Remote Sensing for Monitoring Potato Nitrogen Status

Abstract

Potato (Solanum tuberosum L.) is one of the most consumed food crops in the world and plays critical roles in human and animal health. Proper nitrogen (N) management is essential to producing high tuber yield and good quality while not having detrimental impacts on the environment. Efficient in-season monitoring of plant N status can guide potato growers to apply the right amount of N fertilizer at the right time. The traditional analytical methods for monitoring are destructive, labor-intensive, time-consuming, and have poor spatio-temporal resolution. In comparison, the remote sensing (RS) technologies provide non-destructive assessments with capabilities to cover large areas with high resolution. RS monitoring employs spaceborne, airborne, and ground-based platforms with multispectral or hyperspectral sensors in which physically-based or data-driven models are used to predict and map relevant plant or agronomic measurements. However, most of the research on application of these technologies to potato N management is exploratory and not yet mature. This paper reviews 109 previously published manuscripts to provide a comprehensive review of potato reflectance characteristics, three RS platforms (spaceborne, airborne, and ground-based) and two types of optical sensors (multispectral or hyperspectral), three types of models that can predict potato N status using spectral data, how the modeling process is performed, how RS can contribute to precision N application, and challenges and future outlooks for RS technologies to be applied to commercial N management in potatoes. Overall, RS has the potential for assisting potato growers with understanding the spatio-temporal variation of their crop N status, and fine-tuning their N application to avoid excessive or unnecessary use of fertilizer, so eventually N leaching and groundwater contamination can be reduced.