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Genetics Engine

The core computational logic of BijMantra revolves around tracking lineage and phenotypic expression over multi-generational crosses.

The Challenge​

Modern genetic breeding results in exponential combinatorial data. A single "seed" plot may contain 1,000 plants, each individually sampled, crossed, and harvested.

How do we represent this deep lineage in a browser-based application without exhausting client-side memory, overloading network payloads, or making field workflows fragile under weak connectivity?

Data Modeling Strategy (Draft)​

The system currently attempts to model this using Directed Acyclic Graphs (DAGs), where:

  • Nodes = Unique Germplasm IDs or Seed Batches.
  • Edges = Breeding actions (Crosses, Self-pollinations, Selections).

Seeking Geneticists​

We require professional breeders and computational geneticists to actively review our BrAPI compatibility mapping. We must ensure the graph algorithms we build locally can synchronize effectively with global pedigree databases.