Nondestructive Measurement of Fruit and Vegetable Quality

Nicolaı̈, Bart; Defraeye, Thijs; Ketelaere, Bart De; Herremans, Els; Hertog, Maarten; Saeys, Wouter; Torricelli, Alessandro; Vandendriessche, Thomas; Verboven, Pieter

doi:10.1146/annurev-food-030713-092410

Cited by 167 publications

(71 citation statements)

References 171 publications

(167 reference statements)

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“…However, when the MLR model was performed for the combination of three monochromatic wavelengths (635, 525, and 470 nm), it generated better correlation compared with that of individual wavelengths. 81 All these wavelengths are very common to show the spectral signatures of pigment composition of fruits, such as chlorophyll, anthocyanins, and carotenoids. As for the firmness measurement, the algorithm was suitably generated by linear regression, as represented in Eq.…”

Section: Resultsmentioning

confidence: 99%

Simplified optical fiber RGB system in evaluating intrinsic quality of Sala mango

et al. 2015

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This study presents an alternative approach for the nondestructive assessment of fruit quality parameters with the use of a simplified optical fiber red-green-blue system (OF-RGB). The optical sensor system presented in this work is designed to rapidly measure the firmness, acidity, and soluble solid content of an intact Sala mango on the basis of color properties. The system consists of three light-emitting diodes with peak emission at 635 (red), 525 (green), and 470 nm (blue), as well as a single photodetector capable of sensing visible light. The measurements were conducted using the reflectance technique. The analyses were conducted by comparing the results obtained through the proposed system with those measured using two commercial spectrometers, namely, QE65000 and FieldSpec 3. The developed RGB system showed satisfactory accuracy in the measurement of acidity (R 2 ¼ 0.795) and firmness (R 2 ¼ 0.761), but a relatively lower accuracy in the measurement of soluble solid content (R 2 ¼ 0.593) of intact mangoes. The results obtained through OF-RGB are comparable with those measured by QE65000 and FieldSpec 3. This system is a promising new technology with rapid response, easy operation, and low cost with potential applications in the nondestructive assessment of quality attributes.

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Section: Resultsmentioning

confidence: 99%

Simplified optical fiber RGB system in evaluating intrinsic quality of Sala mango

et al. 2015

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“…In x-ray digital radiography (DR), a single image consisting of a projection of transmitted x-rays through an object is acquired. DR is widely used commercially for the detection of contaminants in foods (Nicolai et al, 2014). A few studies have employed DR for the investigation of infestation damage in fruits (Jiang et al, 2008) and understanding quality attributes of nuts (Kim & Schatzki, 2001).…”

Section: Introductionmentioning

confidence: 99%

A method to determine the density of foods using X-ray imaging

Kelkar

Boushey

Okos

2015

Journal of Food Engineering

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Density of foods is an important physical property, which depends on structural properties of food. For porous foods such as baked foods, accurate measurement of density is challenging since traditional density measurement techniques are tedious, operator-dependent and incapable of precise volume measurement of foods. To overcome such limitations, a methodology was developed using both digital radiography(DR) and computed tomography(CT) x-ray imaging to directly determine density of foods. Apparent density was determined directly from x-ray linear attenuation coefficients by scanning at 40, 60, 80 kVp on DR and 45, 55, 70 kVp on CT. The apparent density can be directly determined using CT however sample thickness is needed to determine density using DR. No significant difference (p<0.05) was observed between density obtained from traditional methods, with density determined from x-ray linear attenuation coefficients. Density determined on CT for all foods with mean 0.579 g/cm3 had a standard deviation, SD = 0.0367 g/cm3. Density determination using x-ray linear attenuation was found to be a more efficient technique giving results comparable with conventional techniques.

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“…Progress has been made in the development of non-destructive imaging techniques to detect spatially distributed internal disorders Nicolaï et al, 2014). Techniques such as magnetic resonance imaging (MRI, Clark et al, 1999;Defraeye et al, 2013;Hernández-Sánchez et al, 2006;Lammertyn et al, 2003a,b;Zhang andMcCarthy, 2013 Lammertyn et al, 2003a,b;Zhang and McCarthy, 2013), nuclear magnetic resonance (NMR, Defraeye et al, 2013;Lammertyn et al, 2003a,b;Zhang and McCarthy, 2013), visible/ near infrared spectroscopy (Magwaza et al, , 2012Nicolaï et al, 2007), hyperspectral imaging (Haff et al, 2013;Xing et al, 2007) and optical coherence tomography (OCT, Magwaza et al, 2013;Verboven et al, 2013), as well as X-ray radiographs and X-ray computed tomography (CT, Donis-González et al, 2014;Herremans et al, 2013;Kotwaliwale et al, 2014;Lammertyn et al, 2003a,b Herremans et al, 2013Kotwaliwale et al, 2014,b;Lammertyn et al, 2003a,b) have been subjects of research into non-destructive evaluation of internal quality in fresh food products.…”

Section: Introductionmentioning

confidence: 99%

“…The resolution varies from 1 mm in medical scanners down to the micrometer level on dedicated micro-CT scanners (Verboven et al, 2008). X-ray CT has been used successfully to detect internal disorders in pear (Lammertyn et al, 2003a), apple Nicolaï et al, 2014;Schatzki et al, 1996) and pineapple (Haff et al, 2006). However, the equipment is expensive and the 3-dimensional reconstruction comes at a high computational cost making it difficult to apply into existing sorting lines.…”

Section: Introductionmentioning

confidence: 99%

A segmentation and classification algorithm for online detection of internal disorders in citrus using X-ray radiographs

Dael

Lebotsa

Herremans

et al. 2016

Postharvest Biology and Technology

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Oranges and lemons can be affected by the physiological disorders granulation and endoxerosis respectively, decreasing their commercial value. X-ray radiographs provide images of the internal structure of citrus on which the disorders can be discerned. An image processing algorithm is proposed to detect these disorders on X-ray projection images and classify samples as being affected or not. The method automatically segments healthy and affected tissue, calculates a set of image features and uses these to classify the images using a naïve Bayes or kNN classifier. The developed method avoids the need for labour-intensive destructive sampling and allows for non-destructive inspection of all fruits while preventing losses due to destructive sampling. The proposed algorithm classifies 95.7% of oranges and 93.6% of lemons correctly. The classification method is fast, robust to noise and can be applied to any existing inline X-ray radiograph equipment.

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Nondestructive Measurement of Fruit and Vegetable Quality

Cited by 167 publications

References 171 publications

Simplified optical fiber RGB system in evaluating intrinsic quality of Sala mango

Simplified optical fiber RGB system in evaluating intrinsic quality of Sala mango

A method to determine the density of foods using X-ray imaging

A segmentation and classification algorithm for online detection of internal disorders in citrus using X-ray radiographs

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