Location: Food Quality Laboratory2019 Annual Report
1: Enable new or refine commercial optical, viscometry and physical technologies that integrate indicators of starch soundness in wheat and barley. A. Identify sources of variation in viscometry-based methodologies (e.g., falling number) that are used to indicate starch soundness, then develop and test alternative procedures to reduce precision error. B. Develop a near-infrared spectroscopy model, or alternatively a Raman spectroscopy model, for ascertaining mixture levels of conventional and waxy hexaploid wheat. 2: Enable new, real-time rapid optical methods to measure defects and vitreousness in commercial wheat kernels. A. Develop hyperspectral imaging procedures for identification of wheat kernels damaged by scab (Fusarium head blight), black point, heat, and frost, as defined by official inspection criteria. B. Develop imaging system for assessing the percentage of vitreous kernels in durum and hard red spring wheat.
Determine the underlying precision of the falling number procedure under ideal conditions, that is, the test when run with samples for which sampling error has been minimized. Samples of soft white wheat and three samples of club wheat that are representative pre-harvest sprouting will be evaluated. Within each subclass, the three samples are designed to be representative of low (< 300 s), moderate (300-375 s), and high (> 375 s) falling number. All thermal conditions of the falling number instrument within a test day will be held constant as practicable, including the starting temperature of the meal-water mixture, the temperature of the instrument’s bath, the volume of water within the bath, and the mass and volume of the meal-water test sample. In addition to the runs that are based on the conventional amount of meal and water (treatment A: 7 g + 25 mL), three alternate preparations will be examined. Treatment (A, B, C, D) and wheat class or subclass (SWW, Club) will be specified as fixed factors. Samples within wheat class, grind, and portions will be specified as random factors. Minimum-width 95% confidence intervals for the variance estimates will be calculated as wil best linear unbiased predictors (BLUPs) obtained from the mixed model provide estimates of FN averages for each treatment and wheat class sample. Once the precision of the FN method under standard and modified conditions has been established, the research will proceed in two tacks. First, the issue of sampling error will be addressed. Sampling will occur at typical transfer points, such as the truck dump bin at the country elevator, railcar fill sites, and the entry point to the mill. Second, if under standard operation the procedure produces coefficients of variation greater than 3%, modifications to the mixing and heating stage will be explored in an attempt to reduce air bubble entrainment, with rheological measurements (conducted in parallel) performed using a rheometer under constant shear and heating rate conditions. NIR calibrations for mixture levels of conventional and waxy wheat will be developed with accuracies < 5%. Both Linear and non-linear quantitative modeling will be performed on both whole kernel and ground meal binary mixtures. In hyperspectral imaging research of wheat kernels for damage or vitreousness, PCA will be examined to identify the wavelengths at local minima and maxima which inherently possess the greatest contrast. The 10 most sensitive wavelengths will be examined in paired combinations exhaustively (45 trials) using reflectance ratios. Linear discriminant analysis will be used to identify the wavelength pair whose image band ratio produces the greatest percentage of correctly classified kernels, and so on for the next pair. Three regions of interest (ROI) on the kernel, namely the endosperm, germ, and entire kernel, will be separately examined. With each ROI, image processing will be done at the pixel level, whereby subregions of damage in the ROI are first identified; then, depending on the size of the subregion, a decision will be made on whether to categorize the ROI and/or the kernel as normal or damaged.
Significant progress was made in the objectives of this project, which falls under National Program 306, Component 1, Problem Statement 1.A: Define, Measure, and Preserve/Enhance/Reduce Attributes that Impact Quality and Marketability. At the request of USDA-Federal Grain Inspection Service (FGIS) a study began in fall 2018 on developing a standard material for use in falling number instruments for eventual control charting operations of networked instruments. (Falling number is the name given to a wheat quality test that measures viscosity of a heated mixture of ground wheat and water. Viscosity is strongly influenced by alpha-amylase, the enzyme that breaks down starch into smaller chain molecules and, eventually, into glucose. Excessive enzyme activity translates into poor product quality.) We devised a protocol and selected a standard material to be used in an 8-week pre-collaborative study, which upon successful conclusion, could become the blueprint for an interlaboratory study to establish accuracy and precision limits, and eventually become a standard for periodic evaluation. Pure corn starch was tested at weekly intervals. Six instruments were used during the experimentation period of early November 2018 to late January 2019. Results indicate that while a date effect is statistically significant, it is small and otherwise not relevant and does not trend toward either low or high falling number with storage time. Small modifications to the protocol were discussed with FGIS, in anticipation of the full interlaboratory study in the coming year. Stemming from the results of the pre-collaborative study, in which we noticed more variation in falling number with pure corn starch than with wheat meal (the material of normal testing), we decided to examine other starches in just one laboratory. That wheat meal was not considered a good candidate for a material standard, despite producing low variability in falling number at a single time instant (i.e., a day), has to do with the unstable nature of the meal over an extended time period (months, years). Hence, other starch or starch-like materials were considered, with the criteria being 1) food-grade substance, 2) be directly operable with falling number equipment, 3) produce repeatability precision comparable or better than wheat meal, and 4) have a 1-year minimum shelf life. Four native (unmodified) starches, wheat, corn, potato and rice, were obtained from a laboratory chemical supplier. As of early summer 2019, 10 weekly runs of these four starches have been repeatedly collected on two instruments as part of a 3-month study. Preliminary findings indicate that rice and corn starches are most promising in giving consistent (low variability) results, while potato starch is most variant. In the remaining months of this fiscal year, these starches will also be characterized experimentally for amylase activity, amylose/amylopectin ratio, protein and ash contents (with both contents expected to be nil). We completed the second and final year of a study on how falling number may be affected by the terrain in which the wheat plant grows. This is of especial interest for field owners in U.S. Pacific Northwest, particularly eastern Washington and northern Idaho, who cultivate hillier areas than other wheat producing areas in the country and are also more prone to the late-maturity amylase (LMA) condition. We hypothesized that microclimate variation within a field due to differences in elevation and solar exposure could result in differences in falling number within the same field. If such differences occur, then local (sub-field) topographical data could be used to make decisions on segregating potentially low falling number wheat from susceptible regions. In two consecutive seasons, six large fields in commercial production were studied to reveal possible effects of elevation and solar exposure on falling number. Between 17 and 21 geospatially referenced sites from each field were selected based on prior satellite imagery representing the greatest diversity in topography within the respective field. Elevation, slope, and aspect were determined through referencing land coordinates to government (USGS) elevation datasets and commercial geospatial software. Theoretical direct solar radiation flux energy increments were summed over the growing period. Findings indicate that for five of the six fields an elevation effect on falling number was not significant despite a variation by as much as 50 m within a field. Direct energy flux was positively correlated with falling number for two fields (r = 0.48 to 0.69) in the first season, but negatively correlated for one field in the second season (r = -0.51). However, even in cases when energy flux or elevation trends were significant, these effects were minor. Therefore, we conclude that in circumstances of favorable weather conditions, as which occurred for the two years studied, in-field segregation of wheat during combining is not necessary. Lastly for falling number, we initiated a study on how the cause of low falling number (high amylolytic activity) wheat can be determined. Two weather conditions are known to cause the condition: pre-harvest sprouting (PHS), in which rainy cold conditions right before harvest causes the seed on the spike to break dormancy; and LMA, in which large daily temperature fluctuations during the period of grain fill cause alpha-amylase activity to rise but do not affect the activities of proteolytic and lipolytic enzymes involved in germination. Because the former condition affects end-product quality more severely than the latter, a rapid method to distinguish between the two conditions (currently not available) is desired by the wheat processing industry. We conducted a preliminary study using a programmable viscometer to accentuate differences in the viscosity profiles between two wheat samples, one of which possessed naturally low falling number due to PHS, and the other that was originally of high falling number but spiked with barley malt amylase to reduce the falling number to be the same as the first sample. The differences were established using an 18% (v/v) ethanol solution instead of pure water and a reduced maximum hold temperature of 85 ºC (instead of the default 95 ºC). We are currently collecting wheat samples that represent both low falling number conditions naturally, which will allow us to perform viscometry studies in which solute:solvent ratio, heating, holding, and cooling profile, and shearing rate will be optimized for separating the two conditions. In addressing the project’s second objective, we completed a study on the development of hyperspectral imaging (HSI) for evaluation of mold damage in wheat kernels, particularly that caused by scab, also known as Fusarium head blight (FHB). FHB is among the most common fungal diseases affecting wheat, resulting in decreased yield, low-density kernels, and production of the mycotoxin deoxynivalenol, a compound toxic to humans and livestock. Human visual analysis of representative wheat samples has been the traditional method for FHB assessment in both official inspection and plant breeding operations. While not requiring specialized equipment, visual analysis is dependent on a trained and consistent workforce, such that in the absence of these aspects, biases may arise among inspectors and evaluation dates. This research was intended to avoid such pitfalls by using longer wavelength radiation than the visible using hyperspectral imaging (HSI) on individual kernels. Linear discriminant analysis models to differentiate between sound and scab-damaged kernels were developed based on mean of reflectance values of the interior pixels of each kernel at four wavelengths (1100, 1197, 1308, and 1394 nm). Other input variables were examined, including kernel morphological properties and histogram features from the pixel responses of selected wavelengths of each kernel. Although we demonstrated that HSI is successful in estimating fusarium damage, the degree of success is limited to the inherent level of subjectivity associated with reference methodology, which currently remains visual analysis.
1. New software for grain quality evaluation. Collaborative studies among grain researchers rigorously determine the within- and among-laboratory variation of analytical procedures used industry-wide for grain quality evaluation and facilitates modification to these procedures when required. A scientist in Beltsville, Maryland, developed a computer program that exhaustively calculates the statistical figures of merit of these collaborative studies using definitions supplied by the International Union of Pure and Applied Chemists (IUPAC). The program systematically evaluates multi-laboratory datasets for outlying laboratories and samples and determines repeatability and reproducibility statistics that measures testing rigor across laboratories. The program was made available to the cereals research community (AACC International) and serves as an important tool for collaborative studies in the cereals research community, thus replacing manual calculation.
Delwiche, S.R., Torres Rodriguez, I., Rausch, S.R., Graybosch, R.A. 2019. Estimating percentages of fusarium-damaged kernels in hard wheat by near-infrared hyperspectral imaging. Journal of Cereal Science. 87:18-24.
Delwiche, S.R., Stommel, J.R., Kim, M.S., Esquerre, C. 2019. Hyperspectral fluorescence imaging for shelf life evaluation of fresh-cut Bell and Jalapeno Pepper. Scientia Horticulturae. 246:749-758.