CN-122018596-A - Fresh milk pre-fermentation flavor regulation and control and multi-temperature-zone collaborative distribution method and system

CN122018596ACN 122018596 ACN122018596 ACN 122018596ACN-122018596-A

Abstract

The application provides a method and a system for regulating and controlling the pre-fermentation flavor of fresh milk and cooperatively distributing the fresh milk in a multi-temperature zone, belongs to the technical field of intelligent control of food supply chains, and is used for solving the problem that the flavor quality is unstable after distribution due to control dislocation of production and logistics links in a traditional fresh milk supply chain in the related technology. The method maps the state of the whole supply chain from production to distribution of fresh milk to a high-dimensional statistical manifold in a unified way, updates the manifold geometric structure through online learning, calculates an optimal geodesic line for connecting the current state with the target state, and further cooperatively regulates and controls the physical field of the production end and the temperature control field of the distribution end to guide the system to evolve along an optimal path. The system comprises a corresponding holographic sensing layer, a field regulation and control execution layer and a calculation layer. The application realizes the dynamic integrated collaborative optimization of fresh milk flavor formation and logistics environment, and ensures the flavor and taste of the end product.

Inventors

ZHAN JIAWEI
WU NANA
LIU HANG
LIN QIN
MA LE

Assignees

北京新鲜晨配科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260203

Claims (10)

1. A method for regulating and controlling the pre-fermentation flavor of fresh milk and cooperatively distributing the fresh milk in a multi-temperature zone is characterized by comprising the following steps: the method comprises the steps of uniformly mapping the state of a full supply chain of fresh milk from production to distribution to points on a high-dimensional statistical manifold for representation; updating the geometry of the high-dimensional statistical manifold based on real-time perceptual data, the geometry characterized by a degree gauge tensor and affine contact; calculating an optimal geodesic between a point on the connection manifold representing the current supply chain state and a point or region representing the target supply chain state, the optimal geodesic being defined by the affine contact; the geometric structure of the high-dimensional statistical manifold is changed by regulating and controlling a physical field acting on the fresh milk production process and a temperature control field acting on the distribution process so as to guide the actual evolution track of the supply chain system.
2. The method of claim 1, wherein mapping the full supply chain status of fresh milk from production to distribution to points on a high-dimensional statistical manifold comprises: Acquiring microbial metabolism status data from a production process and multi-physical field data from a distribution process; respectively converting the microorganism metabolism state data and the multi-physical field data into corresponding probability distribution representations; Mapping the transformed probability distribution representation to a unified hidden space by an encoder, and constructing the hidden space into the high-dimensional statistical manifold.
3. The method of claim 2, wherein the updating the geometry of the high-dimensional statistical manifold based on real-time perceptual data comprises: the parameters of the encoder are adjusted on line through neural manifold learning by utilizing the sensing data stream acquired in real time; And updating the degree gauge tensor of the hidden space through a pull-back mapping according to the adjusted encoder, so as to update the geometric structure of the high-dimensional statistical manifold.
4. The method of claim 1, wherein the affine contact is decomposed into a production contact component, a logistic contact component, and a coupling contact component; wherein the coupling connection component is described by a canonical field for characterizing dynamic interactions between the production process and the logistics process; The geometric structure of the high-dimensional statistical manifold is changed by regulating and controlling a physical field and a temperature control field, and the affine communication is changed by regulating and controlling parameters of the physical field and the temperature control field.
5. The method of claim 1, further comprising the step of state verification and repair: The sensor network deployed in the production and distribution link is regarded as a discretization boundary of the high-dimensional statistical manifold; Calculating a correlation function between sensor data on the boundary, and verifying whether the correlation function meets a preset constraint equation set; if the verification is not satisfied, repairing the internal geometry of the high-dimensional statistical manifold by adjusting the control parameters on the boundary.
6. The method of claim 5, wherein repairing the internal geometry by adjusting control parameters on the boundary comprises: identifying boundary variables that cause the constraint equation set to be violated; And introducing corresponding adjustment items into the boundary system model and optimizing coefficients of the adjustment items to enable a new boundary correlation function to satisfy the constraint equation set again.
7. The method of claim 1, wherein the modulating the physical field acting on the fresh milk production process comprises applying programmable multiphysics to the fermentation system to form a spatial interference pattern to modulate the metabolic activity profile of the microflora.
8. The method of claim 1, wherein the regulating the temperature control field that acts on the dispensing process comprises: A temperature control unit having anisotropic thermal conductivity characteristics within the dispensing container is controlled to form a non-reciprocal heat flow path within the container to construct a desired dynamic temperature field profile.
9. The method of claim 1, wherein the real-time sensory data comprises a first type of data reflecting microbial quantum coherence, a second type of imaging data reflecting spatial distribution of microscopic dielectric properties of the fresh milk, and a third type of sensory data reflecting spatial distribution of multiple physical fields within the dispensing container.
10. A fresh milk pre-fermentation flavour modulating and multi-temperature zone co-dispensing system for performing the method according to any one of claims 1 to 9, characterized in that the system comprises: the holographic sensing layer comprises a first sensing unit for acquiring the first type of data, a second imaging unit for acquiring the second type of imaging data and a third distributed sensing unit for acquiring the third type of sensing data; The field regulation and control execution layer comprises a multi-physical field modulation unit which is arranged in the fermentation system and used for generating a programmable space interference pattern, and a temperature control unit which is arranged in the distribution container and used for realizing a non-reciprocal heat flow path; And the calculation layer is used for constructing and updating the high-dimensional statistical manifold, calculating the optimal geodesic and generating a regulation and control instruction for the field regulation and control execution layer.

Description

Fresh milk pre-fermentation flavor regulation and control and multi-temperature-zone collaborative distribution method and system Technical Field The application relates to the technical field of intelligent control of food supply chains, in particular to a method and a system for regulating and controlling the pre-fermentation flavor of fresh milk and cooperatively distributing the fresh milk in multiple temperature areas. Background With the continuous improvement of the requirements of consumers on the freshness and the flavor of foods with short shelf life such as fresh milk, how to ensure the stable quality of the foods from production to consumption becomes an industry key challenge. The flavor formation of fresh milk depends on the biochemical process of the fermentation of probiotics at the production end, and the quality maintenance of the fresh milk in the distribution link is strictly limited by the temperature environment at the logistics end. These two links traditionally belong to different management systems, and natural fracture exists in the control objective and execution logic. The prior art focuses on optimization of a single link. In the production link, the flavor is controlled mainly by adjusting fermentation process parameters, and in the logistics link, constant low temperature is maintained mainly by a cold chain technology. However, these methods often consider fresh milk as a static, passive cargo, ignoring its nature as an active system that continues to undergo biochemical reactions. The pre-fermented fresh milk is still in a slow post-ripening stage in the delivery process, and the flavor substance composition and the pH value of the pre-fermented fresh milk continuously change and are extremely sensitive to temperature. The main disadvantage of the prior art is the disjointing of production and logistics control. The static and constant dispensing temperature control strategy cannot adapt to the dynamic biochemical state change of fresh milk in the way, and post acidification is easy to cause or flavor development is insufficient. Meanwhile, the traditional method lacks unified modeling and real-time perception capability of the state of the full supply chain, and cannot dynamically adjust the control strategy according to actual quality evolution, so that consistency of flavor and mouthfeel after long-distance distribution is difficult to ensure. Therefore, an intelligent solution capable of penetrating through production and logistics links and realizing dynamic sensing and cooperative regulation and control on the active state of fresh milk is needed. Disclosure of Invention The application provides a method and a system for regulating and controlling the pre-fermentation flavor of fresh milk and cooperatively distributing the fresh milk in multiple temperature areas, which can dynamically represent and cooperatively optimize the whole process state of the fresh milk from fermentation to distribution by a unified mathematical model, thereby solving the problem of flavor quality fluctuation caused by disjoint production and logistics control. In a first aspect, the application provides a method for regulating and controlling the pre-fermentation flavor of fresh milk and cooperatively distributing the fresh milk in multiple temperature zones. The method comprises the following steps of mapping fresh milk from production to distribution to points on a high-dimensional statistical manifold in a unified mode to represent, updating the geometric structure of the high-dimensional statistical manifold based on real-time perception data, wherein the geometric structure is characterized by a degree rule tensor and affine connection, calculating an optimal geodesic line between the point representing the current supply chain state and the point or area representing the target supply chain state on the connecting manifold, wherein the optimal geodesic line is defined by the affine connection, and changing the geometric structure of the high-dimensional statistical manifold by regulating and controlling a physical field acting on a fresh milk production process and a temperature control field acting on the distribution process so as to guide the actual evolution track of a supply chain system. By adopting the technical scheme, the application creatively abstracts complex biochemical and physical processes into geometric evolution problems on high-dimensional manifold. The optimal geodesic line connecting the current state and the target state is calculated and tracked, so that accurate and globally optimal dynamic track planning is provided for cooperative control of production and logistics, and the fundamental transition from static segmentation control to dynamic integrated optimization is realized. Further, the point of mapping the full supply chain state of the fresh milk from production to distribution onto the high-dimensional statistical manifold comprises the steps of acquirin