The Truth is The Current photoperiod model in science are completely wrong. i brought this up to a few renown plant psyiologist and they had their heads too far up their own butt to even consider my ideas, which i am sure are correct. I have no desire to stray from my plans and go out of the way to preform an experiment using there style and post it as a publication, thats not me if they want to accept and test my ideas good, but i am not going out of my way to prove something to people i dont respect. but for any growers who want to understand how photoperiods truly work, andd not believe all the garbage and bs lies that science believes atm give this a read. - Thanks VW
Auxin-Energy-Resource (AER) Model: A Complete Synthesis
1. Overview: Shifting the Focus from Photoperiod to Auxin
Traditional Photoperiod/Circadian Model (for contrast)
2. Key Components and Mechanisms
2.1 Auxin as the Master Regulator
3. The Concept of Amplitude
3.1 Auxins as “Regulators of Change”
4. Cotyledon-Based Early Indicators
A practical outcome of the AER Model is the ability to predict a plant’s hormonal tendencies from cotyledon traits:
5. Parallels with Other Organisms
5.1 Humans (Analogy, Not Direct Biology)
6. Reconciling “Latitude” with AER Model
6.1 Old Idea: Latitude → Day Length → Flowering
7. Evidence & Predictions
8. Concluding Remarks
9. Next Steps for Validation
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Auxin-Energy-Resource (AER) Model: A Complete Synthesis
1. Overview: Shifting the Focus from Photoperiod to Auxin
Traditional Photoperiod/Circadian Model (for contrast)
- Core Premise: Plants measure day length (photoperiod) using internal clocks (circadian rhythms). When days are sufficiently long (or short), certain genes like CONSTANS (CO) and FLOWERING LOCUS T (FT) switch on, prompting flowering. Photoreceptors (e.g., phytochromes, cryptochromes) are said to “count” light hours.
- Limitations: This view struggles to explain phenomena such as:
- Autoflowering in some species (e.g., certain cannabis varieties) that flower regardless of day length.
- Stress-induced flowering (e.g., triggered by drought or low light intensity), where actual “day length” may be irrelevant.
- Central Hypothesis: Auxin levels—and the plant’s overall energy/resources—serve as the primary regulators of flowering, with CO and FT operating within an auxin-driven framework.
- Photoreceptors’ Role: Rather than acting as day-length counters, photoreceptors detect light quality (intensity, spectrum) and adjust auxin accordingly. Auxin, in turn, modulates the genetic components (CO, FT).
- Environmental & Metabolic Factors: The plant’s energy status, nutrient availability, and stress conditions also influence auxin production or distribution, thereby affecting the transition to flowering.
2.1 Auxin as the Master Regulator
- High Auxin → Blocks Flowering:
- Maintains CO gene activity, which in turn inhibits FT expression.
- Delays the plant’s switch from vegetative to reproductive growth.
- Low Auxin → Triggers Flowering:
- Reduces CO gene activity, unblocking FT.
- FT (florigen) then initiates the reproductive phase.
- CO Gene:
- Acts like a bridge between auxin levels and FT.
- If auxin is high, CO stays active, keeping FT off → no flowering.
- If auxin drops, CO activity falls → FT is free to accumulate → flowering begins.
- FT as Florigen:
- A mobile signal produced once CO is no longer actively blocking it.
- Moves to the shoot meristem, initiating bud and flower development.
- Not Day-Length Meters:
- Phytochromes and cryptochromes sense light wavelengths and intensities (e.g., red/far-red ratios, blue light quantity), but do not literally “count” hours.
- Information Hubs:
- The quality and intensity of light data inform the plant’s hormonal status—especially auxin distribution and synthesis.
- Environmental shifts that alter light intensity or spectrum can modulate auxin levels, indirectly regulating CO → FT transitions.
- Metabolic Reserves:
- Even if auxin drops, the plant must have enough energy or nutrient resources to support flowering.
- Environmental stress (lack of nutrients, drought, excessive heat/cold) can prompt a “bailout” strategy: the plant lowers auxin to allow flowering before conditions worsen further.
- Resource Flexibility:
- Under the AER Model, the plant responds to real-time conditions. If resources are abundant, it may maintain higher auxin longer (delayed flowering, bigger vegetative form). If resources are scarce, auxin falls sooner (faster flowering switch).
3.1 Auxins as “Regulators of Change”
- Amplitude = The magnitude or dramatic nature of a growth or flowering transition.
- High Auxin → Greater Amplitude:
- Acts as a “buffer,” delaying major changes (like flowering). Once the transition finally happens, shifts in leaf complexity or bud formation can be more pronounced.
- Low Auxin → Faster Transitions, Lower Amplitude:
- With less auxin “resistance,” the plant moves quickly between developmental stages but with fewer dramatic morphological overhauls.
- Not Exclusively Auxin-Based:
- Other hormones (gibberellins, cytokinins), genetic factors, and external stresses also influence how big or abrupt these transitions are. High gibberellin, for instance, can produce notable elongation even if auxin is low.
- High-Auxin, High-Amplitude Plants: Typically exhibit delayed but striking flowering phases—e.g., sudden surge in bud growth.
- Low-Auxin, Low-Amplitude Plants: Tend to flower quickly with steadier, less explosive transitions.
A practical outcome of the AER Model is the ability to predict a plant’s hormonal tendencies from cotyledon traits:
- Size:
- Larger Cotyledons: Suggest higher auxins, potentially leading to slower but more dramatic growth shifts.
- Smaller Cotyledons: Indicate lower auxins, enabling faster transitions and simpler structural changes.
- Shape:
- Broad (Cytokinin Influence): More lateral, bushier growth.
- Skinny/Elongated (Gibberellin Influence): Taller, apical dominance.
- Symmetry vs. Asymmetry:
- Symmetrical Cotyledons: Implies a stable hormonal profile; transitions are more predictable.
- Asymmetrical (one broad, one narrow): Suggests dynamic hormonal interplay; could see “hybrid” growth with multiple phases of lateral and vertical expansion.
- Ratio (Length-to-Width):
- Low Ratio (short & wide): Favors compact, branching structure (cytokinin).
- High Ratio (long & narrow): Favors elongation, early flowering potential (gibberellin), contingent on auxin levels.
5.1 Humans (Analogy, Not Direct Biology)
- Hormonal Gradients:
- Growth hormones, metabolic signals, etc., can be thought of as “auxin-like,” controlling when and how the body invests in growth or energy storage.
- Adaptations to Environment:
- Just as plants in low-resource environments might flower early, humans in harsh climates often develop traits favoring resource efficiency (more “compact” growth or fat storage).
- Diverse Influences:
- Many factors (genetics, environment, nutrition) create amplitude in human growth patterns, akin to how multiple hormones shape plant amplitude.
6.1 Old Idea: Latitude → Day Length → Flowering
- Traditional photoperiod logic claims plants “measure” day length at certain latitudes and decide when to flower based on that measurement.
- Light Quality & Intensity:
- Higher latitudes may have different angles of sunlight, altered spectral composition, or intense seasonal shifts in overall light.
- These factors modulate auxin via photoreceptors, not because the plant is counting hours.
- Seasonal Resource Changes:
- Temperature, soil nutrient cycling, and water availability often correlate with latitude.
- These resource fluctuations also impact auxin and the plant’s readiness to flower.
- Autoflowering Explained:
- Certain genetic backgrounds have intrinsic auxin behaviors that do not rely on big changes in light conditions. They drop auxin levels after a certain developmental stage, allowing FT to turn on “automatically.”
- Stress-Induced Flowering:
- Low light intensity, drought, or nutrient depletion can trigger a drop in auxin, reducing CO gene activity → FT can activate → plant flowers as a survival strategy.
- Manipulating Hormones vs. Manipulating Photoperiod:
- AER Model predicts that artificially reducing auxin or blocking its synthesis should induce flowering even under otherwise “non-flowering” light conditions.
- In contrast, simply changing photoperiod (if auxin remains high) might not always force flowering.
- Gene Mutants (CO, FT, Circadian Genes):
- Traditional view: If circadian genes are mutated, plants “miscount” day length, altering flowering times.
- AER view: These mutations primarily alter hormonal (auxin) balances or disrupt how photoreceptors feed into auxin regulation, indirectly impacting CO and FT.
- A New Hierarchy: The Auxin-Energy-Resource Model treats hormones—especially auxin—as the upstream “gatekeepers” of flowering.
- FT Remains Florigen, but Auxin Decides When It’s Unleashed: CO gene is maintained by high auxin; once auxin falls, CO recedes, freeing FT to trigger flowering.
- Photoreceptors as Real-Time Light Sensors, Not Day-Length Counters: The plant processes light quality and intensity to modulate auxin, which then influences CO → FT.
- Amplitude as a Valuable Concept: High auxin can produce bigger, more dramatic morphological leaps, whereas low auxin fosters quicker but subtler shifts.
- Cotyledon Clues for Breeding: By observing early leaf traits (size, shape, symmetry), breeders can anticipate a plant’s eventual growth pattern, amplitude, and flowering behavior.
- Auxin-Manipulation Experiments:
- Grow plants under identical light conditions but vary auxin levels (via exogenous application or inhibitors) to see if flowering times shift independently of “day length.”
- Molecular Studies:
- Track how changes in auxin concentration directly affect CO and FT gene expression.
- Investigate how photoreceptor-mediated signals feed into auxin synthesis or transport mechanisms.
- Multi-Species Trials:
- Test the AER Model in species with distinct flowering strategies (e.g., short-day, long-day, autoflowering plants) to confirm consistency.
- Peer Collaboration and Data Sharing:
- Publish findings in scientific forums. Compare with labs focusing on hormone and gene regulatory networks to refine or challenge the model.
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