and realizing dynamic early warning of the health state of the prawns by combining real-time monitoring data and a water quality pathopoiesis knowledge graph. Water quality related diseases can be effectively prevented and controlled, and the stability and yield of shrimp culture are improved.

The invention discloses a KASP molecular marker primer combination for detecting peanut late spot disease resistance and application of the KASP molecular marker primer combination, and belongs to the technical field of peanut molecular breeding. The molecular marker linked with the late spot resistance character can be used for detecting the genotype of peanuts so as to judge whether a material has late spot resistance or not, through high-throughput genotyping detection, manpower and material resources are greatly saved, the detection is not influenced by environmental factors, the result is accurate and reliable, and the molecular marker can be used for early screening of peanut late spot resistance varieties and can be applied to early screening of peanut late spot resistance varieties. The breeding period can be shortened and the breeding efficiency is improved.

The invention provides a digital twinborn monitoring, regulating and controlling method for a copepod bait biological domestication process. The method comprises the following steps: establishing a micro-ecology and population dynamics coupled twinborn model, and defining a monitoring parameter and control object unified term system; collecting multi-source sensing data at an edge end, and performing clock synchronization, signal denoising and state estimation to obtain a micro-ecology, group and water body state joint estimation result; executing parameter online identification based on state estimation, and constructing a safety constraint set of ammonia nitrogen, dissolved oxygen, death rate, environment change rate and the like; the breeding efficiency improvement and the system stability balance are realized through a multi-objective optimization function; and generating a micro-ecological pulse and environment gradual change cooperative control action set according to a solving result, and when a set condition is met, outputting a domestication prescription and terminating the process. Intelligent, low-stress and high-stability regulation and control of a copepod domestication process are realized through digital twin modeling, rolling predictive control and a self-evolution updating mechanism.

The invention provides a key habitat identification method, device and equipment based on a species-habitat network. The method comprises the following steps: acquiring landscape type vector data and species survey data of a research area; dividing multiple habitat types based on the landscape type vector data; on the basis of habitat types, a species and habitat incidence matrix is constructed in combination with species survey data; constructing a species-habitat bipartite network based on the species and habitat incidence matrix; determining a plurality of centrality indexes of each habitat type node in the species-habitat bipartite network; performing standardization processing on the plurality of centrality indexes, and determining a comprehensive importance index of each habitat type based on the centrality indexes after standardization processing and a preset weight; and sorting habitat types based on the comprehensive importance index, and identifying a key habitat. By means of the mode, quantitative expression of the structural relation between the habitat and the species and applicability and flexibility of habitat importance identification are achieved, and deviation caused by dependence on a single index is avoided.

Veterinary pharmaceutical compositions for direct systemic introduction, also known as DSI pharmaceutical compositions. One veterinary pharmaceutical composition for direct systemic introduction includes about 10-17 dry mass % bovine gelatin; about 10-17 dry mass % mannitol; about 0-1 dry mass % of a surfactant; and about 65-80 dry mass % of the active pharmaceutical ingredient which is a proton pump inhibitor. A method of manufacturing a veterinary pharmaceutical composition for direct systemic introduction includes combining one or more pharmacologically inactive compounds to form a first solution; using one or more surfactants to form a second solution; adding an active pharmaceutical ingredient to the second solution to form a first mixture; adding the first solution to the first mixture to form a pre-formulation; freezing the pre-formulation; and lyophilizing the pre-formulation.

The invention discloses a tetraploid crassostrea gigas parent-child relationship identification method based on SNP sites, and belongs to the technical field of tetraploid crassostrea gigas molecular assisted breeding. The method for identifying the parent-child relationship of tetraploid crassostrea gigas comprises the following steps: (1) sequencing adductor muscles of tetraploid crassostrea gigas to be detected; (2) comparing the reference genome of the crassostrea gigas to obtain the genotype of the specified SNP site of the tetraploid crassostrea gigas; (3) calculating IBS and LOD of the to-be-detected parents and the to-be-detected offspring according to an SNP typing result; and (4) identifying the parent-child relationship between the to-be-detected parent and the filial generation by combining IBS and LOD. The SNP loci have the advantages that 1000 SNP loci for identifying the parent-child relationship of the tetraploid crassostrea gigas are disclosed for the first time, data support is provided for identifying the parent-child relationship of the tetraploid crassostrea gigas, a foundation is laid for developing a liquid phase chip for identifying the parent-child relationship of the tetraploid crassostrea gigas, and the SNP loci have good application prospects.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker related to calving interval traits of dairy cows and application of the SNP molecular marker. The number of the SNP molecular markers is four, and the nucleotide sequences of the four markers are as shown in SEQ ID NO.1-4. Researches find that the four SNP molecular markers are significantly related to the Chinese Holstein cattle calving interval traits, and can be used for molecular marker-assisted breeding of the Chinese Holstein cattle calving interval traits to accelerate breeding of Chinese Holstein cattle with strong fecundity. The SNP molecular marker is used for identifying the calving interval character of the Chinese Holstein cattle, the four SNP loci are detected in actual breeding, seed selection and matching are guided, the breeding efficiency is improved, the non-pregnant period is shortened, the production performance of the dairy cattle can be comprehensively improved, the breeding strategy can be optimized, and the population genetic progress can be accelerated.

The invention relates to the technical field of animal monitoring, and provides a wild animal epidemic disease monitoring, prevention and control method and system based on artificial intelligence, and the system collects the video stream, the shell temperature, the air pathogen concentration, the sound characteristics, the VOCs spectrogram and other data of wild animals in real time through arranging multi-mode sensor nodes. Real-time reasoning is carried out through a wildness degree AI model in the edge calculation unit, the health state and epidemic disease risk of animals are evaluated, a multi-source risk knowledge graph and a graph neural network are combined, an epidemic situation occurrence probability threshold value is dynamically adjusted by the system, and accurate prevention and control instructions such as risk area division, isolation early warning and material putting schemes are generated; after the epidemic disease risk is confirmed, the system sends early warning information to a prevention and control center through various communication links, and continuously optimizes a prevention and control strategy through reinforcement learning. According to the method, intelligence and precision of epidemic disease prevention and control of wild animals are achieved, complex ecological environment changes can be coped with in real time, and prevention and control efficiency and accuracy are remarkably improved.

The invention provides a pleurotus citrinopileatus physiological maturity detection method and device, and relates to the technical field of crop growth monitoring, and the method comprises the steps: collecting the hue feature information of a to-be-detected pleurotus citrinopileatus image, inputting the hue feature information of the to-be-detected pleurotus citrinopileatus image into a physiological maturity quantification model, and determining the physiological maturity of the to-be-detected pleurotus citrinopileatus image; and obtaining the physiological maturity of the pleurotus citrinopileatus to be measured output by the physiological maturity quantification model. According to the pleurotus citrinopileatus physiological maturity detection method provided by the invention, accurate and rapid detection of the pleurotus citrinopileatus physiological maturity is realized based on the hue feature information of the pleurotus citrinopileatus image and the machine learning model.

The invention belongs to the technical field of farm environment regulation and control, and discloses a farm environment regulation and control system and method, and the system comprises a multi-source sensing module, a data analysis module, an intelligent decision module, and a regulation and control execution module. According to the method, the dynamic environment coupling model is constructed, the environment state is comprehensively evaluated in combination with the multi-source sensing data, and the internal conflicts and cooperative relationships among the regulation and control parameters are accurately identified, so that the cooperative regulation and control instruction set considering multiple targets is formulated. Therefore, the problem of linkage environment imbalance caused by single regulation and control in traditional control is avoided, and the overall stability and comprehensive comfort of the breeding environment are remarkably improved. According to the invention, animal behavior perception is taken as a core feedback and feedforward signal, and conversion of a regulation strategy from passive response to active prediction is realized. The system can pre-judge the change of a local environment in advance according to the moving trend of animals and perform fine adjustment, so that stress events such as ammonia peak value or violent fluctuation of temperature and humidity are effectively avoided.

The utility model discloses a differentiated zoned irrigation and fertilization system for seed corn, which relates to the technical field of agricultural drip irrigation and fertilization equipment and comprises a plurality of drip irrigation tape units, male parent irrigation branch pipes and female parent irrigation branch pipes. The drip irrigation tape unit comprises single male parent drip irrigation tapes, single female parent drip irrigation tapes and double female parent drip irrigation tapes, and the ratio of the number of the single male parent drip irrigation tapes to the number of the single female parent drip irrigation tapes to the number of the double female parent drip irrigation tapes is 1: 1: 3; the single male parent drip irrigation tape is connected with the male parent irrigation branch pipe, and the single female parent drip irrigation tape and the double female parent drip irrigation tape are connected with the female parent irrigation branch pipe; the male parent irrigation branch pipe and the female parent irrigation branch pipe are connected with an original farmland irrigation pipe network through a shunt valve, and a master control valve is arranged between the shunt valve and the original farmland irrigation pipe network; the water inlet ends of the male parent irrigation branch pipe and the female parent irrigation branch pipe are respectively provided with a control valve. The device can meet the water and fertilizer requirements of male parents and female parents respectively, the emergence rate and uniformity of the male parents and the female parents are improved, the seed yield and quality are improved, and the water and fertilizer utilization efficiency is improved.

The invention provides an uncertainty analysis method and device for a livestock target detection model. The method comprises the following steps: acquiring an RGB image of a livestock target; constructing an uncertainty analysis model of the livestock target detection model, and calling the uncertainty analysis model to detect the livestock target in the RGB image to obtain the category of the livestock target and a detection frame coordinate; and respectively calculating a cognitive uncertainty index and a random uncertainty index of the livestock target detection model according to the category and the coordinates of the detection frame. The method is used for solving the problems that in the prior art, an uncertainty analysis method is not comprehensive enough, uncertainty result attribution is lacked, and the uncertainty evaluation effect is poor.

The invention relates to the technical field of prawn culture, in particular to a high-density culture optimization method for penaeus monodon based on multi-source culture environment analysis. A scale evaluation system of different preset cultivation environment condition combinations is built based on high-density penaeus monodon cultivation to evaluate the trend radiation diagram, whether the current cultivation density scale of the penaeus monodon is reasonable or not is analyzed through thermal polymerization after evaluation, and a multi-source cultivation environment analysis result is obtained; if one or more high-density abnormal breeding areas exist in a multi-source breeding environment analysis result, a simplex table model is constructed with the maximum bearing force as a constraint and the expected breeding density coefficient as a target function, and the optimal solution of the simplex table model is solved to determine the optimal breeding density scale of the high-density abnormal breeding areas. According to the method, the multi-source culture environment data can be fused to reasonably and scientifically analyze the high-density culture of the penaeus monodon and make an accurate and optimized culture strategy, so that the yield of the penaeus monodon per unit area is increased, and the low survival rate of the high-density culture is improved.

The invention discloses an automatic cattle checking method and system based on two-dimensional panoramic vision, and belongs to the technical field of computer vision and intelligent breeding, and the method comprises the following steps: reasonably arranging a plurality of fixed cameras in a cattle farm area, obtaining the internal reference and distortion coefficient of each camera through employing a camera calibration technology, and obtaining the internal reference and distortion coefficient of each camera; performing real-time distortion correction on the collected video frames; on the basis of side-by-side splicing or homography matrix perspective transformation, all paths of corrected images are fused into a complete two-dimensional panoramic image, and a view blind area of a single camera is eliminated; calling a lightweight target detection model on the panorama, and extracting bounding boxes and confidence coefficients of all cattle at one time; sorting according to the confidence from high to low, performing IOU non-maximum suppression de-duplication on the detection frame, and ensuring that the same cattle only counts once in an overlapping region; and the whole process is completed through the edge computing node. According to the invention, efficient, real-time and accurate on-site cattle checking of a large-scale cattle farm can be realized.

The invention discloses a pheromone binding protein derived peptide capable of effectively monitoring sex pheromones of fall webworms and a biosensor, and belongs to the field of biosensors. At present, methods such as sample plot survey and sex traps commonly used in fall webworm monitoring have the problems of poor timeliness, high labor cost, insufficient data continuity and the like. In order to solve the problem, the pheromone binding protein-derived peptide provided by the invention has an amino acid sequence as shown in SEQ ID NO: 2, the biosensor comprises a substrate and an interdigital electrode, a single-walled carbon nanotube is attached to the electrode, and the electrode is also connected with the pheromone binding protein-derived peptide. The sensor can specifically detect sex pheromones of fall webworms, has no response to 17 plant volatile matters, and can detect sex pheromones released by as low as five live female fall webworms under laboratory conditions. The method has application potential in the fields of early pest monitoring, prevention and control efficiency improvement, ecological safety guarantee and the like.

The invention discloses a sheep coccidiosis parasitic ovum accurate detection method based on deep learning, and the method comprises the following steps: automatically collecting a sheep manure sample image, carrying out the noise removal and enhancement of the image, and guaranteeing the image quality; the preprocessed image is input into an automatic sheep coccidiosis parasitic ovum detection model for training, the training process comprises image segmentation, feature extraction and accurate recognition, and a deep learning model is used for automatically recognizing sheep coccidiosis parasitic ovum; performing infection density analysis according to the number of sheep coccidiosis parasitic ova output by the improved deep learning model, and evaluating the infection risk of the sheep flock; the detection result is visually displayed, detailed analysis reports including the number, type distribution and infection density data of sheep coccidiosis parasitic ova are generated, hours or even longer time needed by a traditional method is shortened, and high accuracy of the detection result is ensured.

The invention discloses a caged laying duck head key feature detection method based on an improved yolov8 model in the technical field of computer vision, and the method comprises the steps: 1, collecting the image data of caged laying ducks in a poultry enterprise production base; step 2, performing data cleaning, image preprocessing and expert-assisted marking of target detection frames of different parts, including the head, the beak and the eyes, on the acquired image, and constructing a caged laying duck head key feature detection data set; and step 3, aiming at the image data of the caged laying ducks, firstly performing pixel removal on the caged laying duck main body shielding cage net, then complementing the removed pixels, and finally constructing a caged laying duck head key feature detection data set after data enhancement according to the mapping relation between the image and the label. The key feature parts of the head of the cage-rearing laying duck can be detected more quickly, and the detection accuracy is improved.

An accessory mount allows accessories to be removably and adjustably mounted to a surface. In an example, the surface may be that of a watercraft, and the accessory may be a fishing rod. The mount may be used with a track fixable to an environmental surface or mounted directed to the environmental surface. When used with a track, a post of the accessory mount releasably engages the track. Slidable engagement of the post allows lateral or horizontal adjustment of the accessory. An accessory engaging member is adjustable in relation to the post about a horizontal axis and a vertical axis, so that angular and azimuthal rotational adjustments of the accessory are enabled. A single lever is used to make angular and rotational adjustments, and to release the accessory engaging member from the post.

The invention provides a method for identifying abnormal behaviors and death states of chickens based on attitude angles, which comprises the following steps of: continuously acquiring three-axis attitude angle signals (namely a pitch angle Pitch, a yaw angle Yaw and a roll angle Roll) by using an inertial sensing device worn on the body surface of a chicken, constructing a low-frequency behavior track sequence, and identifying the abnormal behaviors and the death states of the chicken according to the low-frequency behavior track sequence; and through a set posture change threshold value, posture stability judgment, frequency distribution analysis and a posture imbalance recognition algorithm, whether the chicken is in the states of dysphoria, abnormally static, prostration, stiff head raising or death or not is judged. The method does not depend on acceleration or six-axis fusion signals, has the advantages of being low in power consumption, high in adaptability, easy and convenient to deploy and the like, and is suitable for continuous health monitoring and death early warning management of chicken individuals in a large-scale farm. The method has the characteristics of clear signal input boundary, accurate recognition mechanism, economical system deployment and the like, and the digital management efficiency and the animal welfare guarantee level of poultry breeding are remarkably improved.

The invention discloses a macrobrachium rosenbergii cherax ratio prediction and breeding method based on phenotypic omics analysis, which comprises the following steps: selecting a plurality of macrobrachium rosenbergii for multi-generation breeding, recording pedigree data of each individual, and constructing a macrobrachium rosenbergii breeding database; the method comprises the following steps: extracting phenotypic characteristics of macrobrachium at different culture stages, analyzing a rule between a growth index and a chelate ratio, carrying out heritability evaluation, and constructing a macrobrachium phenotypic omics network; the growth path of macrobrachium rosenbergii is analyzed, abnormal events in the breeding period are recognized, and a macrobrachium rosenbergii growth situation network is generated; constructing a macrobrachium phenotype knowledge map, and constructing a macrobrachium cherax ratio prediction model; and performing data acquisition on a macrobrachium rosenbergii population to be bred to obtain early phenotypic data, performing breeding decision, and performing breeding path recommendation on bred individuals by using the macrobrachium rosenbergii phenotypic knowledge graph. Meanwhile, whether the breeding path is deviated or not in the breeding process is analyzed, and a correction scheme is formulated for pushing, so that the breeding period of the macrobrachium is shortened, and the breeding accuracy and efficiency are improved.

The invention belongs to the technical field of liquid chromatography-mass spectrometry detection pretreatment, and particularly relates to a pretreatment method for liquid chromatography-tandem mass spectrometry analysis of pesticide and veterinary drug residues in serum, which comprises the following steps: (S1) carrying out heating reaction on Sc (III) salt, Cu (II) salt and 1H-pyrazole-4-formic acid (H2PyC) in a polar aprotic solvent, and cooling to obtain a green crystal, namely MOF-919; the chemical formula of the MOF-919 is [Sc < 3 > (mu3-O) (OH) < 3 >] [Cu3 (mu3-O) (mu-PyC) < 3 > (H2O) < 6 >] < 2 >; (S2) mixing the serum sample with an acetonitrile solution containing formic acid, carrying out ultrasonic treatment, vortex oscillation and centrifugation, taking supernate, and diluting the supernate with an aqueous solution containing formic acid to obtain a to-be-purified solution; and (S3) adding MOF-919 into the to-be-purified liquid, mixing, performing ultrasonic treatment, performing vortex oscillation, centrifuging, and taking supernate, thereby completing the pretreatment of the to-be-purified liquid. According to the method, the MOF-919 is used for adsorbing chemical pollutant residues in serum, especially phospholipids, so that the purpose of removing the chemical pollutant residues in blood is achieved. The method is simple and convenient to operate, small in organic solvent consumption and good in purification effect, and can be widely applied to residue analysis of chemical pollutants in serum.

Embodiments are directed to an advanced, modular, and scalable system integrating a Dissolved Gas Infusion (DGI) system and a Programmable Logic Controller (PLC) to automate and optimize processes such as water filtration, oxygenation, and waste management. The DGI system infuses high-purity oxygen directly into the water, maintaining optimal dissolved oxygen (DO) levels from the post-larvae stage to harvest, and significantly reducing oxygen wastage compared to traditional bubble aeration processes. The system includes modular raceways with load-bearing support beams, twist locks for secure stacking, and observation ports for easy access. This innovative approach ensures efficient, cost-effective, and reliable shrimp production, leading to higher survival rates, faster growth, and improved overall health of the shrimp.

The invention belongs to the technical field of pig molecular marker-assisted selection, and particularly relates to application of an SNP molecular marker related to the character of the number of live piglets born by pigs. The SNP molecular marker is a basic group of a 32663785th site of a ninth chromosome in a pig genome Sscrofa11.1. 109, the SNP site of the molecular marker has C / T polymorphism, and T is a favorable allelic variation of the character of the number of live piglets born by a pig. The dominant alleles of the SNP are preferably selected, the frequency of the dominant alleles can be increased generation by generation, the number of live piglets of pigs is increased, and the genetic improvement progress of the pigs is accelerated, so that the breeding and production benefits of the pigs are effectively improved.

The invention discloses an artificial breeding method of epinephelus fuscoguttatus and pink pterus coerulescens hybrid species, which comprises the following steps: screening healthy epinephelus fuscoguttatus as a female parent, screening healthy pink pterus coerulescens as a male parent, and carrying out enhanced breeding on the male parent and the female parent, the gonad maturation of the parent is promoted; the method comprises the following steps: collecting egg liquid of a female parent and semen of a male parent, inseminating to obtain a fertilized egg, incubating the fertilized egg to obtain a hybrid spot, performing authenticity identification on the hybrid spot by using one or more of sequences SEQ ID NO.1-SEQ ID NO.8, and determining that the hybrid spot inherits genetic information of the female parent and the male parent. The technical blank of crossbreeding of the pink pink bass as the parent grouper is filled, so that the hybrid obtained by hybridizing the epinephelus fuscoguttatus and the pink pink bass is reliable in authenticity, and inherits genetic information of male and female parents on the molecular level.

The invention discloses a coastal culture pond expansion recognition and mangrove forest ecological occupation and supplement balance evaluation method, and belongs to the technical field of environment remote sensing monitoring and ecological evaluation. Aiming at the problems that a mangrove forest ecological system is damaged by expansion of a coastal culture pond and a dynamic monitoring and quantitative evaluation mechanism is lacked, the evaluation method is provided and comprises the following steps: preprocessing a multi-temporal satellite remote sensing image; using a convolutional neural network computer model to supervise, classify and distinguish culture ponds, mangrove forests and other land types; extracting boundaries of the two-time-phase culture pond and identifying a newly-added area; in combination with the mangrove forest distribution map, obtaining an occupied area through spatial overlay analysis; establishing a biomass regression model based on the vegetation index value of the infringed area to estimate the biomass per unit area, and hierarchically calculating the carbon reserve loss amount; and calculating a compensation area according to the carbon loss amount and the unit carbon reserve of the mature mangrove forest in the target area, and generating an occupation and compensation balance scheme in combination with unutilized mud flat spatial distribution. The method is used for dynamic monitoring, accurate quantification and scientific compensation of mangrove forest ecological loss.

A system toilet for a pet includes an excretion container, including a liquid-permeable bottom surface portion, that houses toilet litter, a tray, disposed below the excretion container, that houses an absorbent sheet that absorbs liquid having passed through the liquid-permeable bottom surface portion, a lower container that holds the tray, and an upper container disposed to cover an upper part of the excretion container and having an opening portion through which a pet enters and exits. The upper container includes a pair of side wall portions disposed to face each other on both sides in a width direction of the opening portion and extending in a front-rear direction, an upper wall portion disposed above the opening portion to bridge over the pair of side wall portions, a lower wall portion disposed below the opening portion, and a side wall guide portion.