Raman spectroscopy for nutritional stress detection in plant vascular tissue

Next-generation agriculture must address its high energy-intensive resource utilization footprint such as excessive use of fertilizer and water. Plants are also sources of natural polymers (cellulose, lignin, and pectin) that have important implications in sustainable materials design. Hence healthy plant growth with optimum utilization and production is essential for future growth, which demands new technologies and sensors for on-field precision agriculture. Here we used Raman spectroscopy (RS) to non-invasively monitor soybean development, a plant of immense economic importance for fuel, feed, and food. We focus on its compositional changes at multiple time points as it transitions from the vegetative (or rapid growth) to the reproductive (or flowering) stage subjected to nitrogen and nutrient stress to identify several indicators of health. The longitudinal growth was severely limited under total nutritional stress. Simultaneously, the cell wall showed early lignification to control growth and allow for efficient transport of limited resources. Healthier plants showed activation of early defense mechanisms via tetraterpenes, greater protein production capacity via glutamic acid, and late lignification by week 12. Nitrogen stressed plants also showed stunted growth though they showed a similar defense mechanism and later lignification as the healthy condition. These differences in the concentrations of structural polymers, stress signaling molecules, and structural growth inhibitors at different time points and variable stress demonstrated the suitability of Raman spectroscopy for precision plant health monitoring. Development such as the current study is a step towards creating tools, devices, and computational models for next-generation farming.

Automated summary

Next-generation agriculture needs to address energy-intensive resource utilization and optimize plant growth. This study used Raman spectroscopy to monitor soybean development and identified indicators of plant health under different stress conditions. The results demonstrate the suitability of Raman spectroscopy for precision plant health monitoring.