Association of spectroscopically determined leaf nutrition related traits and breeding selection in Sassafras tzumu

Liu, Jun; Sun, Yang; Liu, Wenjian; Tan, Zifeng; Jiang, Jingmin; Li, Yanjie

doi:10.1186/s13007-021-00734-5

Cited by 3 publications

(3 citation statements)

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“…Recent research has shown that variable selection of the original spectrum can reduce computational complexity and improve the predictiveness of the model (Alizadeh et al, 2019). In this study, Backward Variable Elimination (bve) (Eason, 1990;Austin, 2008), regularization elimination (rep) (Molajou et al, 2021), and significant multivariate correlation (sMC) algorithm (Liu et al, 2021) were used for variable selection.…”

Section: Spectral Pre-processing and Selection Of Characteristic Wave...mentioning

confidence: 99%

Hyperspectral imaging-based prediction of soluble sugar content in Chinese chestnuts

Yang

Gong

Jiang

2023

Front. For. Glob. Change

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Soluble sugars are critical determinants of fruit quality and play a significant role in human nutrition. Chestnuts, rich in soluble sugars, derive their sweetness from them. However, their content varies with cultivar, location, and environmental conditions. Traditional methods for determining soluble sugar content in chestnuts are time-consuming, laborious, and destructive. Therefore, there is a pressing need for rapid, non-destructive, and straightforward methods for determining soluble sugars in chestnuts to expedite genetic selection. This study aimed to develop a hyperspectral imaging-based prediction model for soluble sugar content in Chinese chestnuts. Firstly, abnormal samples were eliminated using ensemble partial least squares for outlier detection. We then compared the average original and block scale (BS) spectra, with the latter demonstrating significant differences. The BS pretreatment exhibited two small absorption peaks in the 403.7 ∼ 429.1 nm band and 454.7 ∼ 500 nm band, less fluctuation in the spectral curves from 503.2 to 687.2 nm, and a substantial increase in spectral absorption between 690.6 and 927.8 nm. Subsequently, we developed a partial least squares (PLS) model using BS pretreatment and regularized elimination (rep) variable selection, which showed better accuracy in predicting chestnut soluble sugar content than other variable selection methods. The model fitting accuracy after the spectra treatment was marginally better than that of the original spectra, with a calibration set correlation coefficient (R2) of 0.59 and root mean square error (RMSE) of 1.02, and a validation set R2 of 0.66 and RMSE of 0.94. The wavelengths at 464.3, 503.2, 539.3, 579, and 711.3 nm were identified as critical for developing the soluble sugar content prediction model. The study demonstrated the potential of Near-Infrared Spectroscopy (NIS) as a rapid and non-destructive method for predicting chestnut soluble sugar content, which could be beneficial for quality control and sorting in the food industry.

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Section: Spectral Pre-processing and Selection Of Characteristic Wave...mentioning

confidence: 99%

Hyperspectral imaging-based prediction of soluble sugar content in Chinese chestnuts

Yang

Gong

Jiang

2023

Front. For. Glob. Change

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“…The outcomes demonstrated that precipitation of driest month, precipitation of wettest month, temperature seasonality, and mean temperature of wettest quarter chiefly influenced the distribution. Furthermore, a comparison between the simulated outcomes of the distribution range during distinct periods revealed that the suitable habitat for S. tzumu contracted and shifted from the southern to the northern regions [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Environment influences the genetic structure and genetic differentiation of Sassafras tzumu (Lauraceae)

Guan,

Liu,

Liu

et al. 2024

BMC Ecol Evo

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Background Sassafras tzumu, an elegant deciduous arboreal species, belongs to the esteemed genus Sassafras within the distinguished family Lauraceae. With its immense commercial value, escalating market demands and unforeseen human activities within its natural habitat have emerged as new threats to S. tzumu in recent decades, so it is necessary to study its genetic diversity and influencing factors, to propose correlative conservation strategies. Results By utilizing genotyping-by-sequence (GBS) technology, we acquired a comprehensive database of single nucleotide polymorphisms (SNPs) from a cohort of 106 individuals sourced from 13 diverse Sassafras tzumu natural populations, scattered across various Chinese mountainous regions. Through our meticulous analysis, we aimed to unravel the intricate genetic diversity and structure within these S. tzumu populations, while simultaneously investigating the various factors that potentially shape genetic distance. Our preliminary findings unveiled a moderate level of genetic differentiation (FST = 0.103, p < 0.01), accompanied by a reasonably high genetic diversity among the S. tzumu populations. Encouragingly, our principal component analysis painted a vivid picture of two distinct genetic and geographical regions across China, where gene flow appeared to be somewhat restricted. Furthermore, employing the sophisticated multiple matrix regression with randomization (MMRR) analysis method, we successfully ascertained that environmental distance exerted a more pronounced impact on genetic distance when compared to geographical distance (βE = 0.46, p < 0.01; βD = 0.16, p < 0.01). This intriguing discovery underscores the potential significance of environmental factors in shaping the genetic landscape of S. tzumu populations. Conclusions The genetic variance among populations of S. tzumu in our investigation exhibited a moderate degree of differentiation, alongside a heightened level of genetic diversity. The environmental distance of S. tzumu had a greater impact on its genetic diversity than geographical distance. It is of utmost significance to formulate and implement meticulous management and conservation strategies to safeguard the invaluable genetic resources of S. tzumu.

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“…The outcomes demonstrated that precipitation during the driest quarter, precipitation during the wettest month, temperature seasonality, and mean temperature during the wettest quarter chie y in uenced the distribution. Furthermore, a comparison between the simulated outcomes of the distribution range during distinct periods revealed that the suitable habitat for S. tzumu contracted and shifted from the southern to the northern regions [17]. Genotyping-by-sequence (GBS) technology represented one of the streamlined genome sequencing methodologies, aiming to reduce genome complexity through the application of restriction enzymes and the incorporation of single nucleotide polymorphisms (SNPs) [18].…”

Section: Introductionmentioning

confidence: 99%

Environment influences the genetic structure and genetic differentiation of Sassafras tzumu (Lauraceae)

Liu,

Gong

et al. 2023

Preprint

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Background Sassafras tzumu , an elegant deciduous arboreal species, belongs to the esteemed genus Sassafras within the distinguished family Lauraceae. With its immense commercial value, escalating market demands and unforeseen human activities within its natural habitat have emerged as new threats to S. tzumu in recent decades, so it is necessary to study its genetic diversity and influencing factors, to propose correlative conservation strategies. Results In this investigation, we employed genotyping-by-sequencing technology to scrutinize the genetic diversity and structure of 106 individuals of S. tzumu, carefully gathered from 13 naturally occurring habitats in China. The primary results could be summarized as follows: the genetic diversity of S. tzumu was inferior to those of most other woody plants. Moreover, S. tzumu exhibited a moderate level of genetic differentiation (FST=0.103), with the preponderance of genetic variation residing within populations (71%). Our findings unveiled that the 13 populations could be categorically classified into four distinct genetic clusters (K = 4). Notably, the populations from Mount Hengshan (HS) and Mount Shaoshan (SS) coalesced into a single genetic cluster, while the populations from Mount Lushan (LS) and Mount Meiling (ML) formed another genetic cluster, with the remaining two populations occupying unique genetic clusters. Utilizing the multiple matrix regression with randomization (MMRR) analysis method, we unveiled that genetic distance was concurrently influenced by both geographical distance and environmental distance (r = 0.57, p < .01). However, it was noteworthy that the regression coefficient of environmental distance was nearly threefold greater than that of geographical distance, thus underscoring the prominence of environmental distance in shaping genetic distance (βE = 0.46, p < .01; βD = 0.16, p < .01). Conclusions S. tzumu had a moderate level of genetic differentiation and low genetic diversity in our study. The environmental distance of S. tzumu had a greater impact on its genetic diversity than geographical distance. It is of utmost significance to formulate and implement meticulous management and conservation strategies to safeguard the invaluable genetic resources of S. tzumu.

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Association of spectroscopically determined leaf nutrition related traits and breeding selection in Sassafras tzumu

Cited by 3 publications

References 80 publications

Hyperspectral imaging-based prediction of soluble sugar content in Chinese chestnuts

Hyperspectral imaging-based prediction of soluble sugar content in Chinese chestnuts

Environment influences the genetic structure and genetic differentiation of Sassafras tzumu (Lauraceae)

Environment influences the genetic structure and genetic differentiation of Sassafras tzumu (Lauraceae)

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