Oilseed Processing

Oilseed-processing

Near Infrared Spectroscopy (NIR) is a widely accepted tool for quality control in the oilseed processing industry. Typical oilseeds include soybeans, rapeseed (canola), corn, sunflower, sesame and grape seeds.  Depending on the specific seed type, NIR can be used to optimize the extraction and monitor the production of the end products.

Globally, the most common oilseed is the soybean.  NIR analysis can help optimize the oil extraction process increasing the production of high value components and minimizing the energy and solvents needed in the extraction.  NIR analysis is also conducted on soybean meal, soybean hulls, and soybean “white flakes” to monitor milling and oil extraction processes. Another product of interest to the soybean processors is soy protein concentrate (SPC). Soy protein concentrate is produced by immobilizing the soy proteins in the defatted flakes while extracting the soluble carbohydrates during this process. The resulting product is approximately 70% protein. Other methods that can be used are wet chemistry and image analysis but , but these methods can require more time, dangerous chemicals, and are not as effective.

Rapeseed (canola) and sunflowers are also common oilseeds that are processed both for their oils but also for the meals and other by-products.

During the extraction process, seeds are crushed and the oil extracted, usually with a solvent.  Timely analysis of the meal can be used as inputs for process control to optimize the extraction and get the maximum amount of oil using the minimal amount of energy, solvent and time.

Many of the by-products from oilseed processing are sold on a specific quality basis, usually protein.  The meal and other by-products are used as protein sources in animal feed and other end uses.  Accurate monitoring of by-product production will minimize claims and maximize the return from these products.

NIR can be used as a quick, reliable analytical tool from intake to finished products.  Timely, accurate analytical data will provide the plant manager with the inputs needed to optimize the process and maximize profits.

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