This page has only limited features, please log in for full access.
V. Liakos; E. Smith; J. Andreis; G. Vellidis; D. Pavlou; A. Orfanou; W. Porter; T. Onker; A. Rabia. 104. Blueberry app: a tool for irrigation scheduling on blueberries for the Southeastern USA. Precision agriculture ’21 2021, 1 .
AMA StyleV. Liakos, E. Smith, J. Andreis, G. Vellidis, D. Pavlou, A. Orfanou, W. Porter, T. Onker, A. Rabia. 104. Blueberry app: a tool for irrigation scheduling on blueberries for the Southeastern USA. Precision agriculture ’21. 2021; ():1.
Chicago/Turabian StyleV. Liakos; E. Smith; J. Andreis; G. Vellidis; D. Pavlou; A. Orfanou; W. Porter; T. Onker; A. Rabia. 2021. "104. Blueberry app: a tool for irrigation scheduling on blueberries for the Southeastern USA." Precision agriculture ’21 , no. : 1.
Remotely sensed-based surface temperature is an important tool for crop monitoring and has great potential for improving irrigation management. However, current thermal satellite platforms do not display the fine spatial resolution required for identifying crop water status patterns at the field scale. The thermal sharpening (TsHARP) utility provides a technique for downscaling coarse thermal images to match the finer resolution of images acquired in the visible and near infrared bandwidths. This sharpening method is based on the inverse linear relationship between vegetation fraction calculated from the normalized difference vegetation index (NDVI) and land surface temperature (LST). The current study used the TsHARP method to sharpen low-resolution thermal data from the Moderate Resolution Imaging Spectrometer MODIS (1 km) to the finer resolution of Sentinel-2 (10 m) and Vegetation and Environment New micro-Spacecraft (VENµS) (5 m) visible-near infrared images. The sharpening methodology was evaluated at scene and field scales in southern Georgia and northern Mississippi, USA. A comparison of sharpened temperature was made with reference temperatures from Landsat-8 Operational Land Imager (OLI) in four different spatial resolutions (30, 60, 120, and 240 m) for method validation. Coarse resolution comparison on the dates in which imagery from both sensors were acquired on the same day resulted in average observed mean absolute error (MAE) of 1.63 °C, and R2 variation from 0.34 to 0.74. Temperature errors at the field scale ranged from 0.25 to 3.11 °C using both Sentinel-2 and VENµS. Sharpened maps at 120 and 60 m resolution showed the highest consistency for all fields and dates. Maps sharpened using VENµS images showed comparable or higher accuracy than maps sharpened using Sentinel-2. The superior performance coupled with the better revisit time indicates that the VENµS platform has high potential for frequent in-season crop monitoring. Further research with ground data collection is needed to explore field use limitations of this methodology, but these results give useful insights of potential benefits of implementing the TsHARP technique as a tool for crop stress monitoring.
Lorena Lacerda; Yafit Cohen; John Snider; Hanna Huryna; Vasileios Liakos; George Vellidis. Field Scale Assessment of the TsHARP Technique for Thermal Sharpening of MODIS Satellite Images Using VENµS and Sentinel-2-Derived NDVI. Remote Sensing 2021, 13, 1155 .
AMA StyleLorena Lacerda, Yafit Cohen, John Snider, Hanna Huryna, Vasileios Liakos, George Vellidis. Field Scale Assessment of the TsHARP Technique for Thermal Sharpening of MODIS Satellite Images Using VENµS and Sentinel-2-Derived NDVI. Remote Sensing. 2021; 13 (6):1155.
Chicago/Turabian StyleLorena Lacerda; Yafit Cohen; John Snider; Hanna Huryna; Vasileios Liakos; George Vellidis. 2021. "Field Scale Assessment of the TsHARP Technique for Thermal Sharpening of MODIS Satellite Images Using VENµS and Sentinel-2-Derived NDVI." Remote Sensing 13, no. 6: 1155.
Precision Agriculture (PA) is a crop site-specific management system that aims for sustainability, adopting agricultural practices more friendly to the environment, like the variable rate application (VRA) technique. Many studies have dealt with the effectiveness of VRA to reduce nitrogen (N) fertilizer, while achieving increased profit and productivity. However, only limited attention was given to VRA’s environmental impact. In this study an International Organization for Standardization (ISO) based Life Cycle Assessment (LCA) performed to identify the environmental effects of N VRA on a small pear orchard, compared to the conventional uniform application. A Cradle to Gate system with a functional unit (FU) of 1 kg of pears was analyzed including high quality primary data of two productive years, including also the non-productive years, as well as all the emissions during pear growing and the supply chains of all inputs, projecting them to the lifespan of the orchard. A methodology was adopted, modelling individual years and averaging over the orchard’s lifetime. Results showed that Climate change, Water scarcity, Fossil fuels and Particulate formation were the most contributing impact categories to the overall environmental impact of the pear orchard lifespan, where climate change and particulates were largely determined by CO2, N2O, and NH3 emissions to the air from fertilizer production and application, and as CO2 from tractor use. Concerning fertilization practice, when VRA was combined with a high yield year, this resulted in significantly reduced environmental impact. LCA evaluating an alternative fertilizer management system in a Greek pear orchard revealed the environmental impact reduction potential of that system.
Anna Vatsanidou; Spyros Fountas; Vasileios Liakos; George Nanos; Nikolaos Katsoulas; Theofanis Gemtos. Life Cycle Assessment of Variable Rate Fertilizer Application in a Pear Orchard. Sustainability 2020, 12, 6893 .
AMA StyleAnna Vatsanidou, Spyros Fountas, Vasileios Liakos, George Nanos, Nikolaos Katsoulas, Theofanis Gemtos. Life Cycle Assessment of Variable Rate Fertilizer Application in a Pear Orchard. Sustainability. 2020; 12 (17):6893.
Chicago/Turabian StyleAnna Vatsanidou; Spyros Fountas; Vasileios Liakos; George Nanos; Nikolaos Katsoulas; Theofanis Gemtos. 2020. "Life Cycle Assessment of Variable Rate Fertilizer Application in a Pear Orchard." Sustainability 12, no. 17: 6893.
The objectives of this study were to compare variable rate and uniform fertilizer applications in apple (Malus domestica Borkh.) and its effect on production and economic return. In the study, 59.6% and 63.4% less fertilizer were applied in the variable rate treatments (VRT) in 2011 and 2012, respectively, with less than 4% difference in yield. Soil properties did not significantly affect yield and fruit quality. The VRT fertilizer cost was reduced by 2.3% and 7.6% in 2011 and 2012, respectively, and fruit quality was not significantly affected. Assessing yield to calculate fertilizer demand suggests variable rate fertilizer inputs can potentially increase the profitability of an apple orchard.
Vasileios Liakos; Erick Smith; Spyros Fountas; George Nanos; Dimitris Kalfountzos; Theofanis Gemtos. On-Farm Evaluation of Variable Rate Fertilizer Applications Using Yield-Based Mathematical Formulae in a Greek Apple Orchard. International Journal of Fruit Science 2020, 20, S48 -S65.
AMA StyleVasileios Liakos, Erick Smith, Spyros Fountas, George Nanos, Dimitris Kalfountzos, Theofanis Gemtos. On-Farm Evaluation of Variable Rate Fertilizer Applications Using Yield-Based Mathematical Formulae in a Greek Apple Orchard. International Journal of Fruit Science. 2020; 20 (sup2):S48-S65.
Chicago/Turabian StyleVasileios Liakos; Erick Smith; Spyros Fountas; George Nanos; Dimitris Kalfountzos; Theofanis Gemtos. 2020. "On-Farm Evaluation of Variable Rate Fertilizer Applications Using Yield-Based Mathematical Formulae in a Greek Apple Orchard." International Journal of Fruit Science 20, no. sup2: S48-S65.
V. Liakos; W. Porter; J. Kichler; A. Sawyer; D. Pavlou; A. Orfanou; G. Vellidis. A model for precision irrigation scheduling of soybeans for the South-eastern U.S. Precision agriculture ’19 2019, 1 .
AMA StyleV. Liakos, W. Porter, J. Kichler, A. Sawyer, D. Pavlou, A. Orfanou, G. Vellidis. A model for precision irrigation scheduling of soybeans for the South-eastern U.S. Precision agriculture ’19. 2019; ():1.
Chicago/Turabian StyleV. Liakos; W. Porter; J. Kichler; A. Sawyer; D. Pavlou; A. Orfanou; G. Vellidis. 2019. "A model for precision irrigation scheduling of soybeans for the South-eastern U.S." Precision agriculture ’19 , no. : 1.
This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015 and 2016 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed within the fields. These strips were irrigated according to either UGA SSA or Irrigator Pro recommendations. The results showed that Irrigator Pro is a conservative irrigation method which results in high yields. On the other hand the UGA SSA recommendations worked very well with the VRI system and in both years it recommended an average of 25% less irrigation water than the Irrigator Pro.
V. Liakos; W. Porter; Xi Liang; M. A. Tucker; A. McLendon; G. Vellidis. Dynamic Variable Rate Irrigation – A Tool for Greatly Improving Water Use Efficiency. Advances in Animal Biosciences 2017, 8, 557 -563.
AMA StyleV. Liakos, W. Porter, Xi Liang, M. A. Tucker, A. McLendon, G. Vellidis. Dynamic Variable Rate Irrigation – A Tool for Greatly Improving Water Use Efficiency. Advances in Animal Biosciences. 2017; 8 (2):557-563.
Chicago/Turabian StyleV. Liakos; W. Porter; Xi Liang; M. A. Tucker; A. McLendon; G. Vellidis. 2017. "Dynamic Variable Rate Irrigation – A Tool for Greatly Improving Water Use Efficiency." Advances in Animal Biosciences 8, no. 2: 557-563.
Pre-harvest aflatoxin contamination (PAC) is a major problem facing peanut production worldwide. Produced by the ubiquitous soil fungus, Aspergillus flavus, aflatoxin is the most naturally occurring known carcinogen. The interaction between fungus and host resulting in PAC is complex, and breeding for PAC resistance has been slow. It has been shown that aflatoxin production can be induced by applying drought stress as peanut seeds mature. We have implemented an automated rainout shelter that controls temperature and moisture in the root and peg zone to induce aflatoxin production. Using polymerase chain reaction (PCR) and high performance liquid chromatography (HPLC), seeds meeting the following conditions were selected: infected with Aspergillus flavus and contaminated with aflatoxin; and not contaminated with aflatoxin. RNA sequencing analysis revealed groups of genes that describe the transcriptional state of contaminated vs. uncontaminated seed. These data suggest that fatty acid biosynthesis and abscisic acid (ABA) signaling are altered in contaminated seeds and point to a potential susceptibility factor, ABR1, as a repressor of ABA signaling that may play a role in permitting PAC.
Josh Clevenger; Kathleen Marasigan; Vasileios Liakos; Victor Sobolev; George Vellidis; Corley Holbrook; Peggy Ozias-Akins. RNA Sequencing of Contaminated Seeds Reveals the State of the Seed Permissive for Pre-Harvest Aflatoxin Contamination and Points to a Potential Susceptibility Factor. Toxins 2016, 8, 317 .
AMA StyleJosh Clevenger, Kathleen Marasigan, Vasileios Liakos, Victor Sobolev, George Vellidis, Corley Holbrook, Peggy Ozias-Akins. RNA Sequencing of Contaminated Seeds Reveals the State of the Seed Permissive for Pre-Harvest Aflatoxin Contamination and Points to a Potential Susceptibility Factor. Toxins. 2016; 8 (11):317.
Chicago/Turabian StyleJosh Clevenger; Kathleen Marasigan; Vasileios Liakos; Victor Sobolev; George Vellidis; Corley Holbrook; Peggy Ozias-Akins. 2016. "RNA Sequencing of Contaminated Seeds Reveals the State of the Seed Permissive for Pre-Harvest Aflatoxin Contamination and Points to a Potential Susceptibility Factor." Toxins 8, no. 11: 317.
V. Liakos; G. Vellidis; M. Tucker; C. Lowrance; X. Liang. A decision support tool for managing precision irrigation with center pivots. Precision agriculture '15 2015, 677 -684.
AMA StyleV. Liakos, G. Vellidis, M. Tucker, C. Lowrance, X. Liang. A decision support tool for managing precision irrigation with center pivots. Precision agriculture '15. 2015; ():677-684.
Chicago/Turabian StyleV. Liakos; G. Vellidis; M. Tucker; C. Lowrance; X. Liang. 2015. "A decision support tool for managing precision irrigation with center pivots." Precision agriculture '15 , no. : 677-684.
G. Vellidis; V. Liakos; M. Tucker; C. Perry; J. Andreis; C. Fraïssé; K. Migliaccio. A smartphone app for precision irrigation scheduling in cotton. Precision agriculture '15 2015, 701 -708.
AMA StyleG. Vellidis, V. Liakos, M. Tucker, C. Perry, J. Andreis, C. Fraïssé, K. Migliaccio. A smartphone app for precision irrigation scheduling in cotton. Precision agriculture '15. 2015; ():701-708.
Chicago/Turabian StyleG. Vellidis; V. Liakos; M. Tucker; C. Perry; J. Andreis; C. Fraïssé; K. Migliaccio. 2015. "A smartphone app for precision irrigation scheduling in cotton." Precision agriculture '15 , no. : 701-708.