Written by Vasileia Fanarioti

Quality assessment in the coffee industry has long been a challenging endeavor, with defining standards across the supply chain proving to be a complex task. International trade standards necessitate a meticulous screening process to identify issues such as discoloration, mold growth, insect damage, and shell defects before roasting.

Traditionally, green coffee buyers would request samples to assess the quality of the product. The process of sampling green coffee beans is structured across various stages in the sales cycle, progressing from type samples to stocklot samples, followed by offer samples, and ultimately concluding with pre-shipment samples.

Certified tasting experts, known as Q Graders, have been responsible for assessing coffee quality by conducting physical and sensorial evaluations, including examinations of color, aroma, and flavor. Despite their advanced training and reliance on the industry-standard coffee tasting wheel, this method exhibits inherent subjectivity, posing challenges to consistency and objectivity in quality evaluation. The Q grading process involves roasting, grinding, and brewing, adding intricacy to an already complex assessment.

At the farm level, a palpable lack of access to knowledge and essential tools leaves coffee producers with a limited understanding of how they can improve the quality of their crops. This informational deficit perpetuates a cycle of uncertainty and missed opportunities. It hinders the coffee producers' ability to comprehend the true value of their harvest and obstructs their capacity to implement improvements. These issues create a significant gap in the potential for quality enhancement across the coffee value chain.

AI's role in precision coffee quality control

Artificial Intelligence (AI) stands as a transformative force with global implications across diverse industries, offering solutions that revolutionize processes and enhance efficiency. In the coffee industry, AI emerges as a game-changer, promising to enhance not only the efficiency of grading processes but also the overall quality of the final product.

The complex and subjective nature of traditional methods highlights the demand for a more precise and streamlined approach in coffee quality control. With its machine learning algorithms and computer vision technologies, AI introduces a level of precision that surpasses what conventional methods can achieve. Emerging AI-driven solutions allow for a swiftly and accurate evaluation of green coffee samples, alleviating some of the inefficiencies of traditional quality assessment processes.

One of the overarching goals of these tools is to collect and analyze data on a large scale. This data-driven approach facilitates informed decision-making throughout the entire coffee value chain. Producers and cooperatives can leverage these tools to gain insights into improving the quality of their crops, breaking the cycle of uncertainty and missed opportunities. Traders benefit from the streamlined grading process, reducing time and resource inefficiencies associated with sample transport and enabling more informed decision-making, while roasters stand to gain from enhanced precision in quality assessment, ensuring a consistent and superior final product.

In essence, these emerging AI solutions are poised to revolutionize how the coffee industry assesses and enhances its quality. By providing efficient and objective grading mechanisms, as well as harnessing data-driven insights, these tools offer a pathway to more streamlined, sustainable, and informed processes across the coffee market. As the technology becomes more mainstream, the anticipated decrease in prices will render these tools more accessible to smallholder producers and smaller roasters, fostering a more inclusive and innovative landscape for the entire industry.

In anticipation of the transformative impact of AI on coffee quality control, the following section provides a roundup of some of the AI solutions already available in the market.

Demetria

Demetria, an Israeli-Colombian agritech startup, developed a data intelligence platform powered by AI that matches each coffee bean profile with the industry-standard coffee flavor wheel. The solution comprises a handheld near-infrared (NIR) spectrometer and a machine learning algorithm that assesses the chemical composition of green coffee beans. The spectrometer measures various parameters such as bean size, weight, and humidity levels, relaying this information to a mobile app developed by Demetria. The NIR sensors provide a chemical "fingerprint," which the algorithm maps to the eventual taste of the coffee post-roasting and brewing in the app.The organized data is then compiled into a quality and traceability data cloud, created by collecting insights from Q Graders.

Best suited for: Traders, consultants, roasters, producers
Type: Hardware & Software
Application focus: Green coffee flavor & quality assessment
Data insights: Green bean flavor assessment, green bean profiling, quality measurement, traceability via unique digital fingerprint

Csmart

Brazil-based agritech startup Csmart specializes in automating specialty coffee processes through cutting-edge technology. Their flagship product, Csmart Digit, employs computer vision, AI, and data analysis. The device, equipped with features like an automatic electromagnetic feeder, integrated LED lighting, and a high-speed CMOS camera, allows users to classify green coffee, extract quality data, and generate grading reports. The AI software within Csmart Digit provides in-depth analysis, batch evaluations, and custom databases, promoting traceability and providing defect prediction. Through continuous flow system integration, Csmart Digit can also assess machine efficiency for quality compliance.

Best suited for: Traders, dry-mill facilities, warehouses, medium to large coffee roasters and producers
Type: Hardware & Software
Application focus: Green coffee grading
Data insights: Green coffee quality assessment, lot price estimation, lot comparisons, green coffee classification, operational efficiency assessment of machines such as gravity tables, color sorters, and destoners.

Agrivero

Agrivero, a Germany-based start-up, has recently developed an AI-enabled solution designed for green coffee grading. The process involves loading samples of up to 500 grams of green coffee into the VeroLab device. VeroLab then utilizes a high-resolution camera, AI and Computer Vision to individually scan and analyze each green coffee bean from both sides. Results are available within 4 minutes on both the device's screen and the Agrivero Web App, offering analytical insights for efficient decision-making in the green coffee grading process. Users may also use the Agrivero device offline. The company is currently developing an API and integrations into popular ERP systems.

Best suited for: Importers, exporters, dry mills, large coffee producers, cooperatives
Type: Hardware & Software
Application focus: Green coffee grading
Data insights: Green coffee quality assessment, defects classification, comparison of pre-shipment and arrival samples, traceability via unique ID of samples

ProfilePrint

ProfilePrint, a Singapore-based AI-powered food fingerprint platform, utilizes molecular analysis to predict sensory profiles in green coffee samples. Requiring just 50 grams of coffee beans, the platform scans and generates a comprehensive digital report, including cupping scores and sensory parameters. By employing a wide range of wavelengths of light, covering both the visible spectrum and the NIR spectrum, ProfilePrint creates a unique fingerprint for each sample. This spectral data is fed into an AI algorithm, facilitating early-stage assessment of cupping scores, as well as flavor profiles.

Best suited for: Importers, exporters, consultants, roasters, producers
Type: Software
Application focus: Green coffee grading
Data insights: Green bean quality assessment, green bean profiling, traceability via unique digital fingerprint, recommendations on potential blends, rapid sourcing based on profiling

avercasso

avercasso, a subsidiary of AVer Information Inc., has ventured into the coffee industry with an AI-driven green coffee sorting machine, the CS One. Inside the machine, a pair of 4K cameras capture multiple images of each green bean while it moves from the hopper to an interior chamber. The machine recognizes primary and secondary defects in green coffee, aligning with Specialty Coffee Association classifications. Defective beans are propelled by compressed air along a motorized path within the machine into a separate receptacle. The machine features a 10.1-inch touch panel with a user interface, while a dedicated mobile app delivers real-time updates, offering detailed insights into the percentage of beans removed due to defects.

Best suited for: Traders, medium to large coffee roasters and producers, consultants
Type: Hardware & Software
Application focus: Green coffee sorting
Data insights: Good bean recognition, identification of SCA-classified primary and secondary defects, personalized green bean database generation for bean identification and analysis