Decision support for banana production

More banana
in every box.

OPTIcut combines real-time computer vision, fruit profiling and AI-assisted cutting recommendations to help producers maximise saleable fruit, understand damage and trace quality loss back to its source.

OPTIcut workspace comparing a high-waste conventional strategy with a lower-waste optimised cutting strategy
Decision support Optimised cutting strategy
Computer vision Fruit profile
Potentially
50%

higher annual fruit utilisation.

Small waste reductions scale fast.

The OPTIcut project estimates that a 1% reduction in waste can translate into 1.3 million additional boxes per year in Costa Rica alone. The goal is simple: convert more harvested fruit into saleable product.

External and internal banana-hand views with individual finger-length measurements
01 / Finger length

External and internal views capture the length of individual fingers, building a measurable profile of each banana hand.

External and internal banana-hand views with grade measurements
02 / Fruit grade

Image-based measurements describe finger thickness from both sides of the hand, supporting consistent fruit grading.

Overview of original banana images, segmentation, finger length and grade
03 / A complete fruit profile

Original images, segmentation, length and grade are brought together to support informed cutting decisions.

Capture. Analyse. Decide.

Cameras can be deployed at packing plants, mobile stations or remote inspection points. Visual data is analysed by the OPTIcut AI engine and converted into recommendations without taking the final decision away from the producer.

  1. 01
    Capture

    High-resolution images of green banana hands.

  2. 02
    Analyse

    Fruit profiles and cutting options are generated within seconds.

  3. 03
    Decide

    Operators receive recommendations and remain in control of execution.

TraditionalOPTIcut
Traditional production on the left and OPTIcut-guided production on the right, from incoming fruit through processing to packed boxes

From fruit profile to an optimised cut.

OPTIcut converts measured fruit profiles into practical cutting recommendations. The side-by-side operating view makes the effect visible from incoming fruit through the line to packed boxes.

01

Compare conventional operation with OPTIcut-guided cutting.

02

Match cutting decisions to the fruit actually arriving at the line.

See where quality is being lost.

OPTIcut links detected damage with geo-referenced production data so recurring issues can be traced back to their source plot. Teams can move from a visible defect to a location they can investigate.

Farm map highlighting Plot A, its responsible person and recorded affected fruit
Farm monitoringTrace detected damage to its source plot.

Measure size. Detect damage.

Image-based inspection brings physical measurements and visible defects into one quality workflow, improving consistency while creating a digital record that can feed monitoring and cutting decisions.

Full banana bunch at a packing plant, shown beside its AI segmentation
Whole-bunch inspection

Compare the original capture with AI segmentation to identify individual fruit across the bunch and build a structured record for quality analysis.

Close-up banana bunch shown beside an instance segmentation of individual fingers
A closer view of each finger

Detailed segmentation separates individual fingers, providing a basis for size measurement and closer inspection of visible damage.

Manual measurement of banana finger length on the left and visible skin damage on green bananas on the right
From size measurement to visible damage

On the left, a tape measure records the length of an individual banana finger. On the right, dark marks and visible skin damage illustrate the defects that quality inspection needs to capture. Together, these examples show why fruit size and surface condition matter when assessing saleable quality.

Waste less.
Pack more.

Tell us about your operation and what you’d like to improve.

elizondo@dmu.ac.uk

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