{"@context":"https://schema.org","@type":"TechArticle","id":"FLV-PT-001","slug":"scale-up-transfer","canonical_url":"https://flavorotor.com/research/scale-up-transfer","machine_readable_url":"https://flavorotor.com/research/data/chapters/scale-up-transfer.json","markdown_url":"https://flavorotor.com/research/markdown/scale-up-transfer","title":"Plant Teleport: validated recipe replication and greenhouse scale transfer","description":"A complete engineering and scientific framework for replicating a validated FlavoRotor recipe on another calibrated unit and translating it to a greenhouse using measured plant-level targets, local command compilation, uncertainty-aware acceptance and preregistered outcome equivalence.","chapter":"Plant Teleport","version":"3.0","updated":"2026-07-30","table_of_contents":[{"id":"article-references","label":"Sources used on this page"},{"id":"executive-conclusion","label":"Executive conclusion"},{"id":"engineering-feasibility-decision","label":"Engineering feasibility decision"},{"id":"in-plain-terms","label":"In plain terms"},{"id":"canonical-terminology-and-units","label":"Canonical terminology and units"},{"id":"why-flavorotor-is-structurally-suited-to-recipe-transfer","label":"Why FlavoRotor is structurally suited to recipe transfer"},{"id":"what-property-transfer-means","label":"What “property transfer” means"},{"id":"the-decisive-distinction-target-transfer-versus-command-copying","label":"The decisive distinction: target transfer versus command copying"},{"id":"the-plant-teleport-contract","label":"The Plant Teleport contract"},{"id":"transfer-status-pt0-pt5","label":"Transfer status PT0–PT5"},{"id":"recipe-compiler-architecture","label":"Recipe compiler architecture"},{"id":"measuring-exposure-fidelity","label":"Measuring exposure fidelity"},{"id":"uncertainty-aware-environmental-compliance","label":"Uncertainty-aware environmental compliance"},{"id":"translation-by-physical-domain","label":"Translation by physical domain"},{"id":"cross-unit-replication-protocol","label":"Cross-unit replication protocol"},{"id":"cross-location-reproduction","label":"Cross-location reproduction"},{"id":"greenhouse-scale-translation","label":"Greenhouse scale translation"},{"id":"chemical-and-sensory-confirmation","label":"Chemical and sensory confirmation"},{"id":"how-equivalence-is-decided","label":"How equivalence is decided"},{"id":"exact-research-programme","label":"Exact research programme"},{"id":"marketplace-and-licensing-model","label":"Marketplace and licensing model"},{"id":"recipe-integrity-signing-and-marketplace-trust","label":"Recipe integrity, signing and marketplace trust"},{"id":"llm-and-machine-readable-interpretation","label":"LLM and machine-readable interpretation"},{"id":"failure-modes-and-safeguards","label":"Failure modes and safeguards"},{"id":"evidence-boundary","label":"Evidence boundary"},{"id":"questions-the-completed-research-must-answer","label":"Questions the completed research must answer"},{"id":"definition-of-done-for-the-first-credible-plant-teleport-demonstration","label":"Definition of done for the first credible Plant Teleport demonstration"},{"id":"final-definition","label":"Final definition"}],"html":"\n\n
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Plant Teleport

Replicate a validated cultivation result on another calibrated FlavoRotor and translate it to a greenhouse by transferring measured plant-level exposure targets, not machine-specific commands.

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SCIENTIFIC CONCLUSIONThe Plant Teleport architecture is technically feasible because its components-calibration, machine-independent recipes, environmental sensing, local control, metadata, independent replication and equivalence testing-are established engineering and scientific methods. What remains to be demonstrated experimentally is the achievable fidelity for each crop, property, machine pair and greenhouse implementation.
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CURRENT FLAVOROTOR STATUSThe public FlavoRotor record defines the transfer framework but does not yet contain a completed cross-unit or greenhouse dataset demonstrating equivalent chemical and sensory outcomes. No figure in this article is presented as measured Plant Teleport performance unless it is explicitly labelled as measured data.
\n\n## Executive conclusion\n\nPlant Teleport builds on established engineering and scientific methods. A digital recipe can store calibrated physical targets, another system can compile those targets into its own actuator commands, and the delivered environment can be measured. Modern controlled-environment systems already combine sensors, actuators, time-varying targets and model-based control. [R69] Published plant research also demonstrates that controlled cultivation inputs can change quality-related plant chemistry and sensory-relevant outcomes under specified conditions. [R01] [R71]\n\nThe difficult and scientifically valuable part is not sending the file. It is proving that the destination produced a sufficiently equivalent plant outcome.\n\nTherefore, the strongest accurate statement is:\n\n> **FlavoRotor can provide the infrastructure required to encode, translate, execute and validate portable cultivation recipes. The fidelity of a particular aroma, taste, colour or texture must then be established by independent cross-system measurements.**\n\nThis converts a broad development goal into a structured research programme with defined validation milestones and concrete product architecture.\n\n\n
\n \n \"Three\n \n
\n PT-F15 · FRAMEWORK\n Evidence boundary\n

Design, external support and FlavoRotor results must not be conflated.

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Does not show: Any current Plant Teleport experimental result.

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Sources: [I01] [I02] [R64] [R67] [R69] [R70]

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\n\n\n## Engineering feasibility decision\n\n**Decision: technically feasible as an architecture; experimentally unverified for crop-specific property fidelity.**\n\nThe required operations are established independently: measure physical exposure, calibrate actuators, store versioned metadata, translate targets to local hardware, operate closed-loop control, identify independent experimental units and test a predefined equivalence hypothesis. [R69] [R65] [R70]\n\nThe remaining uncertainty is empirical rather than conceptual: how closely a particular destination can reproduce a specified chemical, physical or sensory profile for a named cultivar and recipe version.\n\nThis decision creates two non-interchangeable statements:\n\n| Statement | Status |\n|---|---|\n| A calibrated destination can attempt to reproduce machine-independent physical targets. | Engineering architecture supported. |\n| A specific aroma, taste or texture will be equivalent after transfer. | Must be demonstrated for the stated scope. |\n\n
\"Matrix
PT-F20 · FRAMEWORKCompatibility matrix

Transfer scope depends jointly on biological and hardware compatibility.

Does not show: A quantified probability of success or universal compatibility rule.

Sources: [R09] [R11] [R14] [R64] [R78]

\n\n## In plain terms\n\nPlant Teleport is FlavoRotor’s name for **evidence-gated recipe portability**. It does not mean that a plant or molecule is literally transported.\n\nA source FlavoRotor records:\n\n- the biological material;\n- the time-indexed environment experienced by the plant;\n- the machine and calibration version;\n- the harvest and post-harvest protocol;\n- the measured chemical, physical and sensory result;\n- the uncertainty, deviations and evidence level.\n\nA destination system receives that package and determines whether it can reproduce the required physical targets. It then calculates its own commands, runs the cultivation under measurement and repeats the outcome analysis.\n\n\n
\n \n \"Architecture\n \n
\n PT-F01 · FRAMEWORK\n Plant Teleport transfer architecture\n

Machine-independent targets can be translated into local commands and verified.

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Does not show: A measured cross-unit or greenhouse success rate.

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Sources: [I01] [I02] [R23] [R24] [R38] [R39] [R67] [R69]

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\n\nThe product interaction can still be simple:\n\n\n
\n \n \"Six-step\n \n
\n PT-F11 · FRAMEWORK\n One-click workflow\n

A single user action can orchestrate a rigorous workflow.

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Does not show: A guaranteed successful outcome from one action.

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Sources: [R38] [R39] [R43] [R65]

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\n\nA single click may start the workflow. It cannot legitimately skip compatibility, calibration, biological variation or validation.\n\n\n## Canonical terminology and units\n\nPlant Teleport uses one canonical meaning for each term so a human, controller and LLM interpret the recipe consistently.\n\n| Term | Canonical meaning |\n|---|---|\n| **Command** | Machine-specific instruction such as PWM duty, valve time or motor setpoint. |\n| **Target** | Desired physical quantity at a named plant or system location. |\n| **Measured exposure** | Time- and position-resolved quantity actually observed during cultivation. |\n| **Recipe** | Versioned biological, environmental, procedural and evidence package. |\n| **Reference run** | Validated source execution against which a destination is compared. |\n| **Destination run** | Execution on another machine, site or cultivation architecture. |\n| **Property endpoint** | Predefined chemical, physical or sensory response used in the transfer decision. |\n| **Equivalence margin** | Largest acceptable difference for a named endpoint, justified before data review. |\n| **Bridge experiment** | Controlled comparison required when machine, site or cultivation architecture changes materially. |\n\nCanonical reporting uses physical units rather than percentages wherever possible:\n\n- PPFD in µmol·m⁻²·s⁻¹;\n- DLI in mol·m⁻²·d⁻¹;\n- temperature in °C;\n- relative humidity in % and VPD in kPa;\n- EC in mS/cm with temperature or compensation method;\n- pH with electrode and calibration record;\n- elemental concentration in mmol/L or mg/L with the named chemical species;\n- liquid delivery in mL or g;\n- rotational speed in rev/min or angular velocity in rad/s;\n- airflow in m/s at a defined canopy position.\n\nA percentage may remain as a local command in the destination log, but it is not the portable recipe quantity.\n\n## Why FlavoRotor is structurally suited to recipe transfer\n\nThe architecture is favourable for portability because FlavoRotor is conceived as one integrated research platform rather than a loose collection of manually operated equipment. According to the internal design records, it combines programmable lighting, nutrient dosing, pH and electrical-conductivity monitoring, temperature sensing, rotation, imaging and versioned software records. [I01] [I02]\n\nThis integration offers five specific advantages.\n\n### 1. Common timing\n\nEvery relevant event can be represented on one time axis: lighting transitions, dosing, reservoir measurements, rotation, imaging and harvest. Cross-system transfer is substantially weaker when the records come from unrelated clocks or handwritten logs.\n\n### 2. Calibration-backed actuation\n\nA recipe can refer to a physical target rather than an arbitrary interface percentage. Calibration and measurement uncertainty provide the bridge between the requested quantity and the local actuator. [R38] [R39]\n\n### 3. Complete provenance\n\nThe system can preserve the relationship between recipe version, hardware version, sensor calibration, plant lot, images, raw logs, analytical samples and conclusions. MIAPPE and FAIR principles provide relevant structures for making such data interpretable and reusable. [R23] [R24]\n\n### 4. Closed-loop verification\n\nThe destination can measure whether it is achieving the target instead of assuming that commands were delivered correctly. This is central to current recommendations for environmental reporting in plant research. [R67]\n\n### 5. A natural path to a marketplace\n\nA recipe can be distributed together with its compatibility requirements, evidence level, supported crop material, required analyses and validated system scope. The marketplace object becomes a controlled technical specification rather than a vague promise.\n\n## What “property transfer” means\n\nA property is a measured response. Examples include:\n\n- concentrations of selected volatile compounds;\n- a defined chemical fingerprint;\n- soluble solids or titratable acidity;\n- colour coordinates;\n- dry matter or firmness;\n- a trained-panel sensory profile;\n- a consumer-liking result, when the claim concerns preference rather than descriptive equivalence.\n\nPublished studies show that lighting, nutrient supply, temperature and other pre-harvest conditions can influence quality-related responses in specified crops and conditions. [R01] [R09] [R11] [R71]\n\nProperty transfer means:\n\n> Reproducing a predefined outcome profile within declared limits by reproducing the relevant plant-level exposure trajectory, biological material, developmental state, harvest procedure and measurement method.\n\nIt does not mean exact identity between individual plants. Biological systems exhibit variation even under carefully standardised protocols. A ten-laboratory study demonstrated that dedicated standardisation can produce similar growth results across a core group of laboratories, while small environmental and handling differences can still affect phenotypes and metabolite profiles. [R64]\n\n\n
\n \n \"Causal\n \n
\n PT-F09 · FRAMEWORK\n Causal stack for property fidelity\n

Outcome fidelity depends on biology, exposure, architecture, timing, handling and measurement.

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Does not show: The relative effect size of each layer.

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Sources: [R09] [R11] [R14] [R64] [R66] [R67]

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\n\n## The decisive distinction: target transfer versus command copying\n\nThe transferable object must not be:\n\n```text\nLED = 73%\npump A = 12 seconds\nfan = 40%\nrotation motor = 35%\n```\n\nThose commands are properties of one machine.\n\nThe transferable object should be closer to:\n\n```text\ncanopy spectral photon target = versioned time series\nPPFD and DLI target = measured at defined plant positions\nelemental nutrient formulation = named species and concentrations\npH and EC = target trajectories with temperature and measurement method\nroot-zone temperature and wetting cycle = defined physical exposure\nair temperature, RH, VPD and airflow = measured at defined locations\nrotation and mechanical exposure = encoder-verified schedule\nharvest state = objective biological and chronological criteria\n```\n\nThe destination translates each target through its own calibrated hardware.\n\n\n
\n \n \"Graph\n \n
\n PT-F02 · ILLUSTRATIVE - NOT FLAVOROTOR DATA\n Machine command decoupling\n

Different machines can use different commands to deliver the same physical target.

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Does not show: Actual FlavoRotor pump flow, accuracy or drift.

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Sources: [R38] [R39]

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\n\nFor a liquid target:\n\n
PT-1
tpump = Vtarget / Qcal
Purpose: convert the required volume into a pump-specific nominal running time. Vtarget is the target volume and Qcal is the calibrated flow for that pump, tube, liquid and operating condition.
DEFINITIONAL TRANSLATION - DELIVERY MUST STILL BE VERIFIED
\n\nIf two pumps deliver 2 mL/min and 5 mL/min, respectively, both can target 10 mL, but their nominal commands are 5 minutes and 2 minutes. The recipe remains constant while the commands change.\n\n## The Plant Teleport contract\n\nA transferable recipe is a contract between the source evidence and the destination capability.\n\n### A. Biological passport\n\nThe recipe records:\n\n- species and cultivar;\n- seed lot, clone batch or other material identifier;\n- propagation method;\n- germination or rooting conditions;\n- developmental stage at each recipe transition;\n- plant density and position;\n- replacement and exclusion rules;\n- plant-health observations;\n- definition of the independent experimental unit.\n\nCultivar cannot be treated as a cosmetic label. Nutrient-strength and temperature responses can depend on genotype. [R09] [R11]\n\n### B. Time-indexed exposure targets\n\nThe package stores trajectories, not only averages:\n\n- spectral photon distribution;\n- PPFD;\n- DLI;\n- photoperiod and light transitions;\n- air and leaf temperature;\n- relative humidity and VPD;\n- carbon dioxide where controlled or material;\n- source-water composition;\n- elemental nutrient formulation;\n- pH, EC and solution temperature;\n- dissolved oxygen where relevant;\n- irrigation, immersion, drainage and aeration timing;\n- air velocity;\n- rotation and mechanical stimulation;\n- stage transitions and harvest timing.\n\nDynamic plant-environment research shows why a time-varying regime can be more informative than one static mean. [R68]\n\n### C. Capability declaration\n\nThe destination publishes:\n\n- controllable range;\n- measurable range;\n- resolution;\n- uncertainty;\n- spatial coverage;\n- sampling interval;\n- valid calibration;\n- actuation delay;\n- safety limits;\n- unsupported variables.\n\nThe interface must refuse validated execution when a mandatory variable cannot be controlled or verified.\n\n### D. Harvest and post-harvest protocol\n\nChemical and sensory properties may change after harvest. The recipe therefore defines:\n\n- objective harvest state;\n- time of day;\n- sample position and mass;\n- washing, cutting or preparation;\n- storage temperature and duration;\n- delay before instrumental or sensory analysis;\n- random coding and blinding.\n\n### E. Reference outcome fingerprint\n\nA single number called “aroma” is normally insufficient. The fingerprint can contain multiple primary and supporting endpoints.\n\n\n
\n \n \"Circular\n \n
\n PT-F13 · FRAMEWORK\n Outcome fingerprint\n

Sensory property transfer must use a declared multidimensional endpoint set.

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Does not show: Any universal weighting or measured FlavoRotor profile.

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Sources: [R01] [R41] [R71] [R73] [R75] [R76] [R77]

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\n\nDescriptive sensory profiling, assessor selection, sensory-room control and general sensory methodology should follow defined methods. [R41] [R73] [R74] [R75] Sensory vocabulary should be standardised. [R76] Consumer liking is a different question from descriptive equivalence and requires an appropriate consumer test. [R77]\n\n### F. Provenance and evidence\n\nEvery claim links to raw and processed records.\n\n\n
\n \n \"Data\n \n
\n PT-F10 · FRAMEWORK\n Data provenance\n

A claim should be traceable to raw data, calibrations, analysis and scope.

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Does not show: Current completeness of FlavoRotor public datasets.

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Sources: [R23] [R24] [R38] [R39] [R43]

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\n\n## Transfer status PT0–PT5\n\n\n
\n \n \"Stair-step\n \n
\n PT-F04 · FRAMEWORK\n Plant Teleport evidence ladder\n

Claims increase only when independent evidence increases.

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Does not show: Current achievement of any PT2–PT5 status.

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Sources: [R43] [R50] [R64] [R65]

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\n\n| Level | Name | Minimum meaning | Public wording |\n|---|---|---|---|\n| PT0 | Saved recipe | The source recipe and evidence package are complete. | “Recorded on the originating system.” |\n| PT1 | Repeated | Independent cycles on the same source system support the declared direction and variability. | “Repeated on the originating FlavoRotor.” |\n| PT2 | Cross-unit replicated | A second calibrated FlavoRotor meets the environmental and outcome criteria. | “Replicated on another calibrated FlavoRotor.” |\n| PT3 | Cross-location reproduced | PT2 is extended to another site with local water, room and handling effects addressed. | “Reproduced at another site under the stated conditions.” |\n| PT4 | System translated | A greenhouse or different cultivation architecture passes a bridge experiment. | “Translated and validated for greenhouse/system X.” |\n| PT5 | Independently verified | An independent partner executes and analyses the registered protocol. | “Independently verified within the published scope.” |\n\nThe evidence burden increases as hardware, location and cultivation architecture diverge.\n\n\n
\n \n \"Qualitative\n \n
\n PT-F05 · FRAMEWORK\n Transfer envelope\n

Increasing system and environmental differences require stronger bridge validation.

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Does not show: A quantified probability of success.

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Sources: [R14] [R64] [R66] [R67]

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\n\n## Recipe compiler architecture\n\nThe compiler performs a preflight before the run button is enabled.\n\n### Preflight gates\n\n1. **Biological compatibility** - the correct cultivar and material identifier are available.\n2. **Range compatibility** - the destination can reach every mandatory target.\n3. **Measurement compatibility** - the destination can verify those targets at the required location and frequency.\n4. **Calibration validity** - all mandatory sensors and actuators have valid calibration records.\n5. **Method compatibility** - the required harvest, laboratory and sensory methods are available.\n6. **Safety compatibility** - target and abort rules are compatible with the destination.\n7. **Evidence compatibility** - the requested public claim does not exceed the available validation level.\n8. **Licence compatibility** - the recipe version and permitted use are valid.\n\nThe result is one of four states:\n\n- **compatible**;\n- **compatible with declared adaptation**;\n- **research-only**;\n- **incompatible**.\n\n\n
\n \n \"Decision\n \n
\n PT-F12 · FRAMEWORK\n Transfer release decision\n

Release status follows compatibility, exposure and outcome gates.

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Does not show: A current pass/fail result.

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Sources: [R43] [R46] [R65] [R70]

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\n
\n\n### Subsystem translation\n\n\n
\n \n \"Engineering\n \n
\n PT-F16 · FRAMEWORK\n Subsystem translation\n

Recipe portability is implemented as calibrated translation for each subsystem.

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Does not show: That all listed subsystems are already fully validated on FlavoRotor.

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Sources: [I01] [I02] [R17] [R38] [R39] [R67] [R69] [R72]

\n
\n
\n\nA recent digital-twin framework demonstrates that vendor-agnostic sensor/actuator mapping, model calibration, dynamic targets and adaptive control are technically implementable in controlled-environment agriculture. Its published case study is simulation-based, so it supports the software architecture rather than proving physical Plant Teleport performance. [R69]\n\n## Measuring exposure fidelity\n\nFor controlled quantity j:\n\n
PT-2
ej(t) = yj(t) − rj(t)
Purpose: compute instantaneous tracking error. yj(t) is the measured value; rj(t) is the target at the same time and location.
MEASUREMENT DEFINITION
\n\n
PT-3
qj(t) = |ej(t)| / Δj
Purpose: normalise the error by the preregistered tolerance Δj. q ≤ 1 means the observation is inside the declared tolerance.
NORMALISED COMPLIANCE METRIC - NOT A BIOLOGICAL RESULT
\n\n
PT-4
Pj = 100 · ΣI(qj ≤ 1) / N
Purpose: report the percentage of valid observations inside tolerance. N is the number of valid observations; I is an indicator equal to one when the condition is true.
CONTROL-PERFORMANCE SUMMARY
\n\nThe acceptance value for Pj, excursion duration and safety limits must be established by protocol. No universal percentage is claimed.\n\n\n
\n \n \"Illustrative\n \n
\n PT-F03 · ILLUSTRATIVE - NOT FLAVOROTOR DATA\n Exposure fidelity over time\n

Transfer requires time-resolved exposure compliance, not matching a single average.

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Does not show: Any measured FlavoRotor trajectory or tolerance.

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Sources: [R38] [R39] [R67] [R68]

\n
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\n\nEnvironmental compliance is necessary but not sufficient. A destination can reproduce the target environment and still obtain a different biological result because of seed material, microbiology, developmental timing or unmeasured differences.\n\nA valid transfer therefore uses a conjunctive decision:\n\n
PT-5
Gtransfer = Gbiology ∧ Gexposure ∧ Gmethod ∧ Goutcome
Purpose: express that a validated transfer requires every mandatory gate to pass. The logical AND symbol means that one failed critical gate prevents the full claim.
DECISION LOGIC - NOT A CONTINUOUS PERFORMANCE SCORE
\n\n\n## Uncertainty-aware environmental compliance\n\nA measured value close to a tolerance boundary cannot be treated as an unquestioned pass when measurement uncertainty overlaps that boundary. Calibration, uncertainty and acceptance must therefore be connected. [R38] [R39] [R43]\n\nFor a measured estimate yj, target rj, tolerance Δj, standard uncertainty uj and chosen coverage factor k, a conservative guard-band rule can be written as:\n\n
PT-5A
|yj − rj| + k·uj ≤ Δj
Purpose: require the measured deviation plus the declared uncertainty allowance to remain inside the tolerance. The coverage factor and decision rule must be specified by the protocol; they are not universal constants.
ILLUSTRATIVE GUARD-BAND RULE BASED ON METROLOGY PRINCIPLES
\n\n**Illustrative example.** A target is 22.0 °C with a tolerance of ±0.5 °C. The measured estimate is 22.3 °C and the standard uncertainty is 0.1 °C. If the protocol uses k = 2, the guarded deviation is 0.3 + 2 × 0.1 = 0.5 °C, exactly at the declared limit. This example explains the rule; it is not a FlavoRotor acceptance specification.\n\n
\"Illustrative
PT-F17 · ILLUSTRATIVE - NOT FLAVOROTOR DATAUncertainty-aware environmental acceptance

Measurement uncertainty should be included in the environmental acceptance rule.

Does not show: A universal coverage factor, tolerance or measured FlavoRotor uncertainty.

Sources: [R38] [R39] [R43]

\n\nThe environmental report must distinguish:\n\n- target uncertainty or allowable biological tolerance;\n- instrument calibration uncertainty;\n- spatial sampling uncertainty;\n- temporal interpolation uncertainty;\n- missing data;\n- actuator-delivery uncertainty.\n\nA recipe should not declare a tolerance narrower than the destination can credibly measure and control.\n\n## Translation by physical domain\n\n### Light\n\nThe recipe stores spectrum, intensity, distribution and timing at plant level.\n\nFor a constant PPFD interval:\n\n
PT-6
DLI = PPFD · τ · 10−6
Purpose: convert PPFD in µmol·m⁻²·s⁻¹ over duration τ in seconds into DLI in mol·m⁻². For variable light, integrate the measured PPFD time series.
PHOTON-EXPOSURE DEFINITION
\n\nMatching DLI alone is insufficient when spectrum, spatial distribution or within-day trajectory differs. Artificial and natural lighting can produce different metabolic responses even when important lighting characteristics are approximated. [R66]\n\n### Nutrient composition\n\nEC is an aggregate conductivity measurement, not an ion-specific recipe. Different ion mixtures can produce similar EC, and recirculating systems can change individual nutrient concentrations. [R17]\n\nThe portable recipe therefore stores:\n\n- source-water analysis;\n- named nutrient species;\n- stock formulation;\n- intended elemental concentrations;\n- pH and EC trajectories;\n- reservoir volume and replacement rules;\n- mixing verification;\n- analytical checkpoints where necessary.\n\n### Root-zone exposure\n\nA rotating hydroponic system and a greenhouse substrate system do not expose roots identically. Translation must consider:\n\n- contact or irrigation duration;\n- drainage;\n- oxygen availability;\n- root-zone temperature;\n- solution movement;\n- biofilm and sanitation;\n- water-holding properties of the destination medium.\n\nCultivation-system comparisons show that system architecture can materially alter crop performance. [R14]\n\n### Air and leaf environment\n\nCanopy air temperature is not always leaf temperature. Room relative humidity is not necessarily canopy humidity. The transfer protocol therefore defines sensor placement and records temperature, humidity, VPD, airflow and carbon dioxide when relevant.\n\n### Mechanical and rotation exposure\n\nRotation can simultaneously affect watering, orientation and mechanical stimulation. If rotation is part of a validated treatment, the destination must separate:\n\n- root wetting caused by rotation;\n- light-exposure geometry;\n- mechanical stimulus;\n- air movement;\n- position-dependent effects.\n\nA greenhouse child recipe may reproduce the relevant physical exposure through different hardware, but this requires a bridge experiment rather than semantic relabelling.\n\n### Camera and plant-state alignment\n\nA camera can support transfer by detecting:\n\n- germination and establishment;\n- leaf area;\n- canopy coverage;\n- colour changes;\n- growth rate;\n- visible stress;\n- developmental transitions;\n- positional non-uniformity.\n\nThe camera does not directly measure taste or aroma. It can align recipe stages and detect deviations that would otherwise make two runs biologically incomparable. The imaging algorithm, model version, confidence threshold and manual-audit rule become part of the recipe record.\n\n## Cross-unit replication protocol\n\nThe first demonstration should use two FlavoRotor systems of the same supported hardware generation.\n\n### Required design\n\n- frozen recipe and analysis plan;\n- one cultivar and traceable material lot;\n- independent biological units;\n- randomised plant positions;\n- multiple independent cultivation cycles;\n- calibrated light, dosing, environmental and rotation subsystems;\n- predefined primary endpoints;\n- matched harvest and post-harvest methods;\n- full deviation reporting.\n\nThe number of plants and cycles cannot be selected by a universal rule. It must be calculated using pilot variability, the justified equivalence margin, desired power and the actual experimental-unit structure.\n\nPseudoreplication must be avoided. Multiple leaves from one plant or several plants sharing one unreplicated environment do not automatically represent independent treatment units. [R65]\n\n\n
\n \n \"Four\n \n
\n PT-F14 · ILLUSTRATIVE - NOT FLAVOROTOR DATA\n Independent replication and blocking\n

Reference and destination units should be independently replicated and spatially blocked.

\n

Does not show: A required sample size or actual FlavoRotor layout.

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Sources: [R65]

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\n
\n\n### Minimum reports\n\n- calibration report for both units;\n- empty-system spatial and temporal map;\n- source and destination exposure comparison;\n- biological baseline;\n- chemical and physical results;\n- sensory report when sensory equivalence is claimed;\n- statistical analysis;\n- raw dataset and analysis code;\n- failed or excluded units with reasons.\n\n## Cross-location reproduction\n\nAnother country or room introduces additional variables:\n\n- local water chemistry;\n- ambient temperature and humidity;\n- electrical and maintenance differences;\n- operator handling;\n- sample transport;\n- laboratory method and instrument;\n- sensory language and panel context.\n\nA cross-location transfer should use either the same analysis laboratory or a documented inter-laboratory method comparison. Measurement-method reproducibility and biological reproducibility must remain distinct. [R50]\n\n## Greenhouse scale translation\n\nA greenhouse is not a physically enlarged FlavoRotor. It is a new cultivation architecture exposed to sunlight, weather disturbances, spatial gradients and different root-zone dynamics.\n\nThe correct process is:\n\n1. map the greenhouse;\n2. define controllable zones;\n3. measure plant-level conditions;\n4. compile supplemental controls;\n5. run a bridge experiment;\n6. compare outcomes;\n7. release a greenhouse-specific child recipe.\n\n\n
\n \n \"Greenhouse\n \n
\n PT-F06 · FRAMEWORK\n Greenhouse zone translation\n

Greenhouse transfer must be measured and compiled per zone.

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Does not show: The number, dimensions or performance of a real greenhouse.

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Sources: [R66] [R67] [R68] [R69] [R72]

\n
\n
\n\n\n### Spatial mapping and sensor placement\n\nA greenhouse average is not a plant-level exposure record. Light, temperature, humidity and airflow can vary across positions, and controlled chambers can also exhibit spatial or chamber effects. [R78] Greenhouse mapping methods likewise begin from spatial measurements rather than assuming homogeneity. [R79]\n\nThe recommended workflow is:\n\n1. deploy a temporary dense sensor grid during representative operating periods;\n2. quantify spatial and temporal gradients at canopy and root-zone locations;\n3. identify zones that can be controlled as coherent units;\n4. select representative permanent sensors;\n5. validate the reduced sensor arrangement against the dense map;\n6. repeat mapping after material changes in crop height, layout, season, glazing, airflow or equipment.\n\n
\"Diagram
PT-F18 · FRAMEWORKGreenhouse mapping strategy

Greenhouse translation should begin with measured spatial mapping and validated operational zones.

Does not show: A universal sensor count, zone layout or mapping accuracy.

Sources: [R67] [R79]

\n\nThe number of sensors is an experimental design decision. Plant Teleport does not prescribe a universal sensor density.\n\n### Supplemental light balance\n\n
PT-7
DLIsupp = max(0, DLItarget − DLIsun,usable)
Purpose: estimate the daily supplemental photon amount after measured usable sunlight is credited. Spectrum, timing, distribution and plant state remain separate matching requirements.
FIRST-ORDER BALANCE - NOT A COMPLETE GREENHOUSE TRANSLATION
\n\nIf the target DLI is 16 mol·m⁻²·d⁻¹ and measured usable sunlight contributes 10 mol·m⁻²·d⁻¹, the first-order supplement is 6 mol·m⁻²·d⁻¹. These numbers are an explanatory example, not a FlavoRotor crop recommendation.\n\n### Zone control\n\nEach zone converts physical targets into its own:\n\n- supplemental-light schedule;\n- fertigation events;\n- nutrient-stock commands;\n- heating, cooling and ventilation;\n- humidification or dehumidification;\n- airflow;\n- carbon-dioxide control where used;\n- alarms and recovery rules.\n\nSensor-controlled fertigation can be evaluated in greenhouse hydroponic production using quality, yield and resource-use outcomes. [R72] This supports the practical feasibility of local sensor-to-actuator control; it does not prove transfer of a FlavoRotor aroma profile.\n\n### Bridge experiment\n\nThe greenhouse bridge includes:\n\n- validated source condition;\n- translated greenhouse condition;\n- spatial blocks and independent units;\n- repeated production periods;\n- matched cultivar and biological material;\n- same primary analytical endpoints;\n- matched harvest and post-harvest handling;\n- blinded sensory method when sensory equivalence is claimed;\n- a declared acceptable loss if strict equivalence is not the intended objective.\n\nThe greenhouse child recipe receives a new identifier.\n\n\n
\n \n \"Recipe\n \n
\n PT-F08 · FRAMEWORK\n Recipe lineage\n

Every transfer creates a traceable child record and report.

\n

Does not show: Actual released FlavoRotor recipes.

\n

Sources: [R23] [R24]

\n
\n
\n\n## Chemical and sensory confirmation\n\nA chemical difference can exist without a perceptible sensory difference. A sensory difference can also reflect compounds not included in a narrow targeted analysis. Plant Teleport therefore treats chemical and sensory evidence as complementary.\n\n\n### Three property-claim tiers\n\n“Same aroma” is ambiguous unless the evidence domain is named.\n\n
\"Three
PT-F19 · FRAMEWORKProperty claim tiers

A precise transfer claim must identify whether it concerns chemistry, descriptive sensory attributes or consumers.

Does not show: That success at one tier guarantees success at another.

Sources: [R01] [R41] [R73] [R74] [R75] [R76] [R77]

\n\n- **Tier A - chemical and physical profile:** selected volatile compounds, non-volatile chemistry, colour or texture meet predefined analytical criteria.\n- **Tier B - descriptive sensory equivalence:** trained assessors produce equivalent intensities for predefined attributes under a controlled protocol.\n- **Tier C - consumer response:** a stated consumer population does not detect a relevant difference or shows comparable liking under the chosen design.\n\nA recipe may pass one tier and fail another. Chemical similarity does not prove perceptual equivalence, and comparable liking does not prove chemical identity.\n\n### Chemical layer\n\nDepending on the claim:\n\n- targeted volatile compounds;\n- broader volatile fingerprint;\n- sugars and organic acids;\n- pigments;\n- minerals;\n- dry matter;\n- compounds linked to pungency, bitterness or aroma;\n- method uncertainty and quality-control samples.\n\n### Physical layer\n\n- colour coordinates;\n- firmness;\n- fracture or compression response;\n- water content;\n- structural measurements.\n\n### Descriptive sensory layer\n\nA trained panel may profile intensity of defined attributes. Panel recruitment and training, test-room conditions, vocabulary, sample preparation and analysis must be documented. [R41] [R73] [R74] [R75] [R76]\n\n### Consumer layer\n\nConsumer liking is not proof of descriptive equivalence. It answers whether a defined consumer population prefers or accepts the samples. [R77]\n\n## How equivalence is decided\n\nA result is not equivalent merely because a difference was not statistically significant. Insufficient sample size can produce a non-significant result even when important differences remain.\n\nFor one continuous primary endpoint:\n\n
PT-8
CI90%(μD − μR) ⊂ [−Δ, +Δ]
Purpose: declare equivalence only when the complete confidence interval for the destination-minus-reference effect lies inside the predeclared equivalence interval. Δ must be justified before data review.
CLASSICAL TWO ONE-SIDED TESTS FRAMEWORK
\n\n\n
\n \n \"Four\n \n
\n PT-F07 · ILLUSTRATIVE - NOT FLAVOROTOR DATA\n Equivalence decision examples\n

A complete confidence interval must lie inside a justified equivalence margin.

\n

Does not show: A FlavoRotor margin, sample size or measured effect.

\n

Sources: [R46] [R70]

\n
\n
\n\nFor multiple endpoints:\n\n- primary endpoints are declared in advance;\n- every essential endpoint must satisfy its criterion;\n- multiplicity is handled in the analysis plan;\n- yield and plant-health guardrails cannot be ignored;\n- chemical and sensory evidence are not substituted for one another;\n- exploratory endpoints remain labelled exploratory;\n- missing-data and outlier rules are preregistered.\n\nThere is no universal ±10% aroma margin. Each margin must be justified using measurement capability, baseline biological variation and the intended product claim.\n\n## Exact research programme\n\n### Experiment PT-E01 - same-machine repeatability\n\n**Question:** Can one frozen recipe be executed across independent cycles on one FlavoRotor with stable exposure and outcome variability?\n\n**Outputs:** PT1 recipe, calibration bundle, baseline variance, endpoint shortlist.\n\n### Experiment PT-E02 - second-unit replication\n\n**Question:** Can a second calibrated FlavoRotor independently reproduce the required exposure trajectory and primary outcome profile?\n\n**Outputs:** PT2 transfer report, command-translation comparison, failed-variable analysis.\n\n### Experiment PT-E03 - cross-location reproduction\n\n**Question:** Does the recipe remain equivalent when executed at another site after water, room, operator and analytical differences are controlled?\n\n**Outputs:** PT3 report, site adaptation record, inter-laboratory method check where necessary.\n\n### Experiment PT-E04 - greenhouse pilot bridge\n\n**Question:** Can a defined greenhouse zone reproduce the relevant physical exposure and outcome endpoints?\n\n**Outputs:** zone map, greenhouse child recipe, PT4 report or documented non-equivalence.\n\n### Experiment PT-E05 - independent verification\n\n**Question:** Can an independent partner execute the frozen package without unpublished assistance and obtain the declared result?\n\n**Outputs:** PT5 report, independent raw data, audit of ambiguities and required clarifications.\n\nThis programme creates a direct sequence from prototype engineering to a commercially meaningful validated recipe network.\n\n## Marketplace and licensing model\n\nA recipe listing should display:\n\n- crop and cultivar;\n- version and lineage;\n- status PT0–PT5;\n- supported machine versions;\n- supported location or greenhouse scope;\n- required biological material;\n- mandatory cartridges and analysis;\n- primary outcome endpoints;\n- equivalence scope;\n- known unsupported transfers;\n- licence terms;\n- linked reports and datasets.\n\nA buyer should be able to distinguish:\n\n- **recipe available**;\n- **validated on source unit**;\n- **replicated on another unit**;\n- **translated to named greenhouse**;\n- **independently verified**.\n\nThis evidence structure is commercially favourable because it converts trust from a marketing statement into a visible product attribute.\n\n\n## Recipe integrity, signing and marketplace trust\n\nPortability creates a new engineering risk: a valid recipe can become unsafe or scientifically misleading if its file, evidence status or calibration requirements are altered.\n\nEvery released package should therefore include:\n\n- immutable recipe ID and semantic version;\n- parent recipe ID and lineage;\n- SHA-256 checksums for recipe, data and analysis files;\n- signer identity and signature method;\n- creation and expiry or review date;\n- supported hardware and cultivar scope;\n- minimum calibration bundle;\n- exact PT status and linked reports;\n- revoked and superseded status;\n- licence and permitted-use metadata.\n\nThe destination must reject or downgrade a run when:\n\n- the signature or checksum fails;\n- the recipe version is revoked;\n- required calibration is expired;\n- source IDs resolve to different records;\n- mandatory variables are unavailable;\n- the requested claim exceeds the recipe’s evidence status.\n\nA marketplace rating is not scientific evidence. User feedback can identify usability problems, but PT status can change only through the declared validation records.\n\n## LLM and machine-readable interpretation\n\nThe machine-readable record must state explicitly:\n\n```json\n{\n \"claim_status\": \"framework_not_yet_demonstrated_by_public_transfer_dataset\",\n \"portable_object\": \"plant_level_physical_targets_plus_biological_and_evidence_metadata\",\n \"does_not_establish\": [\n \"identical flavour guaranteed worldwide\",\n \"equivalence from copied device settings\",\n \"transfer across cultivars without validation\",\n \"completed greenhouse transfer\"\n ]\n}\n```\n\nEvery visual record states:\n\n- whether it is a framework, an illustrative example or measured data;\n- the exact claim it supports;\n- what it does not show;\n- its source IDs.\n\nThis prevents an LLM from converting a conceptual graph into an experimental result.\n\n## Failure modes and safeguards\n\n| Failure mode | Consequence | Required safeguard |\n|---|---|---|\n| Same interface percentages, different physical exposure | False portability | Store physical targets and calibrations |\n| Same EC, different ion balance | Different nutrient treatment | Store elemental formulation and water chemistry |\n| Same average DLI, different spectrum or trajectory | Different plant response | Store spectrum and time-resolved light |\n| Same cultivar name, different lot or propagation | Different starting biology | Biological passport |\n| One chamber per treatment | Treatment confounded with chamber | Independent units and valid blocking |\n| Greenhouse average hides spatial zones | Unmeasured local exposure | Canopy-level zone mapping |\n| Different harvest maturity | Different chemistry and texture | Objective harvest state |\n| Different post-harvest handling | Altered aroma or texture | Frozen sample-handling protocol |\n| “No significant difference” used as equivalence | False positive claim | Predeclared margins and equivalence analysis |\n| Simulation presented as physical validation | Evidence inflation | Explicit model status and bridge experiment |\n| Only successful transfers published | Biased marketplace | Retain failure and inconclusive records |\n| New hardware inherits old status | Invalid lineage | New version and transfer report |\n\n## Evidence boundary\n\nPublished research supports that:\n\n- controlled pre-harvest conditions can influence horticultural quality-related traits; [R01] [R71]\n- standardisation can improve cross-laboratory reproducibility, while residual site effects remain; [R64]\n- actual environmental measurement is essential for interpretation and repeatability; [R67]\n- dynamic environmental trajectories can be reproduced in controlled infrastructure; [R68]\n- digital-twin and adaptive-control architectures can integrate heterogeneous sensors and actuators; [R69]\n- sensor-coupled greenhouse fertigation is technically practical; [R72]\n- independent replication and equivalence methods are established scientific tools. [R65] [R70]\n\nThe public FlavoRotor evidence does not yet establish:\n\n- equivalent aroma on two physical FlavoRotor units;\n- cross-country reproduction of a measured property profile;\n- a validated greenhouse child recipe;\n- universal compatibility or equivalence margins;\n- identical sensory results from a downloaded file.\n\n## Questions the completed research must answer\n\n1. Which measured properties are stable enough to become primary transfer endpoints?\n2. What fraction of variability comes from machine delivery, biological material, site and analysis?\n3. Which variables must be matched exactly and which can be compensated?\n4. How far can hardware versions differ before a bridge experiment is required?\n5. Can camera-derived plant state improve recipe-stage alignment and outcome fidelity?\n6. Which crops are best suited to initial cross-unit validation?\n7. What equivalence margins are scientifically and commercially meaningful?\n8. How much greenhouse zoning is necessary for a stable child recipe?\n9. Can failed transfers be used to improve the recipe compiler?\n10. What evidence badge is understandable to consumers without overstating certainty?\n\n\n## Definition of done for the first credible Plant Teleport demonstration\n\nThe first public PT2 claim is complete only when all of the following are available:\n\n- two independently calibrated physical FlavoRotor units;\n- a frozen recipe and biological material identifier;\n- a preregistered design with a correctly identified experimental unit;\n- independent cycles and positional randomisation;\n- empty-system light, temperature, solution and rotation maps;\n- source and destination exposure logs;\n- a declared primary chemical or physical endpoint;\n- a defined sensory method if sensory equivalence is claimed;\n- justified equivalence margins;\n- raw and processed datasets;\n- versioned analysis code;\n- calibration, replication and deviation reports;\n- a public result classified as passed, failed or inconclusive.\n\nA failed or inconclusive first transfer remains valuable. It reveals which part of the portable specification or local compiler requires improvement and prevents premature commercial claims.\n\n## Final definition\n\n> **Plant Teleport is FlavoRotor’s evidence-gated system for moving a validated cultivation specification between calibrated machines and into larger controlled environments. It transfers time-indexed plant exposure targets, biological material definitions, harvest rules and an outcome fingerprint; compiles those targets into local commands; verifies the delivered environment; and releases a replication or scale-transfer claim only after independent measurements meet preregistered criteria.**\n\nThe transferable asset is a validated specification and evidence chain.\n\nThe ambition is clear and technically credible:\n\n> **Create a plant property profile once, validate it rigorously, reproduce it on another calibrated FlavoRotor, and translate it to commercial cultivation with measured and published fidelity.**\n\n
\n

Article bibliography

\n

Sources used on this page

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    \n

  1. R69 Frontzek, Julius; Wagner, Zühal; Streif, Stefan (2026). Dynamic, adaptive and modular Digital Twin framework for resource-efficient Controlled Environment Agriculture. Frontiers in Plant Science, 17, 1864757. 10.3389/fpls.2026.1864757

    Used for: Supports vendor-agnostic sensor and actuator integration, dynamic target trajectories, model calibration and adaptive control as an architecture for translating targets to local equipment.

    Evidence boundary: Its case study is simulation-based and uses synthetic data; physical, sensory and cross-facility recipe transfer remain unvalidated.

    2. \n

  2. R01 Hammock, Hunter A.; Sams, Carl E. (2023). Variation in supplemental lighting quality influences key aroma volatiles in hydroponically grown 'Italian Large Leaf' basil. Frontiers in Plant Science. 10.3389/fpls.2023.1184664

    Used for: Shows that a defined spectral treatment can alter selected aroma-related volatile measurements in one named hydroponic basil cultivar.

    Evidence boundary: It does not demonstrate that the result transfers to another cultivar, machine, location or greenhouse.

    3. \n

  3. R71 Zhao, Xinyi; Peng, Jie; Zhang, Li; et al. (2024). Optimizing the quality of horticultural crop: insights into pre-harvest practices in controlled environment agriculture. Frontiers in Plant Science, 15, 1427471. 10.3389/fpls.2024.1427471

    Used for: Reviews how pre-harvest manipulation of nutrients, light and other controlled-environment factors can affect horticultural quality, including colour, aroma and taste-related outcomes.

    Evidence boundary: A broad review establishes scientific plausibility and candidate mechanisms; it does not validate any FlavoRotor recipe, universal optimum or cross-system transfer.

    4. \n

  4. I01 FlavoRotor project team (2026). FlavoRotor prototype implementation record. Internal engineering report. /research/platform

    Used for: Documents the built rotating prototype, sensing electronics, dashboard and current validation limitations.

    Evidence boundary: An internal engineering record does not demonstrate cross-machine recipe replication or biological property transfer.

    5. \n

  5. I02 FlavoRotor project team (2026). FlavoRotor v2.0 system architecture. Internal engineering design report. /research/platform

    Used for: Documents the proposed magnetic drive, axial lighting, four-channel peristaltic dosing and imaging architecture.

    Evidence boundary: Architecture and design targets are not a measured demonstration of Plant Teleport.

    6. \n

  6. R64 Massonnet, Catherine; Vile, Denis; Fabre, Justine; et al. (2010). Probing the Reproducibility of Leaf Growth and Molecular Phenotypes: A Comparison of Three Arabidopsis Accessions Cultivated in Ten Laboratories. Plant Physiology, 152(4), 2142–2157. 10.1104/pp.109.148338

    Used for: Shows that detailed standardisation can produce similar growth in a core group of laboratories, while small laboratory-environment differences can still alter growth and metabolite phenotypes.

    Evidence boundary: The study used Arabidopsis and did not test hydroponic flavour, FlavoRotor hardware or one-click recipe transfer.

    7. \n

  7. R67 Vincent, Christopher; Leisner, Courtney P.; Locke, Anna M.; Teshome, Demissew Tesfaye; et al. (2025). Importance of measuring and reporting environmental conditions across plant science subdisciplines. Plant Physiology, 199(2), kiaf405. 10.1093/plphys/kiaf405

    Used for: Supports measuring actual environmental conditions—rather than reporting equipment settings alone—to improve replicability and cross-scale interpretation.

    Evidence boundary: The paper proposes reporting practices and does not demonstrate Plant Teleport or define crop-specific tolerances.

    8. \n

  8. R70 Schuirmann, Donald J. (1987). A comparison of the Two One-Sided Tests Procedure and the Power Approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics, 15(6), 657–680. 10.1007/BF01068419

    Used for: Provides the classical two one-sided tests framework for evaluating whether an effect lies within predeclared equivalence margins.

    Evidence boundary: The method originated in bioequivalence; FlavoRotor must justify crop- and endpoint-specific margins, models and multiplicity handling before using it.

    9. \n

  9. R65 Rogers, Alistair; Dietz, Karl-Josef; Gifford, Miriam L.; Lunn, John E. (2021). The importance of independent replication of treatments in plant science. Journal of Experimental Botany, 72(15), 5270–5274. 10.1093/jxb/erab268

    Used for: Explains independent experimental units, randomisation and why pseudoreplication can invalidate treatment claims.

    Evidence boundary: It provides experimental-design requirements, not evidence that a FlavoRotor recipe has been replicated.

    10. \n

  10. R09 Senizza, Biancamaria; Zhang, Leilei; Miras-Moreno, Begoña; et al. (2020). The Strength of the Nutrient Solution Modulates the Functional Profile of Hydroponically Grown Lettuce in a Genotype-Dependent Manner. Foods. 10.3390/foods9091156

    Used for: Demonstrates that nutrient-strength responses may depend on genotype.

    Evidence boundary: A recipe cannot be assumed portable across cultivars or genetic material.

    11. \n

  11. R11 Thakulla, Dharti; Dunn, Bruce; Hu, Bizhen; Goad, Carla; Maness, Niels (2021). Nutrient Solution Temperature Affects Growth and °Brix Parameters of Seventeen Lettuce Cultivars Grown in an NFT Hydroponic System. Horticulturae. 10.3390/horticulturae7090321

    Used for: Shows cultivar-dependent responses to root-zone temperature.

    Evidence boundary: The tested NFT conditions and °Brix response do not define a universal transfer recipe.

    12. \n

  12. R14 Hutchinson, George Kerrigan; Nguyen, Lan Xuan; Ames, Zilfina Rubio; Nemali, Krishna; Ferrarezi, Rhuanito Soranz (2025). Substrate system outperforms water-culture systems for hydroponic strawberry production. Frontiers in Plant Science. 10.3389/fpls.2025.1469430

    Used for: Shows that cultivation-system architecture can materially change crop performance.

    Evidence boundary: A result from one root-zone architecture cannot be copied to another without a bridge experiment.

    13. \n

  13. R78 Porter, Amanda S.; Evans-Fitz.Gerald, Christiana; McElwain, Jennifer C.; Yiotis, Charilaos; Elliott-Kingston, Caroline (2015). How well do you know your growth chambers? Testing for chamber effect using plant traits. Plant Methods, 11, 44. 10.1186/s13007-015-0088-0

    Used for: Demonstrates that nominally identical controlled-environment chambers can produce chamber effects and supports independent sensing, pilot testing, randomisation and replicated experimental units.

    Evidence boundary: The study used Vicia faba in walk-in growth chambers; it does not quantify FlavoRotor unit-to-unit variability or property-transfer fidelity.

    14. \n

  14. R23 Papoutsoglou, E. A. et al. (2020). Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytologist. 10.1111/nph.16544

    Used for: Provides reusable metadata structures for investigations, studies, biological material and observed variables.

    Evidence boundary: Metadata interoperability does not prove biological equivalence.

    15. \n

  15. R24 Wilkinson, Mark D. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. 10.1038/sdata.2016.18

    Used for: Defines findable, accessible, interoperable and reusable data principles.

    Evidence boundary: FAIR data can make a recipe reusable, but does not make its biological result automatically reproducible.

    16. \n

  16. R38 Joint Committee for Guides in Metrology (2008). Evaluation of measurement data — Guide to the expression of uncertainty in measurement. JCGM 100:2008. 10.59161/JCGM100-2008E

    Used for: Defines measurement uncertainty and uncertainty propagation.

    Evidence boundary: It provides a measurement framework, not crop-specific tolerances.

    17. \n

  17. R39 Joint Committee for Guides in Metrology (2012). International vocabulary of metrology — Basic and general concepts and associated terms. JCGM 200:2012. 10.59161/JCGM200-2012

    Used for: Defines calibration, accuracy, precision, repeatability and related terms.

    Evidence boundary: Metrology vocabulary does not define a transferable flavour profile.

    18. \n

  18. R43 International Organization for Standardization (2017). ISO/IEC 17025:2017 General requirements for the competence of testing and calibration laboratories. ISO/IEC. https://www.iso.org/standard/66912.html

    Used for: Supports traceable testing, calibration, method control and records.

    Evidence boundary: Use of an external laboratory must not imply accreditation outside its verified scope.

    19. \n

  19. R66 Annunziata, Maria Grazia; Apelt, Federico; Carillo, Petronia; et al. (2017). Getting back to nature: a reality check for experiments in controlled environments. Journal of Experimental Botany, 68(16), 4463–4477. 10.1093/jxb/erx220

    Used for: Demonstrates that natural sunlight and artificial controlled-light regimes can produce different metabolic profiles even when important lighting features are approximated.

    Evidence boundary: The study used Arabidopsis and does not quantify FlavoRotor-to-greenhouse flavour transfer.

    20. \n

  20. R68 Heuermann, Marc C.; Knoch, Dominic; Junker, Astrid; Altmann, Thomas (2023). Natural plant growth and development achieved in the IPK PhenoSphere by dynamic environment simulation. Nature Communications, 14, 5783. 10.1038/s41467-023-41332-4

    Used for: Shows the value of reproducing time-varying environmental trajectories rather than only static averages when bridging controlled and natural conditions.

    Evidence boundary: The work concerns maize development in the IPK PhenoSphere; it does not demonstrate hydroponic aroma equivalence or FlavoRotor greenhouse transfer.

    21. \n

  21. R41 International Organization for Standardization (2016). ISO 13299:2016 Sensory analysis — Methodology — General guidance for establishing a sensory profile. International Standard. https://www.iso.org/standard/58042.html

    Used for: Supports structured sensory-attribute and intensity profiling.

    Evidence boundary: A sensory profile must still be defined for each crop, product and claim.

    22. \n

  22. R73 International Organization for Standardization (2023). ISO 8586:2023 Sensory analysis — Selection and training of sensory assessors. International Standard. https://www.iso.org/standard/76667.html

    Used for: Defines criteria and procedures for selecting and training trained and expert sensory assessors.

    Evidence boundary: Training assessors improves method control; it does not guarantee that two plant samples are sensorially equivalent.

    23. \n

  23. R75 International Organization for Standardization (2017). ISO 6658:2017 Sensory analysis — Methodology — General guidance. International Standard. https://www.iso.org/standard/65519.html

    Used for: Provides general guidance on sensory tests and the statistical treatment of sensory-analysis results.

    Evidence boundary: It does not prescribe a universal Plant Teleport experiment or guarantee outcome equivalence.

    24. \n

  24. R76 International Organization for Standardization (2008). ISO 5492:2008 Sensory analysis — Vocabulary. International Standard, with Amendment 1:2016. https://www.iso.org/standard/38051.html

    Used for: Defines sensory-analysis terminology relating to senses, organoleptic attributes and methods.

    Evidence boundary: Vocabulary alignment improves semantic precision but does not create experimental evidence.

    25. \n

  25. R77 International Organization for Standardization (2014). ISO 11136:2014 Sensory analysis — Methodology — General guidance for conducting hedonic tests with consumers in a controlled area. International Standard, with Amendment 1:2020. https://www.iso.org/standard/50125.html

    Used for: Provides guidance for measuring consumer liking and preference under controlled conditions.

    Evidence boundary: Consumer liking is distinct from descriptive sensory equivalence and must not replace chemical or trained-panel evidence.

    26. \n

  26. R74 International Organization for Standardization (2007). ISO 8589:2007 Sensory analysis — General guidance for the design of test rooms. International Standard, with Amendment 1:2014. https://www.iso.org/standard/36385.html

    Used for: Provides guidance for sensory test-room design and separation of testing, preparation and support areas.

    Evidence boundary: The standard is under revision and does not define crop-specific attributes, assessors or equivalence margins.

    27. \n

  27. R50 International Organization for Standardization (2025). ISO 5725-2:2025 Accuracy (trueness and precision) of measurement methods and results — Part 2: Basic method for the determination of repeatability and reproducibility of a standard measurement method. International Standard. https://www.iso.org/standard/90054.html

    Used for: Supports estimation of repeatability and reproducibility of measurement methods.

    Evidence boundary: Measurement-method reproducibility is distinct from biological recipe reproducibility.

    28. \n

  28. R46 Heckert, N. Alan; Filliben, James J.; Croarkin, C. M.; et al. (2002). NIST/SEMATECH e-Handbook of Statistical Methods. NIST Handbook 151. https://www.nist.gov/publications/handbook-151-nistsematech-e-handbook-statistical-methods

    Used for: Supports experimental design, calibration regression, residual analysis and statistical process control.

    Evidence boundary: The handbook does not define biologically meaningful equivalence margins for FlavoRotor.

    29. \n

  29. R17 Vought, Kelsey; Bayabil, Haimanote K.; Pompeo, Jean; Crawford, Daniel; Zhang, Ying; Correll, Melanie; Martin-Ryals, Ana (2024). Dynamics of micro and macronutrients in a hydroponic nutrient film technique system under lettuce cultivation. Heliyon. 10.1016/j.heliyon.2024.e32316

    Used for: Supports the statement that bulk EC does not uniquely specify individual ion concentrations.

    Evidence boundary: NFT lettuce nutrient dynamics are not numerically transferable to every reservoir and crop.

    30. \n

  30. R72 Hutchinson, George Kerrigan; Nguyen, Lan Xuan; Rubio Ames, Zilfina; Nemali, Krishna; Ferrarezi, Rhuanito Soranz (2025). Sensor-controlled fertigation management for higher yield and quality in greenhouse hydroponic strawberries. Frontiers in Plant Science, 15, 1469434. 10.3389/fpls.2024.1469434

    Used for: Demonstrates that sensor-coupled fertigation strategies can be evaluated for yield, quality and resource use in greenhouse hydroponic strawberry production.

    Evidence boundary: The study concerns specified cultivars, substrate, sensors and management strategies; it does not prove FlavoRotor-to-greenhouse aroma transfer.

    31. \n

  31. R79 Brentarolli, Elia; Locatelli, Silvia; Nicoletto, Carlo; Sambo, Paolo; Quaglia, Davide; Muradore, Riccardo (2024). A spatio-temporal methodology for greenhouse microclimatic mapping. PLOS ONE, 19(9), e0310454. 10.1371/journal.pone.0310454

    Used for: Supports temporary dense sensing, spatial modelling and greenhouse microclimate mapping when a single environmental average is insufficient.

    Evidence boundary: The paper presents a greenhouse mapping methodology; it does not define FlavoRotor sensor placement, aroma equivalence or a universal number of greenhouse zones.

    32. \n
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\n","text":"Plant Teleport Replicate a validated cultivation result on another calibrated FlavoRotor and translate it to a greenhouse by transferring measured plant-level exposure targets, not machine-specific commands. SCIENTIFIC CONCLUSION The Plant Teleport architecture is technically feasible because its components-calibration, machine-independent recipes, environmental sensing, local control, metadata, independent replication and equivalence testing-are established engineering and scientific methods. What remains to be demonstrated experimentally is the achievable fidelity for each crop, property, machine pair and greenhouse implementation. CURRENT FLAVOROTOR STATUS The public FlavoRotor record defines the transfer framework but does not yet contain a completed cross-unit or greenhouse dataset demonstrating equivalent chemical and sensory outcomes. No figure in this article is presented as measured Plant Teleport performance unless it is explicitly labelled as measured data. ## Executive conclusion Plant Teleport builds on established engineering and scientific methods. A digital recipe can store calibrated physical targets, another system can compile those targets into its own actuator commands, and the delivered environment can be measured. Modern controlled-environment systems already combine sensors, actuators, time-varying targets and model-based control. [R69] Published plant research also demonstrates that controlled cultivation inputs can change quality-related plant chemistry and sensory-relevant outcomes under specified conditions. [R01] [R71] The difficult and scientifically valuable part is not sending the file. It is proving that the destination produced a sufficiently equivalent plant outcome. Therefore, the strongest accurate statement is: > **FlavoRotor can provide the infrastructure required to encode, translate, execute and validate portable cultivation recipes. The fidelity of a particular aroma, taste, colour or texture must then be established by independent cross-system measurements.** This converts a broad development goal into a structured research programme with defined validation milestones and concrete product architecture. PT-F15 · FRAMEWORK Evidence boundary Design, external support and FlavoRotor results must not be conflated. Does not show: Any current Plant Teleport experimental result. Sources: [I01] [I02] [R64] [R67] [R69] [R70] ## Engineering feasibility decision **Decision: technically feasible as an architecture; experimentally unverified for crop-specific property fidelity.** The required operations are established independently: measure physical exposure, calibrate actuators, store versioned metadata, translate targets to local hardware, operate closed-loop control, identify independent experimental units and test a predefined equivalence hypothesis. [R69] [R65] [R70] The remaining uncertainty is empirical rather than conceptual: how closely a particular destination can reproduce a specified chemical, physical or sensory profile for a named cultivar and recipe version. This decision creates two non-interchangeable statements: | Statement | Status | |---|---| | A calibrated destination can attempt to reproduce machine-independent physical targets. | Engineering architecture supported. | | A specific aroma, taste or texture will be equivalent after transfer. | Must be demonstrated for the stated scope. | PT-F20 · FRAMEWORK Compatibility matrix Transfer scope depends jointly on biological and hardware compatibility. Does not show: A quantified probability of success or universal compatibility rule. Sources: [R09] [R11] [R14] [R64] [R78] ## In plain terms Plant Teleport is FlavoRotor’s name for **evidence-gated recipe portability**. It does not mean that a plant or molecule is literally transported. A source FlavoRotor records: - the biological material; - the time-indexed environment experienced by the plant; - the machine and calibration version; - the harvest and post-harvest protocol; - the measured chemical, physical and sensory result; - the uncertainty, deviations and evidence level. A destination system receives that package and determines whether it can reproduce the required physical targets. It then calculates its own commands, runs the cultivation under measurement and repeats the outcome analysis. PT-F01 · FRAMEWORK Plant Teleport transfer architecture Machine-independent targets can be translated into local commands and verified. Does not show: A measured cross-unit or greenhouse success rate. Sources: [I01] [I02] [R23] [R24] [R38] [R39] [R67] [R69] The product interaction can still be simple: PT-F11 · FRAMEWORK One-click workflow A single user action can orchestrate a rigorous workflow. Does not show: A guaranteed successful outcome from one action. Sources: [R38] [R39] [R43] [R65] A single click may start the workflow. It cannot legitimately skip compatibility, calibration, biological variation or validation. ## Canonical terminology and units Plant Teleport uses one canonical meaning for each term so a human, controller and LLM interpret the recipe consistently. | Term | Canonical meaning | |---|---| | **Command** | Machine-specific instruction such as PWM duty, valve time or motor setpoint. | | **Target** | Desired physical quantity at a named plant or system location. | | **Measured exposure** | Time- and position-resolved quantity actually observed during cultivation. | | **Recipe** | Versioned biological, environmental, procedural and evidence package. | | **Reference run** | Validated source execution against which a destination is compared. | | **Destination run** | Execution on another machine, site or cultivation architecture. | | **Property endpoint** | Predefined chemical, physical or sensory response used in the transfer decision. | | **Equivalence margin** | Largest acceptable difference for a named endpoint, justified before data review. | | **Bridge experiment** | Controlled comparison required when machine, site or cultivation architecture changes materially. | Canonical reporting uses physical units rather than percentages wherever possible: - PPFD in µmol·m⁻²·s⁻¹; - DLI in mol·m⁻²·d⁻¹; - temperature in °C; - relative humidity in % and VPD in kPa; - EC in mS/cm with temperature or compensation method; - pH with electrode and calibration record; - elemental concentration in mmol/L or mg/L with the named chemical species; - liquid delivery in mL or g; - rotational speed in rev/min or angular velocity in rad/s; - airflow in m/s at a defined canopy position. A percentage may remain as a local command in the destination log, but it is not the portable recipe quantity. ## Why FlavoRotor is structurally suited to recipe transfer The architecture is favourable for portability because FlavoRotor is conceived as one integrated research platform rather than a loose collection of manually operated equipment. According to the internal design records, it combines programmable lighting, nutrient dosing, pH and electrical-conductivity monitoring, temperature sensing, rotation, imaging and versioned software records. [I01] [I02] This integration offers five specific advantages. ### 1. Common timing Every relevant event can be represented on one time axis: lighting transitions, dosing, reservoir measurements, rotation, imaging and harvest. Cross-system transfer is substantially weaker when the records come from unrelated clocks or handwritten logs. ### 2. Calibration-backed actuation A recipe can refer to a physical target rather than an arbitrary interface percentage. Calibration and measurement uncertainty provide the bridge between the requested quantity and the local actuator. [R38] [R39] ### 3. Complete provenance The system can preserve the relationship between recipe version, hardware version, sensor calibration, plant lot, images, raw logs, analytical samples and conclusions. MIAPPE and FAIR principles provide relevant structures for making such data interpretable and reusable. [R23] [R24] ### 4. Closed-loop verification The destination can measure whether it is achieving the target instead of assuming that commands were delivered correctly. This is central to current recommendations for environmental reporting in plant research. [R67] ### 5. A natural path to a marketplace A recipe can be distributed together with its compatibility requirements, evidence level, supported crop material, required analyses and validated system scope. The marketplace object becomes a controlled technical specification rather than a vague promise. ## What “property transfer” means A property is a measured response. Examples include: - concentrations of selected volatile compounds; - a defined chemical fingerprint; - soluble solids or titratable acidity; - colour coordinates; - dry matter or firmness; - a trained-panel sensory profile; - a consumer-liking result, when the claim concerns preference rather than descriptive equivalence. Published studies show that lighting, nutrient supply, temperature and other pre-harvest conditions can influence quality-related responses in specified crops and conditions. [R01] [R09] [R11] [R71] Property transfer means: > Reproducing a predefined outcome profile within declared limits by reproducing the relevant plant-level exposure trajectory, biological material, developmental state, harvest procedure and measurement method. It does not mean exact identity between individual plants. Biological systems exhibit variation even under carefully standardised protocols. A ten-laboratory study demonstrated that dedicated standardisation can produce similar growth results across a core group of laboratories, while small environmental and handling differences can still affect phenotypes and metabolite profiles. [R64] PT-F09 · FRAMEWORK Causal stack for property fidelity Outcome fidelity depends on biology, exposure, architecture, timing, handling and measurement. Does not show: The relative effect size of each layer. Sources: [R09] [R11] [R14] [R64] [R66] [R67] ## The decisive distinction: target transfer versus command copying The transferable object must not be: ```text LED = 73% pump A = 12 seconds fan = 40% rotation motor = 35% ``` Those commands are properties of one machine. The transferable object should be closer to: ```text canopy spectral photon target = versioned time series PPFD and DLI target = measured at defined plant positions elemental nutrient formulation = named species and concentrations pH and EC = target trajectories with temperature and measurement method root-zone temperature and wetting cycle = defined physical exposure air temperature, RH, VPD and airflow = measured at defined locations rotation and mechanical exposure = encoder-verified schedule harvest state = objective biological and chronological criteria ``` The destination translates each target through its own calibrated hardware. PT-F02 · ILLUSTRATIVE - NOT FLAVOROTOR DATA Machine command decoupling Different machines can use different commands to deliver the same physical target. Does not show: Actual FlavoRotor pump flow, accuracy or drift. Sources: [R38] [R39] For a liquid target: PT-1 t pump = V target / Q cal Purpose: convert the required volume into a pump-specific nominal running time. Vtarget is the target volume and Qcal is the calibrated flow for that pump, tube, liquid and operating condition. DEFINITIONAL TRANSLATION - DELIVERY MUST STILL BE VERIFIED If two pumps deliver 2 mL/min and 5 mL/min, respectively, both can target 10 mL, but their nominal commands are 5 minutes and 2 minutes. The recipe remains constant while the commands change. ## The Plant Teleport contract A transferable recipe is a contract between the source evidence and the destination capability. ### A. Biological passport The recipe records: - species and cultivar; - seed lot, clone batch or other material identifier; - propagation method; - germination or rooting conditions; - developmental stage at each recipe transition; - plant density and position; - replacement and exclusion rules; - plant-health observations; - definition of the independent experimental unit. Cultivar cannot be treated as a cosmetic label. Nutrient-strength and temperature responses can depend on genotype. [R09] [R11] ### B. Time-indexed exposure targets The package stores trajectories, not only averages: - spectral photon distribution; - PPFD; - DLI; - photoperiod and light transitions; - air and leaf temperature; - relative humidity and VPD; - carbon dioxide where controlled or material; - source-water composition; - elemental nutrient formulation; - pH, EC and solution temperature; - dissolved oxygen where relevant; - irrigation, immersion, drainage and aeration timing; - air velocity; - rotation and mechanical stimulation; - stage transitions and harvest timing. Dynamic plant-environment research shows why a time-varying regime can be more informative than one static mean. [R68] ### C. Capability declaration The destination publishes: - controllable range; - measurable range; - resolution; - uncertainty; - spatial coverage; - sampling interval; - valid calibration; - actuation delay; - safety limits; - unsupported variables. The interface must refuse validated execution when a mandatory variable cannot be controlled or verified. ### D. Harvest and post-harvest protocol Chemical and sensory properties may change after harvest. The recipe therefore defines: - objective harvest state; - time of day; - sample position and mass; - washing, cutting or preparation; - storage temperature and duration; - delay before instrumental or sensory analysis; - random coding and blinding. ### E. Reference outcome fingerprint A single number called “aroma” is normally insufficient. The fingerprint can contain multiple primary and supporting endpoints. PT-F13 · FRAMEWORK Outcome fingerprint Sensory property transfer must use a declared multidimensional endpoint set. Does not show: Any universal weighting or measured FlavoRotor profile. Sources: [R01] [R41] [R71] [R73] [R75] [R76] [R77] Descriptive sensory profiling, assessor selection, sensory-room control and general sensory methodology should follow defined methods. [R41] [R73] [R74] [R75] Sensory vocabulary should be standardised. [R76] Consumer liking is a different question from descriptive equivalence and requires an appropriate consumer test. [R77] ### F. Provenance and evidence Every claim links to raw and processed records. PT-F10 · FRAMEWORK Data provenance A claim should be traceable to raw data, calibrations, analysis and scope. Does not show: Current completeness of FlavoRotor public datasets. Sources: [R23] [R24] [R38] [R39] [R43] ## Transfer status PT0–PT5 PT-F04 · FRAMEWORK Plant Teleport evidence ladder Claims increase only when independent evidence increases. Does not show: Current achievement of any PT2–PT5 status. Sources: [R43] [R50] [R64] [R65] | Level | Name | Minimum meaning | Public wording | |---|---|---|---| | PT0 | Saved recipe | The source recipe and evidence package are complete. | “Recorded on the originating system.” | | PT1 | Repeated | Independent cycles on the same source system support the declared direction and variability. | “Repeated on the originating FlavoRotor.” | | PT2 | Cross-unit replicated | A second calibrated FlavoRotor meets the environmental and outcome criteria. | “Replicated on another calibrated FlavoRotor.” | | PT3 | Cross-location reproduced | PT2 is extended to another site with local water, room and handling effects addressed. | “Reproduced at another site under the stated conditions.” | | PT4 | System translated | A greenhouse or different cultivation architecture passes a bridge experiment. | “Translated and validated for greenhouse/system X.” | | PT5 | Independently verified | An independent partner executes and analyses the registered protocol. | “Independently verified within the published scope.” | The evidence burden increases as hardware, location and cultivation architecture diverge. PT-F05 · FRAMEWORK Transfer envelope Increasing system and environmental differences require stronger bridge validation. Does not show: A quantified probability of success. Sources: [R14] [R64] [R66] [R67] ## Recipe compiler architecture The compiler performs a preflight before the run button is enabled. ### Preflight gates 1. **Biological compatibility** - the correct cultivar and material identifier are available. 2. **Range compatibility** - the destination can reach every mandatory target. 3. **Measurement compatibility** - the destination can verify those targets at the required location and frequency. 4. **Calibration validity** - all mandatory sensors and actuators have valid calibration records. 5. **Method compatibility** - the required harvest, laboratory and sensory methods are available. 6. **Safety compatibility** - target and abort rules are compatible with the destination. 7. **Evidence compatibility** - the requested public claim does not exceed the available validation level. 8. **Licence compatibility** - the recipe version and permitted use are valid. The result is one of four states: - **compatible**; - **compatible with declared adaptation**; - **research-only**; - **incompatible**. PT-F12 · FRAMEWORK Transfer release decision Release status follows compatibility, exposure and outcome gates. Does not show: A current pass/fail result. Sources: [R43] [R46] [R65] [R70] ### Subsystem translation PT-F16 · FRAMEWORK Subsystem translation Recipe portability is implemented as calibrated translation for each subsystem. Does not show: That all listed subsystems are already fully validated on FlavoRotor. Sources: [I01] [I02] [R17] [R38] [R39] [R67] [R69] [R72] A recent digital-twin framework demonstrates that vendor-agnostic sensor/actuator mapping, model calibration, dynamic targets and adaptive control are technically implementable in controlled-environment agriculture. Its published case study is simulation-based, so it supports the software architecture rather than proving physical Plant Teleport performance. [R69] ## Measuring exposure fidelity For controlled quantity j : PT-2 e j (t) = y j (t) − r j (t) Purpose: compute instantaneous tracking error. yj(t) is the measured value; rj(t) is the target at the same time and location. MEASUREMENT DEFINITION PT-3 q j (t) = |e j (t)| / Δ j Purpose: normalise the error by the preregistered tolerance Δj. q ≤ 1 means the observation is inside the declared tolerance. NORMALISED COMPLIANCE METRIC - NOT A BIOLOGICAL RESULT PT-4 P j = 100 · ΣI(q j ≤ 1) / N Purpose: report the percentage of valid observations inside tolerance. N is the number of valid observations; I is an indicator equal to one when the condition is true. CONTROL-PERFORMANCE SUMMARY The acceptance value for P j , excursion duration and safety limits must be established by protocol. No universal percentage is claimed. PT-F03 · ILLUSTRATIVE - NOT FLAVOROTOR DATA Exposure fidelity over time Transfer requires time-resolved exposure compliance, not matching a single average. Does not show: Any measured FlavoRotor trajectory or tolerance. Sources: [R38] [R39] [R67] [R68] Environmental compliance is necessary but not sufficient. A destination can reproduce the target environment and still obtain a different biological result because of seed material, microbiology, developmental timing or unmeasured differences. A valid transfer therefore uses a conjunctive decision: PT-5 G transfer = G biology ∧ G exposure ∧ G method ∧ G outcome Purpose: express that a validated transfer requires every mandatory gate to pass. The logical AND symbol means that one failed critical gate prevents the full claim. DECISION LOGIC - NOT A CONTINUOUS PERFORMANCE SCORE ## Uncertainty-aware environmental compliance A measured value close to a tolerance boundary cannot be treated as an unquestioned pass when measurement uncertainty overlaps that boundary. Calibration, uncertainty and acceptance must therefore be connected. [R38] [R39] [R43] For a measured estimate y j , target r j , tolerance Δ j , standard uncertainty u j and chosen coverage factor k , a conservative guard-band rule can be written as: PT-5A |y j − r j | + k·u j ≤ Δ j Purpose: require the measured deviation plus the declared uncertainty allowance to remain inside the tolerance. The coverage factor and decision rule must be specified by the protocol; they are not universal constants. ILLUSTRATIVE GUARD-BAND RULE BASED ON METROLOGY PRINCIPLES **Illustrative example.** A target is 22.0 °C with a tolerance of ±0.5 °C. The measured estimate is 22.3 °C and the standard uncertainty is 0.1 °C. If the protocol uses k = 2, the guarded deviation is 0.3 + 2 × 0.1 = 0.5 °C, exactly at the declared limit. This example explains the rule; it is not a FlavoRotor acceptance specification. PT-F17 · ILLUSTRATIVE - NOT FLAVOROTOR DATA Uncertainty-aware environmental acceptance Measurement uncertainty should be included in the environmental acceptance rule. Does not show: A universal coverage factor, tolerance or measured FlavoRotor uncertainty. Sources: [R38] [R39] [R43] The environmental report must distinguish: - target uncertainty or allowable biological tolerance; - instrument calibration uncertainty; - spatial sampling uncertainty; - temporal interpolation uncertainty; - missing data; - actuator-delivery uncertainty. A recipe should not declare a tolerance narrower than the destination can credibly measure and control. ## Translation by physical domain ### Light The recipe stores spectrum, intensity, distribution and timing at plant level. For a constant PPFD interval: PT-6 DLI = PPFD · τ · 10 −6 Purpose: convert PPFD in µmol·m⁻²·s⁻¹ over duration τ in seconds into DLI in mol·m⁻². For variable light, integrate the measured PPFD time series. PHOTON-EXPOSURE DEFINITION Matching DLI alone is insufficient when spectrum, spatial distribution or within-day trajectory differs. Artificial and natural lighting can produce different metabolic responses even when important lighting characteristics are approximated. [R66] ### Nutrient composition EC is an aggregate conductivity measurement, not an ion-specific recipe. Different ion mixtures can produce similar EC, and recirculating systems can change individual nutrient concentrations. [R17] The portable recipe therefore stores: - source-water analysis; - named nutrient species; - stock formulation; - intended elemental concentrations; - pH and EC trajectories; - reservoir volume and replacement rules; - mixing verification; - analytical checkpoints where necessary. ### Root-zone exposure A rotating hydroponic system and a greenhouse substrate system do not expose roots identically. Translation must consider: - contact or irrigation duration; - drainage; - oxygen availability; - root-zone temperature; - solution movement; - biofilm and sanitation; - water-holding properties of the destination medium. Cultivation-system comparisons show that system architecture can materially alter crop performance. [R14] ### Air and leaf environment Canopy air temperature is not always leaf temperature. Room relative humidity is not necessarily canopy humidity. The transfer protocol therefore defines sensor placement and records temperature, humidity, VPD, airflow and carbon dioxide when relevant. ### Mechanical and rotation exposure Rotation can simultaneously affect watering, orientation and mechanical stimulation. If rotation is part of a validated treatment, the destination must separate: - root wetting caused by rotation; - light-exposure geometry; - mechanical stimulus; - air movement; - position-dependent effects. A greenhouse child recipe may reproduce the relevant physical exposure through different hardware, but this requires a bridge experiment rather than semantic relabelling. ### Camera and plant-state alignment A camera can support transfer by detecting: - germination and establishment; - leaf area; - canopy coverage; - colour changes; - growth rate; - visible stress; - developmental transitions; - positional non-uniformity. The camera does not directly measure taste or aroma. It can align recipe stages and detect deviations that would otherwise make two runs biologically incomparable. The imaging algorithm, model version, confidence threshold and manual-audit rule become part of the recipe record. ## Cross-unit replication protocol The first demonstration should use two FlavoRotor systems of the same supported hardware generation. ### Required design - frozen recipe and analysis plan; - one cultivar and traceable material lot; - independent biological units; - randomised plant positions; - multiple independent cultivation cycles; - calibrated light, dosing, environmental and rotation subsystems; - predefined primary endpoints; - matched harvest and post-harvest methods; - full deviation reporting. The number of plants and cycles cannot be selected by a universal rule. It must be calculated using pilot variability, the justified equivalence margin, desired power and the actual experimental-unit structure. Pseudoreplication must be avoided. Multiple leaves from one plant or several plants sharing one unreplicated environment do not automatically represent independent treatment units. [R65] PT-F14 · ILLUSTRATIVE - NOT FLAVOROTOR DATA Independent replication and blocking Reference and destination units should be independently replicated and spatially blocked. Does not show: A required sample size or actual FlavoRotor layout. Sources: [R65] ### Minimum reports - calibration report for both units; - empty-system spatial and temporal map; - source and destination exposure comparison; - biological baseline; - chemical and physical results; - sensory report when sensory equivalence is claimed; - statistical analysis; - raw dataset and analysis code; - failed or excluded units with reasons. ## Cross-location reproduction Another country or room introduces additional variables: - local water chemistry; - ambient temperature and humidity; - electrical and maintenance differences; - operator handling; - sample transport; - laboratory method and instrument; - sensory language and panel context. A cross-location transfer should use either the same analysis laboratory or a documented inter-laboratory method comparison. Measurement-method reproducibility and biological reproducibility must remain distinct. [R50] ## Greenhouse scale translation A greenhouse is not a physically enlarged FlavoRotor. It is a new cultivation architecture exposed to sunlight, weather disturbances, spatial gradients and different root-zone dynamics. The correct process is: 1. map the greenhouse; 2. define controllable zones; 3. measure plant-level conditions; 4. compile supplemental controls; 5. run a bridge experiment; 6. compare outcomes; 7. release a greenhouse-specific child recipe. PT-F06 · FRAMEWORK Greenhouse zone translation Greenhouse transfer must be measured and compiled per zone. Does not show: The number, dimensions or performance of a real greenhouse. Sources: [R66] [R67] [R68] [R69] [R72] ### Spatial mapping and sensor placement A greenhouse average is not a plant-level exposure record. Light, temperature, humidity and airflow can vary across positions, and controlled chambers can also exhibit spatial or chamber effects. [R78] Greenhouse mapping methods likewise begin from spatial measurements rather than assuming homogeneity. [R79] The recommended workflow is: 1. deploy a temporary dense sensor grid during representative operating periods; 2. quantify spatial and temporal gradients at canopy and root-zone locations; 3. identify zones that can be controlled as coherent units; 4. select representative permanent sensors; 5. validate the reduced sensor arrangement against the dense map; 6. repeat mapping after material changes in crop height, layout, season, glazing, airflow or equipment. PT-F18 · FRAMEWORK Greenhouse mapping strategy Greenhouse translation should begin with measured spatial mapping and validated operational zones. Does not show: A universal sensor count, zone layout or mapping accuracy. Sources: [R67] [R79] The number of sensors is an experimental design decision. Plant Teleport does not prescribe a universal sensor density. ### Supplemental light balance PT-7 DLI supp = max(0, DLI target − DLI sun,usable ) Purpose: estimate the daily supplemental photon amount after measured usable sunlight is credited. Spectrum, timing, distribution and plant state remain separate matching requirements. FIRST-ORDER BALANCE - NOT A COMPLETE GREENHOUSE TRANSLATION If the target DLI is 16 mol·m⁻²·d⁻¹ and measured usable sunlight contributes 10 mol·m⁻²·d⁻¹, the first-order supplement is 6 mol·m⁻²·d⁻¹. These numbers are an explanatory example, not a FlavoRotor crop recommendation. ### Zone control Each zone converts physical targets into its own: - supplemental-light schedule; - fertigation events; - nutrient-stock commands; - heating, cooling and ventilation; - humidification or dehumidification; - airflow; - carbon-dioxide control where used; - alarms and recovery rules. Sensor-controlled fertigation can be evaluated in greenhouse hydroponic production using quality, yield and resource-use outcomes. [R72] This supports the practical feasibility of local sensor-to-actuator control; it does not prove transfer of a FlavoRotor aroma profile. ### Bridge experiment The greenhouse bridge includes: - validated source condition; - translated greenhouse condition; - spatial blocks and independent units; - repeated production periods; - matched cultivar and biological material; - same primary analytical endpoints; - matched harvest and post-harvest handling; - blinded sensory method when sensory equivalence is claimed; - a declared acceptable loss if strict equivalence is not the intended objective. The greenhouse child recipe receives a new identifier. PT-F08 · FRAMEWORK Recipe lineage Every transfer creates a traceable child record and report. Does not show: Actual released FlavoRotor recipes. Sources: [R23] [R24] ## Chemical and sensory confirmation A chemical difference can exist without a perceptible sensory difference. A sensory difference can also reflect compounds not included in a narrow targeted analysis. Plant Teleport therefore treats chemical and sensory evidence as complementary. ### Three property-claim tiers “Same aroma” is ambiguous unless the evidence domain is named. PT-F19 · FRAMEWORK Property claim tiers A precise transfer claim must identify whether it concerns chemistry, descriptive sensory attributes or consumers. Does not show: That success at one tier guarantees success at another. Sources: [R01] [R41] [R73] [R74] [R75] [R76] [R77] - **Tier A - chemical and physical profile:** selected volatile compounds, non-volatile chemistry, colour or texture meet predefined analytical criteria. - **Tier B - descriptive sensory equivalence:** trained assessors produce equivalent intensities for predefined attributes under a controlled protocol. - **Tier C - consumer response:** a stated consumer population does not detect a relevant difference or shows comparable liking under the chosen design. A recipe may pass one tier and fail another. Chemical similarity does not prove perceptual equivalence, and comparable liking does not prove chemical identity. ### Chemical layer Depending on the claim: - targeted volatile compounds; - broader volatile fingerprint; - sugars and organic acids; - pigments; - minerals; - dry matter; - compounds linked to pungency, bitterness or aroma; - method uncertainty and quality-control samples. ### Physical layer - colour coordinates; - firmness; - fracture or compression response; - water content; - structural measurements. ### Descriptive sensory layer A trained panel may profile intensity of defined attributes. Panel recruitment and training, test-room conditions, vocabulary, sample preparation and analysis must be documented. [R41] [R73] [R74] [R75] [R76] ### Consumer layer Consumer liking is not proof of descriptive equivalence. It answers whether a defined consumer population prefers or accepts the samples. [R77] ## How equivalence is decided A result is not equivalent merely because a difference was not statistically significant. Insufficient sample size can produce a non-significant result even when important differences remain. For one continuous primary endpoint: PT-8 CI 90% (μ D − μ R ) ⊂ [−Δ, +Δ] Purpose: declare equivalence only when the complete confidence interval for the destination-minus-reference effect lies inside the predeclared equivalence interval. Δ must be justified before data review. CLASSICAL TWO ONE-SIDED TESTS FRAMEWORK PT-F07 · ILLUSTRATIVE - NOT FLAVOROTOR DATA Equivalence decision examples A complete confidence interval must lie inside a justified equivalence margin. Does not show: A FlavoRotor margin, sample size or measured effect. Sources: [R46] [R70] For multiple endpoints: - primary endpoints are declared in advance; - every essential endpoint must satisfy its criterion; - multiplicity is handled in the analysis plan; - yield and plant-health guardrails cannot be ignored; - chemical and sensory evidence are not substituted for one another; - exploratory endpoints remain labelled exploratory; - missing-data and outlier rules are preregistered. There is no universal ±10% aroma margin. Each margin must be justified using measurement capability, baseline biological variation and the intended product claim. ## Exact research programme ### Experiment PT-E01 - same-machine repeatability **Question:** Can one frozen recipe be executed across independent cycles on one FlavoRotor with stable exposure and outcome variability? **Outputs:** PT1 recipe, calibration bundle, baseline variance, endpoint shortlist. ### Experiment PT-E02 - second-unit replication **Question:** Can a second calibrated FlavoRotor independently reproduce the required exposure trajectory and primary outcome profile? **Outputs:** PT2 transfer report, command-translation comparison, failed-variable analysis. ### Experiment PT-E03 - cross-location reproduction **Question:** Does the recipe remain equivalent when executed at another site after water, room, operator and analytical differences are controlled? **Outputs:** PT3 report, site adaptation record, inter-laboratory method check where necessary. ### Experiment PT-E04 - greenhouse pilot bridge **Question:** Can a defined greenhouse zone reproduce the relevant physical exposure and outcome endpoints? **Outputs:** zone map, greenhouse child recipe, PT4 report or documented non-equivalence. ### Experiment PT-E05 - independent verification **Question:** Can an independent partner execute the frozen package without unpublished assistance and obtain the declared result? **Outputs:** PT5 report, independent raw data, audit of ambiguities and required clarifications. This programme creates a direct sequence from prototype engineering to a commercially meaningful validated recipe network. ## Marketplace and licensing model A recipe listing should display: - crop and cultivar; - version and lineage; - status PT0–PT5; - supported machine versions; - supported location or greenhouse scope; - required biological material; - mandatory cartridges and analysis; - primary outcome endpoints; - equivalence scope; - known unsupported transfers; - licence terms; - linked reports and datasets. A buyer should be able to distinguish: - **recipe available**; - **validated on source unit**; - **replicated on another unit**; - **translated to named greenhouse**; - **independently verified**. This evidence structure is commercially favourable because it converts trust from a marketing statement into a visible product attribute. ## Recipe integrity, signing and marketplace trust Portability creates a new engineering risk: a valid recipe can become unsafe or scientifically misleading if its file, evidence status or calibration requirements are altered. Every released package should therefore include: - immutable recipe ID and semantic version; - parent recipe ID and lineage; - SHA-256 checksums for recipe, data and analysis files; - signer identity and signature method; - creation and expiry or review date; - supported hardware and cultivar scope; - minimum calibration bundle; - exact PT status and linked reports; - revoked and superseded status; - licence and permitted-use metadata. The destination must reject or downgrade a run when: - the signature or checksum fails; - the recipe version is revoked; - required calibration is expired; - source IDs resolve to different records; - mandatory variables are unavailable; - the requested claim exceeds the recipe’s evidence status. A marketplace rating is not scientific evidence. User feedback can identify usability problems, but PT status can change only through the declared validation records. ## LLM and machine-readable interpretation The machine-readable record must state explicitly: ```json { \"claim_status\": \"framework_not_yet_demonstrated_by_public_transfer_dataset\", \"portable_object\": \"plant_level_physical_targets_plus_biological_and_evidence_metadata\", \"does_not_establish\": [ \"identical flavour guaranteed worldwide\", \"equivalence from copied device settings\", \"transfer across cultivars without validation\", \"completed greenhouse transfer\" ] } ``` Every visual record states: - whether it is a framework, an illustrative example or measured data; - the exact claim it supports; - what it does not show; - its source IDs. This prevents an LLM from converting a conceptual graph into an experimental result. ## Failure modes and safeguards | Failure mode | Consequence | Required safeguard | |---|---|---| | Same interface percentages, different physical exposure | False portability | Store physical targets and calibrations | | Same EC, different ion balance | Different nutrient treatment | Store elemental formulation and water chemistry | | Same average DLI, different spectrum or trajectory | Different plant response | Store spectrum and time-resolved light | | Same cultivar name, different lot or propagation | Different starting biology | Biological passport | | One chamber per treatment | Treatment confounded with chamber | Independent units and valid blocking | | Greenhouse average hides spatial zones | Unmeasured local exposure | Canopy-level zone mapping | | Different harvest maturity | Different chemistry and texture | Objective harvest state | | Different post-harvest handling | Altered aroma or texture | Frozen sample-handling protocol | | “No significant difference” used as equivalence | False positive claim | Predeclared margins and equivalence analysis | | Simulation presented as physical validation | Evidence inflation | Explicit model status and bridge experiment | | Only successful transfers published | Biased marketplace | Retain failure and inconclusive records | | New hardware inherits old status | Invalid lineage | New version and transfer report | ## Evidence boundary Published research supports that: - controlled pre-harvest conditions can influence horticultural quality-related traits; [R01] [R71] - standardisation can improve cross-laboratory reproducibility, while residual site effects remain; [R64] - actual environmental measurement is essential for interpretation and repeatability; [R67] - dynamic environmental trajectories can be reproduced in controlled infrastructure; [R68] - digital-twin and adaptive-control architectures can integrate heterogeneous sensors and actuators; [R69] - sensor-coupled greenhouse fertigation is technically practical; [R72] - independent replication and equivalence methods are established scientific tools. [R65] [R70] The public FlavoRotor evidence does not yet establish: - equivalent aroma on two physical FlavoRotor units; - cross-country reproduction of a measured property profile; - a validated greenhouse child recipe; - universal compatibility or equivalence margins; - identical sensory results from a downloaded file. ## Questions the completed research must answer 1. Which measured properties are stable enough to become primary transfer endpoints? 2. What fraction of variability comes from machine delivery, biological material, site and analysis? 3. Which variables must be matched exactly and which can be compensated? 4. How far can hardware versions differ before a bridge experiment is required? 5. Can camera-derived plant state improve recipe-stage alignment and outcome fidelity? 6. Which crops are best suited to initial cross-unit validation? 7. What equivalence margins are scientifically and commercially meaningful? 8. How much greenhouse zoning is necessary for a stable child recipe? 9. Can failed transfers be used to improve the recipe compiler? 10. What evidence badge is understandable to consumers without overstating certainty? ## Definition of done for the first credible Plant Teleport demonstration The first public PT2 claim is complete only when all of the following are available: - two independently calibrated physical FlavoRotor units; - a frozen recipe and biological material identifier; - a preregistered design with a correctly identified experimental unit; - independent cycles and positional randomisation; - empty-system light, temperature, solution and rotation maps; - source and destination exposure logs; - a declared primary chemical or physical endpoint; - a defined sensory method if sensory equivalence is claimed; - justified equivalence margins; - raw and processed datasets; - versioned analysis code; - calibration, replication and deviation reports; - a public result classified as passed, failed or inconclusive. A failed or inconclusive first transfer remains valuable. It reveals which part of the portable specification or local compiler requires improvement and prevents premature commercial claims. ## Final definition > **Plant Teleport is FlavoRotor’s evidence-gated system for moving a validated cultivation specification between calibrated machines and into larger controlled environments. It transfers time-indexed plant exposure targets, biological material definitions, harvest rules and an outcome fingerprint; compiles those targets into local commands; verifies the delivered environment; and releases a replication or scale-transfer claim only after independent measurements meet preregistered criteria.** The transferable asset is a validated specification and evidence chain. The ambition is clear and technically credible: > **Create a plant property profile once, validate it rigorously, reproduce it on another calibrated FlavoRotor, and translate it to commercial cultivation with measured and published fidelity.** Article bibliography Sources used on this page R69 Frontzek, Julius; Wagner, Zühal; Streif, Stefan (2026). Dynamic, adaptive and modular Digital Twin framework for resource-efficient Controlled Environment Agriculture. Frontiers in Plant Science, 17, 1864757 . 10.3389/fpls.2026.1864757 Used for: Supports vendor-agnostic sensor and actuator integration, dynamic target trajectories, model calibration and adaptive control as an architecture for translating targets to local equipment. Evidence boundary: Its case study is simulation-based and uses synthetic data; physical, sensory and cross-facility recipe transfer remain unvalidated. R01 Hammock, Hunter A.; Sams, Carl E. (2023). Variation in supplemental lighting quality influences key aroma volatiles in hydroponically grown 'Italian Large Leaf' basil. Frontiers in Plant Science . 10.3389/fpls.2023.1184664 Used for: Shows that a defined spectral treatment can alter selected aroma-related volatile measurements in one named hydroponic basil cultivar. Evidence boundary: It does not demonstrate that the result transfers to another cultivar, machine, location or greenhouse. R71 Zhao, Xinyi; Peng, Jie; Zhang, Li; et al. (2024). Optimizing the quality of horticultural crop: insights into pre-harvest practices in controlled environment agriculture. Frontiers in Plant Science, 15, 1427471 . 10.3389/fpls.2024.1427471 Used for: Reviews how pre-harvest manipulation of nutrients, light and other controlled-environment factors can affect horticultural quality, including colour, aroma and taste-related outcomes. Evidence boundary: A broad review establishes scientific plausibility and candidate mechanisms; it does not validate any FlavoRotor recipe, universal optimum or cross-system transfer. I01 FlavoRotor project team (2026). FlavoRotor prototype implementation record. Internal engineering report . /research/platform Used for: Documents the built rotating prototype, sensing electronics, dashboard and current validation limitations. Evidence boundary: An internal engineering record does not demonstrate cross-machine recipe replication or biological property transfer. I02 FlavoRotor project team (2026). FlavoRotor v2.0 system architecture. Internal engineering design report . /research/platform Used for: Documents the proposed magnetic drive, axial lighting, four-channel peristaltic dosing and imaging architecture. Evidence boundary: Architecture and design targets are not a measured demonstration of Plant Teleport. R64 Massonnet, Catherine; Vile, Denis; Fabre, Justine; et al. (2010). Probing the Reproducibility of Leaf Growth and Molecular Phenotypes: A Comparison of Three Arabidopsis Accessions Cultivated in Ten Laboratories. Plant Physiology, 152(4), 2142–2157 . 10.1104/pp.109.148338 Used for: Shows that detailed standardisation can produce similar growth in a core group of laboratories, while small laboratory-environment differences can still alter growth and metabolite phenotypes. Evidence boundary: The study used Arabidopsis and did not test hydroponic flavour, FlavoRotor hardware or one-click recipe transfer. R67 Vincent, Christopher; Leisner, Courtney P.; Locke, Anna M.; Teshome, Demissew Tesfaye; et al. (2025). Importance of measuring and reporting environmental conditions across plant science subdisciplines. Plant Physiology, 199(2), kiaf405 . 10.1093/plphys/kiaf405 Used for: Supports measuring actual environmental conditions—rather than reporting equipment settings alone—to improve replicability and cross-scale interpretation. Evidence boundary: The paper proposes reporting practices and does not demonstrate Plant Teleport or define crop-specific tolerances. R70 Schuirmann, Donald J. (1987). A comparison of the Two One-Sided Tests Procedure and the Power Approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics, 15(6), 657–680 . 10.1007/BF01068419 Used for: Provides the classical two one-sided tests framework for evaluating whether an effect lies within predeclared equivalence margins. Evidence boundary: The method originated in bioequivalence; FlavoRotor must justify crop- and endpoint-specific margins, models and multiplicity handling before using it. R65 Rogers, Alistair; Dietz, Karl-Josef; Gifford, Miriam L.; Lunn, John E. (2021). The importance of independent replication of treatments in plant science. Journal of Experimental Botany, 72(15), 5270–5274 . 10.1093/jxb/erab268 Used for: Explains independent experimental units, randomisation and why pseudoreplication can invalidate treatment claims. Evidence boundary: It provides experimental-design requirements, not evidence that a FlavoRotor recipe has been replicated. R09 Senizza, Biancamaria; Zhang, Leilei; Miras-Moreno, Begoña; et al. (2020). The Strength of the Nutrient Solution Modulates the Functional Profile of Hydroponically Grown Lettuce in a Genotype-Dependent Manner. Foods . 10.3390/foods9091156 Used for: Demonstrates that nutrient-strength responses may depend on genotype. Evidence boundary: A recipe cannot be assumed portable across cultivars or genetic material. R11 Thakulla, Dharti; Dunn, Bruce; Hu, Bizhen; Goad, Carla; Maness, Niels (2021). Nutrient Solution Temperature Affects Growth and °Brix Parameters of Seventeen Lettuce Cultivars Grown in an NFT Hydroponic System. Horticulturae . 10.3390/horticulturae7090321 Used for: Shows cultivar-dependent responses to root-zone temperature. Evidence boundary: The tested NFT conditions and °Brix response do not define a universal transfer recipe. R14 Hutchinson, George Kerrigan; Nguyen, Lan Xuan; Ames, Zilfina Rubio; Nemali, Krishna; Ferrarezi, Rhuanito Soranz (2025). Substrate system outperforms water-culture systems for hydroponic strawberry production. Frontiers in Plant Science . 10.3389/fpls.2025.1469430 Used for: Shows that cultivation-system architecture can materially change crop performance. Evidence boundary: A result from one root-zone architecture cannot be copied to another without a bridge experiment. R78 Porter, Amanda S.; Evans-Fitz.Gerald, Christiana; McElwain, Jennifer C.; Yiotis, Charilaos; Elliott-Kingston, Caroline (2015). How well do you know your growth chambers? Testing for chamber effect using plant traits. Plant Methods, 11, 44 . 10.1186/s13007-015-0088-0 Used for: Demonstrates that nominally identical controlled-environment chambers can produce chamber effects and supports independent sensing, pilot testing, randomisation and replicated experimental units. Evidence boundary: The study used Vicia faba in walk-in growth chambers; it does not quantify FlavoRotor unit-to-unit variability or property-transfer fidelity. R23 Papoutsoglou, E. A. et al. (2020). Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytologist . 10.1111/nph.16544 Used for: Provides reusable metadata structures for investigations, studies, biological material and observed variables. Evidence boundary: Metadata interoperability does not prove biological equivalence. R24 Wilkinson, Mark D. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data . 10.1038/sdata.2016.18 Used for: Defines findable, accessible, interoperable and reusable data principles. Evidence boundary: FAIR data can make a recipe reusable, but does not make its biological result automatically reproducible. R38 Joint Committee for Guides in Metrology (2008). Evaluation of measurement data — Guide to the expression of uncertainty in measurement. JCGM 100:2008 . 10.59161/JCGM100-2008E Used for: Defines measurement uncertainty and uncertainty propagation. Evidence boundary: It provides a measurement framework, not crop-specific tolerances. R39 Joint Committee for Guides in Metrology (2012). International vocabulary of metrology — Basic and general concepts and associated terms. JCGM 200:2012 . 10.59161/JCGM200-2012 Used for: Defines calibration, accuracy, precision, repeatability and related terms. Evidence boundary: Metrology vocabulary does not define a transferable flavour profile. R43 International Organization for Standardization (2017). ISO/IEC 17025:2017 General requirements for the competence of testing and calibration laboratories. ISO/IEC . https://www.iso.org/standard/66912.html Used for: Supports traceable testing, calibration, method control and records. Evidence boundary: Use of an external laboratory must not imply accreditation outside its verified scope. R66 Annunziata, Maria Grazia; Apelt, Federico; Carillo, Petronia; et al. (2017). Getting back to nature: a reality check for experiments in controlled environments. Journal of Experimental Botany, 68(16), 4463–4477 . 10.1093/jxb/erx220 Used for: Demonstrates that natural sunlight and artificial controlled-light regimes can produce different metabolic profiles even when important lighting features are approximated. Evidence boundary: The study used Arabidopsis and does not quantify FlavoRotor-to-greenhouse flavour transfer. R68 Heuermann, Marc C.; Knoch, Dominic; Junker, Astrid; Altmann, Thomas (2023). Natural plant growth and development achieved in the IPK PhenoSphere by dynamic environment simulation. Nature Communications, 14, 5783 . 10.1038/s41467-023-41332-4 Used for: Shows the value of reproducing time-varying environmental trajectories rather than only static averages when bridging controlled and natural conditions. Evidence boundary: The work concerns maize development in the IPK PhenoSphere; it does not demonstrate hydroponic aroma equivalence or FlavoRotor greenhouse transfer. R41 International Organization for Standardization (2016). ISO 13299:2016 Sensory analysis — Methodology — General guidance for establishing a sensory profile. International Standard . https://www.iso.org/standard/58042.html Used for: Supports structured sensory-attribute and intensity profiling. Evidence boundary: A sensory profile must still be defined for each crop, product and claim. R73 International Organization for Standardization (2023). ISO 8586:2023 Sensory analysis — Selection and training of sensory assessors. International Standard . https://www.iso.org/standard/76667.html Used for: Defines criteria and procedures for selecting and training trained and expert sensory assessors. Evidence boundary: Training assessors improves method control; it does not guarantee that two plant samples are sensorially equivalent. R75 International Organization for Standardization (2017). ISO 6658:2017 Sensory analysis — Methodology — General guidance. International Standard . https://www.iso.org/standard/65519.html Used for: Provides general guidance on sensory tests and the statistical treatment of sensory-analysis results. Evidence boundary: It does not prescribe a universal Plant Teleport experiment or guarantee outcome equivalence. R76 International Organization for Standardization (2008). ISO 5492:2008 Sensory analysis — Vocabulary. International Standard, with Amendment 1:2016 . https://www.iso.org/standard/38051.html Used for: Defines sensory-analysis terminology relating to senses, organoleptic attributes and methods. Evidence boundary: Vocabulary alignment improves semantic precision but does not create experimental evidence. R77 International Organization for Standardization (2014). ISO 11136:2014 Sensory analysis — Methodology — General guidance for conducting hedonic tests with consumers in a controlled area. International Standard, with Amendment 1:2020 . https://www.iso.org/standard/50125.html Used for: Provides guidance for measuring consumer liking and preference under controlled conditions. Evidence boundary: Consumer liking is distinct from descriptive sensory equivalence and must not replace chemical or trained-panel evidence. R74 International Organization for Standardization (2007). ISO 8589:2007 Sensory analysis — General guidance for the design of test rooms. International Standard, with Amendment 1:2014 . https://www.iso.org/standard/36385.html Used for: Provides guidance for sensory test-room design and separation of testing, preparation and support areas. Evidence boundary: The standard is under revision and does not define crop-specific attributes, assessors or equivalence margins. R50 International Organization for Standardization (2025). ISO 5725-2:2025 Accuracy (trueness and precision) of measurement methods and results — Part 2: Basic method for the determination of repeatability and reproducibility of a standard measurement method. International Standard . https://www.iso.org/standard/90054.html Used for: Supports estimation of repeatability and reproducibility of measurement methods. Evidence boundary: Measurement-method reproducibility is distinct from biological recipe reproducibility. R46 Heckert, N. Alan; Filliben, James J.; Croarkin, C. M.; et al. (2002). NIST/SEMATECH e-Handbook of Statistical Methods. NIST Handbook 151 . https://www.nist.gov/publications/handbook-151-nistsematech-e-handbook-statistical-methods Used for: Supports experimental design, calibration regression, residual analysis and statistical process control. Evidence boundary: The handbook does not define biologically meaningful equivalence margins for FlavoRotor. R17 Vought, Kelsey; Bayabil, Haimanote K.; Pompeo, Jean; Crawford, Daniel; Zhang, Ying; Correll, Melanie; Martin-Ryals, Ana (2024). Dynamics of micro and macronutrients in a hydroponic nutrient film technique system under lettuce cultivation. Heliyon . 10.1016/j.heliyon.2024.e32316 Used for: Supports the statement that bulk EC does not uniquely specify individual ion concentrations. Evidence boundary: NFT lettuce nutrient dynamics are not numerically transferable to every reservoir and crop. R72 Hutchinson, George Kerrigan; Nguyen, Lan Xuan; Rubio Ames, Zilfina; Nemali, Krishna; Ferrarezi, Rhuanito Soranz (2025). Sensor-controlled fertigation management for higher yield and quality in greenhouse hydroponic strawberries. Frontiers in Plant Science, 15, 1469434 . 10.3389/fpls.2024.1469434 Used for: Demonstrates that sensor-coupled fertigation strategies can be evaluated for yield, quality and resource use in greenhouse hydroponic strawberry production. Evidence boundary: The study concerns specified cultivars, substrate, sensors and management strategies; it does not prove FlavoRotor-to-greenhouse aroma transfer. R79 Brentarolli, Elia; Locatelli, Silvia; Nicoletto, Carlo; Sambo, Paolo; Quaglia, Davide; Muradore, Riccardo (2024). A spatio-temporal methodology for greenhouse microclimatic mapping. PLOS ONE, 19(9), e0310454 . 10.1371/journal.pone.0310454 Used for: Supports temporary dense sensing, spatial modelling and greenhouse microclimate mapping when a single environmental average is insufficient. 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Alan; Filliben, James J.; Croarkin, C. M.; Hembree, B.; Guthrie, William F.; Tobias, P.; Prinz, J.","year":2002,"title":"NIST/SEMATECH e-Handbook of Statistical Methods","publication":"NIST Handbook 151","doi":null,"url":"https://www.nist.gov/publications/handbook-151-nistsematech-e-handbook-statistical-methods","source_type":"official statistical handbook","relevance":"Supports calibration regression, residual analysis, experimental design and statistical process control.","verification":"Official NIST publication record checked 2026-07-26","verified_on":"2026-07-26","verification_status":"OFFICIAL RECORD CHECKED","verified_against":"Named official institution record"},{"id":"R50","authors":"International Organization for Standardization","year":2025,"title":"ISO 5725-2:2025 Accuracy (trueness and precision) of measurement methods and results — Part 2: Basic method for the determination of repeatability and reproducibility of a standard measurement method","publication":"ISO","doi":null,"url":"https://www.iso.org/standard/90054.html","source_type":"international standard","relevance":"Supports estimation of repeatability and reproducibility of measurement methods.","verification":"Official ISO record checked 2026-07-26; ISO 5725-2:2025 is the current published edition.","verified_on":"2026-07-26","verification_status":"OFFICIAL RECORD CHECKED","verified_against":"Official ISO catalogue record"},{"id":"R64","authors":"Massonnet, Catherine; Vile, Denis; Fabre, Justine; et al.","year":2010,"title":"Probing the Reproducibility of Leaf Growth and Molecular Phenotypes: A Comparison of Three Arabidopsis Accessions Cultivated in Ten Laboratories","publication":"Plant Physiology, 152(4), 2142–2157","doi":"10.1104/pp.109.148338","url":"https://doi.org/10.1104/pp.109.148338","source_type":"peer-reviewed multi-laboratory research","relevance":"Shows that detailed standardisation can produce similar growth in a core group of laboratories, while small laboratory-environment differences can still alter growth and metabolite phenotypes.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI, ABSTRACT AND PRIMARY PUBLISHER RECORD CHECKED","verified_against":"Oxford Academic, Plant Physiology"},{"id":"R65","authors":"Rogers, Alistair; Dietz, Karl-Josef; Gifford, Miriam L.; Lunn, John E.","year":2021,"title":"The importance of independent replication of treatments in plant science","publication":"Journal of Experimental Botany, 72(15), 5270–5274","doi":"10.1093/jxb/erab268","url":"https://doi.org/10.1093/jxb/erab268","source_type":"peer-reviewed editorial on experimental design","relevance":"Explains independent experimental units, randomisation and why pseudoreplication can invalidate treatment claims.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI AND PRIMARY PUBLISHER RECORD CHECKED","verified_against":"Oxford Academic, Journal of Experimental Botany"},{"id":"R66","authors":"Annunziata, Maria Grazia; Apelt, Federico; Carillo, Petronia; et al.","year":2017,"title":"Getting back to nature: a reality check for experiments in controlled environments","publication":"Journal of Experimental Botany, 68(16), 4463–4477","doi":"10.1093/jxb/erx220","url":"https://doi.org/10.1093/jxb/erx220","source_type":"peer-reviewed controlled-environment research","relevance":"Demonstrates that natural sunlight and artificial controlled-light regimes can produce different metabolic profiles even when important lighting features are approximated.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI, ABSTRACT AND PRIMARY PUBLISHER RECORD CHECKED","verified_against":"Oxford Academic, Journal of Experimental Botany"},{"id":"R67","authors":"Vincent, Christopher; Leisner, Courtney P.; Locke, Anna M.; Teshome, Demissew Tesfaye; et al.","year":2025,"title":"Importance of measuring and reporting environmental conditions across plant science subdisciplines","publication":"Plant Physiology, 199(2), kiaf405","doi":"10.1093/plphys/kiaf405","url":"https://doi.org/10.1093/plphys/kiaf405","source_type":"peer-reviewed review and reporting guidance","relevance":"Supports measuring actual environmental conditions—rather than reporting equipment settings alone—to improve replicability and cross-scale interpretation.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI, ABSTRACT AND PRIMARY PUBLISHER RECORD CHECKED","verified_against":"Oxford Academic, Plant Physiology"},{"id":"R68","authors":"Heuermann, Marc C.; Knoch, Dominic; Junker, Astrid; Altmann, Thomas","year":2023,"title":"Natural plant growth and development achieved in the IPK PhenoSphere by dynamic environment simulation","publication":"Nature Communications, 14, 5783","doi":"10.1038/s41467-023-41332-4","url":"https://doi.org/10.1038/s41467-023-41332-4","source_type":"peer-reviewed controlled-environment research","relevance":"Shows the value of reproducing time-varying environmental trajectories rather than only static averages when bridging controlled and natural conditions.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI AND PRIMARY PUBLISHER RECORD CHECKED","verified_against":"Nature Communications"},{"id":"R69","authors":"Frontzek, Julius; Wagner, Zühal; Streif, Stefan","year":2026,"title":"Dynamic, adaptive and modular Digital Twin framework for resource-efficient Controlled Environment Agriculture","publication":"Frontiers in Plant Science, 17, 1864757","doi":"10.3389/fpls.2026.1864757","url":"https://doi.org/10.3389/fpls.2026.1864757","source_type":"peer-reviewed original research","relevance":"Supports vendor-agnostic sensor and actuator integration, dynamic target trajectories, model calibration and adaptive control as an architecture for translating targets to local equipment.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI AND FULL PRIMARY ARTICLE CHECKED","verified_against":"Frontiers in Plant Science"},{"id":"R70","authors":"Schuirmann, Donald J.","year":1987,"title":"A comparison of the Two One-Sided Tests Procedure and the Power Approach for assessing the equivalence of average bioavailability","publication":"Journal of Pharmacokinetics and Biopharmaceutics, 15(6), 657–680","doi":"10.1007/BF01068419","url":"https://doi.org/10.1007/BF01068419","source_type":"peer-reviewed statistical methods paper","relevance":"Provides the classical two one-sided tests framework for evaluating whether an effect lies within predeclared equivalence margins.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI, PUBMED AND PUBLISHER METADATA CHECKED","verified_against":"PubMed and Springer metadata"},{"id":"R71","authors":"Zhao, Xinyi; Peng, Jie; Zhang, Li; et al.","year":2024,"title":"Optimizing the quality of horticultural crop: insights into pre-harvest practices in controlled environment agriculture","publication":"Frontiers in Plant Science, 15, 1427471","doi":"10.3389/fpls.2024.1427471","url":"https://doi.org/10.3389/fpls.2024.1427471","source_type":"peer-reviewed review","relevance":"Reviews how pre-harvest manipulation of nutrients, light and other controlled-environment factors can affect horticultural quality, including colour, aroma and taste-related outcomes.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI AND FULL PRIMARY ARTICLE CHECKED","verified_against":"Frontiers in Plant Science"},{"id":"R72","authors":"Hutchinson, George Kerrigan; Nguyen, Lan Xuan; Rubio Ames, Zilfina; Nemali, Krishna; Ferrarezi, Rhuanito Soranz","year":2025,"title":"Sensor-controlled fertigation management for higher yield and quality in greenhouse hydroponic strawberries","publication":"Frontiers in Plant Science, 15, 1469434","doi":"10.3389/fpls.2024.1469434","url":"https://doi.org/10.3389/fpls.2024.1469434","source_type":"peer-reviewed original research","relevance":"Demonstrates that sensor-coupled fertigation strategies can be evaluated for yield, quality and resource use in greenhouse hydroponic strawberry production.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI AND FULL PRIMARY ARTICLE CHECKED","verified_against":"Frontiers in Plant Science"},{"id":"R73","authors":"International Organization for Standardization","year":2023,"title":"ISO 8586:2023 Sensory analysis — Selection and training of sensory assessors","publication":"International Standard","doi":null,"url":"https://www.iso.org/standard/76667.html","source_type":"official standard","relevance":"Defines criteria and procedures for selecting and training trained and expert sensory assessors.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"OFFICIAL RECORD CHECKED","verified_against":"ISO"},{"id":"R74","authors":"International Organization for Standardization","year":2007,"title":"ISO 8589:2007 Sensory analysis — General guidance for the design of test rooms","publication":"International Standard, with Amendment 1:2014","doi":null,"url":"https://www.iso.org/standard/36385.html","source_type":"official standard","relevance":"Provides guidance for sensory test-room design and separation of testing, preparation and support areas.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"OFFICIAL RECORD CHECKED","verified_against":"ISO"},{"id":"R75","authors":"International Organization for Standardization","year":2017,"title":"ISO 6658:2017 Sensory analysis — Methodology — General guidance","publication":"International Standard","doi":null,"url":"https://www.iso.org/standard/65519.html","source_type":"official standard","relevance":"Provides general guidance on sensory tests and the statistical treatment of sensory-analysis results.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"OFFICIAL RECORD CHECKED","verified_against":"ISO"},{"id":"R76","authors":"International Organization for Standardization","year":2008,"title":"ISO 5492:2008 Sensory analysis — Vocabulary","publication":"International Standard, with Amendment 1:2016","doi":null,"url":"https://www.iso.org/standard/38051.html","source_type":"official standard","relevance":"Defines sensory-analysis terminology relating to senses, organoleptic attributes and methods.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"OFFICIAL RECORD CHECKED","verified_against":"ISO"},{"id":"R77","authors":"International Organization for Standardization","year":2014,"title":"ISO 11136:2014 Sensory analysis — Methodology — General guidance for conducting hedonic tests with consumers in a controlled area","publication":"International Standard, with Amendment 1:2020","doi":null,"url":"https://www.iso.org/standard/50125.html","source_type":"official standard","relevance":"Provides guidance for measuring consumer liking and preference under controlled conditions.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"OFFICIAL RECORD CHECKED","verified_against":"ISO"},{"id":"R78","authors":"Porter, Amanda S.; Evans-Fitz.Gerald, Christiana; McElwain, Jennifer C.; Yiotis, Charilaos; Elliott-Kingston, Caroline","year":2015,"title":"How well do you know your growth chambers? Testing for chamber effect using plant traits","publication":"Plant Methods, 11, 44","doi":"10.1186/s13007-015-0088-0","url":"https://doi.org/10.1186/s13007-015-0088-0","source_type":"peer-reviewed original research","relevance":"Demonstrates that nominally identical controlled-environment chambers can produce chamber effects and supports independent sensing, pilot testing, randomisation and replicated experimental units.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI AND FULL PRIMARY ARTICLE CHECKED","verified_against":"Plant Methods / Springer Nature"},{"id":"R79","authors":"Brentarolli, Elia; Locatelli, Silvia; Nicoletto, Carlo; Sambo, Paolo; Quaglia, Davide; Muradore, Riccardo","year":2024,"title":"A spatio-temporal methodology for greenhouse microclimatic mapping","publication":"PLOS ONE, 19(9), e0310454","doi":"10.1371/journal.pone.0310454","url":"https://doi.org/10.1371/journal.pone.0310454","source_type":"peer-reviewed original research","relevance":"Supports temporary dense sensing, spatial modelling and greenhouse microclimate mapping when a single environmental average is insufficient.","verification":"Title, authors, DOI and publication checked against primary record","verified_on":"2026-07-30","verification_status":"DOI, PRIMARY ARTICLE AND PUBMED RECORD CHECKED","verified_against":"PLOS ONE and PubMed"}]}