Predicting Wheat Quality Characteristics and Functionality Using Near‐Infrared Spectroscopy

The accuracy of using near‐infrared spectroscopy (NIRS) for predicting 186 grain, milling, flour, dough, and breadmaking quality parameters of 100 hard red winter (HRW) and 98 hard red spring (HRS) wheat and flour samples was evaluated. NIRS shows the potential for predicting protein content, moisture content, and flour color b* values with accuracies suitable for process control (R² > 0.97). Many other parameters were predicted with accuracies suitable for rough screening including test weight, average single kernel diameter and moisture content, SDS sedimentation volume, color a* values, total gluten content, mixograph, farinograph, and alveograph parameters, loaf volume, specific loaf volume, baking water absorption and mix time, gliadin and glutenin content, flour particle size, and the percentage of dark hard and vitreous kernels. Similar results were seen when analyzing data from either HRW or HRS wheat, and when predicting quality using spectra from either grain or flour. However, many attributes were correlated to protein content and this relationship influenced classification accuracies. When the influence of protein content was removed from the analyses, the only factors that could be predicted by NIRS with R² > 0.70 were moisture content, test weight, flour color, free lipids, flour particle size, and the percentage of dark hard and vitreous kernels. Thus, NIRS can be used to predict many grain quality and functionality traits, but mainly because of the high correlations of these traits to protein content.     

Polarized electron probes of magnetic surfaces

The magnetic properties of surfaces are now being explored with electron spectroscopies that use electron spin polarization techniques. The increased activity in surface magnetic measurements with polarized electron beams is spurred by new scientific and technological challenges and is made feasible by recent advances in the technology of sources and detectors of polarized electrons. The ability to grow thin films and to engineer artificial structures permits new phenomena to be investigated at magnetic surfaces and interfaces. For such investigations, spin-polarized electron techniques-such as polarized electron scattering, polarized photoemission, polarized Auger spectroscopy, and scanning electron microscopy with polarization analysis-have been and will probably continue to be used to great advantage.     

The Current State of Solar Modeling

Data from the Global Oscillation Network Group (GONG) project and other helioseismic experiments provide a test for models of stellar interiors and for the thermodynamic and radiative properties, on which the models depend, of matter under the extreme conditions found in the sun. Current models are in agreement with the helioseismic inferences, which suggests, for example, that the disagreement between the predicted and observed fluxes of neutrinos from the sun is not caused by errors in the models. However, the GONG data reveal subtle errors in the models, such as an excess in sound speed just beneath the convection zone. These discrepancies indicate effects that have so far not been correctly accounted for; for example, it is plausible that the sound-speed differences reflect weak mixing in stellar interiors, of potential importance to the overall evolution of stars and ultimately to estimates of the age of the galaxy based on stellar evolution calculations.     

Ethnicity: An important consideration in Indonesian agriculture

This paper has two purposes: To report the findings of a study of ethnic differences in cognition in a rural West Sumatran area; and to demonstrate the importance of ethnicity—in at least some contexts—for tailoring agricultural research to farmers' needs. A cognitive mapping technique, called a Galileo, was used to measure people's views of soil and its relation to people among three Indonesian ethnic groups living in the same area. Findings from participant observation and from collaborative agricultural fieldwork with farmers of all three ethnic groups are used to evaluate and interpret the Galileo results.Carol J. Pierce Colfer is currently Associate Professor at Sultan Qaboos University in the Sultanate of Oman. She is an anthropologist who served first as the farming systems researcher, and later as Team Leader of the Tropsoils-Indonesia project in Sitiung, with the University of Hawaii.Barbara Newton is Professor of Psychology at the University of Hawaii, West Oahu. She has had extensive experience with Galileo research and analysis.