[HTML][HTML] Integration of remote sensing and machine learning for precision agriculture: a comprehensive perspective on applications

J Wang, Y Wang, G Li, Z Qi - Agronomy, 2024 - mdpi.com
Due to current global population growth, resource shortages, and climate change, traditional
agricultural models face major challenges. Precision agriculture (PA), as a way to realize the …

Knowledge map** of machine learning approaches applied in agricultural management—a scientometric review with citespace

J Zhang, J Liu, Y Chen, X Feng, Z Sun - Sustainability, 2021 - mdpi.com
With the continuous development of the Internet of Things, artificial intelligence, big data
technology, and intelligent agriculture have become hot topics in agricultural science and …

Farm monitoring and disease prediction by classification based on deep learning architectures in sustainable agriculture

A Wongchai, D rao Jenjeti, AI Priyadarsini, N Deb… - Ecological …, 2022 - Elsevier
Agriculture is necessary for all human activities to survive. Overpopulation and resource
competitiveness are major challenges that threaten the planet's food security. Smart farming …

Corn grain yield prediction using UAV-based high spatiotemporal resolution imagery, machine learning, and spatial cross-validation

P Killeen, I Kiringa, T Yeap, P Branco - Remote Sensing, 2024 - mdpi.com
Food demand is expected to rise significantly by 2050 due to the increase in population;
additionally, receding water levels, climate change, and a decrease in the amount of …

Corn grain yield prediction using UAV-based high spatiotemporal resolution multispectral imagery

P Killeen, I Kiringa, T Yeap - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Food demand is expected to rise significantly by 2050 due to the increase in population;
additionally, receding water levels, climate change, and a decrease in the amount of …

Estimating coffee plant yield based on multispectral images and machine learning models

CAM Abreu Júnior, GD Martins, LCM Xavier, BS Vieira… - Agronomy, 2022 - mdpi.com
The coffee plant is one of the main crops grown in Brazil. However, strategies to estimate its
yield are questionable given the characteristics of this crop; in this context, robust …

Pre-Harvest Corn Grain Moisture Estimation Using Aerial Multispectral Imagery and Machine Learning Techniques

P Jjagwe, AK Chandel, D Langston - Land, 2023 - mdpi.com
Corn grain moisture (CGM) is critical to estimate grain maturity status and schedule harvest.
Traditional methods for determining CGM range from manual scouting, destructive …

[PDF][PDF] Models of quantitative estimation of sowing density effect on maize yield and its dependence on weather conditions.

O Kharchenko, S Petrenko… - … Papers. Series A …, 2021 - agronomyjournal.usamv.ro
This paper is focused on dependence of corn yield on plant density at harvest time and the
influence of weather conditions during crop growth period on the parameters of yield–factor …

Defining the ideal phenological stage for estimating corn yield using multispectral images

CAM Abreu Júnior, GD Martins, LCM Xavier… - Agronomy, 2023 - mdpi.com
Image-based spectral models assist in estimating the yield of maize. During the vegetative
and reproductive phenological phases, the corn crop undergoes changes caused by biotic …

Map** the corn residue-covered types using multi-scale feature fusion and supervised learning method by Chinese GF-2 PMS image

W Tao, Y Dong, W Su, J Li, F Xuan, J Huang… - Frontiers in Plant …, 2022 - frontiersin.org
The management of crop residue covering is a vital part of conservation tillage, which
protects black soil by reducing soil erosion and increasing soil organic carbon. Accurate and …