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Towards a Multispectral Imaging System for Spatial Mapping of Chemical Composition in Fresh-Cut Pineapple (Ananas
Kaveh Mollazade1,2, Norhashila Hashim3,4, Manuela Zude-Sasse2
1Department of Biosystems Engineering, Faculty of Agriculture, University of Kurdistan, Sanandaj 6617715175, Iran.
Foods (Basel, Switzerland)
|September 9, 2023
Summary
This study introduces multispectral imaging to map quality attributes like moisture and soluble solids in fresh-cut pineapple. This technology aids in consistent quality control for the growing ready-to-eat fruit market.
Area of Science:
- Food Science and Technology
- Postharvest Biology
- Applied Spectroscopy
Background:
- Increasing demand for ready-to-eat fresh-cut fruit necessitates advanced quality monitoring.
- The fresh-cut pineapple market is expanding due to desirable sensory qualities and processing advancements.
- Current postharvest monitoring technologies require adaptation for consistent product quality.
Purpose of the Study:
- To develop a multispectral imaging approach for mapping key quality attributes in fresh-cut pineapple.
- To identify optimal wavelengths for predicting moisture, soluble solids, and carotenoid content.
- To enable spatially resolved quantification of chemical composition in pineapple slices.
Main Methods:
- Acquisition of hyperspectral images (380-1690 nm) and reference measurements from 60 pineapple fruits.
- Application of ReliefF and CfsSubset algorithms for informative wavelength selection.
- Development of multilayer perceptron neural network models for predicting quality attributes using selected wavelengths.
Main Results:
- Selected wavelengths (e.g., 495, 1215, 1425 nm) enabled prediction of moisture (R=0.56), soluble solids (R=0.52), and carotenoids (R=0.63).
- Multispectral imaging provided spatially distributed maps of chemical composition across pineapple slices.
- Calibration models demonstrated reliable spatial prediction with constant error.
Conclusions:
- Multispectral imaging offers a viable method for assessing fresh-cut pineapple quality attributes.
- The use of commercially relevant wavelengths facilitates practical application in industrial settings.
- This approach supports quality classification in mechanized fresh-cut produce preparation.
