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The present investigation describes the employment of a comprehensive 2-D HPLC system, based on the combination of a silver ion and an RP column, for the characterization of the triacylglycerol (TAG) fraction of a very complex lipidic sample: donkey milk fat. The TAGs were grouped on the resulting bidimensional contour plot according to their double bond numbers (aligned along vertical bands) and according to their partition numbers (aligned along horizontal bands). Peak assignment was supported by using atmospheric pressure chemical ionization mass spectrometric (APCI-MS) detection. The combination of the enhanced resolving power of comprehensive multidimensional LC, the formation of ordered 2-D patterns, and APCI-MS detection proved to be an effective tool for the characterization of the complex matrix, enabling the separation and identification of nearly 60 TAGs.

The separation and determination of triacylglycerols (TAGs), which are the main components of naturally occurring fats and oils, in milk fat is a challenging task due to the very complex nature of this matrix. In the present study the TAG fraction of donkey milk lipids has been characterized by using high performance liquid chromatography-atmospheric pressure chemical ionization mass spectrometry (HPLC-APCI-MS). HPLC in reversed phase mode has been used for TAG separation and silver ion (Ag+) HPLC has been used as a second dimension to clarify and confirm the identification. The RP-HPLC eluate was fractionated and the fractions of interest were injected onto the Ag+-HPLC column. In both cases peak assignment was carried out by combining retention data with APCI-MS spectra information. In total, 55 TAGs in donkey milk fat were identified (without considering the positional isomers) and quantified on the basis of percentage peak areas in the RP-HPLC chromatogram (without the use of correction factors). Amongst the identified triacylglycerols, POLn, POO, PPO, CaPO, POL, and PPoO proved to be the main components of the TAG fraction of donkey milk.

The aim of this study was to evaluate the effect of some lactobacilli on body growth and on the metabolic-nutritional status in growing goat kids. Twenty growing Maltese goat kids (10 Control and 10 Bios) were studied. The animals of the Bios group received a concentrate including 1 g x kg(-1) of SEB Bovino (spray-dried), Akron S.r.l., Italy, with non bacterial components: gum arabic, soybean meal, silicate alum of magnesium, and with bacterial components: 10(11) cfu kg(-1) each of Lactobacillus acidophilus, Lactobacillus salivarius, Lactobacillus reuteri. Monthly, bio-metric and weight evaluations were carried out on each animal and individual blood samples were taken. The Bios group showed the highest body weight (Control 19 vs. Bios 23 kg P < 0.001), anamorphosis (Control 71 vs. Bios 78 P < 0.05) and body proportion (Control 35 vs. Bios 41 P < 0.001) indices; the lowest levels of Non Esterified Fatty Acids (Control 0.778 vs. Bios 0.403 mmol L(-1) P < 0.001), triglycerides (Control 0.21 vs. Bios 0.18 mmol L(-1) P < 0.05), urea (Control 8.83 vs. Bios 7.65 mmol L(-1) P < 0.05) and the highest levels of Alkaline Phosphatase (Control 270 vs. Bios 851 U L(-1) P < 0.01) and Creatine Kinase (Control 173 vs. Bios 285 U L(-1) P < 0.01). The results testify to the better metabolic activity of the Bios group which achieved, at the end of the trial (7 months old), about 99% of the morphological development of the adult, therefore an adequate structure for mating and going into production within the first year of life.

Fast and conventional gas chromatography (GC) techniques were applied to nine different lipidic matrices (butter, lard, tallow, and peanut, corn, sunflower, soya, olive, menhaden oils). Simultaneous methylic transesterification was performed on all samples prior to GC analysis. Several practical aspects concerning high speed analysis were investigated, such as the great increase in linear velocity, the use of fast temperature ramps, column sample capacity and detection systems. Analytical results showed certain losses in resolution, balanced by a consistent reduction in analysis time. The actual time savings were variable (60-70 min) as they were dependent on the complexity of the sample while the speed enhancement factor was equal to 10.5. Peak identification was achieved by means of different information sources, such as fast GC-mass spectrometry (MS), linear retention indices and comprehensive two-dimensional (2D) gas chromatography group patterns. The method developed was shown to be applicable in routine applications on complex natural samples.