[HTML][HTML] Towards smart irrigation: A literature review on the use of geospatial technologies and machine learning in the management of water resources in …

Y Ahansal, M Bouziani, R Yaagoubi, I Sebari, K Sebari… - Agronomy, 2022 - mdpi.com
Agriculture consumes an important ratio of the water reserve in irrigated areas. The
improvement of irrigation is becoming essential to reduce this high water consumption by …

[HTML][HTML] Automatic bunch detection in white grape varieties using YOLOv3, YOLOv4, and YOLOv5 deep learning algorithms

M Sozzi, S Cantalamessa, A Cogato, A Kayad… - Agronomy, 2022 - mdpi.com
Over the last few years, several Convolutional Neural Networks for object detection have
been proposed, characterised by different accuracy and speed. In viticulture, yield …

How many gigabytes per hectare are available in the digital agriculture era? A digitization footprint estimation

A Kayad, M Sozzi, DS Paraforos… - … and Electronics in …, 2022 - Elsevier
The applications of digital agriculture technologies are increasing rapidly with increased
interest from the new generation of farmers to use digital solutions. Such technologies …

[HTML][HTML] Assessment of vineyard vigour and yield spatio-temporal variability based on UAV high resolution multispectral images

MV Ferro, P Catania, D Micciche, A Pisciotta… - biosystems …, 2023 - Elsevier
Accurate, timely assessment of the vineyard on a field scale is essential for successful grape
yield and quality. Remote sensing can be an effective and useful monitoring tool, as data …

[HTML][HTML] Utilizing spectral, structural and textural features for estimating oat above-ground biomass using UAV-based multispectral data and machine learning

R Dhakal, M Maimaitijiang, J Chang, M Caffe - Sensors, 2023 - mdpi.com
Accurate and timely monitoring of biomass in breeding nurseries is essential for evaluating
plant performance and selecting superior genotypes. Traditional methods for phenoty** …

Ensemble and single algorithm models to handle multicollinearity of UAV vegetation indices for predicting rice biomass

R Derraz, FM Muharam, K Nurulhuda, NA Jaafar… - … and Electronics in …, 2023 - Elsevier
Rice biomass is a biofuel's source and yield indicator. Conventional sampling methods
predict rice biomass accurately. However, these methods are destructive, time-consuming …

[HTML][HTML] Speeding up UAV-based crop variability assessment through a data fusion approach using spatial interpolation for site-specific management

S Vélez, M Ariza-Sentís, M Panić, B Ivošević… - Smart Agricultural …, 2024 - Elsevier
Innovations in precision agriculture enhance complex tasks, reduce environmental impact,
and increase food production and cost efficiency. One of the main challenges is ensuring …

A deep learning-based model to reduce costs and increase productivity in the case of small datasets: A case study in cotton cultivation

MA Amani, F Marinello - Agriculture, 2022 - mdpi.com
In this paper, a deep-learning model is proposed as a viable approach to optimize the
information on soil parameters and agricultural variables' effect in cotton cultivation, even in …

[HTML][HTML] A comparison between conventional sprayers and new UAV sprayers: A study case of vineyards and olives in extremadura (Spain)

PA Morales-Rodríguez, E Cano Cano, J Villena… - Agronomy, 2022 - mdpi.com
Recently, technological development has become increasingly pronounced, with great
advances in all production areas, including agriculture. In the agricultural sector …

Upscaling drought resilience by coupling soil data and UAV-multispectral imageries

G Sofia, M Sinatra, P Tarolli, C Zaccone - Science of The Total Environment, 2025 - Elsevier
Monitoring crop responses to drought is crucial for understanding the progressive impact of
drought on food production and identifying management practices that can enhance …