Lag Phase Weight Yield Forecast

Forecast heterogeneous lag-phase cluster masses using supplied calibrated maturity growth factors and represented cluster inventories; unlike count-only yield expansion, weight growth is explicit and not guaranteed.

Description

Lag-phase clusters may gain mass before harvest.

Lag-phase clusters may gain mass before harvest. Explicit maturity factors permit a heterogeneous growth scenario.^[1]

When to use Lag Phase Weight Yield Forecast

Use this tool to forecast heterogeneous lag-phase cluster masses using supplied calibrated maturity growth factors and represented cluster inventories; unlike count-only yield expansion, weight growth is explicit and not guaranteed.

Prepare vineyard measurements, dates or block records for the intended growing period. Keep weights, counts and weather observations in the stated units.

How to use Lag Phase Weight Yield Forecast and understand its results

Prepare vineyard measurements, dates or block records for the intended growing period. Keep weights, counts and weather observations in the stated units.
Enter lagPhaseClusterMassesKg, callerMaturityMassFactors, representedClusterCounts using the field table and calculation rules, then run the tool.
Read modelMatureClusterMassesKg, modelBlockMatureYieldTonnes. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
lagPhaseClusterMassesKg	Lag phase cluster masses kg	list of number	Required
callerMaturityMassFactors	Caller maturity mass factors	list of number	Required
representedClusterCounts	Represented cluster counts	list of number	Required

Align nonnegative lag masses, positive calibrated factors and nonnegative integer represented cluster counts. Return modeled mature masses and their block-scaled total.^[2]

Paired lists must be nonempty and have equal lengths.

mature cluster mass = lag mass × factor; tonnes = Σ mature mass × represented clusters/1000

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
modelMatureClusterMassesKg	Model mature cluster masses kg	list of number
modelBlockMatureYieldTonnes	Model block mature yield tonnes	number

json

{
  "input": {
    "lagPhaseClusterMassesKg": [
      0.1,
      0.2
    ],
    "callerMaturityMassFactors": [
      2,
      3
    ],
    "representedClusterCounts": [
      100,
      200
    ]
  },
  "output": {
    "modelMatureClusterMassesKg": [
      0.2,
      0.6000000000000001
    ],
    "modelBlockMatureYieldTonnes": 0.14
  }
}

Limitations and assumptions

Factors must be independently calibrated; growth and harvest yield are not guaranteed.

Numbers and computed results must be finite; overflow produces an error. Numeric lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Sample Bunch Weight Scaling Tonnage: Scale stratified measured bunch mass using caller known sample inclusion probabilities and actual represented bunch counts, explicitly Hájek weighted mean; not equal-weight count method, exact unbiased population total or random-sample claim. For a complementary task, use Crop Estimate Cluster Count Method: Expand equal-probability sampled vine cluster counts to block yield with caller mature-cluster mass and count-sampling error only; no weight/selection uncertainty, harvest guarantee or optimum crop load.

Further background: Veraison to harvest: vineyard and winery considerations.

References

Veraison to harvest: vineyard and winery considerations — Penn State Extension
Lag Phase Weight Yield Forecast — tool.io

Similar or alternative tools

Sample Bunch Weight Scaling Tonnage
Scale stratified measured bunch mass using caller known sample inclusion probabilities and actual represented bunch counts, explicitly Hájek weighted mean; not equal-weight count method, exact unbiased population total or random-sample claim.
Crop Estimate Cluster Count Method
Expand equal-probability sampled vine cluster counts to block yield with caller mature-cluster mass and count-sampling error only; no weight/selection uncertainty, harvest guarantee or optimum crop load.