Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Murilo M. Maeda"'
Publikováno v:
International Journal of Biometeorology. 66:591-600
Autor:
Alex J. Thomasson, Jinha Jung, Anjin Chang, Murilo M. Maeda, Steve Hague, Andrea Maeda, Don C. Jones, Juan Landivar, Wenzhou Wu, Akash Ashapure
Publikováno v:
Agronomy Journal. 114:331-339
Autor:
Wayne Smith, Juan Landivar, Junho Yeom, Anjin Chang, Jinha Jung, Murilo M. Maeda, Andrea Maeda, Sungchan Oh, Steve Hague, Nothabo Dube, Akash Ashapure
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 169:180-194
In this research a machine learning framework was developed for cotton yield estimation using multi-temporal remote sensing data collected from unmanned aircraft system (UAS). The proposed machine learning model was based on an artificial neural netw
Publikováno v:
International journal of biometeorology. 66(3)
Pigments are known to modify the spectral properties of foliage, which in turn affect the amount of radiant energy stored by the plant canopy. Studies have shown that red pigments (anthocyanin) increase leaf absorptivity of solar radiation, but littl
Autor:
Jinha Jung, Akash Ashapure, Andrea Maeda, Junho Yeom, Juan Landivar, Murilo M. Maeda, Anjin Chang
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 152:49-64
Recent years have witnessed enormous interest in the application of Unmanned Aerial Systems (UAS) for precision agriculture. This study presents a novel approach to use multi-temporal UAS data for comparison of two management practices in cotton, con
Autor:
Juan Enciso, Anjin Chang, Murilo M. Maeda, Jose C. Chavez, Jinha Jung, Junho Yeom, S. Elsayed-Farag, Carlos A. Avila, Juan Landivar
Publikováno v:
Computers and Electronics in Agriculture. 158:278-283
Unmanned aerial vehicles (UAV) have been recognized as excellent tools to provide real time feedback of temporal and spatial conditions found in agricultural fields throughout the growing season. UAVs have also allowed accelerating breeding programs
Autor:
Murilo M. Maeda, J. Tom Cothren, James L. Heilman, Carlos J. Fernandez, Gaylon D. Morgan, Vladimir A. da Costa
Publikováno v:
Journal of Cotton Science. 23:118-130
Upland cotton (Gossypium hirsutum L.) is an important socioeconomic crop throughout most of the southern U.S. In Texas, cotton is the lead cash crop and its productivity is often limited by abiotic stress events such as drought and elevated ambient t
Unmanned Aircraft System- (UAS-) Based High-Throughput Phenotyping (HTP) for Tomato Yield Estimation
Autor:
Junho Yeom, Anjin Chang, Juan Anciso, Carlos A. Avila, Juan Landivar, Juan Enciso, Jinha Jung, Murilo M. Maeda
Publikováno v:
Journal of Sensors, Vol 2021 (2021)
Yield prediction and variety selection are critical components for assessing production and performance in breeding programs and precision agriculture. Since plants integrate their genetics, surrounding environments, and management conditions, crop p
Autor:
Juan Landivar-Bowles, Murilo M. Maeda, Anjin Chang, Jinha Jung, Akash Ashapure, Mahendra Bhandari
Publikováno v:
Current opinion in biotechnology. 70
Modern agriculture and food production systems are facing increasing pressures from climate change, land and water availability, and, more recently, a pandemic. These factors are threatening the environmental and economic sustainability of current an
Autor:
Juan Landivar, Jinha Jung, Henrique da Ros Carvalho, Murilo M. Maeda, Anjin Chang, Junho Yeom
Publikováno v:
Journal of Sensors, Vol 2020 (2020)
Canopy temperature is an important variable directly linked to a plant’s water status. Recent advances in Unmanned Aerial Vehicle (UAV) and sensor technology provides a great opportunity to obtain high-quality imagery for crop monitoring and high-t