What the Data for This Category Looks Like
Data related to livestock and poultry farming yield rates comes primarily from the Ministry of Agriculture and Rural Affairs Livestock Production Monitoring Platform, daily reported data from local livestock technology promotion stations, and internal production ledgers of large-scale breeding entities. Full data from the previous day is synced at fixed daily intervals. Most data documents use structured JSON or CSV formats, with the following core fields: livestock inventory (unit: head), average slaughter weight (unit: kilogram), total feed consumption (unit: kilogram), average purchase price per slaughtered animal (unit: yuan/kg), unit breeding cost (unit: yuan/head), and breeding cycle days (unit: day).
Constraints Imposed on Workflow Orchestration
The daily data update schedule requires a daily scheduled trigger node to avoid duplicate data pulls or missed daily data. The structured multi-field format requires a field mapping node to align raw data fields from different sources to standardized yield calculation fields. Multi-source data aggregation requirements add a data validation node to filter records with missing core fields. Unit differences in breeding data require a unit conversion node to ensure consistency across calculation logic.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Scheduled Trigger Cycle | Daily 06:00 | Matches the fixed daily sync window of Ministry of Agriculture and Rural Affairs monitoring data |
HTTP Request Timeout | 300 seconds | Aligns with the interface response delay characteristics of agricultural data platforms |
Field Mapping Rule | Align source field names to standardized yield calculation fields | Resolves field naming differences across data sources |
Null Value Filter Strategy | Skip records with missing core fields | Prevents yield calculation errors caused by incomplete data |
Matcher Matching Mode | Contains | Fits scenarios where yield broadcast text contains multiple key segments |
Global Variable Scope | Single-session isolation | Prevents variable conflicts across multiple parallel requests |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: When using
equalsorstarts withas the matcher matching rule, all yield broadcast content triggers the ELSE branch. Cause: The multi-segment structure of livestock and poultry broadcast text is not matched, onlycontainsorends withcan cover complete market and yield information. - Phenomenon: Livestock and poultry data pulled via HTTP cannot be correctly passed to the AI node. Cause: The
response.bodyfield of the HTTP response is not correctly mapped to the AI input parameter, and a non-isolated global variable is mistakenly used as a transit carrier. - Phenomenon: Empty field errors occur after workflow execution. Cause: No null value filter strategy is configured, and raw data with missing core fields is directly used for yield calculation.
How to Verify Correct Configuration
- Manually trigger the workflow once, check the return logs of the HTTP node, confirm that the pulled fields match the configured mapping rules.
- Submit test data with missing fields, check if the workflow triggers the null value filter logic, confirm that the filter strategy is active.
- Simulate multiple parallel requests, check if global variables have cross-session contamination, confirm that the scope configuration is correct.
- Adjust the scheduled trigger time to a non-sync window, check if the workflow executes according to the configured cycle, confirm that the scheduled task is active.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.