Dilawar Abbas | Agricultural | Research Excellence Award

Dr. Dilawar Abbas | Agricultural | Research Excellence Award

Chinese Academy of Agricultural Sciences | China

Dilawar Abbas is an emerging researcher in agricultural and insect sciences whose work integrates biological control, integrated pest management (IPM), insect ecology, and applied entomology to address critical challenges in sustainable crop protection. His research spans insect behavior and interactions, physiology, morphology, taxonomy, molecular biology, toxicology, and the application of entomopathogenic nematodes, with a strong emphasis on environmentally responsible pest management strategies. He has conducted laboratory-based investigations on insect diapause intensity and overwintering survival, combining physiological, biochemical, and molecular approaches to elucidate mechanisms of cold tolerance and diapause regulation in major agricultural pests. Complementing this experimental work, his applied research experience includes field-based pest identification, monitoring, and management across diverse cropping systems, contributing to a comprehensive understanding of IPM implementation under real agricultural conditions. This integrated perspective bridges fundamental insect biology with practical pest control solutions aimed at improving crop yield, quality, and sustainability. His research outputs reflect growing scholarly impact, with 14 published documents that have received 19 citations across 17 citing documents and an h-index of 3, demonstrating early but meaningful contributions to the scientific literature. Collectively, his work highlights strong potential for continued innovation in sustainable pest management, ecological research, and biologically based control strategies within modern agricultural systems.

Citation Metrics (Scopus)

20
15
10
5
0

Citations
19

Documents
14

h-index
3

Citations

Documents

h-index

Climate-driven insect pest outbreaks and associated food security risks: adaptive strategies for resilient agricultural systems

– Review Article

Siran Wang | Agricultural | Research Excellence Award

Prof. Siran Wang | Agricultural | Research Excellence Award

Jiangsu Academy of Agricultural Sciences | China

Dr. Siran Wang is a leading researcher in animal nutrition and forage science whose work centers on improving silage quality, feed efficiency, and sustainable livestock production through microbial and fermentation-based innovations. His research focuses on forage processing and efficient utilization, screening and application of functional lactic acid bacteria, and the development and utilization of unconventional feed resources, with particular emphasis on enhancing nutritional value, safety, and stability of animal feeds. He has made substantial contributions to understanding microbial communities, fermentation mechanisms, and their practical application in silage systems, especially under diverse agro-ecological conditions. Dr. Wang plays an active academic service role across multiple high-impact journals, serving as section editor, early-career editorial board member, lead guest editor and guest associate editor for numerous international special issues and research topics related to agriculture, microbiology, fermentation, plant science, and animal science, several of which have resulted in large collections of published peer-reviewed papers. His editorial leadership reflects strong recognition within the scientific community for his expertise in silage microbiology and forage utilization. Dr. Wang has published 111 scientific documents, which have received 1,594 citations across 977 citing documents, and he holds an h-index of 21, highlighting the impact, consistency, and relevance of his research contributions to agricultural and animal science.

Citation Metrics (Scopus)

1600
1200
800
400
0

Citations
1,594

Documents
111

h-index
21

Citations

Documents

h-index

Application of Fermentation Technology in Animal Nutrition: Second Edition

– Fermentation
 

Biological delignification and anaerobic fermentation of wheat straw as a sustainable strategy for crop straw utilization

– Industrial Crops and Products
 

Effects of biological lignin depolymerization on rice straw enzymatic hydrolysis, anaerobic fermentation performance, and in vitro ruminal digestibility

– International Journal of Biological Macromolecules
 

Effects of biological and antifungal additives on ensiling quality, in vitro digestibility, gas production, and aerobic stability of fermented total mixed rations containing wet brewers’ grains

– Acta Prataculturae Sinica
 

Influence of growth stage and storage duration on fermentation traits, microbial community dynamics, functional shifts, and pathogenic risk in fermented Italian ryegrass

– LWT

Melih Altay | Agricultural | Young Researcher Award

Mr. Melih Altay | Agricultural | Young Researcher Award

Hacettepe University | Turkey

Melih Altay is a researcher in geomatics engineering with a strong specialization in photogrammetry, artificial intelligence, and remote sensing. His research is centered on integrating deep learning and machine learning methods with multi-source Earth observation data to address complex geospatial problems. He has developed and applied advanced AI-based segmentation, object detection, and classification approaches for analyzing optical and SAR satellite imagery, with particular emphasis on forest fire assessment, water surface detection, and agricultural land monitoring. His work contributes to improving the accuracy and automation of geospatial data extraction from high-resolution satellite platforms such as PlanetScope and Sentinel series. His research demonstrates strong interdisciplinary integration of GIS, remote sensing, and artificial intelligence, offering scalable solutions for environmental monitoring, land-use analysis, and spatial decision support. Through peer-reviewed conference publications, he has contributed comparative evaluations of deep learning architectures and innovative workflows that enhance geospatial analysis efficiency and reliability. Overall, his work reflects a forward-looking approach to geomatics engineering, emphasizing intelligent automation, high-resolution spatial analytics, and the practical application of AI technologies in Earth observation and digital twin systems.

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Phenology aware agricultural boundary extraction using segment anything model and planet scope imagery (zero shot learning approach)– Advances in Space Research