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Article ; Online: DOTFL1 affects the floral transition in orchid Dendrobium Chao Praya Smile.

Li, Yan / Zhang, Bin / Wang, Yanwen / Gong, Ximing / Yu, Hao

2021 Volume 186, Issue 4, Page(s) 2021–2036

Abstract: ... in Arabidopsis (Arabidopsis thaliana), from the orchid Dendrobium Chao Praya Smile. DOTFL1 is highly expressed ...

Abstract	A major obstacle for orchid (Orchidaceae) breeding and production is a long juvenile phase before orchid reproductive development. The molecular basis for prolonged vegetative growth in orchids remains largely unclear despite many efforts to clarify the relevant mechanisms. In this study, we report functional characterization of Dendrobium Orchid TERMINAL FLOWER1 (DOTFL1), an ortholog of TFL1 in Arabidopsis (Arabidopsis thaliana), from the orchid Dendrobium Chao Praya Smile. DOTFL1 is highly expressed in pseudobulbs and the shoot apical meristem (SAM) before and during the floral transition, but is downregulated in inflorescence apices and open flowers. Ectopic expression of DOTFL1 rescues the early-flowering and terminal-flower phenotypes of tfl1-20 in Arabidopsis. Overexpression of DOTFL1 in Dendrobium orchids delays flowering and produces defective inflorescence meristems and flowers with vegetative traits, whereas knockdown of DOTFL1 accelerates flowering and perturbs the maintenance of the inflorescence meristem. Notably, DOTFL1 suppresses orchid flowering and associated pseudobulb formation during the floral transition. We further reveal that two orchid MADS-box transcription factors, Dendrobium Orchid SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (DOSOC1) and AGAMOUS-LIKE 24 (DOAGL24), could interact with each other and bind to the CArG-box motif at DOTFL1, implying a regulatory hierarchy similar to their counterparts in Arabidopsis. Taken together, our findings suggest that DOTFL1 promotes vegetative growth, modulates successive developmental events required for reproductive success in Dendrobium orchids, and may have evolved with a previously unknown role in controlling pseudobulb formation in the Orchidaceae family.
MeSH term(s)	Dendrobium/genetics ; Dendrobium/growth & development ; Dendrobium/metabolism ; Flowers/genetics ; Flowers/growth & development ; Plant Proteins/genetics ; Plant Proteins/metabolism
Chemical Substances	Plant Proteins
Language	English
Publishing date	2021-04-30
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	208914-2
ISSN	1532-2548 ; 0032-0889
ISSN (online)	1532-2548
ISSN	0032-0889
DOI	10.1093/plphys/kiab200
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Article ; Online: Mapping aboveground biomass of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress using Sentinel-2 imagery

Lingyan Chen / Anqi He / Zhanghua Xu / Bin Li / Huafeng Zhang / Guantong Li / Xiaoyu Guo / Zenglu Li

Ecological Indicators, Vol 158, Iss , Pp 111564- (2024)

2024

Abstract: ... of monitoring techniques for Pantana phyllostachysae Chao, a significant pest of Moso bamboo, its interplay with AGB ...

Abstract	Moso bamboo (Phyllostachys pubescens) stands as a pivotal economic bamboo species globally, holding substantial potential for carbon sequestration. Accurate estimation of aboveground biomass (AGB) in Moso bamboo forests is crucial due to its close ties with the ecosystem's carbon cycle. Despite the maturation of monitoring techniques for Pantana phyllostachysae Chao, a significant pest of Moso bamboo, its interplay with AGB in these forests remains enigmatic. This study addressed this gap by categorizing P. phyllostachysae's impact on Moso bamboo forests into four levels: healthy, mild damage, moderate damage, and severe damage. By scrutinizing field data, we delved into the shifts in Moso bamboo leaf biomass under P. phyllostachysae stress. Leveraging Sentinel-2A/B imagery, we extracted diverse correlation factors, including original wave bands, vegetation indices, texture attributes, and vegetation's physical and chemical parameters. Subsequently, machine learning algorithms-namely, random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) were employed to achieve remote sensing inversion of AGB in Moso bamboo forests, accounting for the presence of insect pests. We analyzed the response of Moso bamboo biomass sensitive factors and to further clarify the changes of AGB of Moso bamboo forests under insect pest stress at the remote sensing level ultimately. The results showed that (1) the degree of Moso bamboo leaf biomass damage was positively related to the damage level, which gradually increased from 15.15 % to 59.42 %; (2) the RF algorithm excelled in estimating Moso bamboo forest AGB, particularly in May, and inclusion of insect pest considerations enhanced AGB estimation accuracy; (3) among the four factor types, Band information and vegetation indices emerged as most impactful, and Band5, Band11, Band12, NDVI68a and MSAVI were selected the most often; (4) at the remote sensing level, AGB in Moso bamboo forests significantly varies under P. phyllostachysae stress. Healthy areas ...
Keywords	Moso bamboo ; Pantana phyllostachysae Chao ; Biomass ; Machine learning ; Sentinel-2A/B imagery ; Ecology ; QH540-549.5
Subject code	700
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Joseph Chao: good research is the search for the truth!

Li, Brad

Journal of gastrointestinal oncology

2018 Volume 9, Issue 5, Page(s) 875–877

Language	English
Publishing date	2018-09-01
Publishing country	China
Document type	News
ZDB-ID	2594644-4
ISSN	2219-679X ; 2078-6891
ISSN (online)	2219-679X
ISSN	2078-6891
DOI	10.21037/jgo.2018.08.14
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Article ; Online: Changing Relationships between Water Content and Spectral Features in Moso Bamboo Leaves under Pantana phyllostachysae Chao Stress

Xu, Zhanghua / Li, Bin / Yu, Hui / Zhang, Huafeng / Guo, Xiaoyu / Li, Zenglu / Wang, Lin / Liu, Zhicai / Li, Yifan / He, Anqi / Huang, Xuying

Forests. 2023 Mar. 29, v. 14, no. 4

2023

Abstract: ... phyllostachysae Chao (PPC) stress and their changes. The results showed that: (1) the LWC showed a decreasing ...

Abstract	Leaf water content (LWC) is very important in the growth of vegetation. LWC and leaf spectra change when the leaves are under pest stress; exploring the change mechanism between LWC, leaf spectra, and pest stress can lay the foundation for pest detection. In this study, we measured the LWC and leaf spectra of moso bamboo leaves under different damage levels, used the Pearson–Lasso method to screen the features, and established a multiple linear regression (MLR) and random forest regression (RFR) model to estimate the LWC. We analyzed the relationship between LWC and spectral features of moso bamboo leaves under Pantana phyllostachysae Chao (PPC) stress and their changes. The results showed that: (1) the LWC showed a decreasing trend as the pest level increased. (2) The spectra changed substantially when the leaves were under pest stress. (3) The number and significance of response features associated with the LWC were diverse under different damage levels. (4) The estimation of LWC under different damage levels differed significantly. LWC, leaf spectra, response features, and the model estimation effect were diverse under different damage levels. The correlation between LWC and features was higher for healthy leaves than for damaged and off-year leaves. The two models were more effective in estimating the LWC of healthy leaves but less effective for damaged and off-year leaves. This study provides theoretical support for the prediction of PPC stress and lays the foundation for remote sensing monitoring.
Keywords	Phyllostachys edulis ; algorithms ; leaves ; pests ; regression analysis ; vegetation ; water content
Language	English
Dates of publication	2023-0329
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2527081-3
ISSN	1999-4907
ISSN	1999-4907
DOI	10.3390/f14040702
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Reply to Chao et al. Comment on "Nahok et al. Monosodium Glutamate Induces Changes in Hepatic and Renal Metabolic Profiles and Gut Microbiome of Wistar Rats.

Nahok, Kanokwan / Selmi, Carlo / Sukmak, Manatsaphon / Phetcharaburanin, Jutarop / Li, Jia V / Silsirivanit, Atit / Thanan, Raynoo / Sharma, Amod / Anutrakulchai, Sirirat / Hammock, Bruce D / Cha'on, Ubon

Nutrients

2022 Volume 14, Issue 20

Abstract: We sincerely appreciate the thorough review and insights of Dr. Huichia Chao and colleagues [...]. ...

Abstract	We sincerely appreciate the thorough review and insights of Dr. Huichia Chao and colleagues [...].
MeSH term(s)	Rats ; Animals ; Sodium Glutamate/pharmacology ; Rats, Wistar ; Gastrointestinal Microbiome ; Nutrients ; Metabolome
Chemical Substances	Sodium Glutamate (W81N5U6R6U)
Language	English
Publishing date	2022-10-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2518386-2
ISSN	2072-6643 ; 2072-6643
ISSN (online)	2072-6643
ISSN	2072-6643
DOI	10.3390/nu14204387
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Article ; Online: Sedimentary DNA reveals over 150 years of ecosystem change by human activities in Lake Chao, China.

Li, Feilong / Zhang, Xiaowei / Xie, Yuwei / Wang, Jizhong

Environment international

2019 Volume 133, Issue Pt B, Page(s) 105214

Abstract: ... micro-eukaryotes) in Lake Chao over the past 150 years, and further explored the effects of long-term ... in Lake Chao have increased by ca. 2 to 4-fold since the 1960s. In response, the community structure ... affecting the bacterial and micro-eukaryotes community in Lake Chao in addition to nutrient. Our study ...

Abstract	Understanding the extent and directionality of the impact of human activities on ecosystems is directly related to their management and protection. However, the lack of historical data limits our understanding of ecosystem changes with long-term exposure to human activities. Recently, lake sedimentary DNA (sedDNA) has become a powerful tool for revealing changes in ecosystems at the century and millennium scales. Here, we used sedDNA to reveal the dynamic of the microbial community (including bacteria and micro-eukaryotes) in Lake Chao over the past 150 years, and further explored the effects of long-term nutrient and heavy metal loads on these communities. Our data show that nutrient and heavy metal loads in Lake Chao have increased by ca. 2 to 4-fold since the 1960s. In response, the community structure, diversity, and ecological network of bacteria and micro-eukaryotes changed significantly during the 1960s, the 1980s and the 2010s. Importantly, community structure was more sensitive to human activities than diversity. We also found that the relative abundance of some taxa associated with nitrification and algal blooms (e.g., taxa in Nitrospira sp., Peridinales) has increased ca. 100-fold since the 1960s. Nutrient could better explain the variation in the bacterial community (ca. twice as much as heavy metal), while heavy metal explained micro-eukaryotes better (ca. 3 or 5-fold as much as nutrient). In particular, based on parsimonious models from distance-based linear model (distLM), we further identified that Pb is the key factor affecting the bacterial and micro-eukaryotes community in Lake Chao in addition to nutrient. Our study reveals the impacts of long-term human activities on lake ecosystems from multiple perspectives of nutrient and heavy metal loads, community structure, diversity and ecological network, these findings will contribute to the management and conservation of lakes in the future.
MeSH term(s)	Bacteria ; China ; DNA ; Ecosystem ; Eutrophication ; Geologic Sediments/microbiology ; Human Activities ; Humans ; Lakes ; Metals, Heavy/analysis
Chemical Substances	Metals, Heavy ; DNA (9007-49-2)
Language	English
Publishing date	2019-10-27
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	554791-x
ISSN	1873-6750 ; 0160-4120
ISSN (online)	1873-6750
ISSN	0160-4120
DOI	10.1016/j.envint.2019.105214
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Article ; Online: Changing Relationships between Nitrogen Content and Leaf Spectral Characteristics of Moso Bamboo Leaves under Pantana phyllostachysae Chao Stress

Zhanghua Xu / Hui Yu / Bin Li / Zhenbang Hao / Yifan Li / Songyang Xiang / Xuying Huang / Zenglu Li / Xiaoyu Guo

Forests, Vol 13, Iss 1752, p

2022 Volume 1752

Abstract: ... in the leaf nitrogen content of Moso bamboo leaves under Pantana phyllostachysae Chao (PPC) stress and leaf ...

Abstract	Nitrogen is an important indicator of vegetation health, but the relationship between changes in the leaf nitrogen content of Moso bamboo leaves under Pantana phyllostachysae Chao (PPC) stress and leaf spectra remains unclear. We analyzed the relationship between the leaf nitrogen content and leaf spectra of Moso bamboo leaves under PPC stress to investigate whether the relationship could be used to detect pests and prevent their spread. We measured the nitrogen content and leaf spectra of Moso bamboo leaves under different damage levels, identified spectral indicators that were correlated with leaf nitrogen content (by removing the envelope and first-order differentiation of the raw spectra), and estimated leaf nitrogen content from the spectral data using regression models. Leaf nitrogen content decreased with increasing pest damage, and the leaf spectral curves changed, with the “green peak” and “red valley” in the visible range disappearing and the slope of the spectral curve decreasing. The wavelength region with the strongest correlation between the nitrogen content and spectral characteristics changed significantly with increasing pest damage, and the correlation in the red-edge region gradually decreased. The fits of nitrogen-content estimation models tended to decrease and then increase with increasing pest damage and were worst among leaves in the moderate damage state (Mo). A disordered relationship between nitrogen content and spectral characteristics indicated possible PPC damage. The degree of disorder was greatest in the Mo state. This study provides theoretical support for remote sensing monitoring of PPC hazards.
Keywords	Pantana phyllostachysae Chao ; Moso bamboo ; nitrogen content ; spectral characteristics ; pest damage ; regression model ; Plant ecology ; QK900-989
Subject code	580
Language	English
Publishing date	2022-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Retrieving chlorophyll content and equivalent water thickness of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework

Zhanghua Xu / Anqi He / Yiwei Zhang / Zhenbang Hao / Yifan Li / Songyang Xiang / Bin Li / Lingyan Chen / Hui Yu / Wanling Shen / Xuying Huang / Xiaoyu Guo / Zenglu Li

Forest Ecosystems, Vol 10, Iss , Pp 100108- (2023)

2023

Abstract: ... Chao (PPC), weakens the performance of the model for estimating biochemical components of Moso bamboo ...

Abstract	Biochemical components of Moso bamboo (Phyllostachys pubescens) are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem. The coupled PROSPECT with SAIL (PROSAIL) radiative transfer model is widely used for vegetation biochemical component content inversion. However, the presence of leaf-eating pests, such as Pantana phyllostachysae Chao (PPC), weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered. Therefore, this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables (LUTs) based on the PROSAIL framework by setting different parameter ranges according to infestation levels. Quantitative inversions of leaf area index (LAI), leaf chlorophyll content (LCC), and leaf equivalent water thickness (LEWT) were derived. The scale conversions from LCC to canopy chlorophyll content (CCC) and LEWT to canopy equivalent water thickness (CEWT) were calculated. The results showed that LAI, CCC, and CEWT were inversely related with PPC-induced stress. When applying multiple LUTs, the p-values were <0.01; the R2 values for LAI, CCC, and CEWT were 0.71, 0.68, and 0.65 with root mean square error (RMSE) (normalized RMSE, NRMSE) values of 0.38 (0.16), 17.56 μg·cm‒2 (0.20), and 0.02 cm (0.51), respectively. Compared to the values obtained for the traditional PROSAIL model, for October, R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT, respectively and RMSE decreased by 0.35 μg·cm‒2 for CCC. The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model, while establishing multiple LUTs under different pest-induced damage levels, was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.
Keywords	Moso bamboo ; Chlorophyll content ; Equivalent water thickness ; PROSAIL model ; Multiple LUTs ; Pantana phyllostachysae Chao ; Ecology ; QH540-549.5
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	KeAi Communications Co., Ltd.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Retrieving chlorophyll content and equivalent water thickness of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework

Xu, Zhanghua / He, Anqi / Zhang, Yiwei / Hao, Zhenbang / Li, Yifan / Xiang, Songyang / Li, Bin / Chen, Lingyan / Yu, Hui / Shen, Wanling / Huang, Xuying / Guo, Xiaoyu / Li, Zenglu

Forest Ecosystems. 2023, v. 10 p.100108-

2023

Abstract: ... Chao (PPC), weakens the performance of the model for estimating biochemical components of Moso bamboo ...

Abstract	Biochemical components of Moso bamboo (Phyllostachys pubescens) are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem. The coupled PROSPECT with SAIL (PROSAIL) radiative transfer model is widely used for vegetation biochemical component content inversion. However, the presence of leaf-eating pests, such as Pantana phyllostachysae Chao (PPC), weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered. Therefore, this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables (LUTs) based on the PROSAIL framework by setting different parameter ranges according to infestation levels. Quantitative inversions of leaf area index (LAI), leaf chlorophyll content (LCC), and leaf equivalent water thickness (LEWT) were derived. The scale conversions from LCC to canopy chlorophyll content (CCC) and LEWT to canopy equivalent water thickness (CEWT) were calculated. The results showed that LAI, CCC, and CEWT were inversely related with PPC-induced stress. When applying multiple LUTs, the p-values were <0.01; the R² values for LAI, CCC, and CEWT were 0.71, 0.68, and 0.65 with root mean square error (RMSE) (normalized RMSE, NRMSE) values of 0.38 (0.16), 17.56 μg·cm‒² (0.20), and 0.02 cm (0.51), respectively. Compared to the values obtained for the traditional PROSAIL model, for October, R² values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT, respectively and RMSE decreased by 0.35 μg·cm‒² for CCC. The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model, while establishing multiple LUTs under different pest-induced damage levels, was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.
Keywords	Phyllostachys edulis ; bamboos ; chlorophyll ; ecosystems ; forest health ; forests ; leaf area index ; leaf chlorophyll content ; leaf reflectance ; model validation ; models ; radiative transfer ; Moso bamboo ; Chlorophyll content ; Equivalent water thickness ; PROSAIL model ; Multiple LUTs ; Pantana phyllostachysae Chao ; Sentinel-2A/B images
Language	English
Publishing place	Elsevier B.V.
Document type	Article ; Online
Note	Use and reproduction
ZDB-ID	2760380-5
ISSN	2197-5620
ISSN	2197-5620
DOI	10.1016/j.fecs.2023.100108
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Monitoring the Severity of Pantana phyllostachysae Chao Infestation in Moso Bamboo Forests Based on UAV Multi-Spectral Remote Sensing Feature Selection

Zhanghua Xu / Qi Zhang / Songyang Xiang / Yifan Li / Xuying Huang / Yiwei Zhang / Xin Zhou / Zenglu Li / Xiong Yao / Qiaosi Li / Xiaoyu Guo

Forests, Vol 13, Iss 418, p

2022 Volume 418

Abstract: ... bamboo forests by Pantana phyllostachysae Chao (PPC), a major leaf-eating pest, at 5 cm resolution ...

Abstract	In recent years, the rapid development of unmanned aerial vehicle (UAV) remote sensing technology has provided a new means to efficiently monitor forest resources and effectively prevent and control pests and diseases. This study aims to develop a detection model to study the damage caused to Moso bamboo forests by Pantana phyllostachysae Chao (PPC), a major leaf-eating pest, at 5 cm resolution. Damage sensitive features were extracted from multispectral images acquired by UAVs and used to train detection models based on support vector machines (SVM), random forests (RF), and extreme gradient boosting tree (XGBoost) machine learning algorithms. The overall detection accuracy (OA) and Kappa coefficient of SVM, RF, and XGBoost were 81.95%, 0.733, 85.71%, 0.805, and 86.47%, 0.811, respectively. Meanwhile, the detection accuracies of SVM, RF, and XGBoost were 78.26%, 76.19%, and 80.95% for healthy, 75.00%, 83.87%, and 79.17% for mild damage, 83.33%, 86.49%, and 85.00% for moderate damage, and 82.5%, 90.91%, and 93.75% for severe damage Moso bamboo, respectively. Overall, XGBoost exhibited the best detection performance, followed by RF and SVM. Thus, the study findings provide a technical reference for the regional monitoring and control of PPC in Moso bamboo.
Keywords	UAV multispectral remote sensing ; Moso bamboo forest ; Pantana phyllostachysae Chao ; feature selection ; detection model ; Plant ecology ; QK900-989
Subject code	629
Language	English
Publishing date	2022-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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