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Integration of ultrasonic and optical sensing systems to assess sugarcane biomass and N-uptake.

Authors :
Portz, G.
Molin, J. P.
Canata, T. F.
Adamchuk, V. I.
Source :
Precision Agriculture. Feb2024, Vol. 25 Issue 1, p83-99. 17p.
Publication Year :
2024

Abstract

Crop canopy optical reflectance and ultrasonic sensors provide a means of estimating the spatial variability of biomass and nitrogen uptake by sugarcane during the in-season period. The objective of this paper is to assess the crop canopy reflectance and ultrasonic crop height for predicting sugarcane biomass and N-uptake until the later fertilization stages. An ultrasonic sensor was deployed to measure canopy height, which were combined with optical reflectance sensor to characterize the spatial variability of the crop growth in four commercial fields in southeast Brazil during three different growing stages for dry and wet seasons. Ten sampling location points in each field were defined to determine plant biomass and N-uptake through traditional measurements. The points in each field were used to relate the actual biomass and N-uptake with the sensor data and compare them using the coefficient of determination and standard errors; this defined the best approach in each situation according to the multivariable statistics. It was found that both sensor systems enable to correlate its data with sugarcane biomass and N-uptake. Canopy reflectance sensor produced a better assessment of crop growth at the earlier growth stage whereas the ultrasonic sensor resulted in more accurate predictions at the later growing stages. It was proven that canopy height is season dependent whereas the reflectance data is growth stage dependent. The integration of both sensing systems improved the predictions of sugarcane biomass and N-uptake. It could be an alternative to guide local interventions by sugarcane industry during the growing season. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13852256
Volume :
25
Issue :
1
Database :
Academic Search Index
Journal :
Precision Agriculture
Publication Type :
Academic Journal
Accession number :
174712304
Full Text :
https://doi.org/10.1007/s11119-023-10059-z