Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring—An Overview
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This article is 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.Abstract:
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.read more
Citations
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An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario
TL;DR: This work presents a platform oriented to the application of IoT, Edge Computing, Artificial Intelligence and Blockchain techniques in Smart Farming environments, by means of the novel Global Edge Computing Architecture, designed to monitor the state of dairy cattle and feed grain in real time, as well as ensure the traceability and sustainability of the different processes involved in production.
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On line detection of defective apples using computer vision system combined with deep learning methods
TL;DR: The overall results indicated that the proposed CNN-based classification model had great potential to be implemented in commercial packing line.
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Recent advances in emerging techniques for non-destructive detection of seed viability: A review
TL;DR: This review focuses on the comparative introduction, development and applications of emerging techniques in the analysis of seed viability, in particular, near infrared spectroscopy, hyperspectral and multispectral imaging, Raman spectroscopic, infrared thermography, and soft X-ray imaging methods.
Journal ArticleDOI
Evaluation of fresh meat quality by Hyperspectral Imaging (HSI), Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI): A review.
TL;DR: The overall evaluation is that work has been performed primarily in an experimental way but generally still lacks real application in the meat industry, and these non-destructive techniques should be improved, especially regarding speed, price and influence of external factors.
Journal ArticleDOI
Hyperspectral imaging technology combined with deep forest model to identify frost-damaged rice seeds.
TL;DR: The results of this study show that the DF model maintains good classification performance in small-scale sample set data, and it has a good application prospect in hyperspectral imaging technology.
References
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Seed Germination and Vigor
Loïc Rajjou,Manuel Duval,Karine Gallardo,Julie Catusse,Julia Bally,Claudette Job,Dominique Job +6 more
TL;DR: It is highlighted that germination vigor depends on multiple biochemical and molecular variables and their characterization is expected to deliver new markers of seed quality that can be used in breeding programs and/or in biotechnological approaches to improve crop yields.
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A review of imaging techniques for plant phenotyping.
Lei Li,Qin Zhang,Danfeng Huang +2 more
TL;DR: A brief review on a variety of imaging methodologies used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress in plant phenotyping.
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Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review
TL;DR: The aim of this review is to give detailed outlines about the theory and principles of hyperspectral imaging and to focus primarily on its applications in the field of quality evaluation of agro-food products as well as its future applicability in modern food industries and research.
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Development of hyperspectral imaging technique for the detection of apple surface defects and contaminations
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