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)

 

Aparna Singh | Agricultural | Best Researcher Award

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Ms. Aparna Singh | Agricultural | Best Researcher Award

Ms. Aparna Singh, Indian Institute of Technology Guwahati, India

Aparna Singh is a dedicated postgraduate researcher specializing in Industrial Biotechnology, with a strong focus on eco-friendly bioremediation and sustainable environmental solutions. Passionate about leveraging scientific advancements to address pressing global issues, Aparna combines academic rigor with innovative thinking to contribute meaningfully to the field of biotechnology.

Profile

Scopus

Strengths for the Award

Diverse Research Contributions:

Aparna’s work spans various impactful domains, including biochar-mediated bioremediation, cytokine roles in immune programming, and sustainable waste management.

Publications in reputable journals (e.g., Chemical Engineering Journal with DOI references) and oral presentations at esteemed international conferences (e.g., IIT-Patna, NYU Abu Dhabi).

Interdisciplinary Expertise:

Her research integrates biotechnology, environmental science, and clinical studies, indicating versatility.

Significant focus on addressing global challenges like environmental pollution and sustainable waste management.

Technical and Soft Skills:

Mastery of molecular and cell culture techniques, bioprocess engineering, and advanced instrumentation demonstrates strong technical acumen.

Academic writing, public speaking, and teamwork showcase her ability to effectively communicate and collaborate in research environments.

Academic Background and Training:

Advanced studies in Industrial Biotechnology from a prestigious institution (NIT Karnataka) paired with specialized training (e.g., fermentation and bioprocess engineering).

Additional certifications in proteomics and cancer metastasis enhance her skill set.

Recognition Through Presentations:

Aparna has presented her work at high-profile platforms, underscoring her contributions to the scientific community.

Vision and Motivation:

A clear, impactful research philosophy—transforming waste into a resource—aligns with sustainability goals and innovation in science.

Areas for Improvement

Focus and Depth in Publications:

While Aparna has made commendable strides in multiple areas, concentrating on one or two core research themes could lead to higher impact and specialization.

More high-impact journal publications with detailed mechanistic studies would bolster her credentials further.

Expanded Collaborative Network:

Collaborating with international research groups or industries could enhance her global exposure and the translational potential of her research.

Skill Development in Computational Tools:

Proficiency in bioinformatics or computational modeling could complement her experimental research, especially in mechanistic studies.

Grant Writing Experience:

Demonstrating ability to secure independent research funding would add a significant dimension to her academic portfolio.

Education 🎓

  • Master of Technology in Industrial Biotechnology, National Institute of Technology Karnataka (2022–2024).
    Thesis: Harnessing Microbial Cell Biochar for Eco-friendly Wastewater Treatment.
  • Bachelor of Technology in Biotechnology, SRM Institute of Science and Technology (2015–2019).
    Thesis: Vitamin D Status and Gestational Diabetes Mellitus: Role of Vitamin D Resistance.
    Minor Project: Effect of Lead and Iron on Scenedesmus obliquus.
    CGPA: 7.98.

Experience 🧪

Aparna brings hands-on experience in bioprocess engineering and environmental biotechnology. With robust skills in molecular and cell culture techniques, biochemical assays, and clinical studies, she has contributed significantly to projects involving microbial biochar systems, water and soil remediation, and the sustainable management of mine waste.

Research Interests 🔬

Aparna’s research interests revolve around:

  • Bioremediation using biochar-bacteria systems.
  • Biochemical and molecular analysis of contaminants in environmental matrices.
  • Role of cytokines in immune programming and metabolic disorders.

Awards 🏆

  • Oral Presentation: “Harnessing Microbial Cell Biochar for Eco-friendly Wastewater Treatment,” IIT-Patna (ICSPT), December 2023.
  • IDEAS Conference: Presented at NYU Abu Dhabi, January 2024.
  • Best Research Paper Award: RASTH-2021 Conference on Applied Science and Health.

Publication Top Notes 📚

  1. Mechanistic understanding of biochar-bacteria system for enhanced chlorpyrifos bioremediation in water and soil medium
  2. Mechanistic studies on bioremediation of dye using Aeromonas veronii immobilized peanut shell biochar
    • Under Review.
  3. Bioprocesses for sustainable management of mine waste in contaminated environmental matrices
    • Book Chapter, Publication Year Pending.
  4. Role of Cytokines on Fetal Immune Programming

 

Conclusions

Aparna Singh demonstrates an exceptional blend of technical expertise, interdisciplinary research focus, and a strong commitment to addressing critical societal challenges. Her achievements and motivation make her a strong contender for the “Best Researcher Award.” Addressing the suggested areas for improvement would further solidify her position as a leading researcher in her field.

 

 

Yeongmi Jang | Agriculture | Best Researcher Award

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Dr Yeongmi Jang |  Agriculture |  Best Researcher Award

PhD at  Chungnam National University, South Korea

Yeongmi Jang is a PhD candidate in the Department of Crop Science at Chungnam National University, Republic of Korea, expecting to complete her degree in August. Her research focuses on Ecology, and she has contributed to various scientific journals, including MDPI publications such as Plants, Agronomy, and Agriculture. Although she has not yet accrued professional work experience, her scholarly efforts have earned her a citation index of 19. Yeongmi is in the process of developing her professional network and contributions, with no current consultancy, publications, or patents to her name.

Profile:

Academic Background:

Yeongmi Jang will complete a PhD in August from Chungnam National University, focusing on Ecology. Although Yeongmi does not have work experience yet, their academic journey promises future contributions to the field.

Research Focus:

Yeongmi Jang’s research in agriculture predominantly explores the effects of environmental stressors and agronomic practices on crop growth and physiology. Key areas of investigation include the impact of long-term salinity stress on mono and mixed crops, and the role of magnesium and calcium sulfate in mitigating such stress in forage crops. Jang has also contributed to understanding the effects of planting density and nitrogen fertilization on forage rice growth in both reclaimed and conventional paddy fields. Additionally, their research addresses the optimal harvest times for maximizing forage value and yield of winter crops and forage rice in South Korea. This work aims to enhance agricultural productivity and sustainability in challenging environmental conditions.

Publication Top Notes:

1. Evaluating the Effects of Long-Term Salinity Stress on the Growth and Physiology of Mono and Mixed Crops
Journal: Agronomy
Date: 2024-01-27
DOI: 10.3390/agronomy14020287
Contributors: Khulan Sharavdorj; Ser-Oddamba Byambadorj; Yeongmi Jang; Youngjik Ahn; Jin-Woong Cho

2. Effects of Planting Density and Nitrogen Fertilization on the Growth of Forage Rice in Reclaimed and General Paddy Fields
Journal: Plants
Date: 2023-12-19
DOI: 10.3390/plants13010013
Contributors: Yeongmi Jang; Khulan Sharavdorj; Youngjik Ahn; Jinwoong Cho

3. Effects of Planting Density and Nitrogen Fertilization on the Growth of Forage Rice in Reclaimed and General Paddy Fields
Date: 2023-11-08
Preprint DOI: 10.20944/preprints202311.0454.v1
Contributors: Yeongmi Jang; Khulan Sharavdorj; Youngjik Ahn; Jinwoong Cho

4. Application of Magnesium and Calcium Sulfate on Growth and Physiology of Forage Crops under Long-Term Salinity Stress
Journal: Plants
Date: 2022-12-18
DOI: 10.3390/plants11243576
Contributors: Khulan Sharavdorj; Ser-Oddamba Byambadorj; Yeongmi Jang; Jin-Woong Cho

5. Growth and Forage Value of Two Forage Rice Cultivars According to Harvest Time in Reclaimed Land of South Korea
Journal: Agronomy
Date: 2022-12-08
DOI: 10.3390/agronomy12123118
Contributors: Yeongmi Jang; Khulan Sharavdorj; Priscilla Nadalin; Suhwan Lee; Jinwoong Cho

6. Effects of Harvest Time on the Yield and Forage Value of Winter Forage Crops in Reclaimed Lands of Korea
Journal: Agriculture
Date: 2022-06-09
DOI: 10.3390/agriculture12060830
Contributors: Yeongmi Jang; Bumsik Choi; Khulan Sharavdorj; Suhwan Lee; Jinwoong Cho

 

Zaryab Murad | Plant Growth | Young Scientist Award

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Mr Zaryab Murad |  Plant Growth  |  Young Scientist Award

Ph.D. Scholar at  Huazhong Agriculture University, China

Zaryab Murad, born on April 14, 1996, is a Pakistani national currently residing in Wuhan, Hubei, China. With a solid academic background in Soil and Environmental Sciences, he is pursuing his Doctor of Philosophy (Ph.D.) at Huazhong Agriculture University. Zaryab completed both his Master of Sciences (Hons) and Bachelor of Sciences (Hons) in Agriculture at The University of Agriculture Peshawar, Pakistan. His research focuses on the effects of bentonite clay and biochar on soil contamination and plant growth. Professionally, he has served as a Field Survey Project Manager at TAMEER-E-KHALAQ Foundation, where he works towards improving food security and agricultural practices. Additionally, he has held the position of Agriculture Policy Officer at the Agriculture Extension Department in KP, Pakistan. Fluent in Urdu and proficient in English, Zaryab has been recognized for his contributions to the field, including being a Gold Medalist at his alma mater. His technical skills include expertise in MS Office, Endnote, Statistics 8.1, Graphpad, and Sigmaplot.

Profile: 

Education and Training:

Zaryab Murad is a Doctoral candidate in Soil Science at Huazhong Agriculture University, Wuhan, China, with a focus on soil and environmental sciences. He completed his Master of Sciences (Hons) and Bachelor of Sciences (Hons) in Agriculture at The University of Agriculture Peshawar, Pakistan. His research includes the effects of bentonite clay and biochar on soil contamination and plant growth. He has gained hands-on experience with various soil analysis techniques, including using Flame Photometers and Atomic Absorption Spectrophotometers.

Work Experience:

Currently, Zaryab is a Field Survey Project Manager at TAMEER-E-KHALAQ Foundation, where he focuses on agricultural development and food security. He has previously served as an Agriculture Policy Officer at the Agriculture Extension Department in KP, Pakistan. His work involves enhancing production, facilitating value addition, and improving crop varieties.

Honors and Awards:

  • Gold Medalist, The University of Agriculture Peshawar, 2022

Certificates and Trainings:

  • Attended workshops and congresses on sustainable soil management and weed science.
  • Participated in the HZAU Happy Festival at Huazhong Agriculture University.

Research Focus: Plant Growth

Zaryab Murad’s research focuses on enhancing plant growth through innovative soil management techniques. His work primarily investigates the effects of soil amendments, such as bentonite clay and biochar, on the phytoavailability of heavy metals and overall plant health. Zaryab’s research aims to improve crop yields and soil fertility while mitigating contamination effects. His studies include evaluating how biochar and other amendments can stabilize heavy metals in soil and enhance the growth of various crops, particularly in contaminated environments. This research contributes to sustainable agricultural practices by improving soil conditions and plant resilience against pollutants.

Publication Top Notes:

  • Murad, Z., Bibi, S., Ahmad, S.E.Y., Manan, U., & Younas, M. (2024). Stabilization of Cd in Soil by Biochar and Growth of Rice (Oryza sativa) in Artificially Contaminated Soil. Sarhad Journal of Agriculture, 40(1), 231–245.
  • Khan, U., Irfan, M., Murad, Z., Waleed, M., & Kamal, A. (2023). Enhancing Lettuce Growth and Cadmium and Lead Tolerance Through Biochar and Bacteria. Gesunde Pflanzen, 75(6), 2685–2696.
  • Ilyas, M., Khan, M.J., Murad, Z., Ullah, A., & Farhan. (2023). Biofortification of Iron in Wheat Varieties Using Different Methods of Application. Gesunde Pflanzen, 75(5), 2177–2185.
  • Murad, Z., Ahmad, I., Waleed, M., Hashim, S., & Bibi, S. (2022). Effect of Biochar on Immobilization of Cadmium and Soil Chemical Properties. Gesunde Pflanzen, 74(1), 151–158.
  • Tariq, M., Khan, M.O., Hussain, A., Khalil, M.K., Muhammad, S., & Murad, Z. (2021). Impact of Soil and Foliar Application of Various Zinc Sources on the Yield and Uptake by Onion Under Agroclimatic Condition of Swat. International Journal of Agricultural and Statistical Sciences, 17, 2363–2376.

 

Alireza Sharifi | Crop yield prediction | Best Researcher Award

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Assoc Prof Dr Alireza Sharifi |  Crop yield prediction |  Best Researcher Award

Dr at  Shahid Rajaee Teacher Training, Iran

Dr. Alireza Sharifi is an Associate Professor at Shahid Rajaee Teacher Training University, specializing in geosciences and remote sensing applications for Precision Agriculture. He obtained his graduate degree from the University of Tehran and has focused his research on Earth Observation Programs, particularly using satellite imagery. Dr. Sharifi has led multiple research projects funded by prestigious organizations such as the National Natural Science Foundation of China, contributing significantly to the fields of hyperspectral image classification, crop mapping, and vegetation monitoring. With numerous publications and a strong academic background, he continues to advance innovative approaches in agricultural sustainability through technology.

Profile:

📚 Academic Background:

Dr. Alireza Sharifi graduated from the University of Tehran with expertise in geosciences and remote sensing applications, focusing on Earth Observation Programs for Precision Agriculture using satellite imagery.

🔍 Research Focus:

His research spans various projects, including hyperspectral image classification, spatio-temporal analysis of forest fires, and integration of satellite images for crop mapping. He has published extensively in reputed journals and holds multiple editorial appointments.

📊 Citations:

  • Citations: 1970 (1878 since 2019)
  • h-index: 28 (since 2019)
  • i10-index: 40 (since 2019)
📄 Publication:

1. Comparison the accuracies of different spectral indices for estimation of vegetation cover fraction in sparse vegetated areas
S Barati, B Rayegani, M Saati, A Sharifi, M Nasri
The Egyptian Journal of Remote Sensing and Space Science 14 (1), 49-56, 2011
Citations: 221

2. Hyperspectral image classification using a hybrid 3D-2D convolutional neural networks
S Ghaderizadeh, D Abbasi-Moghadam, A Sharifi, N Zhao, A Tariq
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Citations: 132

3. Yield prediction with machine learning algorithms and satellite images
A Sharifi
Journal of the Science of Food and Agriculture 101 (3), 891-896, 2021
Citations: 105

4. Spatio-temporal analysis of forest fire events in the Margalla Hills, Islamabad, Pakistan using socio-economic and environmental variable data with machine learning methods
A Tariq, H Shu, S Siddiqui, I Munir, A Sharifi, Q Li, L Lu
Journal of Forestry Research 33 (1), 183-194, 2022
Citations: 76

5. Crop type classification by DESIS hyperspectral imagery and machine learning algorithms
N Farmonov, K Amankulova, J Szatmári, A Sharifi, D Abbasi-Moghadam, …
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Citations: 62

6. Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models
SS Wahla, JH Kazmi, A Sharifi, SA Shirazi, A Tariq, H Joyell Smith
Geocarto International 37 (27), 14963-14982, 2022
Citations: 62

7. Multiscale dual-branch residual spectral–spatial network with attention for hyperspectral image classification
S Ghaderizadeh, D Abbasi-Moghadam, A Sharifi, A Tariq, S Qin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Citations: 60

8. Evaluation of vegetation indices and phenological metrics using time-series MODIS data for monitoring vegetation change in Punjab, Pakistan
P Hu, A Sharifi, MN Tahir, A Tariq, L Zhang, F Mumtaz, SHIA Shah
Water 13 (18), 2550, 2021
Citations: 59

9. Flash flood susceptibility assessment and zonation by integrating analytic hierarchy process and frequency ratio model with diverse spatial data
A Tariq, J Yan, B Ghaffar, S Qin, BG Mousa, A Sharifi, ME Huq, M Aslam
Water 14 (19), 3069, 2022
Citations: 57

10. Remote sensing satellite’s attitude control system: rapid performance sizing for passive scan imaging mode
A Kosari, A Sharifi, A Ahmadi, M Khoshsima
Aircraft Engineering and Aerospace Technology 92 (7), 1073-1083, 2020
Citations: 57

11. Flood mapping using relevance vector machine and SAR data: A case study from Aqqala, Iran
A Sharifi
Journal of the Indian Society of Remote Sensing 48 (9), 1289-1296, 2020
Citations: 55

12. Modeling and predicting land use land cover spatiotemporal changes: A case study in Chalus Watershed, Iran
S Jalayer, A Sharifi, D Abbasi-Moghadam, A Tariq, S Qin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Citations: 54

13. Integration of Sentinel 1 and Sentinel 2 satellite images for crop mapping
S Felegari, A Sharifi, K Moravej, M Amin, A Golchin, A Muzirafuti, A Tariq, …
Applied Sciences 11 (21), 10104, 2021
Citations: 54

14. Development of a method for flood detection based on Sentinel‐1 images and classifier algorithms
A Sharifi
Water and Environment Journal 35 (3), 924-929, 2021
Citations: 54

15. Estimation of forest biomass using multivariate relevance vector regression
A Sharifi, J Amini, R Tateishi
Photogrammetric Engineering & Remote Sensing 82 (1), 41-49, 2016
Citations: 54

16. Agro climatic zoning of saffron culture in Miyaneh city by using WLC method and remote sensing data
A Zamani, A Sharifi, S Felegari, A Tariq, N Zhao
Agriculture 12 (1), 118, 2022
Citations: 50

17. Forest biomass estimation using synthetic aperture radar polarimetric features
A Sharifi, J Amini
Journal of Applied Remote Sensing 9 (1), 097695-097695, 2015
Citations: 49

18. Remotely sensed vegetation indices for crop nutrition mapping
A Sharifi
Journal of the Science of Food and Agriculture 100 (14), 5191-5196, 2020
Citations: 47

19. Using Sentinel-2 data to predict nitrogen uptake in maize crop
A Sharifi
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Citations: 47

20. Speckle reduction of PolSAR images in forest regions using fast ICA algorithm
A Sharifi, J Amini, JT Sri Sumantyo, R Tateishi
Journal of the Indian Society of Remote Sensing 43, 339-346, 2015
Citations: 47

 

Vladimír Langraf | Agroecosystems | Best Researcher Award

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Assoc Prof Dr Vladimír Langraf |  Agroecosystems |  Best Researcher Award

associate professor position at  Constantine the Philosopher University in Nitra,   Slovakia

Doc. RNDr. Vladimír Langraf, PhD, serves as an Associate Professor at Constantine the Philosopher University in Nitra, Slovakia. He has an extensive academic background, completing his PhD in Landscape Protection and Exploitation in 2018 and earning his associate professorship in Biology in 2024. His research primarily focuses on agroecosystems, entomology, biostatistics, and big data.

 

Profile

Academic and Professional Background 📜

  • 2024: Habilitation in Biology, Constantine the Philosopher University in Nitra
  • 2014 – 2018: PhD in Landscape Protection and Exploitation, Constantine the Philosopher University in Nitra
  • 2015 – 2016: Rigorous Degree (RNDr) in Landscape Protection and Exploitation, Constantine the Philosopher University in Nitra
  • 2012 – 2014: Master’s Degree (Mgr) in Biology, Constantine the Philosopher University in Nitra
  • 2009 – 2012: Bachelor’s Degree (Bc) in Biology, Constantine the Philosopher University in Nitra

Agroecosystems Research Focus:

doc. RNDr. Vladimír Langraf PhD, an Associate Professor at Constantine the Philosopher University in Nitra, specializes in the study of agroecosystems. His research delves into the dynamics and interactions within agricultural environments, focusing on the composition and seasonal variation of epigeic arthropods in different types of crops and their ecotones. His work aims to understand the impact of agricultural practices on biodiversity and ecosystem health, particularly through the lens of ecological management and sustainable farming practices.

Citations:

  • Citations: 117 citations by 84 documents
  • h-index: 8

📄 Publication:

  • Habitat Structure Impact on the Occurrence Preferences and Behaviour of the Endangered Species Hipparchia hermione (Lepidoptera, Nymphalidae) in Slovakia
    • Farkasová, S., Kalivoda, H., Langraf, V., Holecová, M.
    • Ekologia Bratislava, 2024, 43(1), pp. 66–75
  • Structure of Beetles (Coleoptera) in the Conditions of Agriculturally Used Land and Natural Habitat of the European Important Territory of the Dunajské luhy
    • Langraf, V., Petrovičová, K., Brygadyrenko, V.
    • Contemporary Problems of Ecology, 2024, 17(2), pp. 325–335
  • Seasonal Dynamics of Epigeic Arthropods under the Conditions of Ecological Management of the Triticum aestivum Crop
    • Langraf, V., Petrovičová, K.
    • Agriculture (Switzerland), 2024, 14(3), 482
  • Comparison of Spatial Dispersion of Epigeic Fauna Between Alluvial Forests in an Agrarian and Dunajské luhy Protected Landscape Area, Southern Slovakia
    • Langraf, V., Petrovičová, K., David, S., Brygadyrenko, V.
    • Central European Forestry Journal, 2024, 70(1), pp. 3–10
  • Ladybird (Coleoptera, Coccinellidae) Communities on Nonnative Blue Spruce in Central Europe
    • Jauschová, T., Sarvašová, L., Saniga, M., Kulfan, J., Zach, P.
    • Folia Oecologica, 2024, 51(1), pp. 18–28

 

Vladimir Verzhuk | Sustainable Crop Production | Best Researcher Award

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Dr Vladimir Verzhuk |  Sustainable Crop Production |  Best Researcher Award

Senior researcher at N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR) St. Petersburg, Russia

Verzhuk Vladimir Grigorevich is a Senior Researcher at the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR) in St. Petersburg, Russia. He holds a Candidate of Biological Sciences degree and has been a pivotal figure in the field of plant cryopreservation since completing his postgraduate studies at VIR in 1976.

 

Profile:

Academic and Professional Background:

Verzhuk Vladimir Grigorevich, a Candidate of Biological Sciences, is a Senior Researcher at the Laboratory of Long-term Storage of Plant Genetic Resources of VIR. He graduated from the Crimean Agricultural Institute in 1971 and completed his postgraduate studies at VIR in 1976, focusing on photosynthesis and productivity. Since 2000, he has led the cryopreservation group, specializing in low-temperature storage of vegetative shoots, buds, and pollen of fruit crops.

Areas of Research:

Verzhuk’s research focuses on developing and improving cryopreservation methods for the genetic resources of vegetatively propagated crops at VIR.

Sustainable Crop Production Research Focus:

Verzhuk’s research emphasizes sustainable crop production through the development of cryopreservation methods for genetic resources. His work ensures the long-term viability and diversity of crop species, contributing to the sustainability of agricultural systems by preserving genetic material that can adapt to changing environmental conditions and stressors.

Publication Top Notes:

  • Conservation of the Bird Cherry (Padus Mill.) Germplasm by Cold Storage and Cryopreservation of Winter Cuttings
    • Journal: Biology
    • Date: 2023-07
    • DOI: 10.3390/biology12081071
    • Contributors: Vladimir Verzhuk, Sergey Murashev, Liubov Novikova, Stepan Kiru, Svetlana Orlova
  • Post-Cryogenic Viability of Peach (Persica vulgaris Mill.) Dormant Buds from the VIR Genetic Collection
    • Journal: Agriculture
    • Date: 2022-12
    • DOI: 10.3390/agriculture13010111
    • Contributors: Vladimir Verzhuk, Victor Eremin, Taisya Gasanova, Oksana Eremina, Liubov Novikova, Galina Filipenko, Maxim Sitnikov, Alexander Pavlov
  • Viability of Red (Ribes rubrum L.) and Black (Ribes nigrum L.) Currant Cuttings in Field Conditions after Cryopreservation in Vapors of Liquid Nitrogen
    • Journal: Agriculture
    • Date: 2020-10
    • DOI: 10.3390/agriculture10100476
    • Contributors: Vladimir Verzhuk, Alexander Pavlov, Liubov Novikova, Galina Filipenko

 

Guoqiang Dun | Agricultural Machinery | Best Researcher Award

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Dr Guoqiang Dun | Agricultural Machinery | Best Researcher Award

Associate professor at  Intelligent Agricultural Machinery Equipment Engineering Laboratory, Harbin Cambridge College, China

Dr. Guoqiang Dun is a distinguished researcher in the field of intelligent agricultural machinery and equipment, with a focus on intelligent precision control sowing and fertilizing equipment, plot breeding machinery, special vegetable and herb sowing machinery, and computer simulation technology. He has authored over 40 papers in academic journals and holds more than 140 patents. In 2022, he was recognized as the first author in the “Leader 5000 – China’s Top Academic Papers in Excellence Journals (F5000)” and received the first prize in the National Agriculture, Animal Husbandry and Fisheries Harvest Award for Agricultural Technology Promotion Achievement. Dr. Dun has successfully led projects totaling nearly 600,000 RMB.

Profile:

📚 Academic and Professional Background:

Dr. Guoqiang Dun is an expert in intelligent agricultural machinery and equipment, specializing in intelligent precision control sowing and fertilizing equipment, plot breeding machinery, special vegetable and herb sowing machinery, and computer simulation technology. He has published over 40 papers and holds more than 140 patents. In 2022, he was recognized as a leading author in “Leader 5000 – China’s Top Academic Papers in Excellence Journals (F5000)” and received the first prize in the National Agriculture, Animal Husbandry and Fisheries Harvest Award. He has led projects worth nearly 600,000 RMB.

🛠️ Areas of Research:

  • Intelligent agricultural machinery and equipment
  • Intelligent precision control sowing and fertilizing equipment
  • Plot breeding machinery and equipment
  • Special vegetable and herb sowing machinery
  • Computer simulation technology

🚜 Research Focus in Agricultural Machinery:

Guoqiang Dun’s research in agricultural machinery encompasses several key areas: Intelligent Precision Control Sowing and Fertilizing Equipment: Development of advanced sowing and fertilizing machinery with precision control mechanisms. Optimization of fertilizer apparatus using discrete element methods. Plot Breeding Machinery and Equipment: Design and improvement of machinery tailored for plot breeding to enhance efficiency and precision. Innovations in seed-metering wheels and specialized seed discharge devices. Special Vegetable and Herb Sowing Machinery: Creation of specialized machinery for sowing vegetables and herbs with specific requirements. Implementation of unique mechanisms to ensure precise sowing and uniform growth. Computer Simulation Technology: Utilization of computer simulations to optimize machinery design and functionality. Application of software like EDEM and SolidWorks for dynamic simulation and analysis of agricultural processes. Guoqiang Dun’s contributions have significantly advanced the field of agricultural machinery, leading to more efficient, precise, and innovative farming practices.

Citations:

  • Citations: 203
  • Documents Cited: 176
  • Total Documents: 20
  • h-index: 8 (View h-index graph)

Publication Top Notes:

  • Design and Experiment of Side-hung Seed-rowing Spoon Type Precision Seed Metering Device for Radish | 红萝卜侧面悬置排种勺式精量排种器设计与试验
  • Design and Experiment of an Electric Control Spiral-Pushing Feed Mechanism for Field Fertilizer Applicator
  • Optimization and Experiment of the Fertilizer Apparatus with Staggered Gears | 错排齿轮式排肥器优化与试验
  • Simulation Optimization and Experiment of Screw Extrusion Precision Fertilizer Ejector | 螺旋挤压式精量排肥器的仿真优化及试验
  • Optimization Design and Experiment for Precise Control Double Arc Groove Screw Fertilizer Discharger
  • Design and Trajectory Simulation Reliability Analysis of a Self-propelled Strawberry Applicator | 自走式草莓施药机设计与轨迹仿真可靠性分析
  • Optimal Design and Experiment of Corn-Overlapped Strip Fertilizer Spreader
  • Optimization Design and Experiment of Oblique Opening Spiral Precision Control Fertilizer Apparatus | 斜口螺旋精控排肥器优化设计与试验
  • Optimization Design and Experiment of Alternate Post Changing Seed Metering Device for Soybean Plot Breeding | 交替换岗式大豆小区育种排种器优化设计与试验
  • Optimal Design and Experiment of Arc-groove Double-spiral Fertilizer Discharge Device | 弧槽双螺旋式排肥器优化设计与试验

 

 

Liang He | Agronomy | Best Researcher Award

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Prof Liang He | Agronomy | Best Researcher Award

dean at  Xinjiang university, China

Dr. He Liang, born in December 1981, is a distinguished professor and serves as the Executive Vice Dean of the School of Computer Science and Technology, as well as the Dean of the School of Intelligence Science and Technology at Xinjiang University. He holds a Ph.D. in Artificial Intelligence and specializes in temporal sequence signal processing, knowledge graphs, and reinforcement learning.

Profile:

Educational Background:

  • Qualification: PhD
  • Specialization: Artificial Intelligence
  • Sub-Division: Knowledge Graphs, Reinforcement Learning

Professional Experience and Achievements:

Dr. He Liang serves as the Executive Vice Dean of the School of Computer Science and Technology and Dean of the School of Intelligence and Science and Technology at Xinjiang University. With a focus on temporal sequence signal processing, knowledge graphs, and reinforcement learning, he has led over 20 scientific research projects and published over 100 academic papers in prestigious journals and conferences, including Nature Communication, IEEE Trans on ASLP, and ICASSP.

He is a well-regarded reviewer for several international journals and conferences such as IEEE Audio, Speech and Language Processing, and Pattern Recognition. Dr. Liang’s contributions to research have earned him over 1000 citations in Scopus/Web of Science.

Research and Development Contributions:

Dr. Liang has made significant contributions to the study of drought stress resistance in cotton plants, exploring optimal irrigation methods to improve yield and conserve water. His research has shown a strong correlation between deficit irrigation and improved cotton yield, leading to optimized irrigation schemes that benefit local agriculture.

Agronomy Research Focus:

Dr. He Liang has directed a significant portion of his research towards addressing agronomic challenges, particularly in the context of arid regions. His work primarily focuses on optimizing agricultural practices through advanced data-driven methodologies and artificial intelligence.

Citations:

  • H-Index: 25 (Total), 24 (Since 2019)
  • i10-Index: 66 (Total), 61 (Since 2019)
  • Total Citations: 2352 (Total), 1836 (Since 2019)

 

Publication Top Notes:

  • Applications of Chemical Vapor Generation in Non-Tetrahydroborate Media to Analytical Atomic Spectrometry
    • Year: 2010
    • Citations: 202
  • Large Margin Softmax Loss for Speaker Verification
    • Year: 2019
    • Citations: 163
  • The Trans-Omics Landscape of COVID-19
    • Year: 2021
    • Citations: 88
  • Speaker Embedding Extraction with Phonetic Information
    • Year: 2018
    • Citations: 77
  • Evaluation of Tungsten Coil Electrothermal Vaporization-Ar/H2 Flame Atomic Fluorescence Spectrometry for Determination of Eight Traditional Hydride-Forming Elements and Cadmium
    • Year: 2008
    • Citations: 55
  • Dynamics and Correlation Among Viral Positivity, Seroconversion, and Disease Severity in COVID-19: A Retrospective Study
    • Year: 2021
    • Citations: 53
  • Enhance Prototypical Network with Text Descriptions for Few-Shot Relation Classification
    • Year: 2020
    • Citations: 53
  • Simultaneous Utilization of Spectral Magnitude and Phase Information to Extract Supervectors for Speaker Verification Anti-Spoofing
    • Year: 2015
    • Citations: 52