Development of multispectral imaging systems for quality evaluation of cereal grains and grain products

Shahin, Muhammad A.; Hatcher, D. W.; Symons, Stephen J.

doi:10.1533/9780857095770.3.451

Cited by 8 publications

(2 citation statements)

References 49 publications

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“…While hyperspectral imaging systems with relevant multivariate analyses are able to identify kernel damage, multispectral systems are much simpler and less expensive. In this regard, Shahin et al [ 97 ] analyzed the hyperspectral data to select the most relevant wavelengths suitable for detecting green barely kernels. They then developed a multispectral imaging system with a single monochromatic camera and a high-speed filter wheel supported with three different band-pass filter centered at wavelengths of 580, 671 and 730 nm as nominated by the hyperspectral data analysis.…”

Section: Applications Of Multispectral Imaging For Seed Quality Momentioning

confidence: 99%

Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring—An Overview

ElMasry

Mandour

Al-Rejaie

et al. 2019

Sensors

149

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As a synergistic integration between spectroscopy and imaging technologies, spectral imaging modalities have been emerged to tackle quality evaluation dilemmas by proposing different designs with effective and practical applications in food and agriculture. With the advantage of acquiring spatio-spectral data across a wide range of the electromagnetic spectrum, the state-of-the-art multispectral imaging in tandem with different multivariate chemometric analysis scenarios has been successfully implemented not only for food quality and safety control purposes, but also in dealing with critical research challenges in seed science and technology. This paper will shed some light on the fundamental configuration of the systems and give a birds-eye view of all recent approaches in the acquisition, processing and reproduction of multispectral images for various applications in seed quality assessment and seed phenotyping issues. This review article continues from where earlier review papers stopped but it only focused on fully-operated multispectral imaging systems for quality assessment of different sorts of seeds. Thence, the review comprehensively highlights research attempts devoted to real implementations of only fully-operated multispectral imaging systems and does not consider those ones that just utilized some key wavelengths extracted from hyperspectral data analyses without building independent multispectral imaging systems. This makes this article the first attempt in briefing all published papers in multispectral imaging applications in seed phenotyping and quality monitoring by providing some examples and research results in characterizing physicochemical quality traits, predicting physiological parameters, detection of defect, pest infestation and seed health.

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Section: Applications Of Multispectral Imaging For Seed Quality Momentioning

confidence: 99%

Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring—An Overview

ElMasry

Mandour

Al-Rejaie

et al. 2019

Sensors

149

View full text Add to dashboard Cite

show abstract

“…Over the past three decades, significant research into the use of non-destructive imaging to evaluate seed quality has been undertaken. Recent reviews outline the use of panchromatic, multispectral, hyperspectral, thermal, and x-ray imaging technology to evaluate seed physiological and physical damage (Shahin et al 2012;Huang et al 2015;Mahajan et al 2015;Rahman and Cho 2016;Saccon et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Quantifying Lygus (Hemiptera: Miridae) damage in faba bean (Fabaceae) seeds using shortwave-infrared imaging

et al. 2019

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Lygus Hahn (Hemiptera: Miridae) feeding in faba beans (Vicia faba Linnaeus (Fabaceae)) often results in a reduction in seed quality and economic losses. Traditionally, seed damage is assessed subjectively through visual examination by a trained individual, but the use of non-destructive imaging to evaluate seed quality is gaining momentum. The focus of this study was to determine the ability to quantify Lygus species damage in faba bean using shortwave-infrared imaging and two analysis techniques: (1) spectral angle mapper and (2) simple reflectance indices. Seed samples were visually assessed for damage before imaging in 242 wavebands between 980 and 2500 nm. Four spectral intervals, involving 102 wavebands, were identified as optimal for the detection of seed damage using spectral angle mapper. A strong relationship was obtained between the area of seed damage derived using spectral angle mapper and visually (R2 = 0.95). Seed damage derived by thresholding of two normalised faba bean damage indices involving reflectance at 1086 and 1313 nm and 2218 and 2342 nm also showed a strong relationship with the visual assessment (R2 = 0.92). The two image analysis techniques provided similar results. The study suggests that imaging in the shortwave-infrared wavelengths and the derivation of simple indices can effectively quantify faba bean damage by Lygus feeding.

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Improving Head Rice Yield and Milling Quality: State-of-the-Art and Future Prospects

Butardo

Sreenivasulu

2018

Methods in Molecular Biology

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Development of multispectral imaging systems for quality evaluation of cereal grains and grain products

Cited by 8 publications

References 49 publications

Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring—An Overview

Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring—An Overview

Quantifying Lygus (Hemiptera: Miridae) damage in faba bean (Fabaceae) seeds using shortwave-infrared imaging

Improving Head Rice Yield and Milling Quality: State-of-the-Art and Future Prospects

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