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CannaForge is a curated, hand-vetted cannabis genetics platform — verified breeders, managed onboarding, and platform-supported fulfillment. By entering, you confirm you are of legal age in your jurisdiction. Seeds are sold for collection where germination is restricted by local law.

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Aroma · 0 strainsnoindexed

Quantitative Trait Loci

Quantitative Trait Loci (QTL) refers to genomic regions that influence the expression of quantitative traits—characteristics controlled by multiple genes rather than a single locus. In cannabis, aroma profiles are polygenic: terpene ratios, volatile compound diversity, and overall scent intensity result from additive effects across numerous QTL segments. Breeders cannot predict exact aroma outcomes from simple Mendelian inheritance because environmental factors (soil, light, temperature, harvest timing) interact with these genetic regions to shape final phenotype. QTL mapping studies help researchers identify chromosome segments associated with aromatic compound production, informing selection strategies.

Lineage Atlas · 0 records

Quantitative Trait Loci strains

No strains tagged into Quantitative Trait Loci yet — they'll appear here as breeders submit lineage records under this aroma.

About Quantitative Trait Loci

Quantitative Trait Loci (QTL) refers to genomic regions that influence the expression of quantitative traits—characteristics controlled by multiple genes rather than a single locus. In cannabis, aroma profiles are polygenic: terpene ratios, volatile compound diversity, and overall scent intensity result from additive effects across numerous QTL segments. Breeders cannot predict exact aroma outcomes from simple Mendelian inheritance because environmental factors (soil, light, temperature, harvest timing) interact with these genetic regions to shape final phenotype. QTL mapping studies help researchers identify chromosome segments associated with aromatic compound production, informing selection strategies.

Breeder relevance

Breeders working with complex aroma goals use QTL data to design crosses that stack favorable genomic regions, increasing the probability of desired terpene expression. This approach is more effective than single-gene selection for multifaceted traits like balanced citrus-floral-spice profiles.

Educational reference · Cultivar metadata only · No medical claims