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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: High-biomass sorghum yield estimate 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: Journal of Applied Remote Sensing (JARS)
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 13, 2011
Publication Date: May 11, 2011
Citation: Sui, R., Hartley, B.E., Gibson, J.M., Yang, C., Thomasson, J., Searcy, S.W. 2011. High-biomass sorghum yield estimate with aerial imagery. Journal of Applied Remote Sensing (JARS). DOI:10.1117/1.3586795, 5,053523.

Interpretive Summary: Relative to other crops, sorghum is an excellent choice for dedicated biomass production because it requires less water per unit dry biomass, and can produce very high biomass yields. There remains a need for technologies that will enable production of high-biomass sorghum at as low a cost as possible. Without these technologies, history dictates that this energy source will not be competitive with other energy sources. 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: 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: 9/21/2014
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