Detecting Fertility and Early Embryo Development of Chicken Eggs Using Near-Infrared Hyperspectral Imaging

Liu, L.; Ngadi, Michael

doi:10.1007/s11947-012-0933-3

Cited by 109 publications

(86 citation statements)

References 13 publications

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“…In the field of poultry farms, hyperspectral imaging is used to design a rapid, accurate and non-distractive method to detect the embryo and fertility improvement in eggs [31]. A near infrared spectral imaging system was introduced for the identification of fertility and early embryo improvement.…”

Section: Discussionmentioning

confidence: 99%

The Role of Hyperspectral Imaging: A Literature Review

Mateen¹,

Wen²,

Nasrullah³

et al. 2018

ijacsa

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Abstract-Optical analysis techniques are used recently to detect and identify the objects from a large scale of images. Hyperspectral imaging technique is also one of them. Vision of human eye is based on three basic color (red, green and blue) bands, but spectral imaging divides the vision into many more bands. Hyperspectral remote sensors achieve imagery data in the form of hundreds of adjoining spectral bands. In this paper, our purpose is to illustrate the fundamental concept, hyperspectral remote sensing, remotely sensed information, methods for hyperspectral imaging and applications based on hyperspectral imaging. Moreover, in the forensic context, the novel methods involving deep neural networks are elaborated in this paper. The proposed idea can be useful for further research in the field of hyperspectral imaging using deep learning.

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Section: Discussionmentioning

confidence: 99%

The Role of Hyperspectral Imaging: A Literature Review

Mateen¹,

Wen²,

Nasrullah³

et al. 2018

ijacsa

View full text Add to dashboard Cite

show abstract

“…It is influenced by many factors such as egg handling, fertility of eggs, breeder flock problem, etc. However, the most critical factor is to be sure that the eggs placed in the incubator are truly fertile eggs 2 . Early detection of infertile and non-hatchable eggs would benefits hatcheries and poultry breeding farms by saving space, handling costs, and preventing contamination from exploder eggs 2 .…”

Section: Introductionmentioning

confidence: 99%

“…However, the most critical factor is to be sure that the eggs placed in the incubator are truly fertile eggs 2 . Early detection of infertile and non-hatchable eggs would benefits hatcheries and poultry breeding farms by saving space, handling costs, and preventing contamination from exploder eggs 2 . In most incubation centers, the process of separating fertilized and non-fertilized eggs is performed by experts (through human vision and traditional ways) before loading the eggs into the incubators.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, usually only some eggs are randomly selected for determination of flock fertility, which means most infertile eggs will remain in the incubator 2 . Moreover to the capacity issue, the remaining infertile eggs inside the incubator will be contaminated, and, as a consequence, some gases will be released into the environment making the situation problematic for the other healthy embryos 1 .…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers have tried to determine the fertility of eggs by employing equipment such as MRI, infrared hyperspectral imaging, or thermal cameras 2,18,19,20,21 . However, using this expensive equipment would not be economical, especially in the case of mass production.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Machine Vision System for Detecting Fertile Eggs in the Incubation Industry

Hashemzadeh¹,

Farajzadeh²

2016

IJCIS

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One of the important factors in increasing the productivity of the incubation industry is to be sure that the eggs placed in the incubators are fertile. In this research, a fertility detection machine vision system is developed and evaluated. To this end, a mechatronic machine is fabricated for acquiring accurate digital images of eggs without harming them. An appropriate and cheap light source is also introduced for illuminating the eggs, which potentially enables a CCD camera to obtain good quality and informative images from inner side of the eggs. Finally, a robust machine vision algorithm is developed to process the captured images and distinguish fertile eggs from infertile ones. In order to evaluate the system, a large egg image dataset is provided using 240 incubated eggs (including 190 fertile and 50 infertile eggs). The fertility detection accuracy of the system on the provided dataset reaches 47.13% at day 1 of incubation, 81.41% at day 2, 93.08% at day 3, 97.73% at day 4, and 98.25% at day 5. Comparisons with existing approaches show that the proposed method achieves a superior performance. The obtained results indicate that the proposed system is highly reliable and applicable in the incubation industry.

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Dark‐field hyperspectral imaging for label free detection of nano‐bio‐materials

Mehta

Sahu

Shaik

et al. 2020

WIREs Nanomed Nanobiotechnol

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Nanomaterials are playing an increasingly important role in cancer diagnosis and treatment. Nanoparticle (NP)‐based technologies have been utilized for targeted drug delivery during chemotherapies, photodynamic therapy, and immunotherapy. Another active area of research is the toxicity studies of these nanomaterials to understand the cellular uptake and transport of these materials in cells, tissues, and environment. Traditional techniques such as transmission electron microscopy, and mass spectrometry to analyze NP‐based cellular transport or toxicity effect are expensive, require extensive sample preparation, and are low‐throughput. Dark‐field hyperspectral imaging (DF‐HSI), an integration of spectroscopy and microscopy/imaging, provides the ability to investigate cellular transport of these NPs and to quantify the distribution of them within bio‐materials. DF‐HSI also offers versatility in non‐invasively monitoring microorganisms, single cell, and proteins. DF‐HSI is a low‐cost, label‐free technique that is minimally invasive and is a viable choice for obtaining high‐throughput quantitative molecular analyses. Multimodal imaging modalities such as Fourier transform infrared and Raman spectroscopy are also being integrated with HSI systems to enable chemical imaging of the samples. HSI technology is being applied in surgeries to obtain molecular information about the tissues in real‐time. This article provides brief overview of fundamental principles of DF‐HSI and its application for nanomaterials, protein‐detection, single‐cell analysis, microbiology, surgical procedures along with technical challenges and future integrative approach with other imaging and measurement modalities. This article is categorized under: Diagnostic Tools > in vitro Nanoparticle‐Based Sensing Diagnostic Tools > in vivo Nanodiagnostics and Imaging Implantable Materials and Surgical Technologies > Nanoscale Tools and Techniques in Surgery

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Detecting Fertility and Early Embryo Development of Chicken Eggs Using Near-Infrared Hyperspectral Imaging

Cited by 109 publications

References 13 publications

The Role of Hyperspectral Imaging: A Literature Review

The Role of Hyperspectral Imaging: A Literature Review

A Machine Vision System for Detecting Fertile Eggs in the Incubation Industry

Dark‐field hyperspectral imaging for label free detection of nano‐bio‐materials

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