Ana I. De Castro - Search Results

Year	Number of Results
2013	2
2014	1
2015	2
2018	1
2019	4
2022	0

1

Automatic UAV-based detection of Cynodon dactylon for site-specific vineyard management.

Jiménez-Brenes FM, López-Granados F, Torres-Sánchez J, Peña JM, Ramírez P, Castillejo-González IL, de Castro AI. Jiménez-Brenes FM, et al. PLoS One. 2019 Jun 11;14(6):e0218132. doi: 10.1371/journal.pone.0218132. eCollection 2019. PLoS One. 2019. PMID: 31185068 Free PMC article.

2

High-Throughput Phenotyping of Bioethanol Potential in Cereals Using UAV-Based Multi-Spectral Imagery.

Ostos-Garrido FJ, de Castro AI, Torres-Sánchez J, Pistón F, Peña JM. Ostos-Garrido FJ, et al. Among authors: de castro ai. Front Plant Sci. 2019 Jul 23;10:948. doi: 10.3389/fpls.2019.00948. eCollection 2019. Front Plant Sci. 2019. PMID: 31396251 Free PMC article.

3

An efficient RGB-UAV-based platform for field almond tree phenotyping: 3-D architecture and flowering traits.

López-Granados F, Torres-Sánchez J, Jiménez-Brenes FM, Arquero O, Lovera M, de Castro AI. López-Granados F, et al. Among authors: de castro ai. Plant Methods. 2019 Dec 26;15:160. doi: 10.1186/s13007-019-0547-0. eCollection 2019. Plant Methods. 2019. PMID: 31889984 Free PMC article.

4

Detection of multi-tomato leaf diseases (late blight, target and bacterial spots) in different stages by using a spectral-based sensor.

Lu J, Ehsani R, Shi Y, de Castro AI, Wang S. Lu J, et al. Sci Rep. 2018 Feb 12;8(1):2793. doi: 10.1038/s41598-018-21191-6. Sci Rep. 2018. PMID: 29434226 Free PMC article.

5

High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques.

de Castro AI, Rallo P, Suárez MP, Torres-Sánchez J, Casanova L, Jiménez-Brenes FM, Morales-Sillero A, Jiménez MR, López-Granados F. de Castro AI, et al. Front Plant Sci. 2019 Nov 18;10:1472. doi: 10.3389/fpls.2019.01472. eCollection 2019. Front Plant Sci. 2019. PMID: 31803210 Free PMC article.

6

Detection of laurel wilt disease in avocado using low altitude aerial imaging.

de Castro AI, Ehsani R, Ploetz RC, Crane JH, Buchanon S. de Castro AI, et al. PLoS One. 2015 Apr 30;10(4):e0124642. doi: 10.1371/journal.pone.0124642. eCollection 2015. PLoS One. 2015. PMID: 25927209 Free PMC article.

7

Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images.

Peña JM, Torres-Sánchez J, de Castro AI, Kelly M, López-Granados F. Peña JM, et al. PLoS One. 2013 Oct 11;8(10):e77151. doi: 10.1371/journal.pone.0077151. eCollection 2013. PLoS One. 2013. PMID: 24146963 Free PMC article.

8

Configuration and specifications of an Unmanned Aerial Vehicle (UAV) for early site specific weed management.

Torres-Sánchez J, López-Granados F, De Castro AI, Peña-Barragán JM. Torres-Sánchez J, et al. PLoS One. 2013;8(3):e58210. doi: 10.1371/journal.pone.0058210. Epub 2013 Mar 6. PLoS One. 2013. PMID: 23483997 Free PMC article.

9

Semi-automatic normalization of multitemporal remote images based on vegetative pseudo-invariant features.

Garcia-Torres L, Caballero-Novella JJ, Gómez-Candón D, De-Castro AI. Garcia-Torres L, et al. PLoS One. 2014 Mar 6;9(3):e91275. doi: 10.1371/journal.pone.0091275. eCollection 2014. PLoS One. 2014. PMID: 24604031 Free PMC article.

10

Quantifying efficacy and limits of unmanned aerial vehicle (UAV) technology for weed seedling detection as affected by sensor resolution.

Peña JM, Torres-Sánchez J, Serrano-Pérez A, de Castro AI, López-Granados F. Peña JM, et al. Among authors: de castro ai. Sensors (Basel). 2015 Mar 6;15(3):5609-26. doi: 10.3390/s150305609. Sensors (Basel). 2015. PMID: 25756867 Free PMC article.

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