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Remote Sensing for Monitoring Potato Nitrogen Status

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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.

Resumen

La papa (Solanum tuberosum L.) es uno de los cultivos alimenticios más consumidos en el mundo y juega un papel crítico en la salud humana y animal. El manejo adecuado del nitrógeno (N) es esencial para producir alto rendimiento de tubérculos y buena calidad, sin tener impactos perjudiciales en el medio ambiente. El monitoreo eficiente durante el ciclo del cultivo del estado de N de la planta puede guiar a los productores de papa a aplicar la cantidad correcta de fertilizante de N en el momento correcto. Los métodos analíticos tradicionales para el monitoreo son destructivos, requieren mucha mano de obra, requieren mucho tiempo y tienen una resolución espacio-temporal pobre. En comparación, las tecnologías de teledetección (RS) proporcionan evaluaciones no destructivas con capacidades para cubrir grandes áreas con alta resolución. El monitoreo RS emplea plataformas espaciales, aéreas y terrestres con sensores multiespectrales o hiperespectrales en los que se utilizan modelos físicos o basados en datos para predecir y mapear mediciones agronómicas o de plantas relevantes. Sin embargo, la mayor parte de la investigación sobre la aplicación de estas tecnologías al manejo del N de la papa es exploratoria y aún no está consolidada. Esta revisión incluye 109 manuscritos publicados previamente para proporcionar una revisión exhaustiva de las características de reflectancia de la papa, tres plataformas RS (espaciales, aéreas y terrestres) y dos tipos de sensores ópticos (multiespectrales o hiperespectrales), tres tipos de modelos que pueden predecir el estado de N de la papa utilizando datos espectrales, cómo se realiza el proceso de modelado, cómo RS puede contribuir a la aplicación precisa de N, y los desafíos y perspectivas futuras para las tecnologías RS que se aplicarán a la gestión comercial de N en papas. En general, RS tiene el potencial de ayudar a los productores de papa a comprender la variación espacio-temporal del estado de N de cultivo, y ajustar su aplicación de N para evitar el uso excesivo o innecesario de fertilizantes, de modo que eventualmente se pueda reducir la lixiviación de N y la contaminación del agua subterránea.

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  1. Department of Horticulture, University of Wisconsin – Madison, Madison, WI, 53706, USA

    Alfadhl Alkhaled & Yi Wang

  2. Department of Forest & Wildlife Ecology, University of Wisconsin – Madison, Madison, WI, 53706, USA

    Philip A. Townsend

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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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