Monitoring of fresh-cut spinach leaves through a multispectral vision system

By Loredana Lunadei, Belén Diezma, L. Lleó, Luis Ruiz-Garcia, Susana Cantalapiedra, M. Ruiz-Altisent. 2012

69 citations recorded by the source corpus.

Abstract This paper reports the development of image processing methods for the detection of superficial changes related to quality deterioration in ready-to-use (RTU) leafy spinach during storage. The experiment was performed on spinach leaves stored at 4.5 °C for 21 days (Set 1) and at 10 °C for 9 days (Set 2). Regarding Set 1, 75 units were evaluated beginning at time zero and after 7, 14, and 21 days of storage (treatments t 1.0 , t 1.1 , t 1.2 , and t 1.3 , respectively). In the case of Set 2, 24 samples were measured at time zero and after 3, 6, and 9 days (treatments t 2.0 , t 2.1 , t 2.2 , and t 2.3 , respectively). Multispectral images were acquired using a 3-CCD camera centered at the infrared (IR), red (R), and blue (B) wavelengths. Opportune combinations of these bands were calculated using virtual images, and a non-supervised classification was performed. A large number of spinach leaves belonging to Set 2 showed injuries due to the effects of in-pack condensation; thus, an image algorithm was developed to separate these defective leaves before applying the classification. For Set 1, Set 2 and all the calculated virtual images, the classification procedure yielded two image-based deterioration reference classes (DRCs): Class A, including the majority of the samples belonging to t 1.0 and t 1.1 (Set 1) and to t 2.0 and t 2.1 (Set 2) treatments and Class B, which comprised mainly the samples belonging to t 1.2 and t 1.3 (Set 1) and to t 2.2 and t 2.3 (Set 2) treatments. An internal validation was performed, and the best classification was obtained with the virtual images based on R and B bands. For each sample, camera classification was evaluated according to reference measurements (visible (VIS) reflectance spectra and CIE L * a * b * coordinates); in all cases, VIS reflectance values corresponded well with storage days, and Classes A and B could be considered homogenous with regards to L * and a * values. Taken together, these results confirmed that a vision system based on R and B spectral ranges could constitute an easy and fast method to detect deteriorating RTU packed spinach leaves under different refrigeration conditions.

Subfields: Analytical Chemistry, Plant Science

View Paper: https://www.semanticscholar.org/paper/764ff514260b11f1b52ffb64114196333a9a28da

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In Analytical Chemistry

In Plant Science

Citations in the corpus

Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment (2012, background): “Different spectral indexes obtained from three wavelengths (450, 650 and 800 nm) were also studied by Lunadei et al. (2012) to monitor changes in quality during the storage of spinach leaves.”