The integration of spectroscopy in agriculture is expanding, as detailed in studies published in Postharvest Biology and Technology and the Journal of Food Quality. Monitoring fruit quality across production, harvest, and marketing stages is poised to play a role in sustaining modern food production.
During production, key data points include soluble solid content, water content, and firmness. Post-harvest, the focus shifts to assessing bruising, scald or frost damage, and rot to maintain uniform quality and optimize productivity.
Research on Fuji apples utilized near-infrared spectroscopy (600-1100 nm) to develop an algorithm correlating fruit parameters like solid content, water content, and firmness. By extracting sensitive wavelengths, researchers aimed to predict internal fruit quality. They investigated strategies for selecting relevant wavelengths to minimize the data set, which is vital for creating portable and inline sensing systems, like those developed by Avantes' OEM partners.
The study employed the AvaSpec-ULS2048 spectrometer, a Tungsten Halogen illumination source (AvaLight-HAL-S-Mini), 400-µm diameter fiber-optic reflection probes (FCR-7IR400-2-ME), and power supply.
Further research on Jonagold apples, published in Postharvest Biology and Technology, analyzed reflectance spectra in the visible/NIR spectra using a spectrometer and camera system. By comparing damaged and healthy tissues, four filters were identified to predict apple quality, aiding in fruit sorting automation. This study used an early version of the AvaSpec-ULS2048-USB2 spectrometer.
Source: AZO Materials