The future of potato production: Remote Sensing for Nitrogen Status Assessment
by Jorge Luis Alonso with ChatGPT-4
Recognized as an important global food crop, potatoes require proper nitrogen management for high yields and environmental sustainability. However, traditional nitrogen monitoring methods are laborious, destructive and lack resolution. In contrast, remote sensing (RS) technologies provide non-destructive, high-resolution coverage over large areas.
These RS technologies, which employ a variety of platforms and sensors, use physical or data-driven models to predict crop measurements. Despite its significant potential, current research on RS for potato nitrogen management is still exploratory and immature.
To fill this gap, this study, conducted by the University of Wisconsin — Madison and published in the American Journal of Potato Research, plunges headlong into a comprehensive exploration of RS technologies. It charts their application in monitoring in-season crop nitrogen (N) status and predicting potato tuber yields, boldly identifying limitations while optimistically envisioning the future of RS in commercial potato production.
Specifically, it outlines three dynamic RS platforms: space-based, airborne and ground-based. The ground-based platform, characterized by handheld sensors, is often the first choice due to its affordability and adaptability. However, the labor and time required make it less suitable for large-scale commercial deployments.
On the other hand, airborne and spaceborne platforms offer exciting potential for large-scale, high-resolution scanning. However, these platforms face challenges, such as reliance on clear weather conditions and potentially high costs.
Regarding analytical models, parametric regression models using vegetation indices collected by multispectral sensors are the primary algorithms used in 58% of the reviewed papers. In addition, nonlinear nonparametric regressions such as partial least squares regression (PLSR) and other machine learning models are gaining popularity for dealing with hyperspectral data that exhibit high multicollinearity.
Looking toward the future, it becomes evident that research should concentrate on enhancing the speed, accuracy, and simplicity of RS technologies. The overarching goal is to provide growers with immediate, in-field guidance to help them understand the variability of their crop’s N status and plan precision fertilizer management. As a result, growers can tailor their N applications to minimize the potential for leaching and groundwater contamination.
The paper concludes by emphasizing the need for collaboration and on-farm trials with growers. The goal is to encourage wider adoption of RS technologies, as the future of agriculture may depend on the successful integration of these powerful tools.
Source: Alkhaled, A., Townsend, P.A. & Wang, Y. Remote Sensing for Monitoring Potato Nitrogen Status. Am. J. Potato Res. 100, 1–14 (2023). https://doi.org/10.1007/s12230-022-09898-9
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