Color Chart Development by Computer Vision for Flue-cured Tobacco Leaf

Zhi, Ruicong; Gao, Mingxuan; Liu, Zhengling; Yang, Yongping; Zhang, Zheng; Bolin, Shi

doi:10.18494/sam.2018.2045

Cited by 2 publications

(2 citation statements)

References 16 publications

(17 reference statements)

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“…Nitrogen metabolism involves two main processes: extracellular nitrate/nitrite transmembrane transport and intracellular oxidation-reduction [101]. The nitrate transporter (NRT) is pivotal in nitrate/nitrite absorption, transportation, and assimilation [102]. In this study, the expression of NRT genes was higher in AKZ-NRGR667 than in D20170203, suggesting that nitrate/nitrite uptake may be more efficient in D20170203.…”

Section: The Nitrogen and Ga Metabolism Synergistically Regulate Till...mentioning

confidence: 66%

Transcriptome Profiling Provides Insights into the Early Development of Tiller Buds in High- and Low-Tillering Orchardgrass Genotypes

Feng,

Xu,

Liu

et al. 2023

IJMS

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Orchardgrass (Dactylis glomerata L.) is among the most economically important perennial cool-season grasses, and is considered an excellent hay, pasture, and silage crop in temperate regions worldwide. Tillering is a vital feature that dominates orchardgrass regeneration and biomass yield. However, transcriptional dynamics underlying early-stage bud development in high- and low-tillering orchardgrass genotypes are unclear. Thus, this study assessed the photosynthetic parameters, the partially essential intermediate biomolecular substances, and the transcriptome to elaborate the early-stage profiles of tiller development. Photosynthetic efficiency and morphological development significantly differed between high- (AKZ-NRGR667) and low-tillering genotypes (D20170203) at the early stage after tiller formation. The 206.41 Gb of high-quality reads revealed stage-specific differentially expressed genes (DEGs), demonstrating that signal transduction and energy-related metabolism pathways, especially photosynthetic-related processes, influence tiller induction and development. Moreover, weighted correlation network analysis (WGCNA) and functional enrichment identified distinctively co-expressed gene clusters and four main regulatory pathways, including chlorophyll, lutein, nitrogen, and gibberellic acid (GA) metabolism pathways. Therefore, photosynthesis, carbohydrate synthesis, nitrogen efficient utilization, and phytohormone signaling pathways are closely and intrinsically linked at the transcriptional level. These findings enhance our understanding of tillering in orchardgrass and perennial grasses, providing a new breeding strategy for improving forage biomass yield.

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Section: The Nitrogen and Ga Metabolism Synergistically Regulate Till...mentioning

confidence: 66%

Transcriptome Profiling Provides Insights into the Early Development of Tiller Buds in High- and Low-Tillering Orchardgrass Genotypes

Feng,

Xu,

Liu

et al. 2023

IJMS

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“…The leaf color is one of the most important factors among them (Wu and Xang, 2021). Color evaluation is crucial for quality management in tobacco farming (Zhi et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Mobile Application for Quality Grade of Tobacco (Nicotiana tabacum L.) Using Correlated Color Temperature

ŞENYER,

OKTAŞ,

ODABAS

et al. 2023

Türkiye Tarımsal Araştırmalar Dergisi

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Concerning tobacco producers, the size and color of the leaf are important factors in understanding the quality grade of tobacco leaves in the market. The color of tobacco leaves serves as an indicator of quality and is referred to as the maturity index when determining the optimal time for harvesting. In this study, a hybrid mobile application was developed to help determine the harvest time. CoLab was preferred as the backend. Python Imaging Library (Pillow) was used for image processing on the server side. Color correction was performed on the images taken with the help of X-rite. The correlated color temperature (CCT) value of the repaired images was calculated. The CCT values were calculated using the Ohno method. Quality grade (QG) was calculated using the mean CCT value. The data of the images obtained depending on the time were used in the application as a graphic. We present quality grade of tobacco automatically identifying the plant leaves in a given image with the help of the mobile application.

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Color Chart Development by Computer Vision for Flue-cured Tobacco Leaf

Cited by 2 publications

References 16 publications

Transcriptome Profiling Provides Insights into the Early Development of Tiller Buds in High- and Low-Tillering Orchardgrass Genotypes

Transcriptome Profiling Provides Insights into the Early Development of Tiller Buds in High- and Low-Tillering Orchardgrass Genotypes

A Hybrid Mobile Application for Quality Grade of Tobacco (Nicotiana tabacum L.) Using Correlated Color Temperature

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