Plant nutrient content reflects their overall metabolic health and has a direct impact on plant growth, development, and reproduction. Nonstructural carbohydrates (NSCs), for example, are a type of temporary storage for carbohydrates that accumulate in trees and are thought to be indicative of plant carbon availability and supply. Nitrogen (N), a primary component of proteins, chlorophyll, nucleic acids, and vitamins, is required for photosynthesis product storage and transport. However, monitoring these nutrients in trees manually or using traditional methods takes a significant amount of time and effort. This necessitates the development of new, modern, and time-saving approaches to assist plant scientists in extracting maximum information in the shortest amount of time.

To this end, a group of researchers from China and New Zealand, including Assistant Professor Yanjie Li from the Chinese Academy of Forestry, have recently utilized artificial intelligence (AI) for the real-time monitoring of N and NSC in the leaves of pine needles. The team used unmanned aerial vehicles (UAVs) or drones to perform imaging studies on pine trees, while flying past their canopy. By combining advanced spectroscopic analysis techniques, advanced statistics, and machine learning algorithms, this new approach can provide information about the biochemical properties, growth rate, health and development status, and genetic variations of these trees. The study was published online in the journal Plant Phenomics on 15 March 2023.

“UAV-based remote sensing is nondestructive, high throughput, and quick. It is an efficient …