Influence of aging and salting on protein secondary structures and water distribution in uncooked and cooked pork. A combined FT-IR microspectroscopy and 1H NMR relaxometry study

Fourier transform infrared (FT-IR) microspectroscopy and low-field (LF) proton NMR transverse relaxation measurements were used to study the changes in protein secondary structure and water distribution as a consequence of aging (1 day and 14 days) followed by salting (3%, 6%, and 9% NaCl) and cooking (65 degrees C). An enhanced water uptake and increased proton NMR relaxation times after salting were observed in aged meat (14 days) compared with nonaged meat (1 day). FT-IR bands revealed that salting induced an increase in native beta-sheet structure while aging triggered an increase in native alpha-helical structure before cooking, which could explain the effects of aging and salting on water distribution and water uptake. Moreover, the decrease in T2 relaxation times and loss of water upon cooking were attributed to an increase in aggregated beta-sheet structures and a simultaneous decrease in native protein structures. Finally, aging increased the cooking loss and subsequently decreased the final yield, which corresponded to a further decrease in T2 relaxation times in aged meat upon cooking. However, salting weakened the effect of aging on the final yield, which is consistent with the increased T2 relaxation times upon salting for aged meat after cooking and the weaker effect of aging on protein secondary structural changes for samples treated with high salt concentration. The present study reveals that changes in water distribution during aging, salting, and cooking are not only due to the accepted causal connection, i.e., proteolytic degradation of myofibrillar structures, change in electrostatic repulsion, and dissolution and denaturation of proteins, but also dynamic changes in specific protein secondary structures.     

Heat-induced changes in myofibrillar protein structures and myowater of two pork qualities. A combined FT-IR spectroscopy and low-field NMR relaxometry study

Low-field NMR T(2) and Fourier transform infrared (FT-IR) measurements were performed on meat samples of two qualities (normal and high ultimate pH) during cooking from 28 degrees C to 81 degrees C. Pronounced changes in both T(2) relaxation data and FT-IR spectroscopic data were observed during cooking, revealing severe changes in the water properties and structural organization of proteins. The FT-IR data revealed major changes in bands in the amide I region (1700-1600 cm(-)(1)), and a tentative assignment of these is discussed. Distributed NMR T(2) relaxation data and FT-IR spectra were compared by partial least-squares regression. This revealed a correlation between the FT-IR peaks reflecting beta-sheet and alpha-helix structures and the NMR relaxation populations reflecting hydration water (T(2B) approximately 0-10 ms), myofibrillar water (T(21) approximately 35-50 ms), and also expelled "bulk" water (T(2) relaxation times >1000 ms). Accordingly, the present study demonstrates that definite structural changes in proteins during cooking of meat are associated with simultaneous alterations in the chemical-physical properties of the water within the meat.     

Nutritional Value of Low-phytate Barley Evaluated in Rats

The nutritional effects of two barley mutant lines with an altered phosphorus (P) profile and phytate content (13 and 43% of total P, respectively) were studied. Because grain quantities were limited, rats served as a model for the pig in a feeding trail. Four groups of five Wistar rats (weighing 65 g) were fed the low-phytate lines, the mother variety and a mixture of barley varieties. All diets were supplemented with vitamins and minerals except for P, calcium, zinc and copper. The apparent digestibility of P was improved by up to 13% in the mutant lines. Although all diets were very similar in their zinc content, only rats fed the mutant lines had a net absorption and a positive zinc balance, indicating the improved availability of this mineral. Rats appear to be a suitable model for P utilization in pigs and can thus provide plant breeders with a mineral bioavailability assay for use at an early stage.     

Discriminant Analysis of Patterns of Jaw Movement During Rumination and Eating in a Cow

Discriminant analysis was used to identify combinations of variables, characterizing patterns of jaw movement (JM) during eating and rumination, that minimize errors when classifying series of successive JM of known behaviour into rumination and eating. JM data from a non-lactating jersey cow were recorded continuously for 72 h. The cow was fed 1800 g of barley straw and 1375 g of dried sugarbeet pulp pellets twice daily. Average times spent eating and ruminating daily were 294 and 462 min. Successive rumination and eating JM were grouped into series when pauses between JM were equal to or longer than a fixed time interval corresponding to the minimum time interval between successive rumination cycles. Time intervals between successive JM, amplitude (the magnitude of the jaw's movement) and number of chews per series of successive JM were calculated for all rumination and eating series and included in the discriminant analyses. The combination of the four variables, basic chewing rate (BCR), mean of amplitude/standard deviation of amplitude, ln(number of chews) and standard deviation of time intervals between successive jaw movements, gave the least minutes of misclassified chewing behaviour per day (3% of total daily chewing time) and yielded a quadratic discriminant function. The order of the variables mentioned rank the variables according to their ability to classify the series. Combinations of the variables BCR and ln(number of chews), and other variables based on mean and standard deviation of time intervals between successive JM and amplitude of JM, can be used with advantage for classifying series of successive JM into rumination and eating behaviour.     

Effects on forest products markets of second-generation biofuel production based on biomass from boreal forests: a case study from Norway

Second-generation biofuels are often seen as essential element in the future bioeconomy strategy. Countries with extensive forest resources such as Norway often view wood as preferred bio-feedstock, yet the effects of wood demand on assortments of harvested wood and other wood-based industries are unclear. Focusing on the importance of feedstock choice, we analyse the impacts of establishing a second-generation medium-scale biofuel plant in Norway. For the analysis, a dynamic forest sector model where the choice of tree species, wood assortments, production of bioenergy, and forest industry products are explicitly included, was applied. We find the optimal biofuel feedstock mix to be dominated by softwood chips from pulpwood comprising 48% of total biomass inputs in 2030 and increasing to 67% by 2055, followed by hardwood chips from birch, comprising initially 34% of total biomass inputs and 16% by 2055. The proportion of harvest residues remained constant at about 18% over time and roundwood was not used at all for biofuel production. Despite the additional demand for chips, the single medium-scale biofuel plant will have only minor effects on existing forest industries and harvests in Norway, as the domestic impact is dampened by changes in foreign trade flows, especially of chips.     

Agricultural Genomics: An Approach to Plant Protection

Genomics studies, focused on whole-genome analysis, have opened up a new era for biology in general, and for agriculture in particular. Along with the use of genetic plant models and the progress in sequencing agriculturally important organisms, the combination of bioinformatics and functional genomics globally enhances agricultural genomics. These studies are likely to pave the way towards better understanding of plant–pathogen biological networks, and eventually to lead to breakthroughs in the promotion of plant resistance to agricultural pests.     

Evaluation of piglet blood utilizing the Technicon H*1

The analytic precision of an automated blood analyzer, the Technicon H*1(R), was evaluated utilizing blood samples collected from 20 piglets at 1 and 14 days of age. The effect of storing the blood samples at 4 degrees C for 24 and 48 hours also was determined. Blood samples were analyzed twice on the first day and once on each of the subsequent tow days. Within-sample coefficient of variation was approximately 1% for hemoglobin concentration, erythrocyte count, hematocrit, mean cell volume, erythrocyte distribution width and hemoglobin distribution width (HDW); and approximately 5% for total leukocyte (WBC), neutrophils and lymphocyte counts. Mean HDW and automated differential WBC counts changed during storage to a degree that could be of clinical importance. Manual determination of differential WBC counts were compared with those obtained from the automated analyzer. Results correlated well for neutrophils (r=0.92 in 1-day-old and r=0.93 in 14-day-old piglets, P<0.001) and lymphocytes (r=0.85 in 1-day-old and r=0.93 in 14-day-old piglets, P<0.001). Other WBC values were too low to compare reasonably.     

Quality control using a multilevel logistic model for the Danish pig Salmonella surveillance antibody-ELISA programme

In Denmark, the level of Salmonella infection in pig herds is monitored with a surveillance programme using an indirect antibody ELISA. Our purpose with the present study was to determine whether sample results from the programme were useful in the quality control of this ELISA. Test results from the year 2003, in which the laboratory experienced a technical problem with an automatic microtitre-plate washing machine, were examined statistically. We chose 3 months for the analysis: January, where the problem was moderate, June with the problem more serious, and November, where the problem had been solved. A logistic analysis was carried out with outcome 0 for a negative test result and 1 for a positive test result. Row and column on the microtitre plates, multiprobe robot, and their interactions were included as fixed effects, and date, plate, and slaughterhouse were included as random effects. Backward elimination was carried out using alpha=0.05 to achieve a final model for each month. The row and the column were significant in January and June, and a robot effect was also included in the model for January. In June, an interaction between row and column was identified. In November, none of the fixed effects was significant. Breaking the months January and June into shorter time intervals showed that the row and column effects were significant also when data were from only 1 week, whereas the robot main effect was not significant in most periods and the interaction effects were not significant throughout. Analysis of the test results from the wells with test samples gave good information on systematic errors across the microtitre plates, and severe errors appeared significant even when data from short time periods were used.