Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef

ElMasry, Gamal; Sun, Da‐Wen; Allen, Paul

doi:10.1016/j.jfoodeng.2011.11.028

Cited by 340 publications

(149 citation statements)

References 54 publications

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“…Each region is correlated to distinctive atomic or molecular transitions, according to the radiation energy. For HSI, NIR to MWIR range radiation is most commonly used for monitoring and quality inspection of agricultural products (ElMasrya et al, 2012;Kandpal et al, 2015).…”

Section: Hsi Foundations and Instrumentationmentioning

confidence: 99%

Outdoor Applications of Hyperspectral Imaging Technology for Monitoring Agricultural Crops: A Review

Ahmed¹,

Yasmin²,

Mo³

et al. 2016

Journal of Biosystems Engineering

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Background: Although hyperspectral imaging was originally introduced for military, remote sensing, and astrophysics applications, the use of analytical hyperspectral imaging techniques has been expanded to include monitoring of agricultural crops and commodities due to the broad range and highly specific and sensitive spectral information that can be acquired. Combining hyperspectral imaging with remote sensing expands the range of targets that can be analyzed. Results: Hyperspectral imaging technology can rapidly provide data suitable for monitoring a wide range of plant conditions such as plant stress, nitrogen status, infections, maturity index, and weed discrimination very rapidly, and its use in remote sensing allows for fast spatial coverage. Conclusions: This paper reviews current research on and potential applications of hyperspectral imaging and remote sensing for outdoor field monitoring of agricultural crops. The instrumentation and the fundamental concepts and approaches of hyperspectral imaging and remote sensing for agriculture are presented, along with more recent developments in agricultural monitoring applications. Also discussed are the challenges and limitations of outdoor applications of hyperspectral imaging technology such as illumination conditions and variations due to leaf and plant orientation.

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Section: Hsi Foundations and Instrumentationmentioning

confidence: 99%

Outdoor Applications of Hyperspectral Imaging Technology for Monitoring Agricultural Crops: A Review

Ahmed¹,

Yasmin²,

Mo³

et al. 2016

Journal of Biosystems Engineering

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“…ElMasry et al [33] have applied hyperspectral imaging (Imspector N17E, Specim, Spectral Imaging Ltd., Oulu, Finland) in the region 900-1700 nm for predicting colour, pH, and tenderness of fresh beef. With more improvement in terms of speed and processing, their approach has potential for nondestructive quality measurements.…”

Section: Authenticationmentioning

confidence: 99%

A Review of Optical Nondestructive Visual and Near-Infrared Methods for Food Quality and Safety

Alander

Bochko

Martinkauppi

et al. 2013

International Journal of Spectroscopy

126

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This paper is a review of optical methods for online nondestructive food quality monitoring. The key spectral areas are the visual and near-infrared wavelengths. We have collected the information of over 260 papers published mainly during the last 20 years. Many of them use an analysis method called chemometrics which is shortly described in the paper. The main goal of this paper is to provide a general view of work done according to different FAO food classes. Hopefully using optical VIS/NIR spectroscopy gives an idea of how to better meet market and consumer needs for high-quality food stuff.

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“…Hyperspectral imaging (HSI) with its advantage of providing both spectral and spatial information of samples simultaneously is receiving a growing interest and attention in the meat industry [23,24]. Spectral information can effectively reflect the chemical components within the meat [25][26][27], while spatial information can evaluate important physical qualities of meat, such as size, shape, texture, etc.…”

Section: Introductionmentioning

confidence: 99%

Fusion of Spectra and Texture Data of Hyperspectral Imaging for the Prediction of the Water-Holding Capacity of Fresh Chicken Breast Filets

Wang

Zhuang

et al. 2018

Applied Sciences

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This study investigated the fusion of spectra and texture data of hyperspectral imaging (HSI, 1000-2500 nm) for predicting the water-holding capacity (WHC) of intact, fresh chicken breast filets. Three physical and chemical indicators-drip loss, expressible fluid, and salt-induced water gain-were measured to be different WHC references of chicken meat. Different partial least squares regression (PLSR) models were established with corresponding input variables including the full spectra, key wavelengths, and texture variables, as well as the fusion data of key wavelengths and the corresponding texture variables, respectively. The results demonstrated that for drip loss and expressible fluid, texture data was an effective supplement to spectra data, and fusion data as an input variable could effectively improve the predictive ability of the independent prediction set (Rp = 0.80, RMSEp = 0.80; Rp = 0.56, RMSEp = 2.10). While the best model to predict salt-induced water gain was based on key wavelengths (Rp = 0.69, RMSEp = 18.04), this was mainly because salt-induced water gain was measured on mince samples, which lacked the important physical structure to represent the texture information of meat. Our results of this study demonstrated the potential to further improve the evaluation of the WHC of chicken meat by HSI.

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Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef

Cited by 340 publications

References 54 publications

Outdoor Applications of Hyperspectral Imaging Technology for Monitoring Agricultural Crops: A Review

Outdoor Applications of Hyperspectral Imaging Technology for Monitoring Agricultural Crops: A Review

A Review of Optical Nondestructive Visual and Near-Infrared Methods for Food Quality and Safety

Fusion of Spectra and Texture Data of Hyperspectral Imaging for the Prediction of the Water-Holding Capacity of Fresh Chicken Breast Filets

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