ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SUGARCANE STALK AND TOTAL BIOMASS YIELD BASED ON MICRONUTRIENT RATES APPLIED IN THE PLANTING FURROW AND TO THE LEAVES

ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SUGARCANE STALK AND TOTAL BIOMASS YIELD BASED ON MICRONUTRIENT RATES APPLIED IN THE PLANTING FURROW AND TO THE LEAVES

ABSTRACT Sugarcane is pivotal in the global bioeconomy, providing a renewable resource for products such as ethanol, sugar, bioenergy, animal feed, and bioplastics. Its versatility makes it an essential crop for industries seeking sustainable alternatives to fossil fuels. This study presents an adva...

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Bibliographic Details
Main Authors: Alfredo Bonini Neto, Maikon V. da Silva Lira, Guilherme C. Meirelles, Luiz F. de M. Santos, Carolina dos S. B. Bonini, Reges Heinrichs
Format: Article
Language:English
Published: Sociedade Brasileira de Engenharia Agrícola 2025-04-01
Series:Engenharia Agrícola
Subjects:
artificial intelligence
predicting
fertilization
micronutrients
sugarcane
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162025001000301&lng=en&tlng=en
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