A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction

M Rashid, BS Bari, Y Yusup, MA Kamaruddin… - IEEE …, 2021 - ieeexplore.ieee.org
An early and reliable estimation of crop yield is essential in quantitative and financial
evaluation at the field level for determining strategic plans in agricultural commodities for …

Proximal hyperspectral sensing of abiotic stresses in plants

A Sanaeifar, C Yang, M de la Guardia, W Zhang… - Science of The Total …, 2023 - Elsevier
Recent attempts, advances and challenges, as well as future perspectives regarding the
application of proximal hyperspectral sensing (where sensors are placed within 10 m above …

Synthetic Minority Over-sampling TEchnique (SMOTE) and Logistic Model Tree (LMT)-Adaptive Boosting algorithms for classifying imbalanced datasets of nutrient and …

AD Amirruddin, FM Muharam, MH Ismail… - … and Electronics in …, 2022 - Elsevier
The conventional method to quantify leaf biochemical properties (nutrients and chlorophylls)
is tedious, labour-intensive, and impractical for vast oil palm plantation areas. Spectral …

Detecting coffee leaf rust with UAV-based vegetation indices and decision tree machine learning models

DB Marin, LS Santana, BDS Barbosa… - … and Electronics in …, 2021 - Elsevier
Coffee leaf rust (CLR) is one of the most devastating leaf diseases in coffee plantations. By
knowing the symptoms, severity, and spatial distribution of CLR, farmers can improve …

On supervised class-imbalanced learning: An updated perspective and some key challenges

S Das, SS Mullick, I Zelinka - IEEE Transactions on Artificial …, 2022 - ieeexplore.ieee.org
The problem of class imbalance has always been considered as a significant challenge to
traditional machine learning and the emerging deep learning research communities. A …

Oil palm and machine learning: Reviewing one decade of ideas, innovations, applications, and gaps

N Khan, MA Kamaruddin, UU Sheikh, Y Yusup… - Agriculture, 2021 - mdpi.com
Machine learning (ML) offers new technologies in the precision agriculture domain with its
intelligent algorithms and strong computation. Oil palm is one of the rich crops that is also …

[HTML][HTML] Expert systems in oil palm precision agriculture: A decade systematic review

XJ Tan, WL Cheor, KS Yeo, WZ Leow - Journal of King Saud University …, 2022 - Elsevier
Abstract Oil palm (Elaeis guineensis Jacq.) is of the most profitable and widespread
commercial high tree crops in the tropical world, typically in Southeastern Asia. The present …

Review–Plant nutritional status analysis employing the visible and near-infrared spectroscopy spectral sensor

SADM Zahir, MF Jamlos, AF Omar, MA Jamlos… - … Acta Part A: Molecular …, 2024 - Elsevier
Experiments demonstrated that visible and near-infrared (Vis-NIR) spectroscopy is a highly
reliable tool for determining the nutritional status of plants. Although numerous studies on …

Machine Learning in the Classification of Soybean Genotypes for Primary Macronutrients' Content Using UAV–Multispectral Sensor

DC Santana, MCM Teixeira Filho, MR da Silva… - Remote Sensing, 2023 - mdpi.com
Using spectral data to quantify nitrogen (N), phosphorus (P), and potassium (K) contents in
soybean plants can help breeding programs develop fertilizer-efficient genotypes …

Oil palm yield estimation based on vegetation and humidity indices generated from satellite images and machine learning techniques

F Watson-Hernández, N Gómez-Calderón, RP da Silva - AgriEngineering, 2022 - mdpi.com
Palm oil has become one of the most consumed vegetable oils in the world, and it is a key
element in profitable global value chains. In Costa Rica, oil palm cultivation is one of the …