Utilization of Spectral Indices for High-Throughput Phenotyping.

Area of Science:

• Agricultural Science
• Plant Breeding
• Remote Sensing

Background:

• Conventional plant breeding faces challenges in precisely and rapidly evaluating large sets of plant phenotypes.
• High-throughput phenotyping (HTP) technologies are crucial for developing genetically improved crops.
• Advancements in remote sensing and artificial intelligence have led to the development of various vegetation indices (VIs).

Purpose of the Study:

• To provide an overview of vegetation indices (VIs) used in agricultural research for crop evaluation.
• To highlight the importance of VIs in crop research, precision agriculture, and HTP.
• To discuss recent technologies like photogrammetry, mapping, and GIS integrated with UAVs for HTP.

Main Methods:

• Review of various vegetation indices (VIs) commonly used in crop and vegetation evaluation.
• Integration of VI-based imaging with artificial intelligence and remote sensing applications.
• Exploration of photogrammetry, mapping, and GIS software combined with unmanned aerial vehicles (UAVs).

Main Results:

• VIs offer high-throughput evaluations for precision agriculture, analyzing vegetation's quantitative and qualitative aspects.
• VIs show a linear relationship with crop output, useful for predicting chlorophyll, health, moisture, and production.
• Integrated UAV, photogrammetry, and GIS technologies enhance HTP capabilities for crop assessment.

Conclusions:

• HTP technologies, particularly VI-based approaches, are vital for efficient and accurate crop breeding.
• The integration of advanced technologies like UAVs and GIS provides powerful tools for precision agriculture.
• Future research should focus on developing new tools and data-driven HTP solutions for assessing agronomic traits and advancing precision breeding.