About

Wei Xu is a professor associated with the Texas A&M University College of Veterinary Medicine & Biomedical Sciences (VMBS). The college is recognized as a leading institution in veterinary education and research, supporting collaborations that translate discoveries into solutions for animal, human, and environmental health. The college emphasizes innovative research, including basic and clinical studies, with a focus on a 'One Health' approach that recognizes the complex interactions between animal, human, and environmental health. While specific details about Wei Xu's research focus or contributions are not provided in the page text, his association with a top-ranked veterinary college engaged in cutting-edge research and comprehensive veterinary education suggests a significant role in advancing veterinary sciences and biomedical research.

Research topics

• Computer Science
• Biology
• Genetics
• Artificial Intelligence
• Ecology
• Machine Learning
• Biochemistry
• Cancer research
• Immunology
• Chemistry
• Data science
• Endocrinology
• World Wide Web
• Molecular biology
• Medicine
• Agronomy
• Cell biology
• Geography

Selected publications

• Optimizing irrigation regimes for foxtail millet (Setaria italica L.) in Northwest China: Effects of irrigation quota and frequency on yield and crop water productivity

  Agricultural Water Management · 2025-11-29

  articleOpen access

  Optimizing irrigation schedules is essential for improving crop yield and crop water productivity (WP c ) in arid and semi-arid regions. A field experiment was conducted to investigate the growth, yield and WP c responses of foxtail millet ( Setaria italica L.) in response to three irrigation quotas (W1–3) with 150, 187.5, or 250 mm and with three different irrigation frequencies (T1–3) (seven, eight or nine irrigations) per season over each of two consecutive growing seasons in Ningxia, China. The results indicated that plant height, stem diameter, tiller number, panicle length and WP c increased and then decreased with increasing irrigation quota, while biomass increased steadily with increasing irrigation quota. The highest grain yields were recorded under W3T2 (8.40 t ha −1 ) in 2022 and W2T2 (8.37 t ha −1 ) in 2023, with no significant difference between yields of these two treatments. Yield was positively correlated with biomass and straw yield but negatively with panicle length and 1000-grain weight. The highest harvest index value occurred in W2T2 in both growing seasons. After a comprehensive evaluation based on grain yield, straw yield, 1000-grain weight, yield stability and WP c , the optimal combination of irrigation quota and irrigation frequency was the W2T2 treatment for millet using drip irrigation under plastic film in Northwest China. • Optimal millet yield and WUE were achieved under 187.5 mm and eight irrigations (W2T2). • Moderate irrigation improved growth traits and aboveground biomass accumulation. • Grain yield correlated positively with biomass and straw yield, negatively with panicle length and grain weight. • WUE peaked under moderate irrigation quota and frequency across two seasons. • TOPSIS analysis confirmed W2T2 as the optimal regime for millet in arid Northwest China.

  PublisherDOI

• INTEGRATED MANAGEMENT OF FIMBRISTYLIS MILIACEA (L.) VAHL IN RICE SYSTEMS: SEED ECOLOGY, HERBICIDE SENSITIVITY, AND CROP COMPETITION EFFECTS

  Applied Ecology and Environmental Research · 2025-01-01

  articleOpen access1st authorCorresponding

  This study investigated the biological characteristics of Fimbristylis miliacea (L.) Vahl (globe fringerush), a prevalent paddy weed, and evaluated its competitive effects on rice growth to inform targeted control strategies.Seed dormancy patterns were characterized through chemical treatments (Sodium hypochlorite (NaClO), Sodium hydroxide (NaOH), Gibberellic acid (GA3)) and germination assays under varying soil moisture conditions.Herbicide sensitivity was assessed via pot experiments, while field trials quantified the weed's impact on rice physiology (plant height, tillering, yield) across competition gradients.Results demonstrated that 0.25% NaClO, 0.4% NaOH, and 800 mg/L GA3 effectively broke seed dormancy, achieving germination rates of 31.70%,25.07%, and 20.23%, respectively.Optimal germination (89.63%) occurred at 100% soil humidity, but submersion inhibited emergence.The F. miliacea population exhibited susceptibility to MCPA dimethylamine salt (ED90 = 396.9g ai/ha), bentazone (314.9 g ai/ha), and propanil (2779.9g ai/ha), but resistance to triafamone, penoxsulam, florpyrauxifen-benzyl, and benzobicyclon.Increasing weed density progressively reduced rice plant height, effective panicles, and yield, with panicle weight significantly declining at densities > 60 plants/m 2 .These findings identify F. miliacea as a dormant-seeded species controllable by selective herbicides, while highlighting its yield-limiting competitive effect in rice production systems.

  PublisherDOI

• Moss removal facilitates decomposition and net nitrogen loss of mixed wood and litter in subtropical forests

  Forest Ecology and Management · 2025-10-23 · 1 citations

  article
  PublisherDOI

• Dosimetric comparison and evaluation of different convergence modes in nasopharyngeal carcinoma using VMAT treatment deliveries

  PeerJ · 2024-12-23 · 2 citations

  articleOpen access

  Background This study investigates the impact of convergence mode (CM) in Eclipse (Varian Medical Systems) on the quality and complexity of volumetric modulated arc therapy (VMAT) plans for nasopharyngeal carcinoma (NPC) patients. Methods We retrospectively analyzed data from 21 NPC patients. For each patient, three VMAT plans with different CM settings (Off, On, and Extended) were created using identical optimization objectives. Plan quality was assessed using indices such as the conformity index (CI) and homogeneity index (HI), as well as evaluating target coverage and sparing of organs at risk (OARs). Complexity was measured by metrics including average leaf pair opening (ALPO), modulation complexity scores for VMAT (MCSv), monitor units (MUs), and optimization time. Dosimetric verification was performed based on the gamma pass rate. Results Different CM settings can generate treatment plans that meet clinical dose objectives for planning target volumes (PTVs) and OARs. The ‘On’ or ‘Extended’ CM settings improved CI and HI for the NPC target volume and reduced OAR doses, especially the mean dose, without compromising target coverage. The ‘Extended’ CM setting produced the most favorable outcomes. ALPO values for CM settings ‘Off’, ‘On’, and ‘Extended’ were 29.1 ± 4.3 mm, 28.6 ± 4.2 mm, and 28.4 ± 4. 2 mm, respectively. MCSv values for these settings were 0.1730 ± 0.0215, 0.1691 ± 0.0204, and 0.1693 ± 0.0208, respectively. MUs were 796.2 ± 110.8 for CM ‘Off’, 798.6 ± 106.1 for CM ‘On’, and 799.7 ± 103.6 for CM ‘Extended’, with no significant differences ( p > 0.05). Gamma pass rates for all plans were above 99% (3%/3 and 2%/2 mm), with no significant differences among groups ( p > 0.05). The average optimization times for CM settings ‘Off’, ‘On’, and ‘Extended’ were 14.4 ± 3.2, 35.9 ± 8.9, and 145.6 ± 50.3 min, respectively ( p < 0.001). Conclusion CM usage can improve the CI and HI of the target volume and decrease the dose to OARs in VMAT plans for NPC patients. This study suggests that CM can be a valuable tool in VMAT planning for nasopharyngeal carcinoma, given adequate planning time.

  PublisherDOI

• Field Evaluation of Experimental Maize Hybrids for Resistance to the Fall Armyworm (Lepidoptera: Noctuidae) in a Warm Temperate Climate

  Insects · 2024-04-19 · 4 citations

  articleOpen access

  The polyphagous fall armyworm (FAW), Spodoptera frugiperda, has become an invasive pest worldwide in recent years. To develop maize germplasm with multiple pest resistance and understand genetic inheritance, 12 experimental hybrids (six pairs of reciprocal crosses) with diverse genetic backgrounds and four commercial checks were examined for FAW resistance in 2013 and 2014. The experiment utilized a randomized complete block design with four replications as the block factor. FAW injury on maize plants was assessed at 7 and 14 d after the artificial infestation at the V6 stage, and predatory arthropod taxa and abundance on maize seedlings were recorded 7 d after the infestation. Spodoptera frugiperda resistance varied significantly among the 16 hybrids. Two reciprocal crosses (‘FAW1430’ × ‘Oh43’ and ‘CML333’ × ‘NC358’) showed the least FAW injury. Eleven arthropod predators [i.e., six coleopterans, three hemipterans, earwigs (dermapterans), and spiders (or arachnids)] were also recorded; the two most common predators were the pink spotted ladybeetle, Coleomegilla maculata, and the insidious flower (or minute pirate) bug, Orius spp. Predator abundance was not correlated to FAW injury but varied greatly between 2013 and 2014. Principal component analysis demonstrated that, when compared with FAW resistant (or Bt-transgenic) checks (‘DKC69-71’, ‘DKC67-88’, and ‘P31P42’), five pairs of the reciprocal crosses had moderate FAW resistance, whereas a pair of reciprocal crosses (‘NC350’ × ‘NC358’ and NC358 × NC350) showed the same FAW susceptibility as the non-Bt susceptible check ‘DKC69-72’. Both parents contributed similarly to FAW resistance, or no maternal/cytoplasmic effect was detected in the experimental hybrids.

  PublisherOA PDFDOI

• 2020-2021 Field Seasons of Maize G x E Project within Maize Genomes to Fields Initiative

  Research Square · 2023-05-11

  preprintOpen access

  Abstract Objectives: This release note describes the Maize G x E project datasets within the Genomes to Fields (G2F) Initiative. The Maize G x E project aims to understand genotype by environment (G × E) interactions and use the information collected to improve resource allocation efficiency and increase genotype predictability and stability, particularly in scenarios of variable environmental patterns. Hybrids and inbreds are evaluated across multiple environments and phenotypic, genotypic, environmental, and metadata information are made publicly available. Data description: The datasets include phenotypic data of the hybrids and inbreds evaluated in 30 locations across the US and one location in Germany in 2020 and 2021, soil and climatic measurements and metadata information for all environments (combination of year and location), ReadMe, and description files for each data type. A set of common hybrids is present in each environment to connect with previous evaluations. Each environment had a collaborator responsible for collecting and submitting the data, the G x E coordination team combined all the collected information and removed obvious erroneous data. Collaborators received the combined data to use, verify and declare that the data generated in their own environments was accurate. Combined data is released to the public with minimal filtering to maintain fidelity to the original data.

  PublisherOA PDFDOI

• 2020-2021 field seasons of Maize GxE project within the Genomes to Fields Initiative

  BMC Research Notes · 2023-09-14 · 21 citations

  articleOpen access

  OBJECTIVES: This release note describes the Maize GxE project datasets within the Genomes to Fields (G2F) Initiative. The Maize GxE project aims to understand genotype by environment (GxE) interactions and use the information collected to improve resource allocation efficiency and increase genotype predictability and stability, particularly in scenarios of variable environmental patterns. Hybrids and inbreds are evaluated across multiple environments and phenotypic, genotypic, environmental, and metadata information are made publicly available. DATA DESCRIPTION: The datasets include phenotypic data of the hybrids and inbreds evaluated in 30 locations across the US and one location in Germany in 2020 and 2021, soil and climatic measurements and metadata information for all environments (combination of year and location), ReadMe, and description files for each data type. A set of common hybrids is present in each environment to connect with previous evaluations. Each environment had a collaborator responsible for collecting and submitting the data, the GxE coordination team combined all the collected information and removed obvious erroneous data. Collaborators received the combined data to use, verify and declare that the data generated in their own environments was accurate. Combined data is released to the public with minimal filtering to maintain fidelity to the original data.

  PublisherOA PDFDOI

• Effects of Irrigation Level of Corn Silage Hybrids at Texas Panhandle on Nutrient Profile, Digestibility, and Aerobic Stability

  SSRN Electronic Journal · 2023-01-01

  preprintOpen access
  PublisherDOI

• Environment‐specific selection alters flowering‐time plasticity and results in pervasive pleiotropic responses in maize

  New Phytologist · 2023-01-23 · 18 citations

  articleOpen access

  Crop genetic diversity for climate adaptations is globally partitioned. We performed experimental evolution in maize to understand the response to selection and how plant germplasm can be moved across geographical zones. Initialized with a common population of tropical origin, artificial selection on flowering time was performed for two generations at eight field sites spanning 25° latitude, a 2800 km transect. We then jointly tested all selection lineages across the original sites of selection, for the target trait and 23 other traits. Modeling intergenerational shifts in a physiological reaction norm revealed separate components for flowering-time plasticity. Generalized and local modes of selection altered the plasticity of each lineage, leading to a latitudinal pattern in the responses to selection that were strongly driven by photoperiod. This transformation led to widespread changes in developmental, architectural, and yield traits, expressed collectively in an environment-dependent manner. Furthermore, selection for flowering time alone alleviated a maladaptive syndrome and improved yields for tropical maize in the temperate zone. Our findings show how phenotypic selection can rapidly shift the flowering phenology and plasticity of maize. They also demonstrate that selecting crops to local conditions can accelerate adaptation to climate change.

  PublisherOA PDFDOI

• 2018–2019 field seasons of the Maize Genomes to Fields (G2F) G x E project

  BMC Genomic Data · 2023-05-25 · 14 citations

  articleOpen access

  OBJECTIVES: This report provides information about the public release of the 2018-2019 Maize G X E project of the Genomes to Fields (G2F) Initiative datasets. G2F is an umbrella initiative that evaluates maize hybrids and inbred lines across multiple environments and makes available phenotypic, genotypic, environmental, and metadata information. The initiative understands the necessity to characterize and deploy public sources of genetic diversity to face the challenges for more sustainable agriculture in the context of variable environmental conditions. DATA DESCRIPTION: Datasets include phenotypic, climatic, and soil measurements, metadata information, and inbred genotypic information for each combination of location and year. Collaborators in the G2F initiative collected data for each location and year; members of the group responsible for coordination and data processing combined all the collected information and removed obvious erroneous data. The collaborators received the data before the DOI release to verify and declare that the data generated in their own locations was accurate. ReadMe and description files are available for each dataset. Previous years of evaluation are already publicly available, with common hybrids present to connect across all locations and years evaluated since this project's inception.

  PublisherOA PDFDOI

Frequent coauthors

• Seth C. Murray

  Texas A&M University

  29 shared

• Sherry Flint‐Garcia

  United States Department of Agriculture

  22 shared

• James B. Holland

  Agricultural Research Service

  22 shared

• Randall J. Wisser

  Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

  20 shared

• Todd Sulchek

  Georgia Institute of Technology

  20 shared

• Edward S. Buckler

  Cornell University

  19 shared

• Kehong Bi

  16 shared

• Natalia de León

  University of Wisconsin–Madison

  16 shared

Education

• Ph.D., Genetics

  University of Missouri

  1992