Suchergebnisse

Models as InraPorc® have been developed to simulate pig growth and to determine nutrient requirements. They are largely applied to conventional breeds but so far not to local breeds. Our study aimed to use InraPorc® to determine nutrient requirements of growing pigs from local breeds in H2020 EU project TREASURE. Data on feed composition, allowance and intake, and body weight (BW) were extracted from literature reports or experiments conducted within the project. They were used to calibrate parameters defining a growth and intake profile in InraPorc®. We obtained 15 profiles from 9 breeds (Alentejano, Basque, Bísaro, Calabrese, Cinta Senese, Iberico, Krškopolje, Mangalitsa Swallow Bellied and Moravka). Breeds had 1 to 3 profiles depending on experimental conditions or data sources. Conditions of the study affected calibration results. The mean protein deposition (PD) was low for all breeds from 39.9 to 91.0 g PD/day vs over 110 g/d in conventional breeds. For 40-100 kg BW range, the age of the pigs at 40 kg BW was between 110 and 206 days, denoting different feeding management in addition to genetic differences. Average daily gain (ADG) and feed intake curves showed similar shape. Protein deposition rate was the highest in breeds with the highest ADG. Lysine requirements were largely covered in all studies and breeds, the highest requirements being observed with the highest ADG. In all breeds a low part of total body energy retention was dedicated to protein, conversely to lipids. Despite some methodological limitations, this study provides a first insight on nutrient requirements for some local breeds. Funded by European Union's Horizon 2020 RIA program (grant agreement no. 634476).

The objective of the present study is to evaluate the potential use of FT-NIRS for predicting intramuscular fat (IMF) and fatty acid groups (MUFA; PUFA; PUFA n-3, PUFA n-6; SFA) on pig grounded muscles. The research considered 160 fresh samples of Longissimus collected from 12 European local pig breeds (TREASURE* project). For every sample, lipids were extracted from IMF and fatty acid profile was determinate by gas chromatography. Two aliquots of each sample were scanned using FT-NIRS Antaris II model. Mathematical pre-treatments (multiplicative scatter correction, 1st and 2nd derivate) were applied and outliers' spectra were identified and removed when necessary. Partial least square regression was used on the average spectrum and the models validated using an external data set. Results are evaluated in terms of coefficient of regression and root mean square errors in calibration (R2- RMSE) and validation (Rp2-RMSEP). As expected, the best results were obtained for IMF with R2 higher than 0.99 and RMSE lower than 0.2. Unsaturated fatty acids, probably due to the absorption of the cis double bond in a specific region of near infrared spectra, obtain acceptable R2 (0.89 for MUFA and 0.75 for PUFA n-3 and PUFA n-6). SFA achieved a R2 of 0.81 that is lower than values reported in other studies probably because of the large variability of genotypes used. The validation models achieved both lower coefficients of determination and higher RMSEP than the calibration models; however, R2 differences between calibration and validation were smaller than 5%, except for SFA. Hence, the FT-NIRS seems promising to estimate the principal parameters of fatty acid groups on muscle samples from different European autochthonous pig breeds. Inclusion of other samples can improve the accuracy and the robustness of the models, especially considering the high variability of the samples. *Funded by European Union's H2020 program (grant agreement No 634476).