The Next-Gen Crop Nutrient Stress Identification with High-Precision Sensing Technology in Digital Agriculture (original) (raw)

Abstract

Crop yields are facing significant losses from nutrient deficiencies. Over-fertilizing also has negative economic and environmental impacts. It is challenging to optimize fertilizing without an accurate diagnosis. Recently, plant phenotyping has demonstrated outstanding capabilities in estimating crop traits. As one of the leading technologies, LeafSpec, provides high-quality crop image data for improving phenotyping quality. In this study, novel algorithms are developed for LeafSpec to identify crop nutrient deficiencies more accurately. Combined with UAV system, this technology will bring growers a robust solution for fertilizing diagnosis and scientific crop management.

Start Date

2-3-2023 3:00 PM

Song, Zhihang; Chen, Ziling; Wei, Xing; and Jin, Jian, "The Next-Gen Crop Nutrient Stress Identification with High-Precision Sensing Technology in Digital Agriculture" (2023). Graduate Industrial Research Symposium. 10.
https://docs.lib.purdue.edu/girs/2023/posters/10

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The Next-Gen Crop Nutrient Stress Identification with High-Precision Sensing Technology in Digital Agriculture

Purdue University, ABE

Crop yields are facing significant losses from nutrient deficiencies. Over-fertilizing also has negative economic and environmental impacts. It is challenging to optimize fertilizing without an accurate diagnosis. Recently, plant phenotyping has demonstrated outstanding capabilities in estimating crop traits. As one of the leading technologies, LeafSpec, provides high-quality crop image data for improving phenotyping quality. In this study, novel algorithms are developed for LeafSpec to identify crop nutrient deficiencies more accurately. Combined with UAV system, this technology will bring growers a robust solution for fertilizing diagnosis and scientific crop management.