[HTML][HTML] A review on beef cattle supplementation technologies

G Defalque, R Santos, M Pache, C Defalque - Information Processing in …, 2023 - Elsevier
The increase in the worldwide population reflects the expansion of beef cattle production
and exportation. Although pasture is the world's primary feed source of cattle food, failures in …

Advancing skyborne technologies and high-resolution satellites for pasture monitoring and improved management: a review

MG Ogungbuyi, C Mohammed, I Ara, AM Fischer… - Remote Sensing, 2023 - mdpi.com
The timely and accurate quantification of grassland biomass is a prerequisite for sustainable
grazing management. With advances in artificial intelligence, the launch of new satellites …

Predictive modeling of above-ground biomass in brachiaria pastures from satellite and UAV imagery using machine learning approaches

CI Alvarez-Mendoza, D Guzman, J Casas, M Bastidas… - Remote Sensing, 2022 - mdpi.com
Grassland pastures are crucial for the global food supply through their milk and meat
production; hence, forage species monitoring is essential for cattle feed. Therefore …

Machine learning models for dry matter and biomass estimates on cattle grazing systems

G Defalque, R Santos, D Bungenstab… - … and Electronics in …, 2024 - Elsevier
Monitoring pasture conditions contributes to the animals' decision-making process, avoiding
supplementation losses, and improving cattle performance. Environmental parameters and …

[HTML][HTML] Monitoring Cover Crop Biomass in Southern Brazil Using Combined PlanetScope and Sentinel-1 SAR Data

FM Breunig, R Dalagnol, LS Galvão, PC Bispo, Q Liu… - Remote Sensing, 2024 - mdpi.com
Precision agriculture integrates multiple sensors and data types to support farmers with
informed decision-making tools throughout crop cycles. This study evaluated Aboveground …

[HTML][HTML] Improvement of pasture biomass modelling using high-resolution satellite imagery and machine learning

MG Ogungbuyi, J Guerschman, AM Fischer… - Journal of …, 2024 - Elsevier
Robust quantification of vegetative biomass using satellite imagery using one or more forms
of machine learning (ML) has hitherto been hindered by the extent and quality of training …

[HTML][HTML] Estimation, Spatiotemporal Dynamics, and Driving Factors of Grassland Biomass Carbon Storage Based on Machine Learning Methods: A Case Study of the …

Q Zhi, X Hu, P Wang, M Li, Y Ding, Y Wu, T Peng, W Li… - Remote Sensing, 2024 - mdpi.com
Precisely estimating the grassland biomass carbon storage is vital for evaluating grassland
carbon sequestration potential and the monitoring and management of grassland resources …

Prediction of pasture yield using machine learning-based optical sensing: a systematic review

C Stumpe, J Leukel, T Zimpel - Precision Agriculture, 2024 - Springer
Accurate and reliable predictions of biomass yield are important for decision-making in
pasture management including fertilization, pest control, irrigation, grazing, and mowing …

Canopy height and biomass prediction in Mombaça guinea grass pastures using satellite imagery and machine learning

IL Bretas, DSM Valente, TF De Oliveira… - Precision …, 2023 - Springer
Remote sensing can serve as a promising solution for monitoring spatio-temporal variability
in grasslands, providing timely information about different biophysical parameters. We …

Using sentinel-2 satellite images and machine learning algorithms to predict tropical pasture forage mass, crude protein, and fiber content

MHMR Fernandes, JS FernandesJunior, JM Adams… - Scientific Reports, 2024 - nature.com
Grasslands cover approximately 24% of the Earth's surface and are the main feed source for
cattle and other ruminants. Sustainable and efficient grazing systems require regular …