these techniques enable automated classification based on ripeness and defects . For instance , colorimetry helps identify the optimal harvest time in apple orchards , enhancing quality while reducing waste through accurate maturity assessment .
2 . Visible & Near-Infrared ( VNIR ) Spectroscopy :
VNIR spectroscopy offers deeper analytical capabilities by assessing the near-infrared range ( 400-2500 nm ) and how materials interact with light . This technique exploits molecular vibrations and overtones , which absorb NIR light , allowing comprehensive insights into the chemical composition of agricultural products . This method enhances the rapid detection of parameters such as moisture content , sugar levels , nitrogen levels , and overall quality used in real-time monitoring for crop optimization and quality control .
Typical progressive change of reflectance spectra at different ripening stages of tomato
In food quality assessment , VNIR spectroscopy is used to quantify the sweetness of fruits by measuring sugar content directly through their skin , allowing for sorting into quality grading without damaging the produce .
Hamamatsu ’ s CCD sensors
3 . Fluorescence Imaging :
Fluorescence imaging is a powerful technique used to identify specific biological compounds and pathogens in agricultural products . By illuminating samples with specific wavelengths , substances that fluoresce can be detected , providing insights into the health and quality of crops . This method is valuable for monitoring stress in plants and assessing the presence of contaminants or toxins .
4 . Hyperspectral Imaging :
With modern sensors , it is now possible to combine the aforementioned techniques and collect a complete continuous spectrum for each pixel . Hyperspectral imaging captures this spectral data of light , providing comprehensive chemical and physical assessments and improving quality control processes . Hyperspectral imaging is particularly useful in detecting
Hyperspectral imaging assessment of different coffee bean types
diseases , assessing ripeness , and identifying contaminants with high precision .
Multispectral imaging ’ s balance between spectral detail and operational simplicity makes it an invaluable tool in agri-food technology . Its focused , rapid analysis capabilities facilitate sustainable farming practices and enhance food quality .
Imaging tools are critical for a sustainable agri-food tech sector
As global demand for food intensifies , precision photonicbased techniques and imaging tools are essential for advancing sustainability in the agri-food sector . By enabling real-time monitoring and non-destructive testing , these technologies support efficient management and contribute to meeting the growing food demand without compromising environmental goals . Adopting such imaging solutions can drive the agri-food industry toward a more sustainable future , ensuring food quality and safety while paving the way for future advancements .
References
For detailed references , please view the full article .
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