Monitoring Crop Nitrogen Status with Satellite Data
Authored by Planet’s Product Subject Matter Expert Agriculture, Ariel Zajdband, PhD
Understanding crop nutrient status is key to optimizing fertilizer applications throughout the season. When it comes to nutrient status, managing crop health is often a delicate balance. In general, farmers and agronomists want to ensure crops are getting what they need to thrive, so their objective is to detect nutrient deficiencies that can result in yield and quality losses. But they are also careful to avoid over-fertilization, which can needlessly increase costs and raise plants’ susceptibility to diseases, pests, lodging, and weed competition.
At Planet, we’re excited that recent research is showing how satellite data can provide a reliable estimation of the crop nitrogen content. Those estimations are a vital piece of intelligence that can serve as the basis for nutrient management programs.
The Old Way
Farmers and agronomists often rely on tissue samples to monitor crop nutrient status. Tissue sampling requires the collection of at least 20 samples from each field. Depending on the crop and the growth stage, different plant parts are collected and shipped to laboratories for chemical analysis. The frequency of sampling depends on the crop. For example, in potatoes it is a common practice to sample each field weekly for six weeks (from 45 to 90 days after planting). Because of its relatively high cost (between $15–20 per sample), only 1 to 2 composite samples are analyzed.
Results from the lab are compared to “sufficiency values” established by university research. These are tables that show healthy ranges for specific crops and growth-stages. For instance, in the case of wheat at the tillering stage, the whole aboveground plant must be sampled. The sufficiency range at this stage indicates that 3.8 to 5% of the plant’s mass is made up of nitrogen. If the result from the lab is below this range, the wheat crop is considered to be “deficient” in nitrogen, and if the values are above 5%, the plant has accumulated nitrogen in excess of what’s needed — so called “luxury” nitrogen.
While tissue sampling provides a diagnostic for a wide range of nutrients, it is an imperfect solution. It’s an expensive and time-consuming process that only provides results from the locations where the samples were taken. In addition, sufficiency tables are generally based on research conducted decades ago, based on hybrids with very different nutritional requirements than the ones used today. Besides, the relationship between growth stage and nitrogen content is based on assumptions that are not always present in the field.
Nitrogen Nutrition Index, An Updated Measurement
An alternative approach to crop nitrogen status is based on the relationship between nitrogen content and crop biomass (Gastal et al. 2015). This relationship is commonly known as the nitrogen dilution curve and it is explained by the increase in proportion of structural tissue (with a lower nitrogen content) with the increase in dry biomass. In other words, the more each plant grows, the less overall nitrogen will be present in its tissue. The minimum nitrogen content (%N) that does not limit yield is known as the “critical nitrogen” for each level of biomass (Figure 1). These values of critical nitrogen are considered optimal from a crop nitrogen status perspective.
The Nitrogen Nutrition Index (NNI) is the ratio between the percentage of nitrogen in the crop and the critical nitrogen concentration for the same level of crop biomass. In other words, when the NNI equals 1, nitrogen nutrition is considered optimal, while an NNI measurement greater than or less than 1 indicates excess and deficient nitrogen nutrition, respectively.
In the end, physically measuring NNI is a more broadly useful approach than tissue sampling, but turns out to be even more time-consuming and expensive. The process requires a measurement of biomass in addition to the analysis of nitrogen concentration.
Satellite Data and Remote Measurement of NNI
What’s exciting for Planet is that remote sensing can provide accurate estimates of NNI by using different, non-correlated vegetation indices. Research led by Carolina Fabbri estimated the two variables (biomass and nitrogen concentration) using the Modified Chlorophyll Absorption in Reflectance Index (MCARI) and the Enhanced Vegetation Index (EVI2). These two indices use a combination of the NIR, red, red-edge and green bands.
The red-edge band in Planet’s SuperDove constellation will enable agronomists and farmers to receive a daily update on the crop nitrogen status of their crops. This technology provides a better diagnostic tool, reduces costs associated with physical sampling, and facilitates corrective nutrient applications, especially important given that application windows are narrowing. Having a better understanding of the crop nitrogen status is key to increase the nitrogen use efficiency in agricultural systems.