[HTML][HTML] Smart applications and digital technologies in viticulture: A review
J Tardaguila, M Stoll, S Gutiérrez, T Proffitt… - Smart Agricultural …, 2021 - Elsevier
It is important to continuously monitor the long-term impact of viticultural management
practices and assess opportunities for improving the environmental footprint of vineyard …
practices and assess opportunities for improving the environmental footprint of vineyard …
A review of the challenges of using deep learning algorithms to support decision-making in agricultural activities
Deep Learning has been successfully applied to image recognition, speech recognition, and
natural language processing in recent years. Therefore, there has been an incentive to …
natural language processing in recent years. Therefore, there has been an incentive to …
Computer vision and deep learning for precision viticulture
During the last decades, researchers have developed novel computing methods to help
viticulturists solve their problems, primarily those linked to yield estimation of their crops …
viticulturists solve their problems, primarily those linked to yield estimation of their crops …
Automated grapevine flower detection and quantification method based on computer vision and deep learning from on-the-go imaging using a mobile sensing …
Grape yield forecasting is a valuable economic and quality issue for the grape and wine
industry. The number of flowers at bloom could be used as an early indicator towards crop …
industry. The number of flowers at bloom could be used as an early indicator towards crop …
Vineyard yield estimation, prediction, and forecasting: A systematic literature review
Purpose—knowing in advance vineyard yield is a critical success factor so growers and
winemakers can achieve the best balance between vegetative and reproductive growth. It is …
winemakers can achieve the best balance between vegetative and reproductive growth. It is …
Olive-fruit variety classification by means of image processing and convolutional neural networks
The automation of classification and grading of horticultural products attending to different
features comprises a major challenge in food industry. Thus, focused on the olive sector …
features comprises a major challenge in food industry. Thus, focused on the olive sector …
A review of the issues, methods and perspectives for yield estimation, prediction and forecasting in viticulture
C Laurent, B Oger, JA Taylor, T Scholasch… - European Journal of …, 2021 - Elsevier
Grapevine yield is defined as the quantity of harvest, expressed as either grape mass or
wine volumeunits, which has been collected per surface unit are and per crop cycle. The …
wine volumeunits, which has been collected per surface unit are and per crop cycle. The …
vitisBerry: An Android-smartphone application to early evaluate the number of grapevine berries by means of image analysis
In agriculture, crop monitoring and plant phenotyping are mainly manually measured.
However, this practice gathers phenotyping information at a lower rate than genotyping …
However, this practice gathers phenotyping information at a lower rate than genotyping …
Deep learning-based accurate grapevine inflorescence and flower quantification in unstructured vineyard images acquired using a mobile sensing platform
Early grapevine yield forecasting at satisfactory accuracy is among the major trends in
precision viticulture research. Conventionally, yield is estimated manually through …
precision viticulture research. Conventionally, yield is estimated manually through …
A new methodology for estimating the grapevine-berry number per cluster using image analysis
Highlights•The segmentation methodology is capable of working under field conditions.•The
algorithm properly analyses images taken with a low-cost device.•A novel set of descriptors …
algorithm properly analyses images taken with a low-cost device.•A novel set of descriptors …