Prediction and Classification of Energy Content in Growing Cane Stalks for Breeding Programmes Using Visible and Shortwave Near Infrared
Author:
Funder
royal golden jubilee (rgj) ph.d. programme
Publisher
Springer Science and Business Media LLC
Subject
Agronomy and Crop Science
Link
https://link.springer.com/content/pdf/10.1007/s12355-021-01075-2.pdf
Reference49 articles.
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2. Biancolillo, Alessandra, Ingrid Måge, and Tormod Næs. 2015. Combining SO-PLS and linear discriminant analysis for multi-block classification. Chemometrics and Intelligent Laboratory Systems 141. Elsevier B.V.: 58–67. https://doi.org/10.1016/j.chemolab.2014.12.001.
3. Bocci, E., A. Di Carlo, and D. Marcelo. 2009. Power plant perspectives for sugarcane mills. Energy 34: 689–698. https://doi.org/10.1016/j.energy.2009.02.004.
4. Bureau of sugar experiment stations. 2014. Laboratory manual for Australian sugar mills. Australia.
5. Carvalho-Netto, Osmar V., Jose A. Bressiani, Hugo L. Soriano, Celso S. Fiori, Joao M. Santos, Geraldo Vs Barbosa, Mauro A. Xavier, Marcos Ga Landell, and Goncalo Ag Pereira. 2014. The potential of the energy cane as the main biomass crop for the cellulosic industry. Chemical and Biological Technologies in Agriculture 1: 1–8. https://doi.org/10.1186/s40538-014-0020-2.
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