Research-Grade XLSForms, Ready for Deployment.

'- Compute liquidity ratio (% of cash available vs obligations) - Assess ability to pay farmers on time - Identify main sources of cash

- 1. Waste-behavior linkages - Overbuying - Overcooking - Poor planning - Storage problems - 2. Food category patterns

- Supplier Identification: Capture the supplier’s name and primary contact person for reference and accountability. - Supplier Location: Record the geographic location of the supplier for mapping and spatial analysis. - Products Supplied: Identify the types of products provided by the supplier. - Performance Ratings: Assess supplier performance on product quality, delivery timeliness, and communication using a 1-5 scale. - Contract Compliance: Confirm whether the supplier complies with agreed contractual terms. - Environmental & Social Compliance: Track compliance with environmental standards and social safeguards (e.g., child labor, worker safety).

'- Multi-product repeat captures detailed information per adulterated product - Risk score combines severity and frequency automatically - Priority category ranks products for intervention - Overall risk index aggregates risk across all products for the respondent - Conditional questions appear only if the respondent is aware of adulteration - Dashboard-ready and ready for Kobo/ODK analytics

- Target users: Veterinarians, Quality Auditors, Lab Technicians - Multi-batch & multi-storage: Tracks multiple batches and storage conditions per product - Weighted stability scoring: 0-10 score accounting for storage condition and spoilage indicators - Low stability follow-ups: Conditional fields triggered for scores <4 - Detailed metadata: Product type, batch size, storage conditions, sensory/microbial observations - Key measures: Days to spoilage, sensory changes, microbial growth

'- Multi-Actor Adaptability: The form uses relevance logic to skip purchase-cost questions for 'Farmers', while capturing them for all other intermediaries. - Real-Time Profitability: Automatically calculates Gross Revenue, Gross Profit per unit, and Net Monthly Profit, allowing the interviewer to verify economic viability on-site. - Standardized Cost Categories: Breaks down operating expenses into Transport, Labor, and Packaging to facilitate cross-actor comparisons of cost structures. - Constraint Ranking: Limits bottleneck selection to the top 3 items to force prioritization, ensuring the data is "analysis-ready" for identifying systemic leverage points. - Unit-Based Financial Logic: Ensures selling price is logically consistent with purchase price via constraints, preventing data entry errors at the source.

'- Standardized Coding: Implements the CIAT/CRS SSSA coding system (1-10 for sources, B-K for acquisition) to ensure data compatibility with global seed security databases. - Dynamic Crop Repeats: Allows enumerators to capture an unlimited number of crops per farmer while maintaining individual data points for quantity and quality per crop. - Seed Security Scoring: Automates a security score based on seed source reliability, differentiating between self-saved seeds, market-purchased seeds, and aid-dependency. - Logical Skip Patterns: Conditional logic ensures that detailed "Seed Aid" and "New Variety" questions only appear if the respondent confirms participation. - Integrated Demographics: Captures critical cross-analysis data such as gender of household head and cultivation area to identify vulnerable farming segments.

'- Farmer and Field Identification: Enables unique identification of farmers and individual fields to support traceability and longitudinal soil monitoring. - Georeferenced Field Data Collection: Captures GPS coordinates and soil texture to accurately locate fields and characterize baseline soil conditions. - Comprehensive Soil Test Recording: Collects key soil fertility parameters including pH, nitrogen, phosphorus, potassium, and organic matter. - Built-in Data Validation: Ensures data quality through required fields and value constraints, reducing errors during field data collection. - Automated Soil Health Classification: Automatically categorizes soil pH and organic matter levels into actionable classes (e.g., Acidic, Neutral, Low, Medium). - Instant Interpretation for Decision Support: Displays calculated soil condition notes to help extension agents and farmers quickly interpret results.

'- GPS-based route segmentation - Time-stamped temperature & humidity logs - Door-open events - Cooling system diagnostics - Shock/vibration monitoring (optional) - Alerts when temperature exceeds thresholds

'- Basic knowledge assessment - Attitudes toward healthy foods - Simple dietary practices monitoring - Easy summary statistics (frequency tables, cross-tabs)

'- Target Audience: Public health researchers, NGOs, government staff, community health workers - Global Scope: Includes all countries worldwide - Sections: Household info, Water Access, Sanitation Facilities, Hygiene Practices - Dynamic Relevance: Child faeces disposal questions only for households with children <5 - Data Quality: Constraints on numeric fields, required fields for critical data - Analysis Ready: Numeric and coded categorical data for statistical analysis