The Hidden Genome
A Field Atlas of Predicted Recessive Phenotypes in Forty Cannabis Cultivars
Dieses E-Book erfüllt die Standards zur Barrierefreiheit und ist mit unterstützenden Technologien kompatibel. Die Einhaltung der Barrierefreiheit wird vom Herausgeber und Urheber festgelegt.
The Hidden Genome Atlas is a field reference for cannabis breeders working with reverse selection — the discipline of recovering recessive phenotypes from inside fixed modern gene pools. Forty cultivars are catalogued in single-page reference format: Afghani #1, OG Kush, Sour Diesel, White Widow, Wedding Cake, Gelato, Durban Poison, Chocolate Thai, and thirty-two others.Each cultivar page predicts the recessive phenotypes lying dormant within that line's genome. For each predicted recessive — over 280 entries across the volume — the atlas names the hidden aromatic direction (tropical fruit, lavender floral, OG fuel, anise-licorice, sandalwood, frankincense, cardamom, eucalyptus, and many more), provides a brief sensory profile, estimates the prevalence at which the recessive surfaces in unselected seedling populations, identifies the ancestral source of the recessive allele, and specifies the leaf-morphological markers that flag candidate plants at the seedling stage.The atlas is organized in six sections: Indica IBLs, Classic Hybrids, OG/Chem/Diesel, Cookies/Gelato/Cake, Fruit and Berry Hybrids, and Sativas and Heritage Lines.A companion reference to Against the Grain: The Reverse Selection Cookbook, this volume distills the predictive layer of reverse selection into single-page, scan-friendly format. Every dominant phenotype is the average of its allele pool. The recessives are the outliers. This atlas tells you which outliers to expect in forty of the most-grown lines in modern cannabis.For working breeders, advanced cultivators, plant geneticists, and reverse selection practitioners.
Details
- Veröffentlicht am
- May 26, 2026
- Sprache
- English
- ISBN
- 9781105259753
- Kategorie
- Haus & Garten
- Copyright
- Alle Rechte vorbehalten - Standard-Urheberrechtslizenz
- Autoren/Mitwirkende
- Von (Autor): Chris Lindholm
Spezifikationen
- Format
- EPUB