Bioenergy offers a sustainable alternative to fossil fuels, addressing energy security and
climate change concerns. This paper reviews the current landscape of machine learning …

Agriculture produce especially sugarcane crop is no exception to diseases as compared to
the other crops. Sugarcane diseases can be mitigated more successfully if they are …

This study was conducted at the Experimental Garden of the Faculty of Agriculture, Islamic
University of North Sumatra, Jalan Karya Wisata, Gedung Johor Village, Medan Johor Sub …

The integration of remote sensing (RS) technology with machine learning (ML) algorithms
can facilitate accurate prediction of sugarcane yield. This paper presents an assessment of …

The impending surge in the global population necessitates innovative approaches that
leverage advanced technologies and data-driven methodologies to maintain food security …

Agriculture is a vital element that contributes significantly to feeding the world's growing
population. Agricultural crop classification based on various parameters can assist farmers …

In the agricultural domain, sugarcane crops, like many others, are susceptible to diseases,
posing a significant threat to both quality and quantity of production. Identifying and …

Abstract Crop production in Tamil Nadu, India, is influenced by various factors including soil
type, climate, and agricultural practices. This study presents a comparative analysis of crop …

This study investigates how machine learning (ML) algorithms can be used in agriculture to
forecast soil fertility and maximize crop yield. Machine learning (ML) models are created to …

The agricultural sector is evolving towards the transformative Agriculture 4.0 model, driven
by advancements in machine learning, big data, and remote sensing. This study aims to …