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1¡¢Classification of Processing Damage in Sugar Beet (Beta vulgaris) Seeds by Multispectral Image Analysis
2¡¢Systematic establishment of colour descriptor states through image-based phenotyping
3¡¢ÀûÓöà¹âÆ׳ÉÏñϵͳ½áºÏ»¯Ñ§¼ÆÁ¿·¨ÎÞËð¼ø±ð¸ßÆ·ÖÊÎ÷¹ÏÖÖ×ӵĿÉÐÐÐÔ¡£
4¡¢Genebank seed accession phenotyping through spectral imaging
5¡¢Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring¡ªAn Overview
6¡¢Utilization of computer vision and multispectral imaging techniques for classifcation of cowpea (Vigna unguiculata) seeds
7¡¢Final report: Application of multispectral imaging (MSI) to food and feed sampling and analysis FSA Contract Reference No.: SEP-EOI-05
Project Deliverable: 5
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1.A virtual seed file: the use of multispectral image analysis in the management of genebank seed accessions
2.Multispectral imaging as a potential tool for seed health testing of spinach (Spinacia oleracea L.)
3.Classification of different tomato seed cultivars by multispectral visible-near infrared spectroscopy and chemometrics
4.Viability prediction of Ricinus cummunis L. seeds using multispectral imaging
5.Online variety discrimination of rice seeds using multispectral imaging and chemometric methods
6.Classification of Processing Damage in Sugar Beet (Beta vulgaris) Seeds by Multispectral Image Analysis
7.Nondestructive determination of transgenic Bacillus thuringiensis rice seeds (Oryza sativa L.) using multispectral imaging and chemometric methods
8.Use of multispectral images and chemometrics in tomato seed studies
9.Discrimination in varieties of rice seeds with multispectral imaging using support vector machine
10.Rapid Discrimination of High-Quality Watermelon Seeds by Multispectral Imaging Combined with Chemometric Methods
11.Non-destructive discrimination of conventional and glyphosate-resistant soybean seeds and their hybrid descendants using multispectral imaging and chemometric methods
12.Discrimination of Kernel Quality Characteristics for Sunflower Seeds Based on Multispectral Imaging Approach
13.Multispectral imaging ¨C a new tool in seed quality assessment?
14.Classification of Haploid and Diploid Maize Seeds by Using Image Processing Techniques and Support Vector Machines
15.Use of partial least squares discriminant analysis on visible-near infrared multispectral image data to examine germination ability and germ length in spinach seeds
16.Identification of Haploid Maize Seeds using Gray Level Co-occurrence Matrix and Machine Learning Techniques
17.Effects of Polymer Coating on Rice Seed Germination
18.Recent advances in emerging techniques for non-destructive detection of seed viability: A review
19.Optimization of Germination Inhibitors Elimination from Sugar Beet (Beta vulgaris L.) Seeds of Different Maturity Classes
20.Differentiation of alfalfa and sweet clover seeds via multispectral imaging
21.Integrating Optical Imaging Tools for Rapid and Non-invasive Characterization of Seed Quality: Tomato (Solanum lycopersicum L.) and Carrot (Daucus carota L.) as Study Cases
22.Determination Of Sitotroga cerealella (Lepidoptera: Gelechiidae) Infestation In Wheat Seeds By Radiographic And Multispectral Image Analysis
23.Geographical and inter-annual patterns of seed viability in the threatened cold desert perennial Ivesia webberi, and the prospect of nondestructive seed testing methods*
24.Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality
25.Discrimination of Pepper Seed Varieties by Multispectral Imaging Combined with Machine Learning
26.Non-destructive identification of single hard seed via multispectral imaging analysis in six legume species
27.Seed germination and seedling growth parameters in nine tall fescue varieties under salinity stress
28.A novel approach for Jatropha curcas seed health analysis based on multispectral and resonance imaging techniques
29.Cultivar Discrimination of Single Alfalfa (Medicago sativa L.) Seed via Multispectral Imaging Combined with Multivariate Analysis
30.Chlorophyll fluorescence as a new marker for peanut seed quality evaluation
31.Non-Destructive Identification of Naturally Aged Alfalfa Seeds via Multispectral Imaging Analysis
32.Autofluorescence?spectral imaging as an innovative method for rapid, non?destructive and reliable assessing of soybean seed quality
33.Research on Classification Method of Eggplant Seeds Based on Machine Learning and Multispectral Imaging Classification Eggplant Seeds
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