scholarly journals Light Penetration Properties of Visible and NIR Radiation in Tomatoes Applied to Non-Destructive Quality Assessment

2021 ◽  
Vol 9 (1) ◽  
pp. 18
Author(s):  
Merel Arink ◽  
Haris Ahmad Khan ◽  
Gerrit Polder

Tomato is an important food product for which the development of non-destructive quality assessment methods is of great interest. Using visible and near-infrared (NIR) spectroscopy, the sugar content, acidity and even taste can be estimated through the use of chemometric methods (e.g., partial least squares regression). In the case of reflection spectra, which are the common modality for imaging spectroscopy, the question arises regarding how much of the interior of the tomato contributes to the measured spectra. An experiment was performed with tomatoes of four different types: beef tomato, classic round tomato, cocktail tomato, and snack tomato. The tomatoes were sliced at different thicknesses and imaged on a 98% reflective white background and a 4% reflective black background. Spectral images were acquired with VNIR (400–1000 nm) and NIR (900–1700 nm) imaging spectrographs. The difference between the spectra with a white and black background was used to determine the relationship between the wavelength and the light penetration depth. The results show that at wavelengths between 600 and 1100 nm, light penetrates the tomatoes up to a distance of 20 mm. The relation more or less follows the law of Lambert–Beer. This relation was the same for all four types of tomatoes. These results help the interpretation of chemometric models based on reflection (imaging) spectroscopy.

2020 ◽  
Vol 38 (No. 2) ◽  
pp. 131-136
Author(s):  
Wojciech Poćwiardowski ◽  
Joanna Szulc ◽  
Grażyna Gozdecka

The aim of the study was to elaborate a universal calibration for the near infrared (NIR) spectrophotometer to determine the moisture of various kinds of vegetable seeds. The research was conducted on the seeds of 5 types of vegetables – carrot, parsley, lettuce, radish and beetroot. For the spectra correlation with moisture values, the method of partial least squares regression (PLS) was used. The resulting qualitative indicators of a calibration model (R = 0.9968, Q = 0.8904) confirmed an excellent fit of the obtained calibration to the experimental data. As a result of the study, the possibilities of creating a calibration model for NIR spectrophotometer for non-destructive moisture analysis of various kinds of vegetable seeds was confirmed.<br /><br />


2002 ◽  
Vol 10 (1) ◽  
pp. 77-83 ◽  
Author(s):  
Tsuyoshi Temma ◽  
Kenkoh Hanamatsu ◽  
Fujitoshi Shinoki

Industries from agriculture to petrochemistry have found near infrared (NIR) spectroscopic analysis useful for quality control and quantitative analysis of materials and products. The general chemical, polymer chemistry, petrochemistry, agriculture, food and textile industries are currently using NIR spectroscopic methods for analysis. In this study, we developed a portable NIR instrument for the non-destructive testing of products in the field, which has resulted in an instrument for commercial sale and use. The instrument consists of a light source, a polychromator, a wave-guide (optical fibre bundle) and a data processing unit. We tested the performance of the portable NIR instrument in determining the sugar content of apples. The performance was also examined at full width at half maximum ( FWHM) of the spectrum. The difference in the absorption of quartz and plastic fibres in the NIR was also compared. The sugar content measurements were confirmed by a high correlation to the Brix value of the apples, and the calibration showed the accuracy of the instrument in practice. Application of this instrument to fruits and vegetables other than apples was explored.


2000 ◽  
Vol 18 (2) ◽  
pp. 121-132 ◽  
Author(s):  
Jeroen Lammertyn ◽  
Ann Peirs ◽  
Josse De Baerdemaeker ◽  
Bart Nicolaı̈

2018 ◽  
Vol 85 (3) ◽  
pp. 184-190 ◽  
Author(s):  
Michael Kopf ◽  
Robin Gruna ◽  
Thomas Längle ◽  
Jürgen Beyerer

Abstract Near-infrared (NIR) spectroscopy is a widespread technology for fruit and vegetable quality assessment. New fields of application of this technology, like mobile food analysis with handheld low-cost spectrometers, increase the demand for chemometric calibration models that are able to deal with multiple products and varieties thereof at once (so-called multi-product calibration models). While there are well studied methods for single-product calibration as partial least squares regression (PLSR), multi-product calibration is still challenging. Conventional approaches that work well for single-product calibration can lead to high errors for multi-product calibration. However, nonlinear methods as local regression and artificial neural networks were found to be suitable E. Micklander, K. Kjeldahl, M. Egebo, and L. Norgaard. Multi-product calibration models of near-infrared spectra of foods. Journal of Near Infrared Spectroscopy, 14:395–402, 2006. L. R. Lopez, T. Behrens, K. Schmidt, A. Stevens, J. A. M. Dematte, and T. Scholten. The spectrum-based learner: A new local approach for modeling soil vis-NIR spectra of complex datasets. Geoderma, 195–196:268–279, 2013. . Preliminary studies in multi-product calibration for quantitative analysis of food with near-infrared spectroscopy showed good results for memory-based learning (MBL) and a classification prediction hierarchy (CPH) M. C. Kopf and R. Gruna. Examination of multiproduct calibration approaches for quantitative analysis of food with near infrared spectroscopy. Bachelor's thesis, Karlsruhe Institute of Technology KIT, 2016. . In this study, three varieties of apples, pears and tomatoes with known sugar content (in ○Brix) are analysed with NIR hyperspectral imaging spectroscopy in the range from 900 nm to 2400 nm. Predictive performance of a linear PLSR model, two nonlinear models (CPH and MBL) and different pre-processing techniques are tested and evaluated. For error estimation, leave-one-product-out and leave-one-out cross-validation are used.


2012 ◽  
Vol 93 (2) ◽  
pp. 238-244 ◽  
Author(s):  
Audrey Pissard ◽  
Juan A Fernández Pierna ◽  
Vincent Baeten ◽  
Georges Sinnaeve ◽  
Georges Lognay ◽  
...  

Foods ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 441 ◽  
Author(s):  
Manuela Mancini ◽  
Luca Mazzoni ◽  
Francesco Gagliardi ◽  
Francesca Balducci ◽  
Daniele Duca ◽  
...  

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market.


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