Light distribution inside mandarin fruit during internal quality assessment by NIR spectroscopy

Fraser, Daniel G.; Jordan, R. B.; Künnemeyer, Rainer; McGlone, Andrew

doi:10.1016/s0925-5214(02)00058-3

Cited by 93 publications

(42 citation statements)

References 16 publications

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“…This is also one of the conclusions of our study. Fraser et al (2003) emphasize the fact that internal boundary layers in the products are critical for transmittance measurements but not so much for other types of sample presentations such as reflectance or interactance. This point is also very relevant for onion bulbs since the internal layers lose tightness during the post harvest period, and will have to be taken into account when trying to shift from interactance to transmittance in order to facilitate online measurements.…”

Section: Discussionmentioning

confidence: 99%

“…However, the transfer of technology to the agroindustry is still a challenge due to a high number of uncontrolled sources of variation which modify the spectral information, and reduce the accuracy of estimations. Some of these sources of variation are: the internal temperature of the product and the spectrometer (Hernández-Sánchez et al, 2003), the skin thickness (Krivoshiev et al, 2000), and the presence of boundary layers and voids inside the product (Fraser et al, 2003).A main issue when developing a new NIR application is selection of the interaction mode between the light and the sample: reflectance, interactance or transmittance. The interactance mode, though it is the most difficult situation for online implementation, has shown encouraging results for obtaining good predictive models (Schaare and Fraser, 2000).…”

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confidence: 99%

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confidence: 99%

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Multivariate diagnosis of the variability of NIR spectrometers under industrial applications

Elorza

Henche²,

Ruiz-Altisent

et al. 2004

Span. j. agric. res.

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The viability of Near Infra Red (NIR) Spectrometry for internal quality assessment in fruit and vegetables is accepted world wide even for real-time applications. However, the transfer of technology to the agroindustry is still a challenge due to a high number of uncontrolled sources of variation which modify the spectral information, and reduce the accuracy of estimations. Some of these sources of variation are: the internal temperature of the product and the spectrometer (Hernández-Sánchez et al., 2003), the skin thickness (Krivoshiev et al., 2000), and the presence of boundary layers and voids inside the product (Fraser et al., 2003).A main issue when developing a new NIR application is selection of the interaction mode between the light and the sample: reflectance, interactance or transmittance. The interactance mode, though it is the most difficult situation for online implementation, has shown encouraging results for obtaining good predictive models (Schaare and Fraser, 2000). AbstractThe transfer of NIR spectroscopy to industry relies on the possibility of real time identification of abnormal spectra as well as uncontrolled sources of variation. This study proposes an unsupervised procedure for the identification under an industrial application of daily events (general changes) and abnormal observations. It consists in defining a spectral database at the beginning of a season, performing a principal component (PC) analysis, and calculating the PC scores over time. Process control statistics (Hotelling T 2 , Q) are used for multivariate supervision of the industrial application. Within this procedure 10,400 average spectra of onion bulbs were evaluated identifying events in 12 out of 66 work dates, as well as spectral trends throughout the season of 2002.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Multivariate diagnosis of the variability of NIR spectrometers under industrial applications

Elorza

Henche²,

Ruiz-Altisent

et al. 2004

Span. j. agric. res.

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“…In dates, at tamar maturation stage, the skin tends to delaminate, and therefore increase the scattering effect of light and alter the reflectance (Lee et al, 2008). As indicated by Fraser et al (2003) skin acts as a barrier for light penetration and reduces the effectiveness of NIR imaging system for this application. The apparition of delamination areas on our samples may have contributed to the relatively poor correlation between NIR absorption/reflectance and TSS content.…”

Section: Tss Prediction For Different Varieties Of Datesmentioning

confidence: 99%

Non-destructive measurement of total soluble solid (TSS) content of dates using near infrared (NIR) imaging

Manickavasagan

Ganeshmoorthy

Claereboudt

et al. 2014

Emir. J. Food Agric

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The total soluble solid (TSS) content is one of the important quality attributes that determines the commercial value of dates. At present, TSS content in dates is measured using destructive techniques that are laborious and time consuming. In this study, the potential of a near infrared (NIR) imaging technique to determine TSS content of dates was evaluated. Date samples of three cultivars (Fardh, Khalas and Naghal) at tamar stage (n=400 fruits) and two ripening stages (tamar and khalal) of Khalas cv. (n=400 fruits) were used in this study. The area scan NIR camera which covers the full spectrum range of 900-1,700 nm was used to capture the images of individual date fruits. Immediately following image acquisition, the TSS content (ºBrix) of each sample was measured using a digital refractometer. The TSS content of dates was in the range of 34-63°Brix and 14-37°Brix for tamar and khalal stages, respectively. Similarly, the percentage of NIR reflectance was 12-38 and 39-64 for tamar and khalal stages, respectively. A multiple linear regression (MLR) prediction model along with a dummy variable concept was established between measured TSS and NIR reflectance. NIR reflectance was inversely proportional to the TSS content of dates. The correlation coefficient (r) between TSS content and NIR reflectance was 0.62 and 0.98 for three cultivars and two ripening stages, respectively. The high correlation among ripening stages indicates the opportunities of NIR technique for potential applications in influencing ripening stages. However, further work is warranted to determine the correlation between TSS and NIR reflectance in different ripening stages of other cultivars.

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“…Further, they found that the skin poses a major barrier for light penetration in mandarin fruit, even at 808 nm. 17 This may also explain the relatively poor predictions of soluble solids content (SSC) in grapefruit that were obtained by Miller and ZudeSasse. 18 The limited penetration depth restricts the potential of diffuse reflection or interactance measurements for detecting internal defects, and decreases the accuracy of NIRS-based measurements of internal quality attributes of thickskinned fruits, such as citrus fruits.…”

Section: Measurement Setupmentioning

confidence: 99%

Vibrational Spectroscopy Techniques in the Quality Assessment of Fruits and Vegetables

Polshin

Lammertyn

Nicolaı̈

2001

Handbook of Vibrational Spectroscopy

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Fruits and vegetables play an important role in the human diet worldwide. Safety and quality are important considerations for the purchase and consumption of fresh raw products. Since the consumers increasingly insist on a very high fruit and vegetable quality nowadays, it is also necessary to provide information about the origin and traceability of these products. One of the alternatives to traditional wet chemistry and human evaluation strategies, which allow quality assessment and control of fruits and vegetables, is vibrational spectroscopy. During the last decade, several vibrational spectroscopic methods have been developed, and have become more widely adopted by the agricultural and food sectors. These methods offer the possibility to rapidly measure several properties of the sample with minimal sample preparation and often to perform nondestructive quality evaluation. In this chapter, an overview of near‐infrared, mid‐infrared, and Raman spectrometries and infrared thermography is given for use in measuring quality attributes of horticultural produce.

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Light distribution inside mandarin fruit during internal quality assessment by NIR spectroscopy

Cited by 93 publications

References 16 publications

Multivariate diagnosis of the variability of NIR spectrometers under industrial applications

Multivariate diagnosis of the variability of NIR spectrometers under industrial applications

Non-destructive measurement of total soluble solid (TSS) content of dates using near infrared (NIR) imaging

Vibrational Spectroscopy Techniques in the Quality Assessment of Fruits and Vegetables

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