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United States Department of Agriculture

Agricultural Research Service


Location: Sugarcane Research Unit

Title: Use of precision agriculture techniques for sugarcane pathology studies

item Grisham, Michael
item Johnson, Richard
item Viator, Ryan
item Zimba, Paul

Submitted to: Sugar Journal
Publication Type: Trade Journal
Publication Acceptance Date: June 20, 2008
Publication Date: June 20, 2008
Citation: Grisham, M.P., Johnson, R.M., Viator, R.P., Zimba, P.V. 2008. Use of precision agriculture techniques for sugarcane pathology studies. Sugar Journal. 71(1):24,27.

Technical Abstract: While resistance is the most effective and economical method of controlling diseases in sugarcane, in some situations, varieties must be grown that are susceptible. For example, following the introduction of a new disease, it may take several years before resistant varieties replace susceptible ones; while for other diseases such as mosaic and leaf scald, new races or strains of the pathogen may arise that can attack previously resistant varieties. Also, identifying resistance to some diseases is challenging because artificial inoculation of the pathogen during disease screening tests is difficult. The Sugarcane yellow leaf virus (SCYLV), for example, is transmitted from a diseased plant to a healthy plant only by aphid vectors. Consequently, other crop management practices that may reduce the impact of disease on susceptible varieties need to be examined. Researchers frequently use replicated, small-plot experiments to measure differences in yield between infected and diseased plants; however, these studies often provide an incomplete picture of what happens in a commercial field as various environmental conditions and cultural practices may influence the incidence and severity of disease out breaks. For this reason, a team of scientists at the USDA-ARS Sugarcane Laboratory in Houma, LA, USA has been conducting research that incorporates new techniques that are not commonly used in plant pathology research such as the application of precision agriculture grid soil sampling, spatial statistical analysis, and remote sensing. In addition, when possible these experiments have been conducted in commercial fields. We recently utilized these new techniques to study the incidence and severity of brown rust (Puccinia melanocephala) infestations in five commercial fields of the susceptible variety, LCP 85-384. A handheld computer equipped with a GPS (global positioning system) receiver and mapping software was used to determine experimental field boundaries and establish grid-sampling points. Field size varied from 0.7 to 8.9 hectares, and grid size varied from 0.02 to 0.4 hectares. Soil samples (0-15-cm) were taken at each grid-sampling point, in addition to weekly rust ratings from mid-May to late June. Rust rating was based on 1 = yellow flecks; 5 = moderate number of pustules, slight premature necrosis of lower leaves; and 9 = numerous pustules, extensive leaf necrosis. Soil properties determined from each sample included soil organic matter, soil pH, soil buffer pH, exchangeable cations (Ca, Mg, K), soil cation exchange capacity (CEC), soil phosphorus, and soil sulfur. Experimental plots were harvested green utilizing a single-row, chopper harvester. The total weight of harvested cane in each plot was determined using a single-axle, high-dump billet wagon equipped with three electronic load sensors and a device to collect a billet sub-sample from each plot for sucrose quality analysis via the prebreaker/press method. Soil properties, rust ratings, and cane yield varied significantly among the sampling points within fields and also between fields. In addition, overall fertility levels of each location were variable. To analyze more closely the interrelation of these factors, contour maps of soil properties, rust levels, and sugar yield were generated (Fig. 1). Rust ratings were found to be positively correlated with several soil properties, most notably phosphorus and sulfur (Fig. 1). In this figure, the darker colors are associated with high rust levels and high phosphorus or sulfur. The figures illustrate that higher rust ratings were found in the areas of the field with high phosphorus and sulfur. These correlations were even more pronounced when phosphorus and sulfur were present at excessive levels. Sucrose and cane yields were negatively correlated to the rust ratings, with higher rust levels (darker colors) causing reduced yields (lighter colors) even in areas of excess nutrition. These combined data suggest that sugarcane growers that apply fertilizer at rates exceeding plant requirements may increase the incidence and severity of rust infestations in their fields. Remote sensing is another new tool that we are applying to sugarcane pathology research. A broad definition of remote sensing is the acquisition of information about an object with a device that is not in physical contact with the object being measured. For agricultural research applications, the acquisition of information may be large scale such as data collected by devices mounted in airplanes or satellites, or small scale where data is collected by devices that may be within a few centimeters or several meters of the target object. In our study, we identified plants infected with either SCYLV or Sorghum mosaic virus (SrMV), the virus that causes mosaic, and noninfected plants using RT-PCR (reverse transcription, polymerase chain reaction) methodology. We also measured reflectance of sugarcane leaves from these plants from 350 to 850-nm using a fiber optic spectrometer mounted 3 cm above the leaf. Leaves were then analyzed for differences in leaf pigments associated with the spectral measurements using HPLC (high-performance liquid chromatography). With both virus diseases, differences in the spectral patterns between diseased and healthy leaves were associated with differences in the concentrations of leaf pigments. In Louisiana, sugarcane plants infected with SCYLV rarely exhibit symptoms of sugarcane yellow leaf disease. From analysis of leaf reflectance measurements, leaves exhibiting either mild or severe mosaic symptoms could be correctly classified in 75 and 68% of the cases, respectively; and leaves infected with SCYLV were correctly identified 77% of the time even though no visible symptom of yellow leaf was expressed (Fig. 2). Precision agriculture techniques offer unique opportunities to conduct sugarcane pathology experiments under production conditions, to investigate interactions with environmental conditions and cultural practices, and, in some situations, to conduct investigations where more traditional methods are not possible. For example, the type of studies that can be conducted on brown rust is limited because establishing the disease in the field through artificial inoculation is difficult. However, with precision agriculture sampling techniques and spatial statistics, we were able to conduct our experiments in production fields where the disease developed under natural infection and, from the results, recommend management practices to minimize the impact of the disease. Similarly, remote sensing provides an alternative method of disease diagnosis and detection that offers a practical and economical method of monitoring disease development.

Last Modified: 4/16/2014
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