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[HTML][HTML] Towards smart irrigation: A literature review on the use of geospatial technologies and machine learning in the management of water resources in …
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 …
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
Over the last few years, several Convolutional Neural Networks for object detection have
been proposed, characterised by different accuracy and speed. In viticulture, yield …
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
The applications of digital agriculture technologies are increasing rapidly with increased
interest from the new generation of farmers to use digital solutions. Such technologies …
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
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 …
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
Accurate and timely monitoring of biomass in breeding nurseries is essential for evaluating
plant performance and selecting superior genotypes. Traditional methods for phenoty** …
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
Rice biomass is a biofuel's source and yield indicator. Conventional sampling methods
predict rice biomass accurately. However, these methods are destructive, time-consuming …
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
Innovations in precision agriculture enhance complex tasks, reduce environmental impact,
and increase food production and cost efficiency. One of the main challenges is ensuring …
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
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 …
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 …
advances in all production areas, including agriculture. In the agricultural sector …
Upscaling drought resilience by coupling soil data and UAV-multispectral imageries
Monitoring crop responses to drought is crucial for understanding the progressive impact of
drought on food production and identifying management practices that can enhance …
drought on food production and identifying management practices that can enhance …