38 / 45
Page 106
conferenceseries
.com
Volume 07
Advances in Crop Science and Technology
ISSN: 2329-8863
Agri 2019
August 15-16, 2019
August 15-16, 2019 | Rome, Italy
14
th
International Conference on
Agriculture & Horticulture
Validation of agronomic UAV and field measurements for tomato varieties
Juan Enciso, Jinha Jung, Carlos Avila, Anjin Chang
and
Junho Yeom
Texas A&M AgriLife Research, USA
U
nmanned 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 by screening varieties or by selecting agronomic traits that confer biotic and abiotic stresses and
selecting the best management practices that optimize the management of soil and water resources. The main objectives of
this study were to assess the potential use of UAVs to determine crop height, canopy cover, and NDVI during the tomato
growing season for eight tomato varieties; to validate tomato height obtained with a UAV; and evaluate the correlation
between leaf area index and canopy cover determined with the UAV. This study was conducted at the Texas A&MAgriLife
Research and Extension Center located inWeslaco, TX. The UAV was flown over a tomato trial planted with 90 plots that
contained eight different tomato varieties; 3 roma (DRP8551, SV8579TE, and Tycoon) and 5 round (Mykonos, TAM-
Hot, Shourouq, TAMH FlA F1, Everglade) replicated three times per row and planted in three rows. The plots of the
tomato varieties Mykonos and DRP-8551 were duplicated so plants could be removed and destroyed to collect biomass
data. Commitment field measurements of plant height, leaf area index, and NDVI were collected weekly (from April 27
to June 22, 2017). All the tomato varieties were healthy without diseases and the NDVI values estimated with the UAV
peaked between 90 and 110 days after planting. A coefficient of determination of 0.72 was observed between canopy cover
estimated with the UAV and leaf area index measured with the ceptometer. The UAV data of crop height was fitted to
sigmoid curve and the coefficient of correlation was 0.9966. In addition, the calculated Fisher’s paired t test statistic showed
no significant difference (P ≤0.05) between the estimated, the UAV and manually measured crop heights. In the future,
UAV crop growth and NDVI monitoring could be improved through temporally dense data acquisition, increasing the
number of ground samples and their geometric coincidence with the grids in UAV images, removal of weather effects, and
other systematic errors caused from image quality and grid size.
juan.enciso@ag.tamu.eduAdv Crop Sci Tech 2019, Volume 07