Digital image-based classification of biodiesel

Costa, Gabriela Maria Cavalcanti; Fernandes, David; Almeida, Valber Elias de; Araújo, Thomas Souto Policarpo; Melo, Jéssica Priscila de; Diniz, Paulo Henrique Gonçalves Dias; Véras, Germano

doi:10.1016/j.talanta.2015.02.043

Cited by 48 publications

(18 citation statements)

References 26 publications

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“…Therefore, we analyzed color data of RGB and grayscale channels for each 39,065 seeds and analyzed it by using pixel distribution graph. Red, green, and blue histograms were used to classify soybean seeds color, and grayscale histograms were used to detect features with distinct patterns [17]. Figure 6 shows graphs of the average values and the values of each object according to the seed brightness of the cc2-003 line using grayscale.…”

Section: Detection Of Specific Traits Using Color Analysismentioning

confidence: 99%

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Baek

Lee

Kim

et al. 2020

Sensors

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Data phenotyping traits on soybean seeds such as shape and color has been obscure because it is difficult to define them clearly. Further, it takes too much time and effort to have sufficient number of samplings especially length and width. These difficulties prevented seed morphology to be incorporated into efficient breeding program. Here, we propose methods for an image acquisition, a data processing, and analysis for the morphology and color of soybean seeds by high-throughput method using images analysis. As results, quantitative values for colors and various types of morphological traits could be screened to create a standard for subsequent evaluation of the genotype. Phenotyping method in the current study could define the morphology and color of soybean seeds in highly accurate and reliable manner. Further, this method enables the measurement and analysis of large amounts of plant seed phenotype data in a short time, which was not possible before. Fast and precise phenotype data obtained here may facilitate Genome Wide Association Study for the gene function analysis as well as for development of the elite varieties having desirable seed traits.

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Section: Detection Of Specific Traits Using Color Analysismentioning

confidence: 99%

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Baek

Lee

Kim

et al. 2020

Sensors

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“…Computer vision, compared with traditional color measurement instruments, is a nondestructive, noncontact, low‐priced, more adaptable, and time‐saving color measurement technology. It has been used for analyzing an image of a sample by computers to obtain information about its color, texture, morphological elements, and defects …”

Section: Introductionmentioning

confidence: 99%

“…It has been used for analyzing an image of a sample by computers to obtain information about its color, texture, morphological elements, and defects. [10][11][12][13][14] Hyssop (Hyssopus officinalis L.) is one of the most important medicinal plants, which is widely cultivated in central and south European countries, including Russia, Spain, France, and Italy. 15 Hyssop could be contaminated by different micro-organisms.…”

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confidence: 99%

Effects of cold plasma on the color parameters of Hyssop (Hyssopus officinalis L.) using color imaging instrumentation and spectrophotometer

Rezaei

Ghobadian

Ebadi

et al. 2019

Color Research & Application

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This research was conducted to evaluate the effects of cold atmospheric plasma treatment on the color of Hyssop (Hyssopus officinalis L.) and also to compare the usage of the spectrophotometer vs the color imaging instrumentation for the evaluation of the treatment on the color parameters. The experiments were investigated at different treatment times of 1, 5, and 10 minutes and the voltage values of 17, 20, and 23 kV. Possible changes of color were evaluated by using CIE L*a*b* values obtained with HunterLab colorimeter and CIE L*a*b* values obtained with a digital still camera (DSC) using digital image processing (MATLAB software). The values of L*, a*, and b* of the samples were obtained using both the methods. The results revealed that the L*, a*, and b* values of the treated Hyssop samples changed with increasing the treatment time and the voltage applied. Evaluating the interaction effects revealed that there was a significant difference in the (−a*/b*) ratio. In addition, the results showed that the effects of all variables on the color parameters were significantly different in the case of the DSC using digital image processing. However, these effects were not significantly different using HunterLab colorimeter except for time variable and interaction effects of a* and (−a*/b*) ratio. The lightest green color and the maximum chlorophyll content loss were observed for 23 kV applied over 10 minutes. Based on the results, the digital image processing can be used as a practical tool to study the variations at the color of dried Hyssop leaves after cold plasma treatment.

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“…Cottonseed oil has a great potential as an alternative commercial source of biofuels production [33,34] and edible oil [35] rich in polyunsaturated fatty acids (PUFAs). The investigation of molecular regulatory mechanism of fatty acid synthesis in developing cotton ovules is pivotal for cottonseed biodiesel development.…”

Section: Discussionmentioning

confidence: 99%

Identification and analysis of oil candidate genes revealed the molecular basis of oil accumulation in Gossypium hirsutum L. for cottonseed biofuels development

Zhang¹,

Gōng²,

Zhang³

et al. 2020

Preprint

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Background Cottonseed oil is increasingly becoming a promising target for biodiesel production with its high content of unsaturated fatty acids as greenhouse gases emission and global warming become more severe. However, the molecular regulatory basis of cottonseed oil accumulation is still unclear so far, and it is necessary to identify vital genes and regulators involved in oil accumulation during developing cottonseed ovules. Results In this study, a recombinant inbred line (RIL) population, developed from a cross between upland cotton cultivars 0-153 and sGK9708, was used to detect quantitative trait loci (QTLs) associated with cottonseed oil content and further identify candidate factors regulating cottonseed lipid synthesis. A total of 39 QTLs located on eighteen different chromosomes were identified across eight different environments. Of these, five QTLs were stable in at least three environments. By integrating candidate gene approach and physical mapping data, we preliminary obtained 43 candidate genes potentially involved in carbon metabolism, fatty acid (FA) synthesis and transcription, and triacylglycerol (TAG) synthesis around the stable QTLs. KEGG pathway enrichment analysis and local BLAST with Arabidopsis oil-related genes, as well as transcriptome analysis further showed that 19 candidate genes, expressed during developing cottonseed ovules, could influence cottonseed oil accumulation. Transcription factors (TFs) and microRNAs (miRNAs) regulatory network analyses suggested six genes, two core miRNAs (ghr-miR2949b and ghr-miR2949c), and one TFs GhHSL1 were considered to be closely associated with cottonseed lipid content. Conclusions The study provides an unprecedented level of insight from QTL mapping and regulatory network analysis to reveal the oil accumulation mechanism in developing cottonseed ovules through the construction of a detailed oil accumulation model. Moreover, the present study of cottonseed oil also lays a foundation for further oil production improvement in oil crops, and contributes to renewable energy production for solving the energy shortage and stabilizing greenhouse gases at a certain extent.

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Digital image-based classification of biodiesel

Cited by 48 publications

References 26 publications

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Effects of cold plasma on the color parameters of Hyssop (Hyssopus officinalis L.) using color imaging instrumentation and spectrophotometer

Identification and analysis of oil candidate genes revealed the molecular basis of oil accumulation in Gossypium hirsutum L. for cottonseed biofuels development

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Digital image-based classification of biodiesel

Cited by 48 publications

References 26 publications

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis

Effects of cold plasma on the color parameters of Hyssop (Hyssopus officinalis L.) using color imaging instrumentation and spectrophotometer

Identification and analysis of oil candidate genes revealed the molecular basis of oil accumulation in Gossypium hirsutum&nbsp;L. for cottonseed biofuels development

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Identification and analysis of oil candidate genes revealed the molecular basis of oil accumulation in Gossypium hirsutum L. for cottonseed biofuels development