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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

“…Due to this developing significance of crop yield prediction, this article provides an exhaustive review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction. …”
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Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli by Mohd Ramli, Mohamad Amirul Asyraf

“…This study focuses on using Python for remote sensing data analysis to identify and classify healthy crops. By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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GIS-Enhanced Crop Yield Modeling with Machine Learning by Venkatesh, S.D., Chitra, K., Harilakshami, V.M.

“…To address these issues, we have developed a system using machine learning algorithms aimed at helping farmers. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Extreme gradient boosting (XGBoost) regressor and shapley additive explanation for crop yield prediction in agriculture by Dennis A/L Mariadass, Ervin Gubin Moung, Maisarah Mohd Sufian, Ali Farzamnia

“…The implementation of the suggested model is extensively evaluated using the Shapley Additive Explanation (SHAP) to discover the essential features such as average temperature, average rainfall, and pesticide in the crop yield prediction. The estimates provided by machine learning algorithms will aid farmers in deciding what to grow because of this research.…”
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Smart agriculture: precision farming through sensor-based crop monitoring and control system by Mohamad Hakhrani, Asyful Azhim, Abdul Hamid, Syamsul Bahrin

“…Notably, prevalent smart agriculture systems predominantly emphasize either IoT components for data monitoring and control or machine learning components for data analysis. Consequently, this project endeavours to develop a system that seamlessly integrates both IoT and machine learning components, culminating in an advanced system capable of real-time crop monitoring and growth prediction. …”
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Chili crop segregation system design and development strategies by Wan Daud, Wan Mohd Bukhari, Abdul Aziz, Mohd Fareezuan, Ahmad Izzuddin, Tarmizi, Norasikin, Mohd Adili, Abdul Rasid, Ahmad Fuad, Wakhi Anuar, Nur Farah Bazilah, M. N. Sukhaimie

“…The image data taken from chili samples can be trained by using Learning Algorithm in the MATLAB program. The performance of the trained network then can be evaluated by using the Confusion Matrix technique. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…Integrating SSA and SVM machine learning algorithms improves decision-making processes, leading to better crop yield through early detection and timely nutrient management. …”
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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

“…This paper presents our work on developing an intelligent system for predicting crop yield, for example oil-palm yield, from climate and plantation data. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

“…A machine learning algorithms, SVM have been used to build species identification models. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. …”

Cornsense: leaf disease detection application / Iffah Fatinah Mohamad Nasir by Mohamad Nasir, Iffah Fatinah

“…The purpose of this project is to develop a mobile application for corn leaf disease detection leveraging the YOLOv8 (You Only Look Once version 8) object detection algorithm. …”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

“…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

“…The project used Back-propagation Neural Network for the algorithm to classified images. Images that capture using digital camera will perform through the algorithm to classified images. …”
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AUTOMATED PLANT DISEASE DETECTION USING DEEP LEARNING ON MOBILE PLATFORM by Vera Ruth, Rewcastle

“…Therefore, this project aims at developing a mobile applicatiJ:;m which is equipped with deep learning algorithm to enable the detection and identification of a disease for a particular plant. …”
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New approach for sugarcane disease recognition through visible and near-infrared spectroscopy and a modified wavelength selection method using machine learning models by Pauline Ong, Pauline Ong, Jinbao Jian, Jinbao Jian, Xiuhua Li, Xiuhua Li, Chengwu Zou, Chengwu Zou, Jianghua Yin, Jianghua Yin, Guodong Ma, odong Ma

“…The proliferation of pathogenic fungi in sugarcane crops poses a significant threat to agricultural productivity and economic sustainability. …”
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Support vector machine in precision agriculture: a review by Kok, Zhi Hong, Mohamed Shariff, Abdul Rashid, M. Alfatni, Meftah Salem, Bejo, Siti Khairunniza

“…The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which may be used for acquiring solutions towards better crop management. …”
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An annotated image dataset of pests on different coloured sticky traps acquired with different imaging devices by Song-Quan Ong, Toke Thomas Høye

“…The images were sorted by device, colour and species and divided into training, validation and test parts for the development of the deep learning model…”
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi

“…This analysis involved the implementation of machine learning (ML) algorithms, including decision trees, random forests, and stacking, to classify soybean FLS severity levels. …”
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