Stress is a physiological condition inhibiting plants from reaching their full genomic potential. Early detection of plant stress is vital for maintaining biomass and water absorption. Using multispectral technology, growers and researchers can effectively measure relative chlorophyll content and nitrogen status and identify infection focal points to prevent stress from damaging plants.
AGRON, an agricultural imagery analytics and drone services company in Hungary, has been evaluating such strategies using drone-based data since 2016. The details of a recent project focusing on wheat using the MicaSense series RedEdge-MX are described below.
The Technology
Using the MicaSense series RedEdge-MX to monitor plant physiological conditions, the AGRON team set out to pinpoint the first signs of stress within a wheat crop. AGRON researchers measured relative chlorophyll content for plant stress, identified areas low in nutrients, and detected infection focal points. The data collected was analyzed using their online platform, AGRONmaps.
Analyzing the Effects of Fertilizers in Plant Chlorophyll Levels
AGRON researchers analyzed the reaction of wheat to different levels of fertilizers throughout the vegetative season. RedEdge-MX not only allowed for easy identification of areas low in nutrients but also helped monitor the effects of fertilizer applications throughout the season and helped determine where new applications were necessary.
During the first experiment, AGRON collected seven datasets from fifteen wheat species with the Soil Plant Analysis Development (SPAD) Chlorophyll Meter and the RedEdge-MX. Treatments were adjusted based on intensive fertilizing methods available (0 > 280 kg/ha, 40 kg/ha steps between treatment) enabling calibration of chlorophyll measurements from long-range spectroscopy-based plant physiology research. As a result, it was possible to separate and evaluate nutrient-deficient plots (Figure 1). Some plots showed earlier signs of deficiency, so a species-specific aspect of the nutrient reaction was also studied.
To visualize differences between plots, AGRON used the Look Up Tables (LUT) or False Coloring methods. The color differences are basic indicators of crop health status. For example, differing colors inside the crop columns below show discrepancies among chlorophyll levels (Figure 1), with red spots indicating chlorophyll deficiency. With such data, AGRON can develop new indexes, such as the AGRON Chlorophyll Index.
Analyzing the Effects of Various Fungicides on Disease Management
AGRON researchers also analyzed the response of various types of wheat to fungicides, focusing on resistance against pathogens like powdery mildew (Blumeria graminis). This experiment included 42 winter wheat, 36 spelt wheat, 36 triticale, 36 barley, and 36 durum wheat. Some of these groups were treated with fungicide and others were not.
The lack of fungicide treatment in some groups led to severe infections of powdery mildew. Infected plants displayed white powdery-like spots. Using the RedEdge-MX, the team could mass identify infection focal points and see which plots contained susceptible species. The chlorophyll map below shows those resistant, (green) and those susceptible to the disease (yellow or red) (Figure 2).
Conclusion
With the data captured by the RedEdge-MX, AGRON is not only able to identify and monitor nutrient deficiency, but also to detect, treat, and analyze the response of wheat to pathogen infection. The success of such experiments proved the RedEdge-MX an effective tool for monitoring the physiological conditions of crops.
