Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content

Peng, Yankun; Lu, Renfu

doi:10.1016/j.postharvbio.2007.09.019

Cited by 207 publications

(102 citation statements)

References 25 publications

Supporting

Mentioning

101

Contrasting

Unclassified

Order By: Relevance

“…Scattering profiles obtained using the procedures described above may suffer from a certain degree of distortion due to the uneven instrumental responses and the surface curvature of the fruit [54,55]. Hence, corrections are needed to address the distortion for accurately quantifying scattering profiles.…”

Section: Correction Of Scattering Profilesmentioning

confidence: 99%

“…From Figure 11b, the point closer to the incident center, has a larger viewing angle and thus a larger detected scattering intensity. To tackle this issue, a model-based method was proposed with an assumption that the angular distribution of scattering intensity on the fruit surface follows the Lambertian Cosine Law [49,54,56]. Then the detected scattering intensity, d S , for the point m can be expressed as follows: …”

Section: Correction Of Scattering Profilesmentioning

confidence: 99%

“…Peng and Lu [50] noted that the scattering profile could be represented by an appropriate mathematical function. Several distribution functions including exponential, Gaussian, Lorentzian and Gompertz, as summarized in Table 1, which are commonly used for describing light scattering in optics, can model scattering profiles [25,[50][51][52]54]. Parameters in these functions can be used as scattering features to characterize the scattering profiles and each scattering profile is thus reduced to two to four features, resulting in great reductions in the raw data volume.…”

Section: Feature Extractionmentioning

confidence: 99%

See 2 more Smart Citations

Innovative Hyperspectral Imaging-Based Techniques for Quality Evaluation of Fruits and Vegetables: A Review

Huang

2017

Applied Sciences

Self Cite

View full text Add to dashboard Cite

New, non-destructive sensing techniques for fast and more effective quality assessment of fruits and vegetables are needed to meet the ever-increasing consumer demand for better, more consistent and safer food products. Over the past 15 years, hyperspectral imaging has emerged as a new generation of sensing technology for non-destructive food quality and safety evaluation, because it integrates the major features of imaging and spectroscopy, thus enabling the acquisition of both spectral and spatial information from an object simultaneously. This paper first provides a brief overview of hyperspectral imaging configurations and common sensing modes used for food quality and safety evaluation. The paper is, however, focused on the three innovative hyperspectral imaging-based techniques or sensing platforms, i.e., spectral scattering, integrated reflectance and transmittance, and spatially-resolved spectroscopy, which have been developed in our laboratory for property and quality evaluation of fruits, vegetables and other food products. The basic principle and instrumentation of each technique are described, followed by the mathematical methods for processing and extracting critical information from the acquired data. Applications of these techniques for property and quality evaluation of fruits and vegetables are then presented. Finally, concluding remarks are given on future research needs to move forward these hyperspectral imaging techniques.

show abstract

Section: Correction Of Scattering Profilesmentioning

confidence: 99%

Section: Correction Of Scattering Profilesmentioning

confidence: 99%

Section: Feature Extractionmentioning

confidence: 99%

See 1 more Smart Citation

Innovative Hyperspectral Imaging-Based Techniques for Quality Evaluation of Fruits and Vegetables: A Review

Huang

2017

Applied Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…Near-infrared (NIR) and visual spectroscopy: Recently, NIR spectroscopy has become a useful technique for measuring soluble solids content (SSC), fruit fi rmness, acidity etc (Peng and Lu 2008). Lu (2003) developed a technique for estimating fruit fi rmness based on analyzing scattering images from fruit at multiple wavelengths in the visible and NIR region.…”

Section: Nuclear Magnetic Resonance (Nmr) Techniquementioning

confidence: 99%

Quality parameters of mango and potential of non-destructive techniques for their measurement — a review

et al. 2010

View full text Add to dashboard Cite

The king of fruits "Mango" (Mangifera indica L.) is very nutritious and rich in carotenes. India produces about 50% of the total world's mango. Many researchers have reported the maturity indices and quality parameters for determination of harvesting time and eating quality. The methods currently used for determination of quality of mango are mostly based on the biochemical analysis, which leads to destruction of the fruits. Numerous works are being carried out to explore some non-destructive methods such as Near Infrared (NIR), Nuclear Magnetic Resonance (NMR), X-ray and Computed Tomography (CT), electronic nose, machine vision and ultrasound for quality determination of fruits. This paper deals with some recent work reported on quality parameters, harvesting and post-harvest treatments in relation to quality of mango fruits and reviews on some of the potential non-destructive techniques that can be explored for quality determination of mango cultivars.

show abstract

“…All these methods allow us to extract the optical properties of turbid tissues, provided that an appropriate radiation transfer equation coupled with an inverse algorithm is used to fit the reflectance data [11][12][13]. Optical techniques devoted to the measurements of quality attributes of fruits, and food products mainly concern the hyperspectral imaging-based spatially-resolved method [14][15][16][17], and time-resolved method [1,2,18,19]. Studies carried out by means of these two systems were based on the major assumption that the interrogated samples are plane and homogeneous.…”

Section: Introductionmentioning

confidence: 99%

Numerical Study of Light Transport in Apple Models Based on Monte Carlo Simulations

2015

View full text Add to dashboard Cite

This paper reports on the quantification of light transport in apple models using Monte Carlo simulations. To this end, apple was modeled as a two-layer spherical model including skin and flesh bulk tissues. The optical properties of both tissue types used to generate Monte Carlo data were collected from the literature, and selected to cover a range of values related to three apple varieties. Two different imaging-tissue setups were simulated in order to show the role of the skin on steady-state backscattering images, spatially-resolved reflectance profiles, and assessment of flesh optical properties using an inverse nonlinear least squares fitting algorithm. Simulation results suggest that apple skin cannot be ignored when a Visible/Near-Infrared (Vis/NIR) steady-state imaging setup is used for investigating quality attributes of apples. They also help to improve optical inspection techniques in the horticultural products.

show abstract

Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content

Cited by 207 publications

References 25 publications

Innovative Hyperspectral Imaging-Based Techniques for Quality Evaluation of Fruits and Vegetables: A Review

Innovative Hyperspectral Imaging-Based Techniques for Quality Evaluation of Fruits and Vegetables: A Review

Quality parameters of mango and potential of non-destructive techniques for their measurement — a review

Numerical Study of Light Transport in Apple Models Based on Monte Carlo Simulations

Contact Info

Product

Resources

About