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Early stage sugarcane biomass accumulation prediction by proximal sensing and crop parameters

Published online by Cambridge University Press:  01 June 2017

M. G. Rocha ,
L. R. Amaral  and
C. F. M. Dencowski
M. G. Rocha*
Affiliation:
University of Campinas – School of Agricultural Engineering, São Paulo, Brazil
L. R. Amaral
Affiliation:
University of Campinas – School of Agricultural Engineering, São Paulo, Brazil
C. F. M. Dencowski
Affiliation:
National University of the East – School of Agronomic Engineering, Minga Guazú, Paraguay
*
†E-mail: murillo.rocha@feagri.unicamp.br
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Abstract

Due to the lack of reliable yield monitor for sugarcane, production factors which impact and limit stalk yield within fields are not well-known. Thus, this study aims to evaluate whether canopy sensor technology is able to identify sugarcane biomass variability and whether obtaining other agronomic variable data can assist on biomass quantification. For that, forty targeted plots were allocated within two sugarcane-producing fields and data consisted on manual biometric evaluation, aboveground biomass measurement and canopy reflectance. As an ongoing experiment, only two evaluations were addressed (~0.3 and 0.5 m stalk height). On the earliest stage, canopy sensor readings were correlated to sugarcane biomass and their sensitivity to biomass variability was high. Further, data collected on the first evaluation was efficient in predicting biomass amount after 30 days. On the second, canopy sensor readings effectiveness to predict biomass was reduced. These findings suggest that crop canopy reflectance sensing is a useful approach to investigate sugarcane biomass spatial-variability within fields on early stages.

Keywords

NDVINDREcanopy sensorreflectanceagronomic variables
Type
Crop Sensors and Sensing
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 216 - 219
Copyright
© The Animal Consortium 2017 

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