Add Trait Observation Data crop_trait_observation_data Directly from the Inventory Screen

Good afternoon @mobreza

The proposal is to streamline the entry of crop_trait_observation_data by enabling their direct registration through the TraitData tab within the inventory detail view. This enhancement is specifically designed to expedite the recording of observations made in controlled environments, such as laboratories.

Current Situation: Currently, recording phenotypic characterization data in GGCE is primarily handled through specialized mobile applications, such as RyM (CIAT's internal app) and FieldBook.

While this workflow is highly efficient for large-scale field trials, it is impractical and inefficient for observations made directly on a specific inventory item in a laboratory. For example:

• Seed quality analysis (germination, weight, etc.).
• Biochemical characterization.
• Pathology evaluations under controlled conditions.

Functionality:

• New Interface: Within the detail view of an inventory, utilize the TraitData tab for this functionality.
• Input Form: In this tab, include a simple form to add a new observation, containing:

1. A selector for the crop being evaluated. This is the first and a crucial step, as the same trait name (e.g., grow_habit) can exist for different crops.
2. A table or list to select the trait to evaluate. Important: This list must only display traits crop_trait that are associated with the crop.
3. A field to enter the observation value (numeric or text, depending on the trait's definition).
4. A selector for the method used (listing from method). This field is mandatory.
5. A "Save" or "Add Observation" button.

• Data Display: Below the form, display a table with all observations already recorded for that inventory, allowing for a quick view of its characterization history.

Implementation Benefits

• Efficiency and Agility: Radically simplifies the workflow for lab personnel.
• Error Reduction: Direct entry and trait filtering by crop eliminate formatting risks and prevent the recording of irrelevant data.
• Data Integrity and Control: Ensures that all characterization information is processed through the GGCE application's business logic and validations, guaranteeing data quality and integrity.
• Improved User Experience (UX): Makes GGCE a more complete, intelligent, and intuitive tool.

Additional Observation:

• UX Justification: It must be emphasized that the current workflow within GGCE for recording a single lab observation is notably inefficient. The process requires an extensive and impractical sequence of steps, resulting in a poor user experience (UX).
• Data Types for Traits: A specific input format for traits that are dates (e.g., sowing_date) must be implemented. Using a calendar picker instead of an open text field is crucial to prevent formatting errors and ensure data consistency.

Sketch examples:

Regrads: JamesArias