HS390 NIR non-destructive inspection + AI vision + smart weighing + patented weight-batching packing — a full-chain digital system covering “inspection, sorting, coding, traceability and data”, so that every durian can be trusted from tree to table.
A fast-growing market, yet trapped in a lagging supply chain.
Traditional sorting that relies on visual inspection and tapping can hardly keep pace with China's explosive demand for quality. The problem is not on the demand side, but in every link on the supply side.
Tapping fruit by hand depends on experience, and the miss rate for underripe, dead-flesh and hard immature fruit remains high, causing frequent customer complaints and seriously damaging brand reputation and consumer trust.
Manual weighing and grading is slow and inconsistent; in peak season, capacity cannot match concentrated arrivals, leading to stock buildup, higher losses and missed sales windows.
The data chain breaks between cultivation, harvest and terminal sales. When quality issues arise, the responsible link cannot be pinpointed and root causes are hard to trace.
Without digital evidence to back claims, fraudulent after-sales cases and malicious compensation demands are hard to distinguish, payouts stay high and no quality-improvement loop can be closed.
Production data lack quantified metrics; worker efficiency, equipment status and capacity bottlenecks cannot be monitored in real time, so management decisions rest on experience alone.
We build a full-chain digital system covering “inspection, sorting, coding, traceability, data and operations”, turning industry data into a core asset that accumulates and can be reused.
The line runs 14-50 m (customized to capacity) in a dual-sided workstation + dual-level conveyor layout, with an integrated empty-tray return system. It is divided into four zones: infeed and inspection, sorting and weight batching, coding and casing, and re-inspection and outbound.
We deploy NIR spectrometers (internal quality), industrial smart cameras (external appearance), high-precision dynamic checkweighers (weight grading) and QR code recognition (identity tracking) to capture every quality dimension of a durian with millisecond precision.
With a Mitsubishi PLC as the central control hub, stepper motors and pneumatic components execute flap sorting with precision; high-power laser coding equipment and industrial label printers apply product information and unique identities at high speed.
High-performance servers and GPU accelerators process massive line data in real time; combined with full-coverage industrial monitoring and a smart sensor network, they keep production transparent and traceable, with real-time alerts and intelligent decisions when anomalies occur.
Dual quality checks with internal spectroscopy and external AI vision, dynamically self-adjusting to handle every durian efficiently.
Real-time multi-dimensional collection through spectroscopy, weight, vision recognition and QR codes, with full coverage of source data.
Real-time logic processing on collected data precisely drives flap sorting and marking triggers, ensuring automation and accuracy.
Laser coding gives every durian a unique ID, permanently binding origin, harvest date and quality grade.
Smart code readers scan and verify automatically, confirming grade and destination so that logistics information stays accurate and traceable.
Aggregates and cleans full-chain data into structured storage, and applies big-data modeling to uncover patterns in production and consumption.
Produces visual monitoring dashboards and quality traceability queries, and provides brands with after-sales anti-counterfeiting and marketing support.
Analytics from the data platform feed back to growers and the line, guiding cultivation techniques, supply-chain product selection and production parameter tuning — a complete loop from data to value.
NIR light penetrates the rind to perform non-destructive screening across all dimensions — ripeness, sugar content, underripe flesh, dead flesh, hard immature flesh and flesh ratio. Each fruit takes <1.5 s, contact-free with no damage to the rind, at ≥90% accuracy — far beyond manual, experience-based judgment.
Equipped with automatic constant-temperature and calibration systems, it adapts to the demanding line environment and delivers 24-hour uninterrupted, stable operation.
A high-precision dynamic weighing module (±0.001 kg) with 32 pneumatic flap units (8 columns × 4 rows), controlled by a Mitsubishi PLC, responds with ≤300 ms latency.
Industrial cameras plus AI image algorithms identify fruit shape, size, surface defects, cracking, insect holes and color, analyzed together with internal quality data.
The system automatically balances flap loads to reduce mechanical wear; abnormal fruit is identified and diverted to dedicated lanes to keep sorting purity. Grades are freely configurable as 6+6 with no overlapping ranges. Internal quality + appearance + weight combine into three-dimensional grading.
A high-power laser coding system provides physical anti-counterfeiting with no adhesive labels, ruling out imitation and tampering. Each engraved code carries origin, harvest batch, quality grade and a unique ID. First-scan activation plus geospatial and time verification intelligently flag malicious claims, cutting fraudulent after-sales claims by 90%.
Powered by tray identity tracking + a global combinatorial optimization algorithm (invention patent applied for), it automatically assembles fruit to satisfy three constraints — total weight, fruit count and per-fruit weight — with a case weight error of ≤±50 g. It supports mixed packing for multi-specification, multi-channel orders.
Traceability drills down from case to individual fruit: inventory can be managed by case, and at any stage you can drill into the full quality record of a single fruit, so logistics, sales and after-sales information flow seamlessly end to end.
Our NIR non-destructive inspection technology is backed by joint research from leading Thai universities, achieving 100% ripeness-classification accuracy on the validation set.
Joint research by Khon Kaen University, King Mongkut's University of Technology Thonburi and Kasetsart University in Thailand, published in the international journal Artificial Intelligence in Agriculture (2023, updated March 2026). It uses short-wave near-infrared spectroscopy (SWNIR, 450-1000 nm) with the LDA algorithm.
160 Monthong samples · 75% training set + 25% validation set · 5-fold cross-validation
It overcomes the need to slice and destroy fruit in conventional methods, testing whole durians directly and fully preserving their commercial value. By fusing spectra from both rind and stem, it breaks through the limits of a single data source.
Rind spectra alone reached 93.77% accuracy, rising to 100% when stem spectra were combined. Stem spectra effectively supplement the rind's feature dimensions and markedly improve model robustness.
It can be applied to in-line, “one-fruit-one-test” screening of export durian, precisely controlling ripeness and reducing quality disputes. Low cost and high efficiency give it strong potential for large-scale deployment.
This study provides solid academic grounding and technical feasibility validation for the scientific principles of the NIR inspection module in Huishi's intelligent sorting line.
We connect isolated production data islands and let data drive decisions, achieving a transparent production process, refined management and optimal efficiency.
Real-time monitoring of output by workstation, OEE metrics and anomaly alarms; the dark industrial-style interface is easy on the eyes and suited to long hours of workshop monitoring.
Industrial video monitoring keeps key processes standardized and compliant, and quality issues can be traced back to specific operators.
Automatically tracks output, working hours and efficiency for individuals and teams, and intelligently generates multi-dimensional performance assessment data.
Remote diagnostics and parameter tuning let you follow equipment status from anywhere on mobile — a leap-forward upgrade.
It covers every node from origin, harvest, transport, inspection, sorting and packing to logistics and the end consumer, delivering transparent management from field to table, and builds a smart after-sales system of “anti-counterfeiting verification, risk screening, online closed loop and data feedback”.
Orchard profiles, harvest dates and batches are kept on file and linked to quarantine certificates, ensuring that fruit is natural and safe from the very source.
Spectral inspection reports and weight-grade records are retained, with processing personnel and time clearly logged, keeping every process controllable.
Warehouse temperature and humidity are monitored in real time, with full tracking of logistics routes and distributor information, ensuring freshness on arrival.
Consumers scan to view the full-chain record and submit after-sales requests in one tap; transparent information builds deep brand trust.
A big-data risk model based on scan frequency, purchase time, product destination and geographic location precisely identifies and blocks fraudulent after-sales claims.
Complaint types and root causes are analyzed, and the data flows back to empower supply-chain optimization, continuously iterating product quality and service.
We aggregate full-dimension data on durian production regions, varieties, quality, distribution and consumption across China to build the country's largest durian industry database, making the leap from “experience-based judgment” to “data-driven decisions”.
Covers core production regions in each country, monitoring orchard output, ripening cycles and origin traceability in real time.
Collects inspection data such as sugar content, ripeness and flesh ratio to establish a standardized quality evaluation and scoring system.
Tracks omnichannel sales, price fluctuations and regional consumer preferences to reveal how market demand is shifting.
Guides procurement planning with production-region and demand data, precisely matching supply and demand and reducing inventory buildup and logistics losses.
Establishes scientific quality grading and pricing standards, bringing order to the market and improving distribution efficiency and premium pricing power.
Big data forecasts market price trends and supply-demand shifts, providing data support for pricing strategy and inventory management.
Integrated projections show significant economic benefits, with a very high input-output ratio and rapid realization capability.
Sorting labor cut by 80%, greatly reducing dependence on manual work, saving over CNY 3 million a year.
The miss rate for underripe and dead flesh drops from 15% to 5%, controlling quality at the source and cutting losses by about CNY 3 million a year.
Full-process data traceability cuts fraudulent after-sales claims by 90%, recovering about CNY 3 million a year.
Manual packing overfills each case by 200 g+; the line controls it to within 50 g, saving over CNY 5 million a year.
Integrated projections show significant economic benefits, with a very high input-output ratio and rapid realization capability.
On-site environment survey, in-depth refinement of business requirements, and finalization of the technical implementation plan and project schedule.
Custom production of hardware and development of software functions, with in-house simulation testing and quality inspection completed in parallel.
On-site equipment installation and system integration, plus professional skills training for operators and the O&M team.
Full-process trial production and validation, followed by acceptance and handover; long-term O&M support and system iterations are provided.
The complete equipment comes with a 1-year free warranty, and extended warranty service is available for core precision components.
Engineers respond on site within 24 hours of a fault report, resolving issues quickly.
System software receives lifetime free iterative upgrades, continuously adapting to business development needs.
Professional engineers visit regularly for inspections and preventive maintenance, minimizing hidden failure risks.
Reshaping the durian industry chain
with digital technology.
By integrating AI vision, IoT and big data, we create a replicable and scalable model for digital transformation of the durian industry, leading the industry from traditional models to smart, efficient operations.