Machine learning in agriculture: A comprehensive updated review

L Benos, AC Tagarakis, G Dolias, R Berruto, D Kateris… - Sensors, 2021 - mdpi.com
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …

A comprehensive review on recent applications of unmanned aerial vehicle remote sensing with various sensors for high-throughput plant phenoty**

L Feng, S Chen, C Zhang, Y Zhang, Y He - Computers and electronics in …, 2021 - Elsevier
High-throughput phenoty** has been widely studied in plant science to monitor plant
growth and analyze the influence of genotypes and environment on plant growth. To meet …

Farmers' perception of the barriers that hinder the implementation of agriculture 4.0

F Da Silveira, SLC Da Silva, FM Machado… - Agricultural …, 2023 - Elsevier
CONTEXT Agriculture 4.0 can drive the growth of the agricultural production in emerging
countries like Brazil, which is known as one of the primary food and meat producers …

Winter wheat yield prediction in the conterminous United States using solar-induced chlorophyll fluorescence data and XGBoost and random forest algorithm

A Joshi, B Pradhan, S Chakraborty, MD Behera - Ecological Informatics, 2023 - Elsevier
Predicting crop yield before harvest and understanding the factors determining yield at a
regional scale is vital for global food security, supply chain management in agribusiness …

Estimation of plant height and yield based on UAV imagery in faba bean (Vicia faba L.)

Y Ji, Z Chen, Q Cheng, R Liu, M Li, X Yan, G Li… - Plant Methods, 2022 - Springer
Background Faba bean is an important legume crop in the world. Plant height and yield are
important traits for crop improvement. The traditional plant height and yield measurement …

Predicting canopy chlorophyll content in sugarcane crops using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imagery

A Narmilan, F Gonzalez, ASA Salgadoe… - Remote Sensing, 2022 - mdpi.com
The use of satellite-based Remote Sensing (RS) is a well-developed field of research. RS
techniques have been successfully utilized to evaluate the chlorophyll content for the …

Estimation of corn yield based on hyperspectral imagery and convolutional neural network

W Yang, T Nigon, Z Hao, GD Paiao… - … and Electronics in …, 2021 - Elsevier
Corn is an important food crop in the world, widely distributed in many countries because of
its excellent environmental adaptability. Moreover, corn is an important feed source for …

Wheat yield prediction using machine learning method based on UAV remote sensing data

S Yang, L Li, S Fei, M Yang, Z Tao, Y Meng, Y ** in a context of global change: What to measure and how to do it
JL Araus, SC Kefauver, O Vergara‐Díaz… - Journal of Integrative …, 2022 - Wiley Online Library
High‐throughput crop phenoty**, particularly under field conditions, is nowadays
perceived as a key factor limiting crop genetic advance. Phenoty** not only facilitates …

Retrieving SPAD values of summer maize using UAV hyperspectral data based on multiple machine learning algorithm

B Sudu, G Rong, S Guga, K Li, F Zhi, Y Guo, J Zhang… - Remote Sensing, 2022 - mdpi.com
Using unmanned aerial vehicle (UAV) hyperspectral images to accurately estimate the
chlorophyll content of summer maize is of great significance for crop growth monitoring …