Articles
Determining lamb’s lettuce postharvest age based on visible/near-infrared reflectance spectroscopy
Article number
1154_2
Pages
9 – 16
Language
English
Abstract
Lamb’s lettuce (Valerianella locusta L.) that is presented to the market is not always freshly harvested.
The product can be stored for up to 28 days and is indistinguishable from fresh material by the human eye.
However, due to the prior storage period, the shelf-life potential is limited, and this leads to losses in distribution and a lower quality for the consumer.
This work aims to develop a rapid and non-destructive methodology using visible/near-infrared (Vis/NIR) reflectance spectroscopy to quantify the postharvest age.
Vis/NIR reflectance spectra were linked to the time in storage by partial least-squares regression (PLS). Two variable selection techniques, genetic algorithms PLS and Monte Carlo uninformative variable elimination PLS, were combined to improve the accuracy and robustness of the prediction model while decreasing the number of wavelengths used.
The final model used only 10% of the original wavelength variables, while the root mean squared error of cross validation decreased from 6.0 to 3.6 days.
The final model was tested using two external test sets and had a maximum root mean squared error of prediction of 3.7 days.
Therefore, it was concluded that Vis/NIR reflectance spectroscopy can be a valid, rapid and non-destructive method for identifying and quantifying the postharvest age of lamb’s lettuce.
The product can be stored for up to 28 days and is indistinguishable from fresh material by the human eye.
However, due to the prior storage period, the shelf-life potential is limited, and this leads to losses in distribution and a lower quality for the consumer.
This work aims to develop a rapid and non-destructive methodology using visible/near-infrared (Vis/NIR) reflectance spectroscopy to quantify the postharvest age.
Vis/NIR reflectance spectra were linked to the time in storage by partial least-squares regression (PLS). Two variable selection techniques, genetic algorithms PLS and Monte Carlo uninformative variable elimination PLS, were combined to improve the accuracy and robustness of the prediction model while decreasing the number of wavelengths used.
The final model used only 10% of the original wavelength variables, while the root mean squared error of cross validation decreased from 6.0 to 3.6 days.
The final model was tested using two external test sets and had a maximum root mean squared error of prediction of 3.7 days.
Therefore, it was concluded that Vis/NIR reflectance spectroscopy can be a valid, rapid and non-destructive method for identifying and quantifying the postharvest age of lamb’s lettuce.
Authors
B.A.J.G. Jacobs, B.E. Verlinden, E. Bobelyn, A. Decombel, P. Bleyaert, J. Van Lommel, I. Vandevelde, W. Saeys, B.M. Nicolai
Keywords
storage, quality, corn salad, lamb¿s lettuce, near infrared, spectroscopy, multivariate statistics
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