Genetic characterization and molecular mapping of novel chlorophyll deficiency gene in air-cured tobacco (Nicotiana tabacum L.)

Shahadati-Moghaddam, Zeinalabedin; Kahrizi, Danial; Kazemi, Elham

doi:10.2298/gensr1701077s

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…Chlorophyll is a group of chromogenic groups existing in plants in various forms, and its derivatives are photosensitizers (Ghobadi et al, 2011;Shahadati-Moghaddam et al, 2017). Under high-intensity light, the existence of chlorophyll will increase the photooxidation rate, cause a free radical reaction, promote lipid oxidation, lead to rancidity and deterioration of the oil, greatly reduce the stability of oil and shorten the shelf life of products.…”

Section: Introductionmentioning

confidence: 99%

The rapid detection method of chlorophyll content in rapeseed based on hyperspectral technology

Tang¹,

Liao²

2021

Turk J Agric For

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The inconsistency of chlorophyll content in rapeseed directly affects the quality of seed, so it is necessary to establish a rapid and nondestructive detection technology of chlorophyll in mature rapeseed. In this paper, the content of chlorophyll in rapeseed samples was determined by ultraviolet-visible spectrophotometry, and the near-infrared spectrum data were collected. The partial least squares regression model of chlorophyll content in rapeseed was established based on hyperspectral technology through first derivative and standard normal variable transformation pretreatment. The results of the cross-test showed that the determination coefficient of the validation set of the prediction model of chlorophyll content in rapeseed was greater than 0.85, and the root mean square error (RMSE) of the cross-test was less than 0.3 mg/kg. The results showed that the method could accurately predict the chlorophyll content in rapeseed and provide important technical support for rapid monitoring of seed quality.

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Section: Introductionmentioning

confidence: 99%

The rapid detection method of chlorophyll content in rapeseed based on hyperspectral technology

Tang¹,

Liao²

2021

Turk J Agric For

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The Application of Hyperspectral Images in the Classification of Fresh Leaves’ Maturity for Flue-Curing Tobacco

Chen

Qin

et al. 2023

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The maturity of tobacco leaves directly affects their curing quality. However, no effective method has been developed for determining their maturity during production. Assessment of tobacco maturity for flue curing has long depended on production experience, leading to considerable variation. In this study, hyperspectral imaging combined with a novel algorithm was used to develop a classification model that could accurately determine the maturity of tobacco leaves. First, tobacco leaves of different maturity levels (unripe, under-ripe, ripe, and over-ripe) were collected. ENVI software was used to remove the hyperspectral imaging (HSI) background, and 11 groups of filtered images were obtained using Python 3.7. Finally, a full-band-based partial least-squares discriminant analysis (PLS-DA) classification model was established to identify the maturity of the tobacco leaves. In the calibration set, the model accuracy of the original spectrum was 88.57%, and the accuracy of the de-trending, multiple scattering correction (MSC), and standard normalization variable (SNV) treatments was 91.89%, 95.27%, and 92.57%, respectively. In the prediction set, the model accuracy of the de-trending, MSC, and SNV treatments was 93.85%, 96.92%, and 93.85%, respectively. The experimental results indicate that a higher model accuracy was obtained with the filtered images than with the original spectrum. Because of the higher accuracy, de-trending, MSC, and SNV treatments were selected as the candidate characteristic spectral bands, and a successive projection algorithm (SPA), competitive adaptive reweighted sampling (CASR), and particle swarm optimization (PSO) were used as the screening methods. Finally, a genetic algorithm (GA), PLS-DA, line support vector machine (LSVM), and back-propagation neural network (BPNN) classification and discrimination models were established. The combination SNV-SPA-PLS-DA model provided the best accuracy in the calibration and prediction sets (99.32% and 98.46%, respectively). Our findings highlight the efficacy of using visible/near-infrared (ViS/NIR) hyperspectral imaging for detecting the maturity of tobacco leaves, providing a theoretical basis for improving tobacco production.

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Genetic characterization and molecular mapping of novel chlorophyll deficiency gene in air-cured tobacco (Nicotiana tabacum L.)

Cited by 2 publications

References 18 publications

The rapid detection method of chlorophyll content in rapeseed based on hyperspectral technology

The rapid detection method of chlorophyll content in rapeseed based on hyperspectral technology

The Application of Hyperspectral Images in the Classification of Fresh Leaves’ Maturity for Flue-Curing Tobacco

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