10581 results about "Fodder" patented technology

The invention discloses a feed regulation and control method and system for beef cattle breeding, and relates to the technical field of feed regulation and control, and the method comprises the steps: carrying out grouping management according to individual differences of beef cattle, and collecting feed component data, growth stage data and climate environment data of beef cattle breeding in each group in real time; on the basis of the feeding and defecation amount of the beef cattle, the nutrient substance digestion and metabolism capacity of the beef cattle is evaluated, a dynamic feeding model driven by multi-modal data is constructed, and a feeding mode and an optimal feed ratio are matched; the optimal feed proportion is converted into a control instruction, and equipment is driven to execute feed blending and feeding; beef cattle growth condition data are monitored in real time, and the feed ratio is optimized according to actual deviation feedback. According to the method, the cattle in different physiological states are finely distinguished, multi-dimensional data such as environmental parameters and metabolic capability evaluation are combined, a dynamic feeding model is constructed, the feed conversion efficiency and the stability of growth performance are remarkably improved, and healthy growth of the beef cattle is guaranteed through effective feeding management.

The invention discloses a sheep flock accurate nutrition supply method based on an intelligent feeding algorithm, and the method comprises the following steps: collecting the body type, physiology, movement and environment data of sheep through a multi-modal sensing device, and constructing individual three-dimensional representation based on a neural radiation field model, historical growth data and a real-time health state are analyzed by utilizing an individual nutritional requirement calculation model, an optimal feed distribution strategy is determined by combining an intelligent sheep flock optimization algorithm, a feeding scheme is dynamically adjusted by adopting deep reinforcement learning, and through a cloud-side collaborative calculation architecture, the calculation efficiency is improved and a feeding decision is optimized. A non-intrusive health monitoring technology is combined, a group health evaluation model is constructed, the feed ratio is adjusted in real time, accurate matching of individual and group nutritional requirements is achieved, and through prediction of the individual and group nutritional requirements, self-adaptive adjustment is conducted on feeding parameters, and a dynamic nutrition supply strategy is optimized. The system effectively improves the feeding precision, reduces the feed waste, and optimizes the health management of the sheep flock.

A food processing machine (10) and a method of cutting slices or portions from a food product (60, 70, 72, 74) in a food processing machine are described. The food processing machine comprises a cutter (30) to cut portions from a food product and a sensing apparatus (43, 45) configured to sense a profile of the food product. The machine is arranged to control sensing and cutting feed rates independently.

The invention discloses a straw feed fermentation treatment control system and method, particularly relates to the technical field of production control, and is used for solving the problem of insufficient identification and regulation of an imbalance phenomenon in a straw fermentation pile caused by non-uniform gas diffusion in the existing fermentation process. The method comprises the following steps: acquiring environmental parameters of a fermentation heap, performing three-dimensional gas concentration field reconstruction processing, identifying a layered air mass region in combination with a fuzzy clustering algorithm, measuring heap pressure distribution and deformation characteristics, analyzing a heap body structure abnormal region, and marking a risk analysis region; through a three-dimensional tensor model and a fractal analysis model, the time dependency and the gas diffusion equilibrium degree of the gas exchange and metabolism process are evaluated respectively, and finally fermentation pile structure parameters and ventilation device operation parameters are dynamically adjusted based on a closed-loop control system; through accurate region identification and a dynamic regulation and control mechanism, the uniformity of the fermentation process and the quality consistency of the straw feed are remarkably improved.

The invention relates to the technical field of animal feed preparation, in particular to a functional feed additive for ruminants and a preparation method of the functional feed additive for the ruminants, and the functional feed additive for the ruminants is characterized by consisting of the following components in percentage by mass: probiotics which are saccharomycetes, bacillus subtilis and enterococcus faecalis; an enzyme preparation, xylanase and protease; prebiotics are added; a microcapsule coating material; a binder; the balance is a carrier; the probiotics and the enzyme preparation are wrapped in the chitosan / sodium alginate composite film through a microcapsule coating technology, adverse factors such as temperature, humidity and illumination in the production, transportation and storage process can be effectively isolated, meanwhile, in the rumen low-pH, strong-protease and complex-microorganism environment, the coating layer can slowly release and protect active ingredients, and the effect of preventing and treating the probiotics and the enzyme preparation is achieved. Effective content and activity during final feeding are ensured, consistent growth promotion can be kept in different varieties, weights and feeding stages, and production benefits and feeding stability are improved.

The invention discloses a method for detecting probiotics in fermented rotten vegetable feed based on the Internet of Things, and relates to the technical field of microbiological detection, and the method comprises the following steps: obtaining complete echo signal time sequence data, and carrying out high-frequency sampling on an echo signal time sequence by a sliding time window with a fixed length, and constructing a three-dimensional optical signal transient feature vector. According to the method, the transient feature vector of the three-dimensional optical signal is constructed, and a disturbance residual error and time sensitive weight mechanism is introduced, so that the abnormal disturbance of the optical signal is accurately recognized; by combining the optical interference index and the dynamic sampling window adjustment strategy, the refractive index mutation area is automatically avoided, the sensing misjudgment and data distortion are avoided, the detection stability and accuracy of the probiotic activity state in the fermentation environment are remarkably improved, and the intelligent monitoring capability of the feed quality is enhanced.

The invention provides an intelligent feed recommendation and precise feeding system based on multi-mode intelligent perception of live pigs. The system comprises a sensing module, a data processing module, a decision module and an execution module. The sensing module collects visual, sound, behavior and physiological data of live pigs, the data processing module cleans, standardizes and fuses the data, the decision module generates a feed feeding decision through a reinforcement learning algorithm, and the execution module automatically controls feeding equipment according to the decision. Data cleaning adopts different strategies to remove noise, standardization ensures compatibility of different modal data, and data fusion extracts features through a convolutional neural network and LSTM and uses a self-attention mechanism to perform weighted fusion. A reinforcement learning algorithm optimizes decisions, balances the health state, the feed utilization rate and the cost, and dynamically adjusts the feeding strategy. Through automatic whole-process management, the system can significantly improve the feed utilization rate, reduce the feed cost, improve the health condition of live pigs, and maximize the economic benefits of a farm.

The invention discloses an unconventional feed quality evaluation grading method and system, and particularly relates to the technical field of feed quality evaluation. Conventional nutrients, functional nutrients and harmful substance components are comprehensively analyzed through a high-precision detection technology; constructing a multi-factor synergistic toxicity evaluation model, quantifying the synergistic effect of the various harmful substances based on the toxicity equivalent factors and a matrix interaction analysis method, and outputting a synergistic toxicity index; the overall quality of feed samples is evaluated by combining detection results and toxicity indexes, the feed samples are classified into high-quality, qualified and unqualified grades, targeted application suggestions and risk control measures are provided, a cloud database is constructed to record evaluation data, and an Internet of Things sensor is used for monitoring supply chain quality fluctuation in real time, automatically identifying abnormities and triggering early warning. Dynamic management of feed quality is achieved, scientificity and accuracy of quality evaluation of unconventional feed are effectively improved, potential safety hazards are reduced, and safe popularization and efficient application of the system in the breeding industry are promoted.

The invention discloses a cattle and sheep farm feeding safety detection method and system based on real-time monitoring, and the method comprises the steps: installing a flow velocity sensor, a flow sensor and a pressure sensor at key positions of a feed conveying pipeline, obtaining the time sequence data of feed conveying in the pipeline, carrying out the preprocessing and feature extraction of the data, and carrying out the feature extraction of the data; and constructing a feed conveying state prediction model, performing online prediction on the conveying state in real time, and triggering early warning when the deviation between a predicted value and an actual value exceeds a threshold value. And specific abnormal types such as pipeline blockage, leakage or equipment failure can be judged by analyzing the change trend of the abnormal data. And abnormal information is pushed to operation and maintenance personnel through the mobile App to assist in quickly positioning and processing problems. According to the method, the model can be continuously optimized by using new abnormal data, the identification capability of different types of anomalies is improved, a decision basis is provided for pipeline maintenance, and the operation reliability and safety of the feed conveying pipeline are effectively improved.

Systems and methods are provided for monitoring operation of an agricultural harvesting machine, such as a forage harvester. A first sensor, operably coupled, in use, to the harvesting machine, obtains first sensor data which is indicative of a crop content measure. A second sensor, operably coupled, in use, to the harvesting machine, obtains second sensor data which is indicative of a crop size measure. A crop processing metric is calculated in dependence on the first and second sensor data and used to control operation of one or more operable components of or otherwise associated with the agricultural harvesting machine, e.g. to adjust a level of processing applied by the harvesting machine.

The invention relates to the technical field of artificial intelligence, and discloses an intelligent rationing system for pig house feed supply, which comprises the following steps: performing identity recognition on pigs in a feeding area through radio frequency identification tags, and extracting weight, growth cycle and behavior characteristics; based on historical ingestion records, health data and environmental factors, a dynamic nutritional requirement model of the pigs is constructed, and the current feed requirement is predicted in combination with a multi-factor regression algorithm; according to the feed demand result, the feeding amount and the feeding frequency of the corresponding trough are adjusted in real time; dynamically adjusting the power of a conveying motor and the pressure difference of a pipeline section by utilizing a variable-frequency driving control technology; and collecting the ingestion response and the feeding execution state of the pigs, and outputting an updated pig allocation result in combination with online feedback and historical data differences. The feeding device has the advantage that the feeding stability is improved.

The invention relates to the technical field of feed additives, and discloses a feed additive and application thereof in yak breeding. The feed additive comprises the following raw materials in parts by mass: 10-20 parts of mixed bean flour, 5-10 parts of a traditional Chinese medicine extract, 3-5 parts of lactic acid bacteria and 1-3 parts of an acid preparation. The feed additive provided by the invention significantly inhibits the expression of foot and mouth disease virus mRNA and inhibits the replication of foot and mouth disease virus; when the feed additive provided by the invention is added into daily feed for yaks, the foot-and-mouth disease of yaks can be effectively prevented and treated.

The invention relates to the technical field of dust concentration monitoring, in particular to a dust concentration monitoring method and system in a feed processing scenario, and the method comprises the steps: collecting dust concentrations and environment parameters of all preset positions at all moments in a feed processing area to form a dust concentration sequence and an environment parameter sequence; determining an environmental action index of the dust concentration at each preset position at the current moment; determining a dust smooth characteristic value of each preset position at the current moment according to the prominence degree of all the environmental parameters of each preset position at the current moment in all the preset positions and the fluctuation degree of the dust concentration sequence of each preset position in combination with the environmental action index; and monitoring the dust concentration at the current moment by utilizing the dust concentration and the dust smoothness characteristic value of each preset position at the current moment. Therefore, the accuracy of monitoring the dust concentration is improved.

The invention provides a feed fermentation parameter intelligent correction method based on the Internet of Things, and the method comprises the steps: carrying out the full-dimensional data collection from a microenvironment in a feed fermentation tank to a cross-regional macroenvironment, and generating a standardized data matrix; detecting communication time delay fluctuation characteristics based on the standardized data matrix, determining a fluctuation period and an amplitude range of a time delay abnormal point, and forming a time delay fluctuation characteristic spectrum; analyzing the influence of a raw material nutrition structure and logistics transportation time efficiency on the purity and concentration uniformity of metabolites through a regional differentiation regulation and control plan, and outputting associated feature distribution of quality control imbalance between regions; and updating an operation instruction of the feed fermentation equipment in real time according to the association feature distribution of the quality control imbalance between the regions, and obtaining equipment state operation feedback data after the operation instruction is updated.

The invention discloses a livestock and poultry precise feeding method, system and device based on image recognition, relates to the technical field of livestock and poultry breeding management, and aims to solve the technical problem that an existing livestock and poultry feeding method is low in efficiency. The method comprises the following steps: acquiring image data of a target livestock and poultry pen; based on the image data of the target livestock and poultry circle, obtaining individual information of each livestock and poultry; on the basis of the image data of the target livestock and poultry circle, carrying out feeding tracking on each livestock and poultry individual, judging whether the feeding amount of each livestock and poultry individual meets a feeding amount threshold value or not, and sending alarm information to a feeder on the basis of a judgment result; based on the image data of the target livestock and poultry pen, judging the feed allowance in each feed trough in the target livestock and poultry pen; adding the feed remaining amounts in all the feed troughs, and judging whether the total feed remaining amount is smaller than a remaining amount threshold value or not; if not, no processing is carried out; if yes, the feed adding amount in the feed trough is calculated based on the feed remaining amount in the feed trough.

The invention relates to the technical field of feed processing, in particular to an efficient energy-saving feed raw material grinding and smashing device which comprises a smashing box body, a feeding groove is formed in the top of the smashing box body, a material passing cavity is formed in the feeding groove, and the bottom of the material passing cavity communicates with a grinding and smashing cavity and a collecting cavity. A plurality of smashing assemblies are arranged on the transmission rotary drum, a plurality of collecting assemblies are arranged in the transmission rotary drum, a feeding driving assembly is arranged in the material passing cavity, an adjusting smashing assembly is arranged in the transmission rotary drum, and a screen piece adjusting assembly is arranged in the collecting cavity. And a control system is arranged in the crushing box body, judges the hardness, density and distribution uniformity of the materials according to data acquired by the acquisition assembly, controls the feeding flow of the raw materials, and dynamically adjusts the screening thickness and the crushing efficiency of the crushing assembly. According to the invention, asymmetric rotor design, dynamic airflow regulation and control and an intelligent feedback system are integrated, so that the particle sorting problem is solved, the energy consumption of crushing and grinding is reduced, and the service life of crushing hammers is prolonged.

The invention relates to the technical field of microorganisms, in particular to application of streptococcus non-lactolyticus GX-7 and a complex microbial inoculant thereof in sugarcane leaf silage, the strain GX-7 is separated from healthy pig manure by a research group, and through detection, the strain has good cholate resistance and is suitable for surviving in intestinal tracts, and the strain GX-7 has good cholate resistance and is suitable for being used as a feed additive. The antibacterial effect on pseudomonas fluorescens, listeria monocytogenes, salmonella choleraesuis and shigella flexneri is achieved; the strain has a good fermentation capability on sugarcane leaves, and the sugarcane leaves are inoculated with a complex microbial inoculant prepared from streptococcus non-lactolyticus GX-7 and streptococcus non-lactolyticus GX-2, so that a synergistic fermentation effect can be achieved; after the silage prepared from the complex microbial inoculant is fed to female buffalo in the gestation period, it is found that the silage can effectively increase the content of milk protein, milk total solids and milk non-fat solids in colostrum of the female buffalo and relieve diarrhea of the female buffalo, and the silage is safe and good.

The invention provides a feed mixing process uniformity dynamic evaluation and parameter adjustment method, and relates to the technical field of data processing, and the method comprises the steps: building a material characteristic matrix according to raw material characteristic data; correspondingly storing the material characteristic matrix and initial operation parameters of the mixing equipment to generate first mixing control data; in the mixing process, collecting local vibration amplitudes and temperature rise rates at different spatial positions, and combining the local vibration amplitudes and the temperature rise rates with the first mixing control data; calculating the vibration amplitude distribution difference in adjacent sampling periods in the feed mixing treatment process to obtain a spatial fluctuation index; when the spatial fluctuation index is continuously reduced and the temperature rise rate is periodically and suddenly increased, generating local accumulation indication data, and triggering short-time acceleration and inversion operation; executing feed mixing treatment, and generating a mixing termination signal when the spatial fluctuation index change rate of three continuous sampling periods is lower than a preset fluctuation threshold value; according to the invention, autonomy and accuracy of feed mixing uniformity adjustment are improved.

The invention discloses a ruminant feed capable of replacing soybean meal as well as a preparation method and application of the ruminant feed. The ruminant animal feed is prepared from the following raw material matrixes in parts by weight through compound probiotic fermentation: 45-55 parts of corn sugar residues, 15-25 parts of corn steep liquor, 10-20 parts of corn germ meal, 3-8 parts of extruded soybeans, 3-8 parts of corn protein powder, 2-4 parts of urea and 0.5-1.5 parts of lysine. The compound probiotics are prepared from saccharomyces cerevisiae, lactobacillus plantarum and bacillus subtilis. The invention further discloses a preparation method of the ruminant feed and application of the ruminant feed in completely replacing soybean meal in daily ration of ruminants. The ruminant feed disclosed by the invention can completely replace soybean meal in daily ration of ruminants, and even if the ruminants are in a fattening period, the soybean meal does not need to be additionally added to maintain protein supply, so that the feed cost is effectively reduced, and multiple targets of saving cost, improving efficiency and protecting environment are achieved.

The invention discloses a livestock feed proportioning method based on livestock growth, and relates to the technical field of feed proportioning, and the livestock feed proportioning method comprises the following steps: collecting the body temperature and motion track data and environmental temperature and humidity data of livestock individuals, monitoring the concentration of amino acids in digestive tracts, preprocessing the collected data, and generating a standardized biological data set; analyzing the compensation amount of vitamins and trace elements according to the metabolic fingerprint spectrum, and constructing a multi-objective optimization function in combination with an individual growth curve; solving the multi-objective optimization function through a quantum annealing algorithm, and matching local raw material inventory data of block chain evidence storage to generate an optimization strategy; and executing the optimization strategy and detecting the mixing uniformity, and when the mixing uniformity index exceeds a preset mixing uniformity threshold, starting the compensation device to adjust the optimization strategy. According to the invention, through a cooperation mechanism of dynamic nutritional requirement identification and multi-constraint optimization, the precise regulation and control capability of livestock breeding is significantly improved.

The invention relates to the technical field of cow breeding early warning, and discloses a cow breeding early warning system and method based on multi-feature fusion analysis, and the system comprises a data collection module, a feature fusion analysis module, an abnormity early warning module, a decision and suggestion module, and a breeding data display module. The feature fusion analysis module is used for analyzing the health condition, the production performance and the environmental comfort of the dairy cow based on the physiological data, the feeding data and the colony house environment data of the dairy cow; and the decision suggestion module is used for making a dairy cow breeding optimization suggestion according to the feature fusion analysis result, and the dairy cow breeding optimization suggestion comprises optimization of feed distribution and dynamic division of activity areas. The system effectively solves the problems of health management lagging, resource waste, difficulty in recognition of environmental hidden dangers, unreasonable region division and the like in traditional cow breeding, remarkably improves the intelligent level of pasture management and breeding efficiency, and has a wide application prospect.

The invention belongs to the technical field of aquaculture, and provides a feed feeding efficiency assessment method and system, and the method specifically comprises the steps: firstly, arranging a monitoring node camera in a farm, reading real-time monitoring data at a monitoring node to calculate a feeding fluctuation value, then calculating a feeding abnormal factor according to the feeding fluctuation value, and recognizing a feeding risk state; and finally, evaluating the feed feeding efficiency through the feeding risk state. The feeding abnormity is that the feeding fluctuation value of each sampling point of each monitoring node in a monitoring period is calculated, the fish feeding enthusiasm microscopic decline performance observed by each monitoring node in a long-period feeding strategy is captured, and the identified feeding risk state can more sensitively prevent the excessive feeding amount of feed; the risks of feed waste and water quality deterioration are avoided, and the feed utilization efficiency and the breeding quality under the long-period feeding strategy are improved.

A batching scale for a feed processing production line belongs to the field of feed production and comprises a weighing cylinder, a discharge conveying belt is mounted at the bottom of the weighing cylinder, and a discharge port corresponding to the discharge conveying belt is formed in the outer wall of one side of the weighing cylinder in a penetrating manner. Through cooperation of the weighing plate and the weighing sensor, the feed falls down, the weighing plate descends to measure the weight, meanwhile, the fixed rod and the pull rope drive the intercepter plate to rotate and shrink the feed port, the feed is rapidly discharged to guarantee the efficiency, the feeding speed is slowed down when the target weight is approached, the excess error is reduced, the accuracy and the efficiency are both considered, and meanwhile the intercepter plate is closed after weighing is completed. The weighing sensor sends a signal, the driving motor drives the weighing plate to turn over and discharge materials, the weighing plate ascends and resets, residues on the inner wall of the weighing cylinder are scraped during next weighing, formula mixing is prevented, in addition, during next weighing, the weighing plate descends to extrude the scraping plate, residues on the stacking surface are evenly scraped under the cooperation of the scraping knife and the sliding block, and the production efficiency is improved. The weighing and discharging total quantity accuracy of each time is ensured, and the weighing accuracy of the device is improved.

The invention relates to the technical field of artificial intelligence, and discloses a method and a system for dynamically predicting the risk of harm of feed mycotoxin to livestock and poultry. The method comprises the following steps: constructing a metabolic digital twin model based on a multi-organ coupling dynamics mechanism, connecting a gastrointestinal tract, a liver and a kidney through blood flow parameters to form a closed loop topology network, establishing a toxin migration rate equation, and verifying bioavailability; collecting feed toxin concentration and livestock and poultry physiological data in real time; after distributing the initial toxin load, iteratively generating target organ dynamic concentration distribution by adopting a Runge-Kutta method; an organ exposure index is calculated based on an organ specific hazard threshold, key organs are positioned, and low / high risk levels and toxin accumulation paths are output. The method solves the problems that a traditional static model is low in efficiency and poor in organ difference adaptability when being used for dynamically predicting the risk of harm to livestock and poultry caused by feed mycotoxin.

The invention relates to the technical field of data processing, in particular to a sheep house-oriented environmental data monitoring method, device and system, and the method comprises the steps: obtaining a feed consumption sequence, an environmental temperature sequence, an infrared image data set and an ammonia concentration sequence of a plurality of historical excrement cleaning periods of a sheep house; the feed consumption degree of the sheep house at the latest moment in the latest excrement cleaning period is obtained; obtaining the influence degree of the temperature on the ammonia gas concentration value at the latest moment; the environment temperature fluctuation degree of the sheep house at the latest moment is obtained; according to the influence degree, the environment temperature fluctuation degree, the current ammonia concentration sequence and the stable class cluster, the real ammonia concentration value of the sheep house at the latest moment is obtained. Under the condition that the ammonia concentration of the sheep house is influenced by the environment temperature, the excrement accumulation amount of the sheep house can be accurately judged, excrement in the sheep house can be cleaned in time, and a proper breeding environment is created for the sheep house.

The invention discloses a feed proportion abnormity identification method and system, and particularly relates to the field of feed proportion abnormity identification, and the method comprises the steps: extracting the disturbance variables of vibration amplitude, feeding speed and voiceprint waveform in multi-source disturbance data, constructing the disturbance time sequence expression of a frequency, form and amplitude triple feature structure, and carrying out the recognition of the vibration amplitude, the feeding speed and the voiceprint waveform. Extracting a disturbance characteristic track with center characterization capability in a cluster through atlas clustering, and writing the disturbance characteristic track into a track benchmark expression library; constructing an aligned trajectory expression set by analyzing the frequency domain structure and the time slice expression of each channel signal in the current batch of disturbance data and combining the binding relationship between the batch number and the formula number; by constructing an offset matching and track consistency judgment mechanism based on multi-source disturbance track expression, structured recognition and path logic verification of a formula drift phenomenon are realized, and the problem that the actual feed nutrition state is misjudged due to the fact that real proportion offset caused by residual feed cannot be recognized is solved.

The invention relates to the field of microbial fermented feed, in particular to bamboo powder fermented feed rich in amino acid and a preparation method thereof. According to the preparation method of the bamboo powder fermented feed provided by the invention, bamboo is used as a base material for fermentation and enzymolysis to prepare amino acid, and then some conventional raw material components of the feed are added to prepare the bamboo powder fermented feed rich in amino acid. The digestibility and the nutrition utilization rate of animals on the feed are higher, the oxidation resistance is stronger, and the palatability is better.

The invention provides a method and system for predicting the utilization rate of feed amino acid in multiple stages of laying hens, and relates to the field of bioinformatics, and the method comprises the following steps: obtaining chemical component measured values of feed raw material samples in different growth stages of the laying hens and in-vivo measured values of standard ileum amino acid digestibility; performing predictive factor screening according to the chemical component measured value and the standard ileum amino acid digestibility in-vivo measured value to obtain a predictive factor combination; constructing a prediction model according to the prediction factor combination to obtain a candidate prediction equation; optimizing according to the candidate prediction equation, and screening to obtain an optimized equation; performing model verification according to the optimization equation to obtain a target prediction model; and performing digestibility prediction according to the target prediction model to obtain a predicted standard ileum amino acid digestibility value. According to the method, the standard ileum amino acid digestibility is accurately predicted based on in-vitro detection data, and the limitation of a traditional in-vivo determination method is effectively overcome.

The invention discloses a microbial compound feed additive, which is prepared from the following ingredients in parts by weight: 35 to 45 parts of traditional Chinese medicine residues, 25 to 35 parts of soybean meal, 15 to 25 parts of bran, 8 to 12 parts of corn flour, 0.3 to 0.7 part of selenium-enriched yeast, 8 to 12 parts of aspergillus niger spore powder, 10 to 15 parts of bacillus subtilis, 6 to 9 parts of lactobacillus plantarum and 5 to 8 parts of candida utilis. The invention relates to the technical field of feed additives, through the synergistic effect of the aspergillus niger, the bacillus subtilis, the lactobacillus plantarum and the candida utilis, the aspergillus niger can generate various enzymes, and decomposition of raw materials and release of nutritional ingredients are facilitated; the bacillus subtilis can enhance the immunity of livestock and poultry and inhibit the growth of harmful bacteria; lactobacillus plantarum can regulate intestinal microecological balance and promote digestion and absorption; candida utilis is rich in protein and vitamins and provides nutrition for livestock and poultry, the four components cooperate with each other, the function limitation of a single strain is broken through, and the health level and production performance of livestock and poultry are comprehensively improved.

The invention relates to the technical field of feed quality control, in particular to an intelligent feed processing quality control method and system. According to the method, the operation parameters and the environment temperature and humidity of the production equipment are acquired in real time, and the environment and equipment state parameter set is established, so that the influence factors of the production conditions are quantified, and an accurate basis is provided for parameter adjustment of the subsequent processing flow. In the production process, the adaptive processing flow threshold value is calculated based on the operation stability of equipment and the change trend of raw material components, and unstable product quality caused by raw material fluctuation or equipment state change is avoided. And whether key indexes in the production process are in an adaptive range or not is dynamically judged by combining the change conditions of the steam absorption rate and the granulation pressure, so that the processing flow control is finer. For trend deviation possibly occurring in the production process, the stability of the production process is analyzed by analyzing the equipment load level, the energy consumption change synchronism and the abnormal trend of processing flow parameters.