Franklin E. Barton

Prediction of cooked rice texture quality using near-infrared reflectance analysis of whole-grain milled samples

ABSTRACT Rice quality is based on chemical and physical properties affecting its appearance, flavor, and texture characteristics. Sensory quality can be assessed by a combination of descriptive sensory and physicochemical property evaluations. The purpose of the present study was to assess the potential of near-infrared reflectance spectroscopy (NIRS) and NIRS in combination with other physicochemical measurements for the determination of sensory texture attributes in whole-grain milled rice samples. Six rice samples representing combinations of variety and growing locations received treatments of two degrees of milling and five drying conditions to achieve final moisture levels of 12 or 15% (n = 120). Quality measurements of the cooked rice included sensory and instrumental texture analyses. Quality measurements of the uncooked rice included amylose and protein (chemical reference), whiteness, transparency, and degree of milling (appearance units of milled rice), and NIRS analyses. Partial least squares ...

Predicting protein content by near infrared reflectance spectroscopy in diverse cereal food products.

Simultaneous determination of constituents (e.g. dietary fibre, protein, fat) by near infrared (NIR) spectroscopy would increase the speed and efficiency of nutrient analysis while substantially reducing the cost. Previous work has described the development of NIR reflectance models for the prediction of dietary fibre in a diverse group of cereal food products. While NIR spectroscopy has been used to measure protein content in cereal samples comprised of a single grain type, the utility of the NIR technique would be greatly improved if it could be expanded to cereal products derived from a diverse cross-section of grains and formulations. The present study was conducted to investigate the potential of NIR spectroscopy for the analysis of protein in a data set that included products with numerous grains, such as wheat, oats, rice, rye, corn, millet, buckwheat and with a wide range of fat, sugar and fibre contents. In addition, numerous processing techniques and food additives were represented in the data set. Nitrogen content of dry-milled cereal products was measured by combustion analysis (AOAC Method 992.23) and the range in nitrogen values was from 0.65 to 3.31% of dry weight. Milled cereal products were scanned from 1100 to 2500nm with a scanning monochromator. A nitrogen calibration was developed, using a commercial analysis program, with modified partial least squares as the regression method. The standard error of cross validation and R2 for nitrogen (n=147 calibration samples) were 0.090% and 0.973, respectively. Independent validation samples (n=72) were predicted with a standard error of performance of 0.079% nitrogen and r2 of 0.984. Because of the diversity of grains in the data set, crude protein was calculated using two nitrogen-to-protein conversion methods and two PLS models were developed for the prediction of crude protein. Crude protein was predicted with a similar precision to nitrogen and the results for both protein models are within the precision required for US nutrition labelling legislation. In conclusion, NIR reflectance spectroscopy can be used for rapid and accurate prediction of nitrogen and crude protein content in a heterogeneous group of cereal products comprised of a wide cross-section of grains and formulations.

Fluorescence Spectroscopy for Rapid Detection and Classification of Bacterial Pathogens

This study deals with the rapid detection and differentiation of Escherichia coli, Salmonella, and Campylobacter, which are the most commonly identified commensal and pathogenic bacteria in foods, using fluorescence spectroscopy and multivariate analysis. Each bacterial sample cultured under controlled conditions was diluted in physiologic saline for analysis. Fluorescence spectra were collected over a range of 200–700 nm with 0.5 nm intervals on the PerkinElmer Fluorescence Spectrometer. The synchronous scan technique was employed to find the optimum excitation (λex) and emission (λem) wavelengths for individual bacteria with the wavelength interval (Δλ) being varied from 10 to 200 nm. The synchronous spectra and two-dimensional plots showed two maximum λex values at 225 nm and 280 nm and one maximum λem at 335–345 nm (λem=λex + Δλ), which correspond to the λex=225 nm, Δλ=110–120 nm, and λex=280 nm, Δλ=60–65 nm. For all three bacterial genera, the same synchronous scan results were obtained. The emission spectra from the three bacteria groups were very similar, creating difficulty in classification. However, the application of principal component analysis (PCA) to the fluorescence spectra resulted in successful classification of the bacteria by their genus as well as determining their concentration. The detection limit was approximately 103–104 cells/mL for each bacterial sample. These results demonstrated that fluorescence spectroscopy, when coupled with PCA processing, has the potential to detect and to classify bacterial pathogens in liquids. The methology is rapid (<10 min), inexpensive, and requires minimal sample preparation compared to standard analytical methods for bacterial detection.

Two-Dimensional Vibration Spectroscopy of Rice Quality and Cooking

ABSTRACT Rice samples were taken from a study of rice milling properties that affect quality. The spectra of milled and cooked samples were taken in the near-infrared, mid-infrared, and Raman region. These spectra, two regions at a time, were regressed by a two-dimensional technique to develop contour maps that indicated the correlation of two spectral regions. These relationships demonstrate that it is possible to recognize the hydration effects caused by gelatinization (cooked samples vs. milled rice). Three water (O-H stretch) spectral bands (960, 1445, 1,930 nm) in the near-infrared (NIR) show marked differences between milled and cooked rice. The difference spectra indicated that there were additional phenomena occurring besides the addition of water. These differences are apparent in both C-O-H and N-H bands, which indicate that water is interacting with both starch and protein. The two-dimensional technique developed in this laboratory was used to get a better interpretation of what occurs during c...

Optimal Geometries for the Development of Rice Quality Spectroscopic Chemometric Models

ABSTRACT Three sample geometries, two different instrument types, and two spectral collection modes (reflectance and transmission) were used to assess rice quality and develop chemometric models for composition and sensory characteristics. Rice samples (120) including three cultivars, two growing locations, five drying treatments, two moisture levels, and two levels of milling were scanned in two locations. Data collected for modeling included amylose, protein, moisture, whiteness, transparency, and milling degree. Taste and texture were determined with the use of separate trained sensory panels. The NIR models show that composition is best modeled in the 1,100–2,500 nm range, while the physical properties of whiteness, transparency and milling degree are best modeled in the 750–1,050 nm range. Additional models were developed using limited data subsets of the spectral data points. In some cases, adequate models were generated with as few as 20 wavelength data points. Results show that no one spectroscopi...

Chemistry of lignocellulose: Methods of analysis and consequences of structure

Abstract Historically, the chemistry of lignocellulose has been the chemistry of the extraction, solvolysis, hydrolysis and analysis of cellulose and lignin from plant material. The analyses used to determine their relative content are empirical, i.e., the value of the cell wall preparation is defined by the conditions used rather than a molecular entity. As a result, there is great difficulty in comparing the results of analyses of one type of plant to another. This review looks at the ways in which cellulose, lignin and lignocellulose have been chemically isolated and determined and at some of the instrumental methods which can more completely characterize the plant cell wall.

Comparison of Responses of 13C NMR and NIR Diffuse Reflectance Spectroscopies to Changes in Particle Size and Order in Cellulose

High-resolution solid-state 13C NMR and NIR diffuse reflectance spectra were obtained on microcrystalline and “noncrystalline” celluloses. Particle sizes and relative crystallinity were confirmed by scanning electron microscopy and MIR transmission spectroscopy, respectively. The results showed that NMR is more sensitive to order changes and less sensitive to particle size. NIR reflectance, on the other hand, is very sensitive to particle size changes and essentially insensitive to differences in order.

Modified flax fibers reinforced soy-based composites: mechanical properties and water absorption behavior

Flax fibers are often used in reinforced composites which have exhibited numerous advantages such as high mechanical properties, low density and biodegradablility. On the other hand, the hydrophilic nature of flax fiber is a major problem. In this study, we prepare the soybean oil based composites reinforced with protein coated and lipid acylated flax fibers and compare their water uptake properties. Results showed that water resistance properties of the composites are improved where treated flax fibers are used. The composite with lipid acylation of the flax fiber exhibited to enhance tensile strength and water resistance properties. Influences of fiber length, fiber loading and pressure on mechanical properties are also reported.

The use of near infrared reflectance spectroscopy to predict the insoluble dietary fibre fraction of cereal products

The insoluble and soluble fractions of dietary fibre have different human physiological effects and their presence in foods is of interest to consumers, the medical community and the cereal product industry. The development of a model, using near infrared (NIR) reflectance spectroscopy, to predict insoluble dietary fibre in a wide range of dry-milled cereal products and grains is described. The products included breakfast cereals, crackers, brans, pastas and flours. Insoluble dietary fibre was measured by the AOAC enzymatic–gravimetric procedure (AOAC 991.43). The range in insoluble dietary fibre was 0–48%. Near infrared reflectance spectra were obtained with a scanning monochromator and data analysed with a commercial analysis program. A calibration (n = 90) was developed for prediction of insoluble dietary fibre using preprocessed spectra and modified partial least squares regression. The standard error of cross validation and R2 were 1.34% and 0.99, respectively. The model was tested with independent validation samples (n = 32) and the resulting standard error of performance and r2 were 1.13% insoluble dietary fibre and 0.99, respectively. The results show that NIR spectroscopy can be used to predict the insoluble dietary fibre content in a wide variety of processed and unprocessed cereal products.