Editorial: Special Issue “Emerging Sensor Technology in Agriculture”
Acknowledgments
Conflicts of Interest
References
- Rueda-Ayala, V.P.; Peña, J.M.; Höglind, M.; Bengochea-Guevara, J.M.; Andújar, D. Comparing UAV-based technologies and RGB-D reconstruction methods for plant height and biomass monitoring on grass ley. Sensors 2019, 19, 535. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zemmour, E.; Kurtser, P.; Edan, Y. Automatic parameter tuning for adaptive thresholding in fruit detection. Sensors 2019, 19, 2130. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Valente, J.; Almeida, R.; Kooistra, L. A Comprehensive Study of the Potential Application of Flying Ethylene-Sensitive Sensors for Ripeness Detection in Apple Orchards. Sensors 2019, 19, 372. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hacking, C.; Poona, N.; Manzan, N.; Poblete-Echeverría, C. Investigating 2-d and 3-d proximal remote sensing techniques for vineyard yield estimation. Sensors 2019, 19, 3652. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Palacios, F.; Diago, M.P.; Tardaguila, J. A Non-Invasive Method Based on Computer Vision for Grapevine Cluster Compactness Assessment Using a Mobile Sensing Platform under Field Conditions. Sensors 2019, 19, 3799. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fuentes, S.; Chacon, G.; Torrico, D.D.; Zarate, A.; Gonzalez Viejo, C. Spatial variability of aroma profiles of cocoa trees obtained through computer vision and machine learning modelling: A cover photography and high spatial remote sensing application. Sensors 2019, 19, 3054. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fuentes, S.; Tongson, E.J.; De Bei, R.; Gonzalez Viejo, C.; Ristic, R.; Tyerman, S.; Wilkinson, K. Non-invasive tools to detect smoke contamination in grapevine canopies, berries and wine: A remote sensing and machine learning modeling approach. Sensors 2019, 19, 3335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Castro-Garcia, S.; Aragon-Rodriguez, F.; Sola-Guirado, R.R.; Serrano, A.J.; Soria-Olivas, E.; Gil-Ribes, J.A. Vibration Monitoring of the Mechanical Harvesting of Citrus to Improve Fruit Detachment Efficiency. Sensors 2019, 19, 1760. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baath, G.S.; Baath, H.K.; Gowda, P.H.; Thomas, J.P.; Northup, B.K.; Rao, S.C.; Singh, H. Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques. Sensors 2020, 20, 867. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Romero-Bravo, S.; Méndez-Espinoza, A.M.; Garriga, M.; Estrada, F.; Escobar, A.; González-Martinez, L.; Poblete-Echeverría, C.; Sepulveda, D.; Matus, I.; Castillo, D. Thermal imaging reliability for estimating grain yield and carbon isotope discrimination in wheat genotypes: Importance of the environmental conditions. Sensors 2019, 19, 2676. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yao, L.; Wang, Q.; Yang, J.; Zhang, Y.; Zhu, Y.; Cao, W.; Ni, J. UAV-borne dual-band sensor method for monitoring physiological crop status. Sensors 2019, 19, 816. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Psota, E.T.; Mittek, M.; Pérez, L.C.; Schmidt, T.; Mote, B. Multi-pig part detection and association with a fully-convolutional network. Sensors 2019, 19, 852. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, P.; Yu, W.; Ou, M.; Gong, C.; Jia, W. Monitoring of the pesticide droplet deposition with a novel capacitance sensor. Sensors 2019, 19, 537. [Google Scholar] [CrossRef] [PubMed] [Green Version]
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Poblete-Echeverría, C.; Fuentes, S. Editorial: Special Issue “Emerging Sensor Technology in Agriculture”. Sensors 2020, 20, 3827. https://doi.org/10.3390/s20143827
Poblete-Echeverría C, Fuentes S. Editorial: Special Issue “Emerging Sensor Technology in Agriculture”. Sensors. 2020; 20(14):3827. https://doi.org/10.3390/s20143827
Chicago/Turabian StylePoblete-Echeverría, Carlos, and Sigfredo Fuentes. 2020. "Editorial: Special Issue “Emerging Sensor Technology in Agriculture”" Sensors 20, no. 14: 3827. https://doi.org/10.3390/s20143827