NIRS PREDICTION FOR PROTEIN AND INTRAMUSCULAR FAT CONTENT OF RABBIT HIND LEG MEAT

The goal of this study was to develop calibration equations to predict the chemical composition of raw, homogenized rabbit meat by means of near infrared spectroscopy (NIRS). 44 Pannon White rabbits were housed in groups in three different pen types (16 anim./m2), and were fed the same diet. Another 45 animals were housed in cages (12 anim./m2) and fed by different feeding regimes. Rabbits were slaughtered at the bodyweight of 2.4-2.5 kg. Homogenized fresh and freeze-dried left total hind leg muscles were investigated by NIRS using a NIRSystem 6500 equipment with small ring cup sample holder. The ether extract and protein content of all samples were determined chemically. Samples 44 of housing experiment were applied in producing LOCAL calibration equations tested on the 45 samples from the separate feeding experiment. Coefficients of determination (R2) of the predictions were 0.89 and 0.99 for fat, 0.85 and 0.96 for protein in fresh and freeze-dried samples, respectively. Results are reassuring, because the equations were applicable, however the analyzed samples were from independent housing and feeding systems. Therefore the chemical compositions differed in the two datasets, i.e. 9.46%, and 11.79% for fat, 85.75% and 83.44% for protein content in calibration and prediction datasets, respectively. The average of NIRS predicted values for fat and protein was 11.36%, 83.88% or 11.54%, 83.45% when using fresh or freeze-dried samples, respectively

Effect of group size and stocking density on productive, carcass, meat quality and aggression traits of growing rabbits

[EN] The aim of the experiment was to examine the effect of group size and stocking density on productive, carcass and meat quality traits. The trial was conducted using 230 Pannon white rabbits weaned at 5 weeks and reared until the age of 11 weeks. Seven groups were formed with different cage/pen sizes (group size) and stocking densities: SC16=small cage (0.12 m2), 16 rabbits/m2 (2 rabbits/cage); LC16=large cage (0.50 m2), 16 rabbits/m2 (8 rabbits/cage); LC12=large cage, 12 rabbits/m2 (6 rabbits/cage); SP16=small pen (0.86 m2), 16 rabbits/m2 (13 rabbits/cage); SP12=small pen, 12 rabbits/m2 (10 rabbits/cage); LP16=large pen (1.72 m2), 16 rabbits/m2 (26 rabbits/cage); LP12=large pen, 12 rabbits/m2 (20 rabbits/cage). Stocking density did not affect production significantly, as stocking densities lower than 16 rabbits/m2 had no effect on the growing rabbits¿ performance. Group size (size of the cage or pen) had an effect on certain growth, carcass and meat quality traits. Increasing group size resulted in lower values for weight gain (SC: 39.2>LC: 39.0> SP: 38.7> LP: 37.8 g/d; P=0.22) and body weight (SC: 2506>LC: 2498> SP: 2487> LP: 2446 g; P=0.35), similarly to other results in the literature, but the differences were not significant. Aggressive behaviour was observed to be more frequent in the larger group sizes. At the age of 11 weeks the proportion of rabbits with ear lesions in the SC, LC, SP and LP groups were 0.0, 7.1, 8.7, and 17.4%, respectively, demonstrating that larger group size increases the risk of ear lesions. The effect of group size on the ratio of the fore part to the reference carcass (SC: 28.5, LC: 28.2, LP: 29.0%; P=0.02) and on the amount of perirenal fat (SC: 21.3, LC: 18.0, LP: 13.7 g; P<0.001) was significant. Meat quality traits (dry matter, protein, fat and ash content, drip loss, pH, L*, a*, b* values) were not affected by group size (cage vs. pen), but successful discriminations were performed using the NIRS method.The authors gratefully acknowledge the financial assistance received from the GAK OMFB-01335/ALAP1- 00121 project.Szendrö, Z.; Princz, Z.; Romvári, R.; Locsmándi, L.; Szabó, A.; Bázár, G.; Radnai, I.... (2009). Effect of group size and stocking density on productive, carcass, meat quality and aggression traits of growing rabbits. World Rabbit Science. 17(3):153-162. https://doi.org/10.4995/wrs.2009.65515316217

A Simple Method for Sample Preparation to Facilitate Efficient Whole-Genome Sequencing of African Swine Fever Virus

In the recent years, African swine fever has become the biggest animal health threat to the swine industry. To facilitate quick genetic analysis of its causative agent, the African swine fever virus (ASFV), we developed a simple and efficient method for next generation sequencing of the viral DNA. Execution of the protocol does not demand complicated virus purification steps, enrichment of the virus by ultracentrifugation or of the viral DNA by ASFV-specific PCRs, and minimizes the use of Sanger sequencing. Efficient DNA-se treatment, monitoring of sample preparation by qPCR, and whole genome amplification are the key elements of the method. Through detailed description of sequencing of the first Hungarian ASFV isolate (ASFV_HU_2018), we specify the sensitive steps and supply key reference numbers to assist reproducibility and to facilitate the successful use of the method for other ASFV researchers

APPLICABILITY OF THE TOBEC METHOD IN SELECTION OF HEN’S EGGS BASED ON THEIR COMPOSITION

Applicability of the TOBEC method (electrical conductivity) was tested for the in vivo determination of different egg components and for the separation of eggs with different composition. Altogether 300 hen’s eggs – originated from a 36 weeks old ROSS-308 hybrid parent stock – were measured by TOBEC, and the extreme and average 5-5% – based on the measured values – were chosen for chemical analysis. It was established that the albumen/yolk ratio and the dry matter, crude protein and crude fat content of the eggs are in medium correlation with the E-value/egg weight ratio (r=0.47, -0.58, -0.59 and -0.35 respectively). The albumen/yolk ratio, the dry matter and the crude protein content of the eggs, selected for high and low E-value/egg weight ratio, differed significantly at P<0.05 level. The difference between the average crude fat content of the eggs in the two extreme groups was significant at P<0.10 level

A near infrared spectroscopic (NIR) approach to estimate quality alterations during prolonged heating of lard

Lard is a preferred frying fat in the Hungarian culinary routine. Our study aimed at measuring conventional fat quality indices and performing NIR-based calibrations of those indices, during prolonged heating. Lard was heated for 4 days at 8 different temperatures (160, 170, 175, 180, 185, 190, 200 and 230 °C) for 8 h a day (n=32+1, i.e. the original sample). Acid value (AV) and carbonyl value (CON) increased in parallel with the duration of heating and heating intensity. Peroxide value (PV) increased in the first 8 h, and decreased back during further treatment. p -Anisidine value (pAV) increased at each heating temperature below 200 °C, while temperatures above 200 °C decreased it. NIR analysis (NIRSystems 6500) was performed on original samples in transflectance mode (400–2500 nm wavelength range, 0.1 mm layer thickness, aluminium-plated reflector). Treatment characteristics (temperature, heat-sum, sampling event) could be estimated effectively. Calibration for AV was robust: R2=0.927; 1-VR=0.786. Weak relationship was found for PV (R2=0.48) and CON (R2=0.109). For pAV, good calibration was gained, expressly below 200 °C, in the 2000–2500 nm wavelength interval (R2=0.912; 1-VR=0.772). Based on calibration and cross-validation results, NIR technique may be a rapid, solvent-free alternative for the estimation of acid value and p-anisidine value of lard below 200 °C

Following the goose liver development by means of cross-sectional digital imaging, liver histology and blood biochemical parameters

A follow-up study was performed to describe characteristic physiological alterations by means of computer tomography, direct chemical analysis and histology of the liver, and blood biochemical parameters during conventional force-feeding of Landes geese. 30 birds were exposed to an 18-day long force-feeding. Sampling was performed at the start and during force-feeding (7th, 11th, 14th, 18th days). Computer tomographic data were plotted in 3D histograms, effectively indicating the volumetric development and the fat deposition of the liver. Applying the so-called fat index, a saturation process was found for the hepatic fat content. Histological sections indicated the appearance of microvesicular fat forms in the hepatocyte cytoplasm, which first turned to a total fatty infiltration, later changing to a macrovesicular form with progressing inflammation; membrane damage was not visualized. In blood metabolites triglyceride, total and HDL cholesterol and uric acid increased measurably, while creatinine concentration decreased. Alanine aminotransferase, aspartate aminotransferase activities increased strongly, while that of lactate dehydrogenase only slightly. Based on the results of macroscopic and microscopic imaging techniques and blood biochemical parameters, a comprehensive follow-up study was performed, elucidating still unknown processes during force-feeding of geese

Development of a model using near-infrared reflectance spectroscopy for the determination of the chemical composition of fatty goose liver

The feasibility of NIR spectroscopy for determining chemical composition of goose fatty liver was studied. The spectra of 50 fresh, homogenized liver samples (ether extract content EE=53.2, SD=4.87%) were taken between 1100 and 2500 nm in reflectance mode, then the chemical composition and the fatty acid profile was measured (gas chromatography). Calibration equations were developed using modified partial least-squares regression. The R2 value in estimation of DM, CP and total EE were 0.72, 0.63 and 0.81, respectively. For the major fatty acids (oleic, palmitic and stearic acid, 51.4, 25.8 and 15.5% of total) the R² values were 0.94, 0.93 and 0.16. The estimation of the total saturated fatty acid (SAT) proportion and the so-called unsaturation index (UI) value was effective (R2 =0.81 and 0.79, respectively). The paper demonstrates the usefulness of the NIRS method as a fast and solvent free alternative of liver qualification. For practical purposes a larger number of fatty liver samples are needed