Browsing by Subject "Fatty acids"

Now showing 1 - 5 of 5

Effect of Omega-3 fatty acids and physical exercise on egg quality, bone characteristics and physiological parameters in laying hens
(2013) Jahja, Ardita; Grashorn, Michael
It is well proven that eggs enriched with omega-3 fatty (n-3) acids have additional health benefits in humans. Various feeding stuffs may be used for enriching eggs with n-3 PUFA. Besides nutrition physical exercise may play a role in this context. Physical exercise influences both the metabolism of fatty acids and the mechanisms of bone formation. Bone breakage is a serious welfare problem of laying hens. Broken bones were found in about 30% of hens before slaughter and the proportion reached 90% at the end of the processing line. Beneficial effects of n-3 fatty acids have been reported on bone strength in Japanese quail and growing chickens. Thus, the objectives of the present study were to elucidate the relationships between sources of dietary fatty acids and physical exercise in laying hens on performance, egg quality, bone characteristics and some physiological criteria of lipid metabolism. In total 36 brown laying hens were used and 12 hens each were fed with three experimental diets differing only in the fat source: Palm oil (PO), Soybean oil (SO), Linseed oil (LO), corresponding to a low content of poly unsaturated fatty acids (PUFA) ? PO, high content of omega-6 (n-6) fatty acids ? SO, and high content of n-3 fatty acids ? LO. Half of hens of each dietary group (6 birds) were exposed to exercise by walking on a treadmill (EG), whereas, the remaining 6 hens served as a control (CG). EG birds were exposed to a running treadmill every day for the whole experimental period (4 wk). On the first day the birds walked 5 min with the speed of 0.5 miles/h. Then duration of walking and speed was increased progressively until day eleven. Thereafter, until the end of the experiment hens walked 25 min/day. On the first day the distance walked was 67 m and increased to 469 m/day on day eleven. The experimental design was: 3 diets x 2 activities x 6 birds = 36 hens. At the end of the experiment eggs were collected to determine yolk fatty acids profiles and hens were slaughtered to collect blood indicators for lipid metabolism, tibia bones to determine bone characteristics and hearts and livers to calculate relative weights. Diets significantly influenced egg weight, yolk proportion and fatty acids profiles. The highest egg weight was observed for SO and the highest yolk proportion for LO. Contents of SAT and MUFA were significantly higher in eggs of group PO, whereas, LO and SO showed a higher content of PUFA. Eggs of treatments SO and LO had the highest proportions of linoleic acid and linolenic acid, respectively. N-6 and n-3 contents in PO and in SO eggs were eight times higher than for LO (P<0.05). Exercise of birds did not affect egg weight, yolk proportion or fatty acids profiles indicating a dominating effect of dietary fat source. The interaction exercise x diet was significant for yolk proportion only. There was no significant effect of diet or physical exercise on bone characteristics determined by computer tomography, but, there was a consistent trend of higher level of total area and corticalis area in the LO group as compared to PO and SO groups. Total density and cortical density showed the opposite tendency. Significant diet x exercise interactions were observed for total area, corticalis area and corticalis density. Running on the treadmill resulted in lower total area and corticalis area for diets LO and PO, whereas, higher values were observed for birds with exercise fed on diet SO. In contrast, for corticalis density lower values were observed for birds without exercise fed on diets LO and PO. Further characteristics of tibia were not significantly affected by main factors or their interaction, but tibia of birds fed on diet PO showed the highest ash, Ca and P contents (% dry matter). Diet PO resulted in lower body weight, increased relative liver weight and serum cholesterol level. Hens fed with diet SO showed the highest serum ALAT level indicating an accelerated lipid metabolism. There were no significant effects of exercise on other characteristics. Interactions between dietary fat and exercise revealed that exercise can compensate negative side-effects of an increased metabolic activity for diets SO and LO, whereas, the unfavourable effects of a diet with a low content of linoleic acid (PO) cannot be removed. In summary, fatty acids profile of egg yolk has been modified by diets as expected. Physical exercise, in contrast did not show any influence on yolk fatty acid profiles. Higher levels of n-3 fatty acids in free range eggs reported in earlier studies are obviously not caused by higher physical exercise. The effect of physical exercise and diet on bone stability is not caused by the individual factors but by their interactions. While physical exercise in the LO and PO diet reduced bone area and increased bone density, the opposite effect was observed for SO diet. Since lower bone density was compensated by larger bone area the treatments did not affect bone breaking strength.
Die Mikroalge Phaeodactylum tricornutum : Bioverfügbarkeit, Sicherheit und potenzieller gesundheitlicher Nutzen für die humane Ernährung
(2023) Kopp, Lena Janine; Bischoff, Stephan C.
The dissertation by Lena Kopp investigated the suitability of the microalga Phaeodactylum tricornutum (PT) for human nutrition. PT contains essential nutrients such as the long-chain omega-3 fatty acid eicosapentaenoic acid (EPA), which is otherwise found mainly in fish. In addition, PT contains a high content of other nutrients such as proteins, carotenoids (in particular fucoxanthin), vitamins and β-glucans, which have nutritive and therapeutic potential. Clinical and animal studies have shown that the PT biomass ingestion is safe and has potential health effects, such as anti-inflammatory and prebiotic effects. The results suggest that PT can be used as a food for human nutrition with possible health-promoting effects.
Prediction of ruminal acidosis in dairy cows from milk constituents
(2022) Seyfang, Gero Marc; Rodehutscord, Markus
Subacute rumen acidosis (SARA) is a common, but hardly assumable disease in modern dairy cows’ herds. SARA incidences are prevalent in two circumstances. The first, when the cows have to adapt fast to a ration high in carbohydrates after parturition. Since the feed composition has to be changed fast, to meet the cows’ requirements energy- and nutrients wise, the rumen microbiota climate has to adapt fast, which can cause unbeneficial rumen circumstances. The second, when the lactating cows have, beside high milk yield also a high feed intake in mid-lactation, when feed high in energy but low in structural carbohydrates is fed. This can lead to high density of VFAs in the rumen, if the outflow and absorption through the ruminal wall, as well as the buffer capacity in the rumen is not sufficient for the high production of those acids. Then the ruminal milieu becomes more acid, which can negatively affect the cow’s health. The cows suffering SARA, if at all, show mild symptoms like reduced water and feed intake, depression, diarrhea, reduced rumen motility, laminitis or reduced milk yield and milk fat depression. Since those symptoms can also show up with a delay in time and can be caused by several other factors, monitoring SARA in herds can be difficult. An unambiguous definition of SARA circumstances in the rumen cannot be found in literature, although it is under research for decades. Since SARA can influence the milk yield and can lead to a milkfat depression and a change in composition of milkfat, we focused on milk parameters and milkfat composition in particular with the aim of correlating those with pH conditions in the rumen. Three trials were made with feeding rations that were predictably capable of inducing SARA conditions in mid-lactation. During the trials, besides performance and ruminal parameters, as well as continuous pH measurement, milk samples were taken. The cows used were all rumen cannulated. Therefore, datalogger with integrated pH meter (Large Ruminant Logger M5-T7, Dascor Inc., Oceanside, USA) were placed in the ventral sac of the rumen to measure reliably and continuously. In Trial 1, three feeding rations with constant 20% grass silage were used. One ration consisted of additionally 20% corn silage and 60% concentrate (treatment CS60), the other two rations included 20 respectively 60% pressed sugar beet pulp silage and 60 respectively 20% concentrate (treatments SBPS60 respectively SBPS20). With those rations, low pH values were induced in the rumen, leading to SARA incidences of 89% in the measured days in the CS60, 100% in the SBPS60, and 61% in the SBPS20 treatment. In Trial 2, for all three rations a fix concentration of 52% concentrate was used. The remaining 48% consisted of corn silage (treatment CS), grass silage (treatment GS) or hay (treatment Hay). In the CS treatment, SARA incidence was 23%, while the GS and Hay treatments did not show SARA incidence. While the first two trials were designed as a 3x3 Latin square, in Trial 3 the cows remained in their respective treatment. One group stayed in the barn with a TMR, including 30% concentrate (treatment CG), while the other group was full time grazing and got additional 1.75 kg concentrate per day (treatment PG). SARA incidences were 7% in the CG and 8% in the PG. Additionally, in an intertrial approach, regression models for SARA detection were developed. Therefore, easily accessible performance data from the barn and milk parameters from the official milk control and milk fatty acids were used to estimate the rumen parameters pH mean and the time spent below pH 5.8. One first model was designed to include 63 variables. Besides 11 parameters gained in the barn or from the official milk control, also 52 parameters that were gaschromatographically detected fatty acids and sums of these fatty acids. A second model was designed to be useable if no gaschromatographical milkfat analysis was available. Therefore, only those FAs were included that can be estimated in a good quality with MIR spectroscopy. With those regression models the SARA days from the 185 measurement days were calculated to test the accuracy of the models. From the original 47 SARA days the first model was able to detect 43 days and the second model detected 39 SARA days. Although the accuracy of SARA prediction based on these models might be too inaccurate for a decision if a single day was SARA prevalent or not, an information on herd basis seems assessable. Still the small number of cows and measured days, as well as the fact that two breeds of cows and only cows in the later lactation phase were integrated in the model establishment has to be considered and further developed before it becomes a useful tool in field use for SARA detection.
The influence of phosphate-availability and phytic acid on the profiles of fatty acids, (poly)phenols, carotenoids, and tocochromanols in maize (Zea mays L.) grains – from field experiments to human in vitro digestion studies
(2022) Lux, Peter Erwin; Frank, Jan
Phosphorus (P) is an essential element for living organisms and involved in phosphorylation reactions, including the biosynthesis of several organic micronutrients. Since P is taken up by plants from soil as phosphates, phosphate fertilizers are applied on fields to support the P-supply for crops. Today, shrinking global P-resources demand a reduction in the application of P-containing fertilizers, but knowledge about possible effects of a reduced phosphate-availability in soils on the quality of maize grains is lacking. Thus, it was hypothesized that a reduced phosphate-availability in soil influences the concentrations of dietary organic compounds (phenolics, fatty acids, carotenoids, and tocochromanols) in grains of maize during cultivation. Moreover, concentration differences in the P-storage form phytic acid in maize grains may impact the oxidative stability of these organic compounds during processing and digestion. Fertilizer experiments with maize hybrids were conducted at study sites with low to high phosphate concentrations in soil (1.6 to 20.6 mg CAL-P/100 g soil) in Germany. GC-MS or HPLC-(MS) analyses of the ground maize grains revealed the identity of fatty acids, insoluble (mostly diferulic and triferulic acids) and soluble (poly)phenols, carotenoids, and tocochromanols. The concentrations of these (poly)phenols, carotenoids, and tocochromanols as well as the fatty acid composition in the grains of the maize plants grown with or without phosphate fertilizer were not significantly (p < 0.05) different. Interaction effects between phosphate application and the locations on the fatty acid composition as well as on carotenoids and tocochromanols were considered as insignificant, concluding that a reduction in phosphate fertilization could be implemented on most fields in Germany when only considering these dietary compounds. Lastly, the influence of phytic acid on oxidation processes in maize during processing of porridge and in vitro digestion was examined. Porridges were prepared from maize flour containing either high phytic acid concentration or low phytic acid concentration supplemented with or without phytate. The porridges were digested using a human in vitro digestion model, resulting in a decrease in tocochromanols, carotenoids and unsaturated fatty acids. Oxidation products (alpha-tocopherylquinone, malondialdehyde) were formed in all samples, implying that phytic acid addition did not show the expected protective effect. The addition of phytate evoked a significant reduction in the micellarization efficiency of most carotenoids. Thus, the knowledge about phytic acid as antinutrient was extended.
The prediction of energy balance of dairy cows from animal, feed, and milk traits with special regard to milk fatty acids
(2017) Becher, Vera; Rodehutscord, Markus
The objective of the present study was to predict the energy balance (EB) of dairy cows from animal, feed, and milk traits. As the milk fatty acid (FA) profile is known to react to physiological conditions like an energy deficit, special regard was given to milk FA in order to identify new potential indicators for negative EB. Visiting six experimental stations in Germany, single milk samples were taken from dairy cows between their 6th and 133th day in milk to create a dataset covering a large spectrum of EB and a variety of practical diets. The milk composition was analyzed by mid-infrared spectrometry, and the milk FA profile via gas chromatography. Energy balance (MJ NEL/d), as response variable, was calculated by subtracting the cow’s energy requirements from energy intake. As candidate variables parity, day of lactation, dietary nutrient composition, milk yield, milk composition, and the milk FA profile were provided resulting in a pool of 62 potential predictors. The prediction of EB was performed in two different ways: first, an automated stepwise variable selection was performed with the whole variable pool (GLMs-N) and with FA only (GLMs-FA-N). As this method recently earned criticism, some other methods were also tested for a first variable selection: the regularized linear regression models Lasso, elastic net (ENET), adaptive Lasso (AdaLasso), and adaptive elastic net (ADAENET). As a machine learning method which also considers interactions and non-linear relationships random forests were also applied. The first variable selection was performed using a five-fold cross-validation which resulted in five models per selection method. All chosen effects were combined to one model (MODEL1) for each method, respectively. Following this, the individual effects of the MODEL1 were used for a forward selection based on the corrected Akaike Information Criterion (AICC) for further model reduction, resulting in MODEL2. Then, the non-significant effects were removed from the MODEL2, achieving the final MODEL3 for each method. The final models were validated using leave-one-out cross-validation. The models showed adequate correlations (r) between the predicted and the observed EB in leave-one-out cross-validation: although GLMs-FA-N had the lowest accuracy (r = 0.79), the result was still remarkable and showed how much information milk FA alone can provide. GLMs-N and AdaLasso performed best with r = 0.86 and 0.85 containing 21 and 18 predictors, respectively. However, other models like ADAENET achieved only slightly lower accuracy (r = 0.83) with only 6 predictors. The composition of the predictors was relatively similar in all models. All (except for GLMs-FA-N) contained days in milk, milk yield, C18:1c9, C15:0iso, and the ratio of omega-6 to omega-3 FA (n-6/n-3) as effects with the strongest impacts on the prediction. While milk yield, days in milk, and C18:1c9 mirrored physiologically obvious effects, the strong and positive impact of n-6/n-3 and C15:0iso was unexpected. The n-6/n-3 ratio might be physiologically connected to EB as might reflect the dietary forage-to-concentrate ratio which influences dietary energy content and thus EB. The importance of C15:0iso, a FA arising from microbial FA synthesis in the rumen, could not be explained satisfyingly. The nature of the potential physiological connections between EB and some FA like C15:0iso or n-6 or n-3 FA might require further research. The present study showed that it is possible to predict the cow’s EB from animal and milk traits with an adequate accuracy. As long as the diets have similar composition and not contain ingredients which strongly affect the milk FA profile, dietary effects have not to be taken into account. However, a practical application of the obtained models is not yet possible: First, as the dataset was relatively small (n = 248), it is not clear whether or not the models would perform adequately with independent datasets. Second, FA analysis by gas chromatography is very expensive. Third, even if gas chromatographic analysis were affordable for standard milk analysis, there are some highly variable, very low concentrated FA as predictors in the models, which might be prone to laboratory effects, and this could spoil the predictions. Although under criticism, automatic stepwise selection provided the best performing model and thus seems sufficient for practical issues like the one dealt with in the present study. However, the differences in accuracy between the applied methods were very small and as regularized linear regression methods, especially ENET and ADAENET, are supposed to deal better with highly correlated variables, it might be safer to use them with datasets containing highly correlated variables such as the one used in the present work.