Nadia Shakoor

Donald Danforth Plant Science Center

Papers

2

Total Citations

65

H-Index

2

About

Nadia Shakoor is a leading researcher at the intersection of plant science, big data, and agricultural technology, with a primary focus on high-throughput field phenotyping and its application to crop productivity. Her work is central to the emerging field of "Big Data Driven Agriculture," where she integrates advanced remote sensing, robotics, and cyberinfrastructure to revolutionize plant breeding and agronomy. Shakoor’s major contribution lies in developing and linking proximal and remote sensing technologies to capture complex plant traits—such as nighttime chlorophyll fluorescence—directly in the field, enabling more precise and scalable phenotyping than traditional methods. Her most-cited paper (2019, 59 citations) outlines a visionary framework for using big data analytics to accelerate genetic gains and address global food security challenges. More recently, her 2022 study on robotic field phenotyping platforms demonstrates her commitment to practical, automated solutions for dark-adapted plant imaging. With growing citation impact, Shakoor’s interdisciplinary approach is shaping the future of sustainable agriculture, making her a key figure for students and researchers interested in the convergence of biology, engineering, and data science.

Research Focus

Key Achievements

2
H-Index
2
Papers
65
Total Citations
33
Avg Citations/Paper
🏆 Most Cited Paper
Big Data Driven Agriculture: Big Data Analytics in Plant Breeding, Genomics, and the Use of Remote Sensing Technologies to Advance Crop Productivity
59 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Donald Danforth Plant Science Center

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago