Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Aikaterini Kasimati"'
Autor:
George Papadopoulos, Simone Arduini, Havva Uyar, Vasilis Psiroukis, Aikaterini Kasimati, Spyros Fountas
Publikováno v:
Smart Agricultural Technology, Vol 8, Iss , Pp 100441- (2024)
This comprehensive review delved into the economic and environmental benefits of Digital Agricultural Technologies (DATs) in crop production, synthesising data from 136 peer-reviewed papers and 28 documents with empirical data from relevant EU projec
Externí odkaz:
https://doaj.org/article/879f61c5ca5c4916b7226e143111e283
Autor:
Aikaterini Kasimati, George Papadopoulos, Valentina Manstretta, Marianthi Giannakopoulou, George Adamides, Damianos Neocleous, Vassilis Vassiliou, Savvas Savvides, Andreas Stylianou
Publikováno v:
Agronomy, Vol 14, Iss 4, p 736 (2024)
Addressing the urgent sustainability challenges in the wine industry, this study explores the efficacy of sustainability-oriented innovations (SOIs) and smart farming technologies (SFTs) across wine value chains in Cyprus and Italy. Utilising a mixed
Externí odkaz:
https://doaj.org/article/c97a9844104748d4b3013b0bf8fe0bce
Publikováno v:
Remote Sensing, Vol 15, Iss 5, p 1214 (2023)
Modeling cotton plant growth is an important aspect of improving cotton yields and fiber quality and optimizing land management strategies. High-throughput phenotyping (HTP) systems, including those using high-resolution imagery from unmanned aerial
Externí odkaz:
https://doaj.org/article/6c1c5a96a554439fa6df9920c3441a82
Autor:
Nicoleta Darra, Borja Espejo-Garcia, Aikaterini Kasimati, Olga Kriezi, Emmanouil Psomiadis, Spyros Fountas
Publikováno v:
Sensors, Vol 23, Iss 5, p 2586 (2023)
In this paper, we propose an innovative approach for robust prediction of processing tomato yield using open-source AutoML techniques and statistical analysis. Sentinel-2 satellite imagery was deployed to obtain values of five (5) selected vegetation
Externí odkaz:
https://doaj.org/article/cdadb0c26601475f9ff121ae029af16e
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
The most common method for determining wine grape quality characteristics is to perform sample-based laboratory analysis, which can be time-consuming and expensive. In this article, we investigate an alternative approach to predict wine grape quality
Externí odkaz:
https://doaj.org/article/c3e6542ed8ba48b787516e67d622d29a
Autor:
Vasilis Psiroukis, Nicoleta Darra, Aikaterini Kasimati, Pavel Trojacek, Gunay Hasanli, Spyros Fountas
Publikováno v:
Remote Sensing, Vol 14, Iss 17, p 4202 (2022)
This paper presents the development and update of a multi-scale yield prediction model for processing tomatoes. The study was carried out under the EU-funded programme “Support to Development of a Rural Business Information System (RBIS)”, and th
Externí odkaz:
https://doaj.org/article/f7fea211371e4e8986705ea8afe17acc
Publikováno v:
Agriculture, Vol 12, Iss 7, p 1027 (2022)
Decision support systems (DSSs) in agriculture are becoming increasingly popular, and have begun adopting visualisations to facilitate insights into complex data. However, DSSs for agriculture are often designed as standalone applications, which limi
Externí odkaz:
https://doaj.org/article/19d8a8df9c6a45be95b92351fed22331
Publikováno v:
Sensors, Vol 22, Iss 9, p 3249 (2022)
Wine grapes need frequent monitoring to achieve high yields and quality. Non-destructive methods, such as proximal and remote sensing, are commonly used to estimate crop yield and quality characteristics, and spectral vegetation indices (VIs) are oft
Externí odkaz:
https://doaj.org/article/0bb860a21a8440398800c711d3d5b0b8
Autor:
Nicoleta Darra, Emmanouil Psomiadis, Aikaterini Kasimati, Achilleas Anastasiou, Evangelos Anastasiou, Spyros Fountas
Publikováno v:
Agronomy, Vol 11, Iss 4, p 741 (2021)
Remote-sensing measurements are crucial for smart-farming applications, crop monitoring, and yield forecasting, especially in fields characterized by high heterogeneity. Therefore, in this study, Precision Viticulture (PV) methods using proximal- and
Externí odkaz:
https://doaj.org/article/848dd9237c0d4aee826205f06aed7a1e
Publikováno v:
SMEs in the Digital Era ISBN: 9781803921648
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7bb3883bf45033a9033b30f1890f812e
https://doi.org/10.4337/9781803921648.00010
https://doi.org/10.4337/9781803921648.00010
