2009 Annual Report
1a.Objectives (from AD-416)
Objective 1: Develop a portable sensor and measurement systems to measure moisture in-shell and shelled peanuts during various post harvest processes.
Objective 2: Develop and maintain a database of peanut quality parameters and processing characteristics for commercial peanut varieties.
Objective 3: Develop peanut curing, transportation, and storage systems and management processes that maintain quality and minimize unit costs and quality deterioration during post harvest processing.
Objective 4: Expand the peanut curing decision support system to include new drying equipment and to support management of inventory from the field into the warehouse.
1b.Approach (from AD-416)
This research will be conducted over a five year period and will consist of laboratory and prototype scale testing. During year 1, runner type peanuts will be dried from various initial moisture contents to a final moisture content of approximately 11% using four levels of incident radiant energy in a laboratory scale catalytic infrared dehydrator. In-shell peanuts will be harvested and divided into five samples approximately 20 kg each. The initial moisture content of each of the samples will be determined using the oven method (ASAE S410.1). As a control, one sample will be dried using conventional forced air curing systems that heat the air 8C above ambient but no higher than 35C. The remaining samples will be dried using four different incident energy levels while recording pod surface temperature. Moisture content will be determined during drying by monitoring the sample mass. Drying will be terminated when the desired mass loss has occurred. The test will be repeated throughout the peanut harvest season, using peanuts with initial moisture contents ranging from 20 to 13%. Each sample will be shelled using a model sheller and kernels separated into commercial sizes to determine milling quality. The shelled peanuts will be subdivided into smaller samples to determine the vigor index, single kernel moisture distribution, and the presence/absence of off flavors. The single kernel moisture distribution will be measured using a Shizouka Seiki CTR-160P.Data will be analyzed using incident energy levels as drying treatments and tests replicated throughout the peanut harvest. The effect of the incident radiant energy on peanut drying time, milling quality, seed germination and vigor, and the incidence of off-flavors will be determined using analysis of variance.
Research was conducted to develop non-destructive methods for measuring peanut quality. A prototype sensor to measure peanut kernel moisture with the shells still intact was tested. In the same study, x-ray images of unshelled peanut samples were used to estimate farmer stock grade factors of percent foreign material, loose shelled kernels, kernels, and hulls. Samples of all four peanut market types (Runner, Spanish, Valencia, and Virginia) were obtained from each of the major peanut producing regions of the U.S. during the 2008 harvest. Grade factors were determined according to conventional methods and compared to estimates using the new sensors. As a result of testing, collaborators continue to develop and improve commercial prototype sensors for further testing. Basic research has been conducted to identify the bands of visible and near infrared light that can be used to measure peanut quality. Reflectance and absorbance of light in the near infrared and visible color spectrum has been measured on intact, unshelled peanut pods then correlated to various peanut kernel characteristics such as oil and moisture content. Preliminary experiments were conducted for matching the peanut pod color with the colors of the maturity profile board using both microscopic imaging (MI) and Near Infrared Red (NIR) analysis. While the MI techniques have to be further refined, the NIR reflectance spectra gave very encouraging results for both peanut kernels and pods. Research was performed to evaluate the use of low oxygen atmospheres for storing bulk farmer stock peanuts. Farmer stock peanuts were stored in 1/10th scale storage structures and flushed with nitrogen to produce and maintain low oxygen atmospheres. Moisture migration within the mass of peanuts caused mold formation at the peak and cost of nitrogen flushing was excessive with no apparent benefit in quality maintenance. In a second test, approximately 5000 lb of farmer stock peanuts were placed in a commercially available, hermetic storage container. Respiration processes within the flexible container rapidly consumed the oxygen (7 days) creating a low oxygen/high carbon dioxide atmosphere within the container. After a 6-mo storage period, peanuts were removed and excessive mold growth was observed on the top layer of peanuts within the container. PECMAN, the decision support system for managing commercial peanut curing operations, required few revisions in response to user feedback. User feedback indicated that approximately 200 – 300,000 tons of farmer stock peanuts are cured during the 2008 harvest using this software tool to reduce labor and improve drying facility management. A collaborating drying facility used PECMAN to record dryer performance data, then provided that data to researchers for analysis. As expected, these data showed that fuel consumption and dryer capacity was closely correlated to dryer airflow. As result of the test, a major peanut dryer manufacturer, modified the size of the drying container.
Peanut Combine Modified to Shell Peanuts During Harvest. Drying and shelling peanuts represent approximately 35% of the costs of processing peanuts for oil and biodiesel production. An existing peanut combine was modified to shell the peanuts while harvesting. By allowing the peanuts to dry in the windrow then harvesting and shelling peanuts, the total cost of growing, harvesting, and processing peanut for biodiesel reduced $0.75/gallon from $4.08 to $3.23/gallon.
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Kandala, C., Butts, C.L., Nelson, S.O. 2007. Determination of moisture content of in-shell peanuts by Parallel-Plate impedance measurements in cylindrical sample holder. Sensing and Instrumentation for Food Quality and Safety. 1:72-78. 2007
Butts, C.L., Lamb, M.C., Sheppard, H.T., Kandala, C. 2009. Using a Conveyor-Mounted Spout Sampler to Obtain Farmer Stock Grade Samples. Applied Engineering in Agriculture. 25(3):385-390. 2009.
Sundaram, J., Kandala, C., Butts, C.L. 2009. Application of Near Infrared (NIR) Spectroscopy to Peanut Grading and Quality Analysis: Overview. Sensing and Instrumentation for Food Quality and Safety. DOI: 1007/s11694-009-9081-5.