Grape Sorting and Selection Techniques

Problem Definition

Grape sorting removes substandard fruit—underripe, overripe, rotten, damaged, or MOG (material other than grapes)—before fermentation. While fruit quality begins in the vineyard, sorting provides the final quality control opportunity before processing. The decision to sort, and the method employed, affects wine quality, labor costs, processing speed, and winery logistics. Understanding the options enables cost-benefit decisions aligned with quality goals.

Technical Context

Material to Remove

MOG (Material Other Than Grapes):

Leaves
Stems (if destemmed)
Insects
Debris

Substandard Fruit:

Underripe: Green berries; herbaceous character
Overripe/Raisined: Dried berries; high sugar; possible VA
Rot-affected: Botrytis (grey rot vs. noble rot), sour rot
Damaged: Split berries; insect damage
Sunburn: Heat-damaged berries

Impact on Wine Quality

Underripe Berries:

Contribute green/herbaceous character
Lower sugar
Unripe tannins

Overripe/Raisined:

High sugar (alcohol)
Dried fruit character
Possible microbial issues

Rot-Affected:

Off-flavors
Laccase enzyme (color degradation)
Microbial contamination

Options and Interventions

Manual Sorting Tables

Configuration:

Conveyor belt at waist height
Workers on both sides
Good lighting essential
Speed adjustable

Process:

Fruit onto conveyor (post-destem or whole-cluster)
Workers remove defects by hand
Sorted fruit continues to crusher/fermenter
Waste collected separately

Advantages:

Highly effective
Human judgment
Flexible (adjust to vintage)
Low capital cost

Disadvantages:

Labor-intensive
Subjective (worker training critical)
Speed limited
Fatigue affects quality

Staffing: 6-12 workers per table; rotation recommended

Vibrating/Shaking Tables

Concept:

Vibration separates by density/size
Raisins and small debris fall through
MOG bounces off
Sorted fruit continues

Advantages:

Removes small defects efficiently
Continuous operation
Complements manual sorting
Moderate cost

Disadvantages:

Not selective (size-based only)
Some good fruit lost
Noise/vibration

Optical Sorters

Technology:

Cameras analyze each berry
Color, size, shape detected
Air jets eject defects
Computer vision processing

Capabilities:

Remove underripe (green) berries
Remove raisins
Remove rot-affected berries
Remove MOG
8-15 tons/hour throughput

Advantages:

Objective, consistent
High speed
No labor fatigue
Data collection possible

Disadvantages:

Very high capital cost
Maintenance requirements
May miss some defects
Limited tactile assessment

Examples: Pellenc Selectiv, Key Technology, WECO

Density Flotation

Concept:

Grapes placed in brine/sugar solution
Underripe berries float
Ripe berries sink
Separation by density

Protocol:

Prepare solution of known density
Destemmed berries into tank
Floaters removed (skimming)
Sinkers processed

Advantages:

Effective for underripe removal
Simple concept
Low labor

Disadvantages:

Water/solution usage
Cleanup required
May stress some berries
Not widely used

Combined Systems

Typical Premium Setup:

Vibrating table: Remove MOG, raisins
Manual table: Selective quality removal
Optical sorter: Final precision sorting

Logic: Each method removes different defect types

Trade-offs and Risks

Over-Sorting

Risk: Removing too much good fruit Impact: Reduced yield; economic loss Mitigation: Appropriate speed; worker training; equipment calibration

Under-Sorting

Risk: Leaving defects in fermentation Impact: Quality issues; wasted downstream effort Mitigation: Multiple sorting stages; appropriate staffing

Sorting Line Bottleneck

Risk: Sorting slows harvest processing Impact: Fruit waiting in sun; oxidation; logistics issues Mitigation: Appropriately sized equipment; harvest scheduling

Fruit Damage During Sorting

Risk: Excessive handling damages berries Impact: Oxidation; juice loss Mitigation: Gentle equipment; appropriate speed; cold fruit

Practical Implications

Variety Considerations

Pinot Noir:

Often whole-cluster sorted
Manual tables common
Gentle handling critical
Thin-skinned; damage-prone

Zinfandel:

Uneven ripening challenge
Raisin removal important
Optical sorters valuable
High sugar variance

Grenache:

Large clusters
May need cluster selection first
Prone to rot in some climates

Economic Analysis

Cost Components:

Equipment capital (optical: $200K-500K+)
Labor (manual: significant)
Throughput (opportunity cost)
Waste/yield loss

Quality Premium:

Sorting enables higher-quality wine
Premium pricing supports sorting cost
Reputation building
Market positioning

When to Sort

Always Sort:

Premium/ultra-premium wines
Difficult vintages (rot, uneven ripening)
Thin-skinned varieties
When fruit condition variable

May Skip/Minimize:

Excellent vintage (healthy, even fruit)
Very large volumes (practical limits)
Entry-level wines (cost-benefit)

References

Iland, P., et al. (2011). “The Grapegrower’s Handbook.” Patrick Iland Wine Promotions. Publisher Link
Jackson, R.S. (2014). “Wine Science: Principles and Applications.” 4th Edition. Academic Press. Publisher Link DOI: 10.1016/C2012-0-01088-3
Coetzee, C. & du Toit, W.J. (2012). “Grape and wine phenolic chemistry.” In: Managing Wine Quality, pp. 296-338. Woodhead Publishing. DOI: 10.1533/9781845699284.2.296
Modern winery equipment manufacturer documentation (Pellenc, Bucher, WECO)

Last Updated: January 6, 2026