Effects of starchy and β-glucan additives on flour, dough, and bread parameters

Composite flours were formulated from wheat flour and additives containing high amylose starch, resistant starches of RS2 and RS3 types, and barley β-glucan. Different parameters of flours, doughs, and final breads were evaluated. Almost all composite flours had significantly worse parameters as flour and dough in comparison to control. Sensory parameters of breads were also lower, though loaves supplemented with up to 15% (w/w) of high amylose starch (Hylon® VII), RS2 (Hi-maize™ 260), and RS3 (Novelose® 330) were considered as acceptable, with higher content of RS observed. Loaves with β-glucan (Barliv™ barley betafiber) were not acceptable either in sensory or technological parameters

An application of kernel methods to variety identification based on SSR markers genetic fingerprinting

<p>Abstract</p> <p>Background</p> <p>In crop production systems, genetic markers are increasingly used to distinguish individuals within a larger population based on their genetic make-up. Supervised approaches cannot be applied directly to genotyping data due to the specific nature of those data which are neither continuous, nor nominal, nor ordinal but only partially ordered. Therefore, a strategy is needed to encode the polymorphism between samples such that known supervised approaches can be applied. Moreover, finding a minimal set of molecular markers that have optimal ability to discriminate, for example, between given groups of varieties, is important as the genotyping process can be costly in terms of laboratory consumables, labor, and time. This feature selection problem also needs special care due to the specific nature of the data used.</p> <p>Results</p> <p>An approach encoding SSR polymorphisms in a positive definite kernel is presented, which then allows the usage of any kernel supervised method. The polymorphism between the samples is encoded through the Nei-Li genetic distance, which is shown to define a positive definite kernel between the genotyped samples. Additionally, a greedy feature selection algorithm for selecting SSR marker kits is presented to build economical and efficient prediction models for discrimination. The algorithm is a filter method and outperforms other filter methods adapted to this setting. When combined with kernel linear discriminant analysis or kernel principal component analysis followed by linear discriminant analysis, the approach leads to very satisfactory prediction models.</p> <p>Conclusions</p> <p>The main advantage of the approach is to benefit from a flexible way to encode polymorphisms in a kernel and when combined with a feature selection algorithm resulting in a few specific markers, it leads to accurate and economical identification models based on SSR genotyping.</p

AT SEED – A MULTIFUNCTIONAL SUBJECT FOR BIOTECHNOLOGY

Oats (Avena sativa L.) among the basic cereals are highly appreciated from the nutritive and the dietetic point of view. This beneficial effect of oat products is primary attributed to the soluble dietary fibre compound β-D-glucan, major polysaccharide constituent of cell walls of oats. Mature grains of naked oat genotypes dispose of higher content of β-D-glucan (Havrlentová and Kraic, 2006) and its value decreases in milled grain with time (Gajdošová et al., 2007). Locality and year influence its content, although it seems that the genotypes with black colour of the glumes account significantly lower standard deviation and variation coefficients in the content of β-D-glucan, what indicates markedly stable biosynthetic mechanism of studied metabolite (Čertík et al., unpublished data). Oat seed is also an important source of dietary fibre and its content can be influenced by both genotype and locality. The importance and exploitation of oats have an increasing style and therefore the monitoring of microsatellite polymorphism of Avena sativa DNA has his foundation. 20 pairs of microsatellite primers occurring in non-coding regions of DNA were tested. The best value of DI (0.938), the maximum value of PIC (0.938), and the minimum value of PI (0.000) was found in the microsatellite AM1. Generally, the oat DNA seems to be very conservative

NUTRITIONAL ENHANCEMENT OF ALFALFA THROUGH GENETIC ENGINEERING

Alfalfa (Medicago sativa L.) is a pasture legume crop of primary importance to animal production throughout the world. The nutritional quality of alfalfa, as of other leguminous forage crops, is mainly determined by their content in selected essential amino acids (EAAs), such as methionine (Met) and cysteine (Cys). In alfalfa, however, these S-containing amino acids constitute only about 1% or less of crude proteins (Frame et al., 1998). This is significantly less than the 3.5% Met+Cys content in the recommended FAO reference protein (FAO, 1973). Recent advances in genetic engineering allow to use the transgenic approach to increase the content of specific essential amino acids in target plant species. A number of different molecular approaches have been developed to address this issue, such as over-expression of a heterologous or homologous Met-rich protein, expression of a synthetic protein, modification of protein sequence, and metabolic engineering of the free amino acid pool and protein sink. To study the possibility of transgenic enhancement of nutritional quality of alfalfa, we used the approach of expression of a heterologous protein rich in Met+Cys in cells of alfalfa. The T-DNA introduced into the genome of alfalfa, using Agrobacterium tumefaciens-mediated genetic transformation, contained the selectable merker gene nptII for kanamycin (Kn) resistance, and a cDNA of Ov gene from Japanese quail (Coturnix coturnix) coding for a high Met+Cys containing ovalbumine (Mucha et al., 1991), both under constitutive promoters. After cocultivation of petiole segment- and leaf blade-explants of two highly embryogenic alfalfa genotypes Rg9/I-14-22 and Rg11/I-10-68 (Faragó et al., 1997) with cells of A. tumefaciens strain AGL1 carrying the nptII and Ov genes, and selection of transgenic cells on Kn containing selective media, more than one hundred putatively transgenic regenerants were obtained through somatic embryogenesis. Biological (Kn rooting assay, paromomycin leaf bleach assay) and molecular (PCR, Western blotting) analyses were performed to confirm the transgenic nature of regenerants. Of the selected lines 96.3% showed the presence of 496 bp fragment of Ov gene. Accumulation of ≈43 kDa Ov protein was detected by Western blot analysis in leaf samples of 8 of 27 analysed transgenic lines. HPLC analysis was performed to analyse the amino acid composition of bulked leaf+stem samples of 32 transgenic and 3 non-transgenic control lines of alfalfa. Of these, three lines, SE/22-14-9-1, SE/22-16-1-3 and SE/22-16-2-2, were found to contain 1.9- to 2,2-fold higher concentration of Me+Cys, in comparison with 0.23 %DW of the non-transformed control

Updated empirical model of genetically-modified maize grain production practices to achieve European Union labeling thresholds

An updated empirical approach is proposed for specifying coexistence requirements for genetically modified (GM) maize (Zea mays L.) production to ensure compliance with the 0.9% labeling threshold for food and feed in the European Union. The model improves on a previously published (Gustafson et al., 2006) empirical model by adding recent data sources to supplement the original database and including the following additional cases: (i) more than one GM maize source field adjacent to the conventional or organic field, (ii) the possibility of so-called “stacked” varieties with more than one GM trait, and (iii) lower pollen shed in the non-GM receptor field. These additional factors lead to the possibility for somewhat wider combinations of isolation distance and border rows than required in the original version of the empirical model. For instance, in the very conservative case of a 1-ha square non-GM maize field surrounded on all four sides by homozygous GM maize with 12 m isolation (the effective isolation distance for a single GM field), non-GM border rows of 12 m are required to be 95% confident of gene flow less than 0.9% in the non-GM field (with adventitious presence of 0.3%). Stacked traits of higher GM mass fraction and receptor fields of lower pollen shed would require a greater number of border rows to comply with the 0.9% threshold, and an updated extension to the model is provided to quantify these effects