Estimation of antioxidant components of tomato using VIS-NIR reflectance data by handheld portable spectrometer

Szuvandzsiev, P.; Helyes, Lájos; Lugasi, A.; Szántó, Csongor; Baranowski, Piotr; Pék, Zoltán

doi:10.2478/intag-2014-0042

Cited by 41 publications

(23 citation statements)

References 24 publications

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“…Initially, PLSR models were developed in the whole range of spectra (325-1075 nm) for predicting various carotenoid contents of processed tomato products nondestructively. PLSR is a usable multivariate regression method when there are few samples and several variables, and the data are multicollinear, especially in tomato puree (Szuvandzsiev et al, 2014). Thereafter the numbers of wavelengths were sequentially minimized to select best performing group of wavelength so as to reduce the cost of the instrument.…”

Section: Resultsmentioning

confidence: 99%

Determination of Carotenoids in Tomato Products Using Vis/Nir Spectroscopy

Saad¹,

Pék²,

Szuvandzsiev³

et al. 2017

J microb biotech food sci

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Carotenoids analysis is complicated by their tendency to react with radical species, resulting in oxidative breakdown and isomerization during extraction. Hence, analysis methods should be rapid and avoid unnecessary exposure to high temperature, acids, and so on. The aim of this work to estimate carotenoid contents of processed tomato products non-destructively. The mean values obtained by visible and near-infrared Vis/NIR spectroscopy and by high performance liquid chromatography (HPLC) for eight carotenoid contents (ß-carotene, 5-cis lycopene, 13-cis lycopene, 9-cis lycopene, all-trans lycopene, zeaxanthin, lycoxanthin and total carotenoids) in four processed tomato products from five different brands were compared. The carotenoid contents were measured using HPLC, and these results were then used to develop partial least squares regression (PLSR) models to predict carotenoid components from Vis/NIR spectra of the same samples. A good correlation was found between HPLC measurements and the Vis/NIRs (590-790 nm) predictions for ß-carotene (RP2= 0.88), 9-cis lycopene (RP2= 0.86), total carotenoids (RP2= 0.84), 13-cis lycopene (RP2= 0.83), 5-cis lycopene (RP2=0.80), zeaxanthin (RP2= 0.80) to passable for all-trans lycopene (RP2= 0.70), but there was only a poor correlation (RP2= 0.20) for the lycoxanthin component. The overall results indicated that Vis/NIRs could be applied to assess carotenoid contents of different processed tomato products.

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Section: Resultsmentioning

confidence: 99%

Determination of Carotenoids in Tomato Products Using Vis/Nir Spectroscopy

Saad¹,

Pék²,

Szuvandzsiev³

et al. 2017

J microb biotech food sci

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“…The treatments were discriminated by the different average values of the reflectance spectra. The values are in decreasing order of K, 50, 75, 100, the order of 100 and 100M was alternating, the higher the water supply the lower the reflectance spectra were in every variety regardless of the variety (Szuvandzsiev et al, 2014).…”

Section: Methodsmentioning

confidence: 99%

“…Rubio-Diaz et al (2010) were also successful in non-destructive measuring the carotenoid composition with infrared spectroscopy in tomatoes. A VIS/NIR reflectance spectrum is suitable for quantification of ingredients, with not a close correlation between the colourful pigments (Szuvandzsiev et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Among the non-destructive methods applied in agriculture, near infrared spectroscopy is probably the most studied and accomplished one. Numbers of studies have investigated the potential of VIS/NIR technology for assessing quality parameters of vegetable products including carrot (Belie et al 2003), Brassica oleracea varieties (Szigedi et al, 2012), and tomatoes (Jha and Matsuoka, 2004;Szuvandzsiev et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Carotenoid determination in tomato juice using near infrared spectroscopy

Deák¹,

Szigedi²,

Pék³

et al. 2015

International Agrophysics

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A b s t r a c t. A rapid non-destructive method for profiling tomato carotenoids was developed using NIR spectrometry. One hundred and twenty tomato samples were produced at the Experimental Farm of Szent István University in Gödöllő (Hungary). The sample preparation was based on homogenization. The mixed samples were scanned with a diode array Perten DA7200 NIR Analyzer (950-1650 nm) and analyzed by high performance liquid chromatography. The calibration was based on partial least squares regression with cross-validation. The performance of the final model was evaluated according to root mean square error of cross-validation. The results indicate that the main carotenoid components were accurately predicted. The correlation between the NIR measurement and the β-carotene content of tomatoes was adequately high [R 2 CV = 0.89; root mean square error of cross-validation = 0.174 µg g -1 ]. The NIR method was also performed for the determination of the all-trans lycopene content (R 2 CV = 0.75; root mean square error of cross-validation = 6.88 µg g -1 ). It can be concluded that the diode array NIR spectrometer has the potential to be used for the determination of the main carotenoids of tomatoes.K e y w o r d s: tomato, carotenoid composition, near-infrared spectroscopy, partial least squares regression INTRODUCTION

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“…The authors reported the related cross-validation error to be less than 6% for chemical and color traits and about 10% for water content and firmness, thereby demonstrating the effectiveness of VIS/NIR for high-throughput assessment of biochemical changes during tomato fruit development and ripening. VIS/NIR has also been applied for the determination of physicochemical parameters-lycopene and polyphenol content-in diverse tomato cultivars and hybrids cultivated in two studies by means of FieldSpec HandHeld 2™ (Analytical Spectral Devices Inc., Longmont, CO, USA, 325-1075 nm) [102] and a Varian Cary 500 UV-vis-NIR scanning spectrophotometer (Varian Inc., Palo Alto, CA, USA) equipped with an integration sphere (Labsphere Inc., North Sutton, NH, USA) [103]. In both studies, the authors reported that bioactive compounds were accurately predicted with a cross-validation error below the 10% between reflectance spectra and lab measurements, while for the other physicochemical traits (i.e., brix, firmness, pH, titratable acidity), prediction was less accurate, partly due to a low variability of these parameters among samples.…”

Section: Vis/nir Studiesmentioning

confidence: 99%

Sensing Technologies for Precision Phenotyping in Vegetable Crops: Current Status and Future Challenges

Tripodi¹,

Massa²,

Venezia³

et al. 2018

Agronomy

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Abstract:Increasing the ability to investigate plant functions and structure through non-invasive methods with high accuracy has become a major target in plant breeding and precision agriculture. Emerging approaches in plant phenotyping play a key role in unraveling quantitative traits responsible for growth, production, quality, and resistance to various stresses. Beyond fully automatic phenotyping systems, several promising technologies can help accurately characterize a wide range of plant traits at affordable costs and with high-throughput. In this review, we revisit the principles of proximal and remote sensing, describing the application of non-invasive devices for precision phenotyping applied to the protected horticulture. Potentiality and constraints of big data management and integration with "omics" disciplines will also be discussed.

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Estimation of antioxidant components of tomato using VIS-NIR reflectance data by handheld portable spectrometer

Cited by 41 publications

References 24 publications

Determination of Carotenoids in Tomato Products Using Vis/Nir Spectroscopy

Determination of Carotenoids in Tomato Products Using Vis/Nir Spectroscopy

Carotenoid determination in tomato juice using near infrared spectroscopy

Sensing Technologies for Precision Phenotyping in Vegetable Crops: Current Status and Future Challenges

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