4.6 Review

Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality MonitoringAn Overview

期刊

SENSORS
卷 19, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/s19051090

关键词

seed; grain; multispectral imaging; hyperspectral imaging; quality evaluation; germination; viability

资金

  1. STDF-IRD-AUF joint research project by Egyptian Science and Technology Development Fund (STDF)
  2. Institut de recherche pour le developpement (IRD)
  3. Agence Universitaire de la Francophonie (AUF)

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Biochemistry & Molecular Biology

Expeditious prediction of post-mortem changes in frozen fish meat using three-dimensional fluorescence fingerprints

Md. Mizanur Rahman, Mario Shibata, Gamal ElMasry, Naho Nakazawa, Shigeki Nakauchi, Tomoaki Hagiwara, Kazufumi Osako, Emiko Okazaki

BIOSCIENCE BIOTECHNOLOGY AND BIOCHEMISTRY (2019)

Article Biochemical Research Methods

Utilization of computer vision and multispectral imaging techniques for classification of cowpea (Vigna unguiculata) seeds

Gamal ElMasry, Nasser Mandour, Marie-Helene Wagner, Didier Demilly, Jerome Verdier, Etienne Belin, David Rousseau

PLANT METHODS (2019)

Article Environmental Sciences

Supervised Image Classification by Scattering Transform with Application to Weed Detection in Culture Crops of High Density

Pejman Rasti, Ali Ahmad, Salma Samiei, Etienne Belin, David Rousseau

REMOTE SENSING (2019)

Article Food Science & Technology

Real-time quality authentication of honey using atmospheric pressure chemical ionisation mass spectrometry (APCI-MS)

Gamal ElMasry, Noha Morsy, Salim Al-Rejaie, Charfedinne Ayed, Robert Linforth, Ian Fisk

INTERNATIONAL JOURNAL OF FOOD SCIENCE AND TECHNOLOGY (2019)

Article Green & Sustainable Science & Technology

Effectiveness of recyclable aluminum cans in fabricating an efficient solar collector for drying agricultural products

Sameh S. Kishk, Ramadan A. ElGamal, Gamal M. ElMasry

RENEWABLE ENERGY (2019)

Article Engineering, Chemical

Effectiveness of specularity removal from hyperspectral images on the quality of spectral signatures of food products

Gamal ElMasry, Pere Gou, Salim Al-Rejaie

Summary: In this study, a non-iterative method based on the dichromatic reflection model and principle component analysis (PCA) was proposed to detect and remove specular highlight components from hyperspectral images. The method effectively reduced the specularity and significantly improved the quality of the extracted spectral data, outperforming other specularity removal methods over datasets of hyperspectral and multispectral images.

JOURNAL OF FOOD ENGINEERING (2021)

Article Nutrition & Dietetics

Supplementation of Morin Restores the Altered Bone Histomorphometry in Hyperglycemic Rodents via Regulation of Insulin/IGF-1 Signaling

Hatem M. Abuohashish, Abdullah F. AlAsmari, Mohamed Mohany, Mohammed M. Ahmed, Salim S. Al-Rejaie

Summary: This study finds that morin can protect against altered bone histomorphometry in diabetic rats by modulating the insulin/IGF-1 pathway, restoring bone density and histomorphology, and alleviating systemic oxidative stress.

NUTRIENTS (2021)

Review Chemistry, Analytical

Recent Advances of Smart Systems and Internet of Things (IoT) for Aquaponics Automation: A Comprehensive Overview

Mohamed Farag Taha, Gamal ElMasry, Mostafa Gouda, Lei Zhou, Ning Liang, Alwaseela Abdalla, David Rousseau, Zhengjun Qiu

Summary: This article comprehensively highlights research efforts devoted to the utilization of automated, fully operated aquaponic systems, discussing all related parameters aligned with smart automation scenarios and IoT supported by examples and research results. It also explores potential gaps in the literature and future contributions related to automated aquaponics. It is expected that aquaponics systems supported with smart control units will become more profitable, intelligent, accurate, and effective.

CHEMOSENSORS (2022)

Article Green & Sustainable Science & Technology

Using Machine Learning for Nutrient Content Detection of Aquaponics-Grown Plants Based on Spectral Data

Mohamed Farag Taha, Ahmed Islam ElManawy, Khalid S. Alshallash, Gamal ElMasry, Khadiga Alharbi, Lei Zhou, Ning Liang, Zhengjun Qiu

Summary: This study developed trustworthy machine learning models to estimate the nitrogen, phosphorus, and potassium contents of aquaponically grown lettuce. By using spectral measurements and various algorithms, predictive models were established for automatic nutrient estimation, resulting in improved intelligence and precision in aquaponics.

SUSTAINABILITY (2022)

Review Agronomy

Thermal Degradation of Bioactive Compounds during Drying Process of Horticultural and Agronomic Products: A Comprehensive Overview

Ramadan ElGamal, Cheng Song, Ahmed M. Rayan, Chuanping Liu, Salim Al-Rejaie, Gamal ElMasry

Summary: This article provides an updated overview of the effects of the drying process on bioactive compounds in agricultural products. It discusses how high drying temperatures lead to degradation of vitamin C, phenols, flavonoids, glycosides, and volatile compounds, while relatively low drying temperatures help maintain their activity.

AGRONOMY-BASEL (2023)

Review Agriculture, Dairy & Animal Science

Non-Invasive Assessment of the Intraventricular Pressure Using Novel Color M-Mode Echocardiography in Animal Studies: Current Status and Future Perspectives in Veterinary Medicine

Ahmed S. Mandour, Ahmed Farag, Mahmoud A. Y. Helal, Gamal El-Masry, Salim Al-Rejaie, Ken Takahashi, Tomohiko Yoshida, Lina Hamabe, Ryou Tanaka

Summary: Traditional echocardiographic imaging is limited in identifying cardiac diseases before symptoms become clear, thus there is a need for new methods for prediction and early diagnosis. Non-invasive assessment of heart function, particularly diastolic function, is gaining attention. Color M-mode echocardiography (CMME) has shown promising results in non-invasive assessment of diastolic function and its relation to catheterization technique measurements. This technique has potential applications for early identification of cardiac dysfunctions in both animal and human studies.

ANIMALS (2023)

Article Biochemistry & Molecular Biology

Molecular Insights into Human Transmembrane Protease Serine-2 (TMPS2) Inhibitors against SARS-CoV2: Homology Modelling, Molecular Dynamics, and Docking Studies

Safaa M. Kishk, Rania M. Kishk, Asmaa S. A. Yassen, Mohamed S. Nafie, Nader A. Nemr, Gamal ElMasry, Salim Al-Rejaie, Claire Simons

MOLECULES (2020)

暂无数据