Linda F. Benedict, Lu, Shyue
Biofuel production is an extensive process that involves developing a biological feedstock, processing and treating the feedstock, and producing and refining fuels and chemicals from the feedstock. In every step of the process, analytical quantifications are needed to maintain efficacy. Research has shown near infrared spectroscopy to be an ubiquitous analytical technique that could fulfill this need. This tool can be calibrated to identify and quantify most, if not all, of the components of interest of both solid and liquid samples from feedstock to final product with usable results obtainable within a matter of minutes. The versatile and adaptive nature of this analysis makes it well suited for the critical needs of biofuel and biochemical production at every stage.
Spectroscopy is a common analytical technique that has been studied since the 17th century. It involves the use of light from any part of the electromagnetic spectrum to reveal information about a sample. Near infrared spectroscopy specifically uses light just past red of the visible spectrum. When infrared light hits sample matter, it causes vibrations in the bonds between atoms. These vibrations can be detected as peaks, including a first fundamental peak and several resonating peaks that follow. The fundamental peaks occur in the mid infrared range and can be directly associated with a chemical component. Near infrared spectroscopy, however, focuses on the smaller resonating peaks and the combinations of peaks that occur from overlapping resonating peaks of different chemical components. This technique is unique in spectroscopy in that you cannot directly associate a peak to a specific chemical component because there is just too much information in the spectra from the scan.
Until the 1990s, near infrared spectroscopy was obscure and rarely used because it was nearly impossible to get usable data out of its spectra. However, with the development of mathematical algorithms called chemometrics, the information-saturated spectra became not only usable, but an asset. With increasingly advanced computing power, chemometric software can use laboratory data from primary analysis methods to decode near infrared spectra of a sample and create calibration models. These calibration models can then be used to quickly analyze unknown samples.
Since the development of chemometric software, near infrared spectroscopy applications have been rapidly expanding into a variety of fields including chemistry, textiles, pharmaceuticals, industrial process control and agriculture. Examples of use in these fields include identifying chemicals such as water, alcohols, and proteins; differentiating polymeric fibers in textiles; quality control in pharmaceutical drugs; and ensuring industrial processes are on track.
The agricultural industry makes extensive use of near infrared spectroscopy technology. For example, fruits and vegetables are scanned intact without any destructive sample preparation to determine properties such as sugar content, dry matter percentage and acidity. Sugarcane is an agricultural crop commonly characterized with near infrared spectroscopy for qualities important in sugar crystallization and used to calculate theoretical recoverable sugar.
Many potential biofuel feedstocks are agricultural products or byproducts. At the LSU AgCenter, biofuel research is focused on sweet sorghum and energycane. These particular feedstock sources provide energy in two forms: readily available fermentable sugars in expressed juice and complex sugars tied up in the fibrous material referred to as lignocellulosic sugars that require further processing. Near infrared spectroscopy is the technique chosen to characterize raw feedstock and determine how much sugar is potentially available for fermentation.
Analytical laboratory techniques are already available to provide primary analysis data to develop near infrared calibration models for components in the juice, including sugars and ash, and components in the fiber, including cellulose, lignin and ash. The process for obtaining this data is time consuming and requires advanced training; thus, it is not a viable solution for analyzing a large number of samples. With the addition of near infrared spectroscopy, it is possible to analyze a smaller number of samples with traditional methods, build near infrared spectroscopy calibration models with that data, and analyze the majority of samples using only a near infrared spectroscopy scan.
The process for obtaining a scan of sweet sorghum or energycane begins with feeding 10 pounds of whole, hand-harvested material into a hammer mill shredder. This material travels via conveyer belt into a homogenizer, which mixes the sample material and packs it into a “cake” to remove any gaps. This sample “cake” travels past the transmission head, which records multiple scans of the material and creates an average spectra representative of the sample’s response to near infrared light. This process happens within one to two minutes per sample and results can be immediately obtained from the chemometric software. Being able to obtain characteristic data this quickly on a large number of samples allows agronomists to more effectively make decisions in breeding and developing feedstock best suited for the needs of biofuel production. This rapid analysis can also be used to determine payment scales for feedstock growers based on the quality of the crops being sold.
While feedstock may be the primary application focus of near infrared spectroscopy in the early stages of biofuel production, it has applications throughout the process. Benchtop versions of near infrared spectroscopy instrumentation allow for the scanning of small liquid and solid samples. Any intermediate samples from the process can be monitored for consistency. For example, fermentation products can be analyzed for the amount of butanol available for purification. Final products can also be analyzed for purity and identification of common contaminants. Coupling the analytical abilities of near infrared spectroscopy with powerful advances in chemometric computing allows for useful applications throughout the biofuel and biochemical production process.
Shyue Lu is a research associate at the Audubon Sugar Institute in St. Gabriel.
(This article was published in the spring 2015 issue of Louisiana Agriculture Magazine.)