CN-121997287-A - Forage grass drying evaluation method and system based on multi-mode fusion

CN121997287ACN 121997287 ACN121997287 ACN 121997287ACN-121997287-A

Abstract

The invention relates to the technical field of forage drying evaluation, and particularly discloses a forage drying evaluation method and a forage drying evaluation system based on multi-mode fusion. According to the method, quality files containing indexes such as moisture content, dry matter content and dryness level are established for each batch of forage grass, feed intake behavior and production performance data of cattle groups are synchronously collected during feeding, a multi-mode association data set is established by taking batch identification and time stamps as association keys, and further correlation analysis, regression analysis and statistical significance inspection are adopted to obtain feed intake performance and production performance response results corresponding to different drying characteristics, and accordingly forage grass drying evaluation standards are dynamically corrected. According to the invention, the forage grass drying characteristic data and the cattle group feed intake, feeding behavior and production performance data are correlated according to batches and time to construct a multi-mode correlation data set, so that a direct corresponding relation between the forage grass drying state and the actual feeding behavior and growth effect of the cattle group is realized.

Inventors

FAN QINGSHAN
BAI JIE
LU JUNMIN
Jiao ting
ZHAO SHENGGUO

Assignees

甘肃农业大学

Dates

Publication Date: 20260508
Application Date: 20260410

Claims (10)

1. The forage grass drying evaluation method based on the multi-mode fusion is characterized by comprising the following steps of: S1, distributing unique batch identification for each batch of forage grass, establishing a forage grass quality file, and collecting and recording drying characteristic data of the forage grass, wherein the drying characteristic data comprise, but are not limited to, moisture content, dry matter content, dryness level and drying uniformity index, and are associated with time information and batch identification of the forage grass; S2, during the batch feeding of the forage grass, carrying out breeding data acquisition on the target cattle group, wherein the breeding data at least comprise at least two types of feed intake data, feed intake behavior data and production performance data; S3, based on the batch identification and the time stamp, correlating the forage quality file with the breeding data to construct a multi-mode correlation data set between forage drying characteristics and cattle farm breeding performance; S4, analyzing the multi-mode associated data set to obtain feeding performance and production performance response results corresponding to different forage grass drying characteristics; S5, comprehensively judging the forage drying evaluation result according to the feeding performance and the production performance response result, and dynamically correcting the forage drying evaluation standard according to the forage drying evaluation result so that the corrected forage drying evaluation standard can reflect the actual feeding effect and the production performance of the cattle group.
2. The method of claim 1 wherein in step S1, the forage quality profile further includes forage grass seed information, source plot information, and sampling point information for characterizing consistency of dryness in the same forage grass batch.
3. The method of claim 1 wherein in step S2, the feed intake data includes total feed intake of a batch of forage grass in a preset time period and feed intake rate per unit time, and the feed intake rate is obtained in real time by a feeding device or a trough weighing device provided with a weighing sensor and mapped with a batch identifier.
4. The forage grass dryness assessment method based on multi-modal fusion of claim 1, wherein in step S2, the feeding performance data includes at least one of a feeding performance level, a rumination time, a chewing frequency, and a pickout performance characteristic of the herd, wherein at least a portion of the feeding performance data is acquired by a collar performance sensor and/or a camera image recognition device worn by the herd.
5. The method of claim 1 wherein in step S2, the performance data includes Average Daily Gain (ADG) of the herd during the corresponding forage feeding stage, and further includes health indicators for characterizing adverse effects.
6. The fodder drying evaluation method based on multi-modal fusion according to claim 1 wherein in step S4 the analysis of the multi-modal associated dataset comprises a correlation analysis and/or regression analysis of fodder drying characteristics with feed intake, feeding behaviour and production performance to determine the corresponding cultivation performance differences for different drying characteristic intervals.
7. The method of claim 1, wherein in step S5, the dynamic modification of the fodder dryness assessment criteria comprises: Based on forage grass drying characteristics of increased feed intake of the herd, improved production performance and no abnormal healthy reaction, marking the corresponding drying characteristics as high-quality drying standards; Based on forage grass drying characteristics of reduced feed intake or reduced productivity of the herd, the corresponding drying characteristics are marked as inferior drying standards.
8. The method of claim 7 wherein the dynamically modified forage dryness assessment criteria are differentially set according to herd type, forage breed or breeding stage for guiding group feeding, forage prioritization or optimization of forage processing objectives.
9. A fodder dryness assessment system based on multi-modal fusion, comprising: The forage grass data acquisition module is used for acquiring the drying characteristic data of the forage grass batch and generating a forage grass quality file; The breeding data acquisition module is used for acquiring feed intake data, feed intake behavior data and production performance data of the corresponding cattle group during the batch feeding period of the forage grass; The data association module is used for associating the forage quality file with the cultivation data in batches and time alignment based on the time stamp and the forage batch identification, and constructing a multi-mode association data set; The data storage module is used for storing the original data, the processed data and the evaluation result by taking the batch identification as an index and supporting version control; The analysis and evaluation module is used for analyzing the multi-mode association data set to obtain feeding performance and production performance response results corresponding to forage grass drying characteristics; And the standard correction module is used for dynamically updating the forage drying evaluation standard according to the output result of the analysis evaluation module, and transmitting the updated result to the pasture management system or the display interface through the decision output interface.
10. The fodder drying evaluation system based on multi-modal fusion of claim 9, wherein the analysis evaluation module comprises a multi-modal fusion analysis unit for comprehensively utilizing fodder drying characteristic data, feed intake data, feeding behavior data and production performance data, comprehensively evaluating fodder drying state by adopting correlation analysis, regression analysis and statistical significance test flow, and outputting palatability evaluation results and confidence or uncertainty indexes.

Description

Forage grass drying evaluation method and system based on multi-mode fusion Technical Field The invention belongs to the technical field of forage drying evaluation, and particularly relates to a forage drying evaluation method and a forage drying evaluation system based on multi-mode fusion. Background In the cultivation process of red cattle in Gansu Pingliang areas, scientific feeding management technology is implemented, and at present, the whole plant silage of corn is recommended to be fed to a cultivation farm, and the dryness of forage grass is an important factor affecting the storage safety and the utilization effect of the forage grass. In the prior art, forage grass drying evaluation usually takes the moisture content or the dry matter content as a main evaluation index, and a unified drying qualification standard is set according to the moisture content or the dry matter content. The retrieval publication No. CN121336932A discloses a non-conventional feed quality assessment method and system, which comprises the following steps of establishing a multidimensional sensing monitoring base line in the high-temperature drying treatment process of feed, continuously acquiring mercury vapor concentration gradient, water evaporation rate and air flow speed field data in a feed drying environment to form a time sequence feature set reflecting mercury evaporation dynamic change, constructing a gas-solid phase interaction analysis model by utilizing the time sequence feature set, and carrying out coupling analysis on mercury vapor migration tracks and temperature distribution and humidity distribution on the surfaces of feed particles to generate a spatial distribution data set representing spatial distribution features of a mercury vapor redeposition area. However, the inventor finds that the forage grass drying evaluation mode based on the single physical index still has the following defects in the actual cultivation production process: The forage grass drying evaluation result is lack of correlation with the actual feeding performance of the cattle group, the prior art only focuses on the physical drying state of forage grass, the feeding behavior difference of the cattle group on forage grass with different drying degrees is not considered, and the conditions that the drying index is qualified, the feeding amount of the cattle group is low and the feeding is serious are easy to occur. The data are split between the drying evaluation and the production performance, and the prior art does not carry out correlation analysis on the forage grass drying evaluation result and the production performance indexes such as average daily gain, health state and the like of the cattle group, so that the forage grass quality evaluation cannot reflect the real cultivation effect. The fixed drying standard is easy to cause excessive drying and energy waste, and under the condition of lacking a feedback mechanism, excessive drying or drying of forage grass is often required to meet the traditional drying standard, so that the energy consumption cost is increased, and the palatability of the forage grass is possibly reduced. Therefore, a need exists for a forage drying evaluation method that can comprehensively analyze forage drying characteristics and feeding behavior and production performance of a herd, so as to overcome the problem of data islanding in the prior art. Disclosure of Invention The invention aims to provide a forage grass drying evaluation method and a forage grass drying evaluation system based on multi-mode fusion, which are used for solving the problem that the existing forage grass drying evaluation in the background technology is only based on physical drying indexes, cannot reflect the actual feeding behavior and production performance of cattle groups, and causes the disjoint of the drying evaluation result, the actual palatability and the cultivation effect. In order to achieve the above purpose, the invention provides a forage grass drying evaluation method based on multi-mode fusion, which comprises the following steps: S1, distributing unique batch identification for each batch of forage grass, establishing a forage grass quality file, and collecting and recording drying characteristic data of the forage grass, wherein the drying characteristic data comprise, but are not limited to, moisture content, dry matter content, dryness level and drying uniformity index, and are associated with time information and batch identification of the forage grass; S2, during the batch feeding of the forage grass, carrying out breeding data acquisition on the target cattle group, wherein the breeding data at least comprise at least two types of feed intake data, feed intake behavior data and production performance data; S3, based on the batch identification and the time stamp, correlating the forage quality file with the breeding data to construct a multi-mode correlation data set between forage drying charact