PREDICTIVE MODELS OF CHLOROPHYLL CONTENT IN SUGARCANE SEEDLINGS USING SPECTRAL IMAGES-Reference-Cited by-同舟云学术

PREDICTIVE MODELS OF CHLOROPHYLL CONTENT IN SUGARCANE SEEDLINGS USING SPECTRAL IMAGES

Published:2021-08 Issue:4 Volume:41 Page:475-484
ISSN:1809-4430
Container-title:Engenharia Agrícola
language:
Short-container-title:Eng. Agríc.

Author:

Oliveros Nelson,Tinini Rodolpho¹,Costa Daniel dos S.²,Ramos Rodrigo²,Wetterich Caio³,Teruel Bárbara^ORCID

Affiliation:

1. Federal University of Minas Gerais, Brazil

2. Federal University of the São Francisco Valley, Brazil

3. Federal Institute of Triangulo Mineiro, Brazil

Publisher

FapUNIFESP (SciELO)

Subject

Agricultural and Biological Sciences (miscellaneous)

Reference29 articles.

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3. Development of pre-sprouted seedlings (PSS) of sugarcane under different amounts of filter cake and application modes;Aquino GS;Ciências Agrárias,2018

4. Use of a digital camera as alternative method for non-destructive detection of the leaf chlorophyll content and the nitrogen nutrition status in wheat;Beresel JP;Computers and Electronics in Agriculture,2017

5. Water stress reveals differential antioxidant responses of tolerant and non-tolerant sugarcane genotypes;Boaretto LF;Plant Physiology and Biochemistry,2014

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1. Simultaneous retrieval of sugarcane variables from Sentinel-2 data using Bayesian regularized neural network;International Journal of Applied Earth Observation and Geoinformation;2023-02