Xiaonan Wang

Prof. Dr. Xiaonan Wang

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 August 2019 in Gene
Verified
Journal Article
Closed access
XLXin Liu
Xin Liu
LFLianshuang Fu
Lianshuang Fu
PQPeng Qin
Peng Qin
YSYinglu Sun
Yinglu Sun
Jun LiuJun Liu
Jun Liu
XWXiaonan Wang
Xiaonan Wang

10 May 2024 in Plant Physiology and Biochemistry
Verified
Journal Article
Closed access
XLXiaoguang Lu
Xiaoguang Lu
FZFuzhi Zhang
Fuzhi Zhang
CZChenglong Zhang
Chenglong Zhang
GLGuorui Li
Guorui Li
YDYuchen Du
Yuchen Du
XWXiaonan Wang
Xiaonan Wang

21 April 2020 in International Journal of Food Engineering
Verified
Journal Article
Open access
PDF file
Jingjing LiuJingjing Liu
Jingjing Liu
SLSimeng Liu
Simeng Liu
TSTie Shi
Tie Shi
XWXiaonan Wang
Xiaonan Wang
YCYizhou Chen
Yizhou Chen
HMHong Men
Hong Men
Precise classification of seeds is important for agriculture. Due to the slight physical and chemical difference between different types of wheat and high correlation between bands of images, it is easy to fall into the local optimum when selecting the characteristic band of using the spectral average only. In this paper, in order to solve this problem, a new variable fusion strategy was proposed based on successive projection algorithm and the variable importance in projection algorithm to obtain a comprehensive and representative variable feature for higher classification accuracy, within spectral mean and spectral standard deviation, so the 25 feature bands obtained are classified by support vector machine, and the classification accuracy rate reached 83.3%. It indicates that the new fusion strategy can mine the effective features of hyperspectral data better to improve the accuracy of the model and it can provide a theoretical basis for the hyperspectral classification of tiny kernels.

20 February 2023 in Agronomy
Verified
Journal Article
Open access
PDF file
XLXiaoguang Lu
Xiaoguang Lu
YWYuhan Wu
Yuhan Wu
CTChaoyue Tang
Chaoyue Tang
CLChang Liu
Chang Liu
NLNinghui Li
Ninghui Li
XWXiaonan Wang
Xiaonan Wang
Recent findings suggest that cold acclimation can enhance cold resistance in wheat. Dongnongdongmai 1 (DM1) is a winter wheat variety that can overwinter at −30 °C; however, its cold acclimation mechanism is yet to be fully elucidated. Here, we elucidated the potential mechanisms of cold acclimation in DM1 and the China Spring (CS) variety, especially the role of the antioxidant system, using transcriptome and physiological analyses. Cold stress increased H2O2 and O2− production in both varieties; however, CS had higher contents of H2O2 and O2− than DM1. Moreover, cold significantly increased ROS-scavenging activities in DM1, especially at 30 days after exposure. Gene ontology (GO) analysis showed that differentially expressed peroxidase (POD) genes were enriched in antioxidant activity, with most POD genes being significantly upregulated in DM1 under cold acclimation. Additionally, cold acclimation increased the expression of cold acclimation protein (CAP), late embryogenesis abundant protein (LEA), and cold-responsive genes in both varieties, with higher expression levels in DM1. Overall, the results showed that DM1 exhibited a higher cold tolerance than CS during cold acclimation by increasing the expression of POD genes, LEA, CAP, and cold-responsive proteins, improving the understanding of the mechanism of cold resistance in DM1.

1 January 2022 in Gene
Verified
Journal Article
Closed access
YDYuchen Du
Yuchen Du
CLChang Liu
Chang Liu
NLNinghui Li
Ninghui Li
XLXiaoguang Lu
Xiaoguang Lu
RGRui Ge
Rui Ge
XWXiaonan Wang
Xiaonan Wang

16 February 2026 in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
Verified
Journal Article
Closed access
WZWei Zhang
Wei Zhang
XWXiaonan Wang
Xiaonan Wang
LDLei Du
Lei Du
PLPu Liu
Pu Liu
LQLixin Qiao
Lixin Qiao
Jingjing LiuJingjing Liu
Jingjing Liu