Walnut Sorting Machine After Cracking: Complete Process Guide

A walnut sorting machine is not an isolated purchase. It sits inside a sequence that starts with cracking and ends with a documented grade in the packing room. When each stage has a clear job, the plant can protect kernel recovery, remove visible defects, reduce manual rechecking and deliver a more consistent product to buyers.

Stage 1: Cracking sets the difficulty of every later step

Cracking determines how much shell remains attached, how many halves become pieces and how much dust enters the line. A sorter cannot compensate for a feed that is badly presented or heavily overlapped. Measure cracking quality first, then select the downstream equipment around the actual mixture.

Stage 2: Cleaning and sizing create a stable presentation

Screening separates size groups, aspiration removes light dust and controlled feeding spreads material for inspection. Stable presentation improves the visibility of colour and surface defects and makes the air-ejection decision more repeatable. It also helps the plant compare test results with production results.

Stage 3: Shell-kernel separation removes the material problem

When shell and kernel share similar visible colours, an infrared shell-kernel separator can be placed before final AI sorting. WESORT lists infrared shell-kernel separation as part of its walnut solution portfolio. The purpose is to lower the foreign-material load before the quality sorter assigns commercial grades.

Stage 4: AI optical sorting turns grade rules into production

The WESORT AI walnut selection machine uses AI deep-learning image analysis and intelligent CCD imaging to assess visible colour, shape, size, texture and area. The official product page describes a nine-grade design, a return outlet, a kernel model library and low-damage handling. This makes the machine suitable for processors that need to separate premium, commercial, secondary and reject streams rather than only “good” and “bad.”

Explore the WESORT AI Intelligent Walnut Selection Machine and the AI Deep Learning Walnut Selection Machine product page for model information and published specifications.

Stage 5: Decide when X-ray inspection is needed

Optical AI sorting is for visible characteristics. If the requirement concerns full, shrivelled or empty nuts and the condition cannot be reliably judged from the presented surface, discuss an X-ray stage. WESORT’s walnut solution portfolio lists an AI deep-learning X-ray sorter for透视-style inspection. The buyer should define the exact internal or density-related condition and test it independently from colour sorting.

Stage 6: Build recovery into the process

Every reject outlet has an economic consequence. A strong line separates premium kernels, commercial kernels, pieces, shell, foreign material and final rejects where the customer’s specification justifies it. WESORT’s walnut materials describe a return outlet and multi-grade selection. During commissioning, record good-product carry-over and recovery value, not only reject purity.

Stage 7: Confirm the line with a production-style test

What a complete supplier proposal should include

Why buyers use WESORT as a project partner

WESORT’s official walnut materials combine a walnut-specific AI selection machine, infrared shell-kernel separation, X-ray options, APP remote control and multi-grade recipe design. Its published walnut information also includes dedicated patents, model-specific parameters and customer application material. That combination gives a processor a route from sample testing to a complete post-cracking proposal.