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United States Department of Agriculture

Agricultural Research Service

Title: Remote Sensing Research in Louisiana Sugarcane

Authors
item Johnson, Richard
item Richard Jr, Edward

Submitted to: Sugar Bulletin
Publication Type: Trade Journal
Publication Acceptance Date: March 15, 2006
Publication Date: April 20, 2006
Citation: Johnson, R.M., Richard Jr., E.P. 2006. Remote sensing research in Louisiana sugarcane. Sugar Bulletin. 84(7):15-16.

Technical Abstract: Louisiana’s sugarcane producers and millers have been under increased economic pressure for the past several years. If the industry is to survive in the long term, then new technologies that maximize productivity and profitability must be identified and adopted. Several tests were initiated in 2005 to determine if leaf reflectance measurements could be used to determine disease presence, identify varieties, and predict sucrose levels. In the first test, leaf samples were collected at several dates before and after the appearance of visual symptoms from sugarcane yellow leaf disease (YLD) and mosaic test plots. Results showed that leaf reflectance could be used to correctly classify samples infected with YLD in 81% of the cases. The YLD-infected leaves also had lower levels of most plant pigments compared to non-infected controls. Samples exhibiting either mild or severe mosaic symptoms could also be correctly classified with leaf reflectance in 75 and 68% of the cases, respectively. In a second study, leaf samples were collected from plots in a historical sugarcane nursery containing seven generations of varieties selected for sucrose accumulation. The varieties were genetically diverse and spanned a time period of more than eighty years. Reflectance measurements were found to be effective in correctly identifying 80% of the varieties present in the study. In the final test, leaf samples were collected from the Sugarcane Research Laboratory 2005 first-stubble maturity study, which examines the natural ripening of released and soon- to-be released varieties, on three separate dates, ranging from early to late in the harvest season. Theoretically Recoverable Sugar (TRS) levels ranged from 134 to 317 lb/T. Leaf reflectance was effective at predicting TRS values in 77% of the cases in the combined data set. The successful development of remote sensing techniques would help growers identify yield limiting crop stress situations at earlier stages so that corrective actions could be taken in a timely and efficient manner. These techniques could also have a potential benefit to varietal development programs by allowing for increased accuracy and efficiency in varietal selection. Finally, growers and mills could potentially use a simple leaf sample taken in the field to develop harvest schedules that could aid in maximizing sugar yields.

Last Modified: 11/27/2014
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