Detect blemishes and bruising under the skin, define ripeness and chemical quality independent of the fruit colour and size, find and remove foreign materials like plastic, wood, paper, metal, or insects. Specim FX cameras can reveal much more than traditional colour and filter cameras or point spectrometers.
Achieve better quality, ripe products with optimized shelf life, and reduce losses and waste.
Integrate Specim FX Cameras to your quality control and sorting processes to enhance their capability in product inspection and process analytics. Non-invasive, real-time inspection replaces visual inspections and time-consuming lab tests. Covers 100% of the product stream. Improves chemical grading and foreign material detection. Detects a range of characteristics simultaneously with a single camera – now and in the future.
Non-invasive, real-time inspection replaces visual inspections and time-consuming lab tests.
Covers 100% of the product stream.
Improves chemical grading and foreign material detection.
Detects a range of characteristics simultaneously with a single camera – now and in the future.
Case example: Avocados
Annual production of avocados reached 5.5 million tons in 2016 – it has nearly doubled in 15 years thanks to its dietary value and health benefits. Avocado fruit does not ripen until detached from the tree and harvesting the fruit at optimum maturity is important to ensure the optimal eating quality. On one hand, the price of the fruit is higher at the beginning of the picking season, therefore the harvesters are tempted to pick immature fruits that do not ripen properly. As a result, the eating quality and the dietary value of the fruit suffers. On the other hand, an over-mature fruit picked at a late phase of harvesting period has a shorter shelf life and added risk of disorders and diseases.
Predicting the avocado eating quality and commercial value is difficult due to is non-apparent visual change. However, Specim sensors can detect and predict changes that are not visible to the eye. The changes in fruit quality have a specific spectral fingerprint that can be detected with Specim sensors. Prediction models can be built and applied to detect the fruits and their parts that are at higher risk to get blemished.