Location: Food Quality Laboratory
2012 Annual Report
Hyperspectral image analysis will also be used to examine three wheat milling properties: milling yield (% straight grade flour) defined as the percent by mass of all flour fractions recovered through a 94-mesh screen; solvent retention capacity in 50% (w/w) sucrose solution, a measure of the water affinity of the macro-polymers (starch, arabinoxylans, gluten, and gliadins); and solvent retention capacity in 5% (w/w) lactic acid, an indicator of gluten strength.
Near-IR spectroscopy will explored as a method for measuring the degree of waxiness in hexaploid wheat. Wild type, partial waxy (waxy null alleles in one or two genomes), and waxy samples (null alleles in all genomes), drawn from breeders' advanced lines of hexaploid wheat, will be used. Gel electrophoresis will be used to identify the waxy protein (granule bound starch synthase, GBSS) in each sample.
Lastly, a near-IR procedure for wheat gluten quality will be developed in conjunction with a rheological procedure. The wheat samples consist of approximately 50 lines grown in field replicated (3x) plots over three consecutive seasons. Half of these lines are transgenic, in which the gene construct modifies the length of the central repeat region within the high molecular weight (HMW) glutenin subunits. Different levels of gene expression, hence, level of glutenin protein, are represented as a function of the transgenic ancestor. Thus, this set will contain a much wider range in the ratio of glutenin-to-gliadin than naturally encountered. Flour from these samples will be evaluated for glutenin and gliadin contents by SE-HPLC another ARS laboratory. At Beltsville, the flour will be scanned in the NIR and FT-mid-IR regions. Rheological properties, such as the recovery response for a gluten specimen subjected to a controlled regiment of compressive force and hold time, will be measured at a third laboratory. Spectral calibrations for glutenin and gliadin concentrations, as well as calibrations for the rheological parameters (percent recovery and recovery time constant), will be developed using partial least squares regression. Additionally, classification algorithms (PLS discriminant analysis and SVM) algorithms will be developed that will identify the genetically modified lines based on their spectral response.
It has only been in the past decade that HSI has developed to the point where it can be used outside of research laboratories. Therefore, a review of first principles of quantum mechanics, light scatter, vibrational spectroscopy, and statistical regression was completed and described in a book chapter for the purpose of expanding this technology to agricultural food quality and safety inspection.
An on-the-fly digital imaging system was designed and fabricated that captures images of freefalling wheat kernels for inspection of defects. The novel aspects of this system include the simultaneous capture of three viewing angles of the object at very short exposure times (~1/30,000 sec) which yields freeze-frame style images that each collectively cover approximately 80% of the whole seed surface. Processing routines were developed that characterize each viewing angle of the kernel by its morphology (size and shape), texture (surface roughness), and boundary silhouette irregularity. The system was tested using a set of weather-damaged breeders samples of hard red and white wheat from a 2011 harvest. Damage conditions included moldy (Fusarium-infected) kernels, kernels with black tip, and sprouted kernels. The image features were subsequently fed into traditional classification algorithms that attempted to distinguish damaged kernels from sound ones. This real time imaging system is to be used in inspection operations and its principles may eventually be applied to online operations in flour mills for removing damaged and diseased kernels from the mainstream.
Morris, C.F., Delwiche, S.R., Bettge, A.D., Mabille, F., Abecassis, J., Pitts, M.J., Dowell, F.E., Deroo, C., Pearson, T.C. 2011. Collaborative analysis of wheat endosperm compressive material properties. Cereal Chemistry. 88:391-396.
Delwiche, S.R., Morris, C.F., Mabille, F., Abecassis, J. 2012. Influence of instrument rigidity and specimen geometry on calculations of compressive strength properties of wheat endosperm. Cereal Chemistry. 89(1):24-29.