American Association of Cereal Chem- ists/AOAC collaborative study was conducted to evaluate the accuracy and reliability of an enzyme assay kit procedure for measurement of total starch in a range of cereal grains and products. The flour sample is incubated at 95°C with thermostable α-amylase to catalyze the hydrolysis of starch to maltodextrins, the pH of the slurry is adjusted, and the slurry is treated with a highly purified amyloglucosidase to quantitatively hydrolyze the dextrins to glucose. Glucose is measured with glucose oxidase-peroxidase reagent. Thirty-two collaborators were sent 16 homogeneous test samples as 8 blind duplicates. These samples included chicken feed pellets, white bread, green peas, high- amylose maize starch, white wheat flour, wheat starch, oat bran, and spaghetti. All samples were analyzed by the standard procedure as detailed above; 4 samples (high-amylose maize starch and wheat starch) were also analyzed by a method that requires the samples to be cooked first in dimethyl sulfoxide (DMSO). Relative standard deviations for repeatability (RSDr) ranged from 2.1 to 3.9%, and relative standard deviations for reproducibility (RSDr) ranged from 2.9 to 5.7%. The RSDr value for high amylose maize starch analyzed by the standard (non-DMSO) procedure was 5.7%; the value
relationship between the spectra and the reported composition that results from the calibration process. Because of the time and expense involved in the development of calibrations that are applicable with confidence in the day-today world of the industry, together with the fact that such work is often proprietary, this type of application does not lend itself to publication in scientific journals. These calibrations call for extensive and expensive research, and the book focuses on the procedures involved in setting up such comprehensive calibration models. Because of the proficiency of modern NIR instruments, the reproducibility and reliability of the future NIRS results will often be superior to those of the reference laboratory.
There are nearly 40 items that should ideally be reported when an NIR (near infrared) spectroscopy project is completed, either as a report or as a scientific paper. However, in our reading of the extensive literature, many of the papers presented or published report no more than 6-10 of these. The purpose of this tutorial is to indicate all of the items and the reasons for reporting them. Most of the items that need to be reported are important for anyone who seeks to duplicate the type of application and methods reported in a peer-reviewed journal article for their own work. Practically, all of the items are significant to any worker if the eventual objective of their work is to extend it to the level of industrial application. The tutorial will summarize these items, and give some explanation for their inclusion. The tutorial should be useful to potential authors, as well as to reviewers.
Whole seed neal~infrared (NIR) analyzers are capable of high, speed compositional analysis of oilseed commodities. This study compared the PerCon Inframatic 8144 (Perten Instruments, North America Inc., Ren~ NV), the Tecator Infratec 1225 (Tecator AB, Hoganas, Sweden) and the NIR-Systems 6500 (NIR Systems, Inc, Silver Spring, MD) analyzers for measurement of oil, protein, chlorophyll and glucosinolates in intact canola seed of composite samples from the Grain Research Laboratory's (Winnipeg, Manitoba, Canada) 8nnual Western Canada Harvest Surveys (1985-1989) for assembly of calibration and prediction sets. No significant differences were found between the three instruments for oil [standard error of prediction (SEP 0.43-0.55%)], protein (SEP 0.35-0.42%) and gheosinolates (SEP 2.4-3.8 mM/g). Neither the Tecator nor the PerCon instruments were effective for determining chlorophylL By combining oil content and fatty acid composition data to give an estimate of the total level of each fatty acid in the sample, high correlations were obtained for total saturates, linolenic acid, and linoleic acid although the RPD (ratio of the S.E. of prediction to the S.D. of the original data) values were not high enough to enable routine use of the method to predict results.
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