Yucheng Jie | Crop Science | Best Researcher Award

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Prof. Dr Yucheng Jie |  Crop Science | Best Researcher Award

Researcher at  Agricultural College / Ramie Research Institute,  China

Yucheng Jie is a distinguished professor and doctoral advisor at Hunan Agricultural University. With extensive expertise in [insert area of expertise, e.g., crop genetics, sustainable agriculture, or other specialties], Professor Jie has made significant contributions to the field through research, teaching, and mentorship. Born in Taoyuan, Hunan Province, his work reflects a deep commitment to advancing agricultural science and innovation.

Profile:

🎓 Education:

  • B.S. in Crop Science, Hunan Agricultural University (1987)
  • Ph.D. in Agriculture, Nanjing Agricultural University (1998)

📚 Professional Experience:

  • Director, Institute of Ramie, Hunan Agricultural University (2007–Present)
  • Visiting Scholar, North Carolina State University, USA (2013–2015)
  • Research Fellow and Director Roles, Chinese Academy of Agricultural Sciences (1993–2007)

🔬 Research Focus:

Specializes in ramie and bast fiber crops, with expertise in crop germplasm innovation, heavy metal soil remediation, and sustainable agricultural technologies.

🏆 Awards and Recognitions:

  • National Science and Technology Progress Award (Second Prize, 2016, 2010)
  • Multiple provincial awards for contributions to agricultural science and technology

📖 Grants and Projects:

Led over 25 national and provincial projects, including studies on cadmium stress tolerance in ramie, crop germplasm resources, and soil remediation technologies.

Citation Metrics:

📊 Total Citations: 631 (from 531 documents)
📄 Total Publications: 54
📈 h-index: 14

Publication Top Notes:

  1. Effects of Nitrogen Fertilizer and Planting Density on Growth, Nutrient Characteristics, and Chlorophyll Fluorescence in Silage Maize
    Han, X., Xiao, X., Zhang, J., Jie, Y., Xing, H.
    Agronomy, 2024, 14(7), 1352
  2. BnXTH1 Regulates Cadmium Tolerance by Modulating Vacuolar Compartmentalization and the Cadmium Binding Capacity of Cell Walls in Ramie (Boehmeria nivea)
    Ma, Y., Jie, H., Zhao, L., Xing, H., Jie, Y.
    Journal of Hazardous Materials, 2024, 470, 134172
  3. Fungal Systems for Lignocellulose Deconstruction: From Enzymatic Mechanisms to Hydrolysis Optimization
    Ren, F., Wu, F., Wu, X., Jie, Y., Gao, L.
    GCB Bioenergy, 2024, 16(5), e13130
  4. Comparative Study on Production Performance of Forage Triticale and Italian Ryegrass in Hunan Province
    He, P., Jie, H., Rasheed, A., Xing, H., Jie, Y.
    Chinese Journal of Grassland, 2024, 46(4), pp. 144–150
  5. Evaluation of Forage Sweet Sorghum Production Performance in Western Hunan
    He, P., Jie, H., Ma, Y., Xing, H., Jie, Y.
    Chinese Journal of Grassland, 2024, 46(3), pp. 100–109
  6. Response of Lignin and Flavonoid Metabolic Pathways in Capsicum annuum to Drought and Waterlogging Stresses
    Lv, X., Xiao, H., Jie, H., Xing, H., Jie, Y.
    Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 2024, 52(2), 13819
  7. Comparison of Silage Maize Production Performance in the Eastern and Western Regions of Hunan Province
    He, P.-L., Jie, H.-D., Zhu, N.-J., Xing, H.-C., Jie, Y.-C.
    Acta Agrestia Sinica, 2024, 32(3), pp. 977–984
  8. Waterlogging Increases Greenhouse Gas Release and Decreases Yield in Winter Rapeseed (Brassica napus L.) Seedlings
    Li, L., Zhang, L., Tang, J., Jie, H., Jie, Y.
    Scientific Reports, 2023, 13(1), 18673

 

Moyses Nascimento | Plant breeding | Best Researcher Award

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Prof Moyses Nascimento |  Plant breeding |  Best Researcher Award

Associate Professor at  Federal University of Vicosa, Brazil

Prof. Moysés Nascimento is an Associate Professor in the Department of Statistics at the Federal University of Viçosa, Brazil. He holds a Ph.D. in Statistics and Agricultural Experimentation from the Federal University of Lavras (UFLA), Brazil. His research interests focus on statistical methods applied to agriculture, bioinformatics, and genomic selection, with significant expertise in cluster analysis and Monte Carlo Markov Chains.

 

Publication Profile

Academic Background:

  • Ph.D. in Statistics and Agricultural Experimentation (2011), Federal University of Lavras (UFLA), Brazil
  • M.S. in Applied Statistics and Biometry (2009), Federal University of Viçosa (UFV), Brazil
  • B.S. in Statistics (2007), Federal University of Espírito Santo (UFES), Brazil

Professional Experience:

  • Associate Professor, Federal University of Viçosa (UFV), Brazil (2010–present)
  • Visiting Scholar, University of Florida, USA (2023–2024)
  • Research Scholar, North Carolina State University, USA (2016–2017)
  • Graduate Research Assistant, Federal University of Lavras and Federal University of Viçosa

Research Interests:

  • Statistical methods applied to agriculture and genomics
  • Cluster analysis, bioinformatics, and Monte Carlo Markov Chains in genetic improvement
  • Neural networks and multivariate analysis applied to agronomy

Awards & Honors:

  • 1st, 2nd, and 3rd place in the 2023 GDM 40th Anniversary Innovation Award
  • Emerald Literati Award (2019) for the paper on craft beer consumer market characterization
  • Best Paper Award, International Symposium on Genetics and Plant Breeding (2021)
  • Best Master’s Paper, Brazilian Region of the International Biometrics Society (2008)

Citations :

  • Citations (All): 2,229
  • Citations (Since 2019): 1,643
  • h-index (All): 26
  • h-index (Since 2019): 21
  • i10-index (All): 68
  • i10-index (Since 2019): 58

Publication Top Notes

  1. Characterization of the consumer market and motivations for the consumption of craft beer
    NB Carvalho, LA Minim, M Nascimento, GHC Ferreira, VPR Minim
    British Food Journal, 120(2), 378-391 (2018)
  2. Avaliação do coeficiente de variação experimental para caracteres de frutos de pimenteiras
    AR Silva, PR Cecon, ER Rêgo, M Nascimento
    Revista Ceres, 58, 168-171 (2011)
  3. Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
    M Nascimento, LA Peternelli, CD Cruz, ACC Nascimento, RP Ferreira, …
    Crop Breeding and Applied Biotechnology, 13, 152-156 (2013)
  4. Alteração no método centroide de avaliação da adaptabilidade genotípica
    M Nascimento, CD Cruz, ACM Campana, RS Tomaz, CC Salgado, …
    Pesquisa Agropecuária Brasileira, 44, 263-269 (2009)
  5. Neural networks for predicting breeding values and genetic gains
    GN Silva, RS Tomaz, IC Sant’Anna, M Nascimento, LL Bhering, CD Cruz
    Scientia Agricola, 71, 494-498 (2014)
  6. Multi-trait multi-environment models in the genetic selection of segregating soybean progeny
    L Volpato, RS Alves, PE Teodoro, MD Vilela de Resende, M Nascimento, …
    PloS One, 14(4), e0215315 (2019)
  7. Technical efficiency of milk production in Minas Gerais: an application of quantile regression
    ACC Nascimento, JE Lima, MJ Braga, M Nascimento, AP Gomes
    Revista Brasileira de Zootecnia, 41, 783-789 (2012)
  8. Adaptability and stability based on nonparametric regression in coffee genotypes
    M Nascimento, A Ferreira, RG Ferrão, ACM Campana, LL Bhering, …
    Pesquisa Agropecuária Brasileira, 45, 41-48 (2010)
  9. Métodos estatísticos
    PR Cecon, AR Silva, M Nascimento, A Ferreira
    Viçosa: Editora UFV (2012)
  10. Quantitative sensory description using the Optimized Descriptive Profile: Comparison with conventional and alternative methods for evaluation of chocolate
    RC dos Santos Navarro, VPR Minim, JDS Carneiro, M Nascimento, …
    Food Quality and Preference, 30(2), 169-179 (2013)
  11. A discriminant function for validation of the cluster analysis and behavioral prediction of the coffee market
    NB Carvalho, VPR Minim, M Nascimento, MCTR Vidigal, MAM Ferreira, …
    Food Research International, 77, 400-407 (2015)
  12. Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms
    IC Sousa, M Nascimento, GN Silva, ACC Nascimento, CD Cruz, …
    Scientia Agricola, 78, e20200021 (2020)
  13. Impact of energy restriction during late gestation on the muscle and blood transcriptome of beef calves after preconditioning
    LP Sanglard, M Nascimento, P Moriel, J Sommer, M Ashwell, MH Poore, …
    BMC Genomics, 19, 1-18 (2018)
  14. Quantile regression for genome-wide association study of flowering time-related traits in common bean
    M Nascimento, ACC Nascimento, FF Silva, LD Barili, NM Vale, …
    PLoS One, 13(1), e0190303 (2018)
  15. Abordagem bayesiana para avaliação da adaptabilidade e estabilidade de genótipos de alfafa
    M Nascimento, FF Silva, T Sáfadi, ACC Nascimento, RP Ferreira, …
    Pesquisa Agropecuária Brasileira, 46, 26-32 (2011)
  16. Independent Component Analysis (ICA) based-clustering of temporal RNA-seq data
    M Nascimento, FF Silva, T Safadi, ACC Nascimento, TEM Ferreira, …
    PLoS One, 12(7), e0181195 (2017)
  17. Perspectiva bayesiana na seleção de genótipos de feijão-caupi em ensaios de valor de cultivo e uso
    PE Teodoro, M Nascimento, FE Torres, LMA Barroso, E Sagrilo
    Pesquisa Agropecuária Brasileira, 50(10), 878-885 (2015)
  18. Superiority of artificial neural networks for a genetic classification procedure
    IC Sant’Anna, RS Tomaz, GN Silva, M Nascimento, LL Bhering, CD Cruz
    Genetics and Molecular Research (2015)
  19. Recommendation of Coffea arabica genotypes by factor analysis
    IP Barbosa, WG da Costa, M Nascimento, CD Cruz, ACB de Oliveira
    Euphytica, 215, 1-10 (2019)
  20. Genotype-environment interaction in common bean cultivars with carioca grain, recommended for cultivation in Brazil in the last 40 years
    LD Barili, NM Vale, AL Prado, JES Carneiro, FF Silva, M Nascimento
    Crop Breeding and Applied Biotechnology, 15(04), 244-250 (2015)