Economic Efficiency of Applying the Innovative Method of X-Ray Analysis of Seed Quality

2019 ◽  
pp. 62-64
Author(s):  
F.B. Musaev ◽  
◽  
S.L. Beletskiy ◽  
Keyword(s):  
Economic Efficiency ◽  
Seed Quality ◽  
X Ray ◽  
Innovative Method

Deep learning-based approach using X-ray images for classifying Crambe abyssinica seed quality

2021 ◽  
Vol 164 ◽  
pp. 113378 ◽  
Author(s):  
André Dantas de Medeiros ◽  
Rodrigo Cupertino Bernardes ◽  
Laércio Junio da Silva ◽  
Bruno Antônio Lemos de Freitas ◽  
Denise Cunha Fernandes dos Santos Dias ◽  
...  
Keyword(s):  
Deep Learning ◽  
Seed Quality ◽  
Crambe Abyssinica ◽  
X Ray

scholarly journals Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality

2020 ◽  
Author(s):  
Vitor J Bianchini ◽  
Gabriel M Mascarin ◽  
Lúcia CAS Silva ◽  
Valter Arthur ◽  
Jean M Carstensen ◽  
...  
Keyword(s):  
Jatropha Curcas ◽  
Seed Quality ◽  
Alternative Methods ◽  
Quality Analysis ◽  
Classification Models ◽  
X Ray ◽  
Imaging Technologies ◽  
X Ray Imaging ◽  
Non Destructive

Abstract Background: The use of non-destructive methods with less human interference is of great interest in agricultural industry and crop breeding. Modern imaging technologies enable the automatic visualization of multi-parameter for characterization of biological samples, reducing subjectivity and optimizing the analysis process. Furthermore, the combination of two or more imaging techniques has contributed to discovering new physicochemical tools and interpreting datasets in real time.Results: We present a new method for automatic characterization of seed quality based on the combination of multispectral and X-ray imaging technologies. We proposed an approach using X-ray images to investigate internal tissues because seed surface profile can be negatively affected, but without reaching important internal regions of seeds. An oilseed plant (Jatropha curcas) was used as a model species, which also serve as a multi-purposed crop of economic importance worldwide. Our studies included the application of a normalized canonical discriminant analyses (nCDA) algorithm as a supervised transformation building method to obtain spatial and spectral patterns on different seedlots. We developed classification models using reflectance data and X-ray classes based on linear discriminant analysis (LDA). The classification models, individually or combined, showed high accuracy (>0.96) using reflectance at 940 nm and X-ray data to predict quality traits such as normal seedlings, abnormal seedlings and dead seeds. Conclusions: Multispectral and X-ray imaging have a strong relationship with seed physiological performance. Reflectance at 940 nm and X-ray data can efficiently predict seed quality attributes. These techniques can be alternative methods for rapid, efficient, sustainable and non-destructive characterization of seed quality in the future, overcoming the intrinsic subjectivity of the conventional seed quality analysis.

scholarly journals Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality

2020 ◽  
Author(s):  
Vitor J Bianchini ◽  
Gabriel M Mascarin ◽  
Lúcia CAS Silva ◽  
Valter Arthur ◽  
Jean M Carstensen ◽  
...  
Keyword(s):  
Jatropha Curcas ◽  
Seed Quality ◽  
Alternative Methods ◽  
Quality Analysis ◽  
Classification Models ◽  
X Ray ◽  
Imaging Technologies ◽  
X Ray Imaging ◽  
Non Destructive

Abstract Background: The use of non-destructive methods with less human interference is of great interest in agricultural industry and crop breeding. Modern imaging technologies enable the automatic visualization of multi-parameter for characterization of biological samples, reducing subjectivity and optimizing the analysis process. Furthermore, the combination of two or more imaging techniques has contributed to discovering new physicochemical tools and interpreting datasets in real time.Results: We present a new method for automatic characterization of seed quality based on the combination of multispectral and X-ray imaging technologies. We proposed an approach using X-ray images to investigate internal tissues because seed surface profile can be negatively affected, but without reaching important internal regions of seeds. An oilseed plant (Jatropha curcas) was used as a model species, which also serve as a multi-purposed crop of economic importance worldwide. Our studies included the application of a normalized canonical discriminant analyses (nCDA) algorithm as a supervised transformation building method to obtain spatial and spectral patterns on different seedlots. We developed classification models using reflectance data and X-ray classes based on linear discriminant analysis (LDA). The classification models, individually or combined, showed high accuracy (>0.96) using reflectance at 940 nm and X-ray data to predict quality traits such as normal seedlings, abnormal seedlings and dead seeds.Conclusions: Multispectral and X-ray imaging have a strong relationship with seed physiological performance. Reflectance at 940 nm and X-ray data can efficiently predict seed quality attributes. These techniques can be alternative methods for rapid, efficient, sustainable and non-destructive characterization of seed quality in the future, overcoming the intrinsic subjectivity of the conventional seed quality analysis.

scholarly journals Dynamic pulse-to-pulse thermal load effects in pulse-train-mode self-seeded X-ray free-electron laser

2020 ◽  
Vol 27 (6) ◽  
pp. 1725-1729
Author(s):  
Zhengxian Qu ◽  
Yanbao Ma ◽  
Guanqun Zhou ◽  
Juhao Wu
Keyword(s):  
Free Electron ◽  
Free Electron Laser ◽  
Thermal Load ◽  
Pulse Train ◽  
Seed Quality ◽  
Thermal Distortion ◽  
Spectral Transmission ◽  
X Ray ◽  
Pulsed Mode ◽  
Load Effects

Thermal load has been a haunting factor that undermines the brightness and coherence of the self-seeded X-ray free-electron laser. Different from uniformly pulsed mode, in pulse train mode a thermal quasi-steady state of the crystal monochromator may not be reached. This leads to a dynamic thermal distortion of the spectral transmission curves and seed quality degradation. In this paper, the pulse-to-pulse thermal load effects on the spectral transmission curves and seed quality are shown, and some instructive information for the tuning process is provided.

scholarly journals Multispectral and X-ray Images for Characterization of Jatropha Curcas L. Seed Quality

2020 ◽  
Author(s):  
Vitor J Bianchini ◽  
Gabriel M Mascarin ◽  
Lúcia CAS Silva ◽  
Valter Arthur ◽  
Jean M Carstensen ◽  
...  
Keyword(s):  
Jatropha Curcas ◽  
Multispectral Imaging ◽  
Seed Quality ◽  
Strong Relationship ◽  
Biodiesel Production ◽  
Alternative Methods ◽  
Quality Analysis ◽  
X Ray ◽  
Jatropha Seed

Abstract Background: Jatropha curcas is an oilseed plant with great potential for biodiesel production. In agricultural industry, the seed quality is still estimated by manual inspection, using destructive, time-consuming and subjective tests that depend on the seed analyst experience. Recent advances in machine vision combined with artificial intelligence algorithms can provide spatial and spectral information for characterization of biological images, reducing subjectivity and optimizing the analysis process.Results: We present a new method for automatic characterization of jatropha seed quality, based on multispectral imaging (MSI) combined with X-ray imaging. We propose an approach along with X-ray images in order to investigate internal problems such as damages in the embryonic axis and endosperm, considering the fact that seed surface profiles can be negatively affected, but without reaching important internal regions of the seeds. Our studies included the application of a normalized canonical discriminant analyses (nCDA) algorithm as a supervised transformation building method to classify spatial and spectral patters according to the classes of seed quality. Spectral reflectance signatures in a range of 780 to 970 nm and the X-ray images can efficiently predict quality traits such as normal seedlings, abnormal seedlings and dead seeds.Conclusions: MSI and X-ray images have a strong relationship with physiological performance of Jatropha curcas L. These techniques can be alternative methods for rapid, efficient, sustainable and non-destructive characterization of jatropha seed quality in the future, overcoming the intrinsic subjectivity of the conventional seed quality analysis.

scholarly journals Radiographic analysis for the evaluation of polyembryony in Swingle citrumelo seeds

2018 ◽  
Vol 40 (2) ◽  
pp. 118-126
Author(s):  
Natália Arruda ◽  
Silvio Moure Cicero ◽  
Francisco Guilhien Gomes Junior
Keyword(s):  
Indirect Method ◽  
Seed Quality ◽  
Direct Method ◽  
Automated Systems ◽  
Radiographic Image ◽  
X Ray ◽  
Internal Morphology ◽  
Non Destructive ◽  
Swingle Citrumelo ◽  
Precision Test

Abstract: The polyembryony rate is a very important factor to consider when choosing a commercial rootstock. Currently, automated systems are used to improve seed quality analyses. X-ray testing is a fast, simple, non-destructive, high-precision test that allows to examine in detail the internal morphology of the seeds to identify damaged areas, their location and types of damage. In this context, the present research aimed to verify the possibility of using X-ray test to evaluate the polyembryony in Swingle citrumelo seeds. Seeds from seven lots were submitted to X-ray tests, direct method (embryo counts) and indirect method (germination). According to the results obtained, it was observed that there was a high coincidence between the number of embryos per seed analyzed using X-ray test and the direct method. Radiographic image analysis is efficient to evaluate the polyembryony in seeds of Swingle citrumelo.

An innovative method to reduce count loss from pulse pile-up in a photon-counting pixel for high flux X-ray applications

2017 ◽  
Vol 12 (03) ◽  
pp. P03006-P03006 ◽  
Author(s):  
D. Lee ◽  
K. Lim ◽  
K. Park ◽  
C. Lee ◽  
S. Alexander ◽  
...  
Keyword(s):  
Photon Counting ◽  
High Flux ◽  
X Ray ◽  
Innovative Method ◽  
Pile Up

Decision Method of Optimal X-Ray Digital Imaging Parameters

2014 ◽  
Vol 511-512 ◽  
pp. 536-540
Author(s):  
Liang Tao ◽  
Yu Jie Tong ◽  
Hang Zhao
Keyword(s):  
Digital Imaging ◽  
Quality Evaluation ◽  
Focal Length ◽  
Sampling Rate ◽  
Optimization Method ◽  
Fusion Welding ◽  
Flat Panel ◽  
X Ray ◽  
Decision Method ◽  
Innovative Method

X-ray Digital imaging is an innovative method of metal fusion welding quality evaluation. To improve the accuracy, the digital imaging sensitivity must be increased by studying the optimal radioactive parameters. At first, the basic elements, inherent characteristics and imaging principle have been analysed systematically. Secondly, the optimization method of sampling rate, stacking frames, focal length, cube voltage and current have been studied based on the phisical characteristic of FPD( Flat Panel Detector). At last, the method has been verified upon two platforms. The experimental results from different systems proved correctness and applicability.

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