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United States Department of Agriculture

Agricultural Research Service

Research Project: DEVELOP, ENHANCE AND TRANSFER GIN TECHNOLOGY TO IMPROVE FIBER QUALITY AND PROFITS

Location: Cotton Ginning Laboratory(Stoneville, MS)

Title: Yield mapping of high-biomass sorghum with aerial imagery

Authors
item Sui, Ruixiu
item Hartley, Brandon -
item Gibson, John -
item Yang, Chenghai -
item Thomasson, J. Alex -
item Searcy, Stephen -

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: August 26, 2010
Publication Date: September 7, 2010
Citation: Sui, R., Hartley, B.E., Gibson, J.M., Yang, C., Thomasson, J., Searcy, S.W. 2010. Yield mapping of high-biomass sorghum with aerial imagery. In Proceedings of ASABE Annual International Meeting (ASABE). Paper No. 1008833. June 20-23, 2010, Pittsburgh, PA.

Interpretive Summary: Remote sensing is a promising technology for many aspects of sorghum production management. Earlier studies on the relationships between the plant canopy spectral and thermal features and physiological characteristics have provided solid fundamentals upon which further research can build. However, using remote sensing in high-biomass sorghum presents several challenges. While traditional sorghum production is concerned with maximizing grain yield, the goal with high-biomass sorghum is maximizing total biomass. Thus, procedures in the literature that relate plant spectral features and various stress indices to grain yields will require reexamination and refinement. Objectives of this study were to compare high-biomass sorghum yield to aerial multispectral imagery and develop predictive relationships. A high-biomass sorghum field was selected as a study site, and aerial multispectral images were acquired with a four-camera imaging system. Sorghum plant samples were collected at predetermined geographic coordinates to determine biomass yield. Aerial images were processed to find relationships between image reflectance and yield of the biomass sorghum. Results showed that sorghum biomass yield in early August was closely related to spectral reflectance and could be estimated well even with a model involving only NIR/Red band-ratio. The eventual outcome of this work could lead to predicted-yield maps based on remotely sensed images, which could be used in developing field management practices to optimize yield and harvest logistics.

Technical Abstract: To reach the goals laid out by the U.S. Government for displacing fossil fuels with biofuels, agricultural production of dedicated biomass crops is required. High-biomass sorghum is advantageous across wide regions because it requires less water per unit dry biomass and can produce very high biomass yields. However, in order to make biofuels economically competitive with fossil fuels it is essential to maximize production efficiency throughout the system. The goal of this study was to use remote sensing technologies to optimize the yield and harvest logistics of high-biomass sorghum with respect to production costs based on spatial variability within and among fields. Specific objectives were to compare yield to aerial multispectral imagery and develop predictive relationships. A 19.2-ha high-biomass sorghum field was selected as a study site, and aerial multispectral images were acquired with a four-camera imaging system on July 17, 2009. Sorghum plant samples were collected at predetermined geographic coordinates to determine biomass yield. Aerial images were processed to find relationships between image reflectance and yield of the biomass sorghum. Results showed that sorghum biomass yield in early August was closely related (R2=0.76) to spectral reflectance and could be estimated well (R2=0.71) even with a model involving only one band ratio of NIR to Red. The eventual outcome of this work could lead to predicted-yield maps based on remotely sensed images, which could be used in developing field management practices to optimize yield and harvest logistics.

Last Modified: 7/30/2014
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