Evaluation of the compositional and functional quality of South African triticale (x Triticosecale Wittmack) cultivars

The baking potential of South African bred triticale (x Triticosecale spp. Wittmack ex A. Camus 1927) cultivars, and the effect of cultivar and environment on baking potential parameters had not previously been studied. At present South African triticale cultivars are used for animal feed as grazing, hay or silage. Seven cultivars harvested over two years from eight localities in the Western Cape region of South Africa were used to examine the baking potential parameters falling number, SDS sedimentation, ash content, particle size index, total protein content and 1000-kernel mass. The quality of the South African bred cultivars compared well with data from cultivars grown in other countries. The triticale cultivars studied here generally had higher ash contents, lower falling numbers and SDS sedimentation values than the bread wheat standard. Significant differences (P<0.05) were observed between cultivars and between localities in each year's harvest, illustrating the effect of genetic as well as environmental factors on the quality of the grain produced. Interactions between cultivars and localities were found to be significant (P<0.05) in all cases

Prediction of triticale grain quality properties, based on both chemical and indirectly measured reference methods, using near-infrared spectroscopy

The increasing demand for triticale as food, feed, and fuel has resulted in the availability of cultivars with different grain quality characteristics. Analyses of triticale composition can ensure that the most appropriate cultivars are obtained and used for the most suitable applications. Near-infrared (NIR) spectroscopy is often used for rapid measurements during quality control and has consequently been investigated as a method for the measurement of protein, moisture, and ash contents, as well as kernel hardness (particle size index [PSI]) and sodium dodecyl sulfate (SDS) sedimentation from both whole grain and ground triticale samples. NIR spectroscopy prediction models calculated using ground samples were generally superior to whole grain models. Protein content was the most effectively modeled quality property; the best ground grain calibration had a ratio of the standard error of test set validation to the standard deviation of the reference data of the test set (RPDtest) of 4.81, standard error of prediction (SEP) of 0.52% (w/w), and r2 of 0.95. Whole grain protein calibrations were less accurate, with optimum RPDtest of 3.54, SEP of 0.67% (w/w), and r2 of 0.92. NIR spectroscopy calibrations based on direct chemical reference measurements (protein and moisture contents) were better than those based on indirect measurements (PSI, ash content, and SDS sedimentation). Calibrations based on indirect measurements would, however, still be useful to identify extreme samples

Feasibility Study on the Use of Visible–Near-Infrared Spectroscopy for the Screening of Individual and Total Glucosinolate Contents in Broccoli

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Agricultural and Food Chemistry, copyright © American Chemical Society, after peer review and technical editing by the publisher. To access the final edited and published work see http://dx.doi.org/10.1021/jf3018113.peer-reviewedThe potential of visible–near-infrared spectroscopy to determine selected individual and total glucosinolates in broccoli has been evaluated. Modified partial least-squares regression was used to develop quantitative models to predict glucosinolate contents. Both the whole spectrum and different spectral regions were separately evaluated to develop the quantitative models; in all cases the best results were obtained using the near-infrared zone between 2000 and 2498 nm. These models have been externally validated for the screening of glucoraphanin, glucobrassicin, 4-methoxyglucobrassicin, neoglucobrassicin, and total glucosinolates contents. In addition, discriminant partial least-squares was used to distinguish between two possible broccoli cultivars and showed a high degree of accuracy. In the case of the qualitative analysis, best results were obtained using the whole spectrum (i.e., 400–2498 nm) with a correct classification rate of 100% in external validation being obtained.J.M.H.-H. thanks the Spanish MICINN for the Juan de la Cierva contract (JCI-2011-09201) and Universidad de Sevilla for the mobility grant (Universidad de Sevilla Research Plan). Spanish MICINN project AGL2011-30254-C02 and Junta de Andalucia PGC project AGR 6331

Quantification of Process Induced Disorder in Milled Samples Using Different Analytical Techniques

pharmaceutic