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We investigated the association of muscle iron concentration, in addition to ultimate pH (pHU), on dark meat formation in sheep of different breeds fed forage-based diets. At 1 h simulated display, redness of meat (a*-value) increased (P <.0001) by about 3 units as the iron concentration increased from 10 to 22 mg/kg of meat, whereas the a*-value decreased by 2 units as pHU increased from 5.5 to 6.2 in fresh meat (P <.0001). After 90 days storage the corresponding responses were about 2 units increase for iron concentration and about 1 unit decrease for pHU, respectively. The results clearly show that increased muscle iron concentration was strongly associated with reduced dark cutting in fresh and stored meat evaluated at 1 h simulated display. We conclude that it may be desirable to measure iron concentration, along with pHU, for evaluation of the potential for carcasses to produce dark cutting meat, and for the meat to turn brown during display. • The association of muscle iron concentration and ultimate pH on redness of sheep meat at retail display was investigated • Increased muscle iron concentration was strongly associated with increased redness at 1 h retail display • The muscle iron effect on redness occurred both in fresh and in stored (aged) meat • The effect of muscle iron concentration was additive to the accepted effect of ultimate pH at 1 h retail display • There is a necessity to measure both iron concentration and ultimate pH when evaluating carcasses for dark cutting meat [ABSTRACT FROM AUTHOR]

• The value of extra pasture DM for livestock production can be estimated using several different methods. • The two-price market value method can be an efficient way to estimate the value of extra seasonal dry matter yield of pasture grown and used. • To demonstrate its application, the method is used to value the seasonal yield of 19 perennial ryegrass cultivars grown in temperate Australia. • The value of extra pasture estimated using the two-price market value method can be easily generalised across a range of farming systems. The challenges of estimating the value of growing and using extra pasture to the farm business often necessitates using complex systems modelling of individual farms. In this paper, a straightforward market value method is outlined, where technical substitutes for which there is a defined market price are used as proxies to estimate an equivalent value for extra pasture used in a farm system. The method can be useful for all grazed livestock production systems where substitutes for pasture are purchased and sold. The two-price approach presented advances on previous applications of using market values by accounting for differences in the value of extra pasture DM used on farm in different seasons. The value per extra kg DM harvested in seasons when pasture typically limits livestock production, for example during summer/autumn in temperate environments, and used on farm equates to the market price of the replacement cost as purchased supplementary feed. This is the maximum the extra pasture DM could be worth when used in the farm system. Conversely, the value per extra kg DM harvested in spring when extra pasture is likely to be in surplus of livestock requirements, equates to its market price if sold, as standing hay for example, termed the salvage value. This two-price approach was applied to value the previously published seasonal DM yield differences of 19 perennial ryegrass cultivars, compared to an industry standard cultivar, grown in three regions of Victoria, Australia. Results were then compared to the value of extra pasture DM previously estimated using system simulation analyses of three farms and applied to the same perennial ryegrass data set. The difference in the value of extra pasture DM estimated using the two methods ranged from $0.01/kg DM to $0.24/kg DM. Overall, the two-price method estimated an extra $24 to $200/ha.year benefit over the industry standard cultivar for the 19 cultivars across the three regions, similar to the extra $0 to ∼ $180/ha.year estimated by the previous system simulation analysis. The two-price market value method can be an efficient way to estimate the value of extra seasonal DM yield of pasture, with results easily generalised across a range of farming systems. [ABSTRACT FROM AUTHOR]

Abstract Agricultural industries are faced with the challenge to reduce their emissions of greenhouse gases (GHG) such as nitrous oxide (N 2 O), carbon dioxide (CO 2) and methane (CH 4). Approximately 27% of the GHG emissions generated by agriculture and 80% of the GHG emissions generated by livestock are in the form of CH 4 from enteric fermentation and manure management. Two feed additives that have been shown to decrease enteric CH 4 emissions are 3-nitrooxypropanol (3-NOP) and nitrate. However, data are lacking on the net impact of these CH 4 mitigating additives on whole farm GHG emissions across different production systems. The objectives of this partial life cycle assessment (LCA) were: 1) to analyse the effect of 3-NOP and nitrate on whole farm GHG emissions of Australian and Canadian beef and dairy farms, and 2) to analyse the effect of different strategies of 3-NOP and nitrate feeding on whole farm GHG emissions. Two Australian dairy farms (ADF), one Australian beef farm (ABF), one Canadian dairy farm (CDF) and one Canadian beef farm (CBF) were modelled over the productive lifespans of dairy and beef herds. Australian farm GHG emissions were estimated based on the Australian National Greenhouse Gas Inventory method using the Greenhouse Accounting Framework calculators for beef and dairy. For the Canadian farms, total GHG emissions were estimated using Holos 3.0.3, a whole-farm software model. For all farms, the system boundary of the partial LCA was defined as the farm gate, including emissions associated with on-farm activities and emissions associated with production and transport of major production inputs. Both additives decreased whole farm GHG emissions; however, 3-NOP had a greater effect than nitrate. Feeding 3-NOP but not nitrate could be economical for both beef and dairy farms, depending on the cost of 3-NOP. It is concluded that 3-NOP can make an important contribution to reducing whole farm GHG emissions; however, a carbon offset method would have to be in place to incentivize its use in the livestock industries. Highlights • Feeding 3-NOP decreased whole farm greenhouse gas emissions. • Feeding nitrate decreased whole farm greenhouse gas emissions. • Feeding 3-NOP had greater effect than nitrate on whole farm greenhouse gas emissions. • With current carbon prices, feeding 3-NOP could be economical for use on farm. [ABSTRACT FROM AUTHOR]

Eighty-four crossbred wether and ewe lambs were allocated to four finishing diets. The diets were: Lucerne pasture (n = 24), Annual ryegrass with sub clover pasture (n = 18), Standard commercial feedlot pellets (n = 24) and Annual ryegrass based pasture and commercial feedlot pellets (500 g/day/head) (n = 18). After 8 weeks of feeding the lambs were slaughtered and the m. longissimus (LL) and m. semimembranosus (SM) were vacuum packaged and held chilled for 5 (fresh) or 60 (long aged) days, after which samples of each were displayed for 4 days under simulated retail conditions. Irrespective of muscle type the long aged samples exhibited a rapid reduction in redness (a*-values) and R630/580 nm ratio values such that consumer acceptable thresholds for both traits were quickly exceeded providing limited shelf life. Long ageing also lead to high TBARS levels measured as MDA mg/kg muscle suggestive of a product likely to exhibit rancidity and off flavours from lipid oxidation. [ABSTRACT FROM AUTHOR]

The effect of feeding flaxseed or algae supplements to lambs on muscle antioxidant potential (vitamin E), major fatty acid groups, lipid oxidation and retail colour was investigated. Lambs (n = 120) were randomly allocated to one of 4 dietary treatments according to liveweight and fed the following diets for eight weeks: Annual ryegrass hay [60%] + subterranean clover hay [40%] pellets = Basal diet; Basal diet with flaxseed (10.7%) = Flax; Basal diet with algae (1.8%) = Algae; Basal diet with flaxseed (10.7%) and algae (1.8%) = FlaxAlgae. Flaxseed or algae supplementation significantly affected major fatty acid groups in muscle. The addition of algae (average of Algae and FlaxAlgae) resulted in lower vitamin E concentration in muscle ( P < 0.003; 1.0 vs 1.3 mg/kg of muscle) compared with lambs fed a diet without algae (average of Basal and Flax). Increasing muscle EPA + DHA by algae supplementation significantly increased lipid oxidation, but retail display colour of fresh meat was not affected. [ABSTRACT FROM AUTHOR]

Abstract: The relationship between muscle vitamin E, forms of iron, polyunsaturated fatty acids (PUFA) and the redness of meat (retail display) at days 3 to 4 post slaughter from lambs offered 2 different diets was examined. Meat redness was positively related to vitamin E and heme iron and negatively related to total n-3, total n-6 and total PUFA content. However, after adjusting for the effects of vitamin E and heme iron content, there was no indication of any residual relationship between redness at days 3–4 of retail display and total n-3, total n-6 or total PUFA. This indicates that the relationship between PUFA and redness in meat is mediated through the effects of heme iron and vitamin E in the muscle. It appears that the level of highly oxidisable PUFAs in muscle tissues do not play a major role in maintenance of redness at days 3–4 of retail display, but the level of vitamin E and heme iron content are important. [Copyright &y& Elsevier]

• Ten mathematical models were created to predict pasture yield and nutritive value • Model inputs were field spectrophotometer readings (with or without added covariates) • The models can be applied in situ without destructive sampling to analyse pasture • The pasture yield, crude protein, and energy fraction models predicted most accurately • Models should not be applied where there is substantial bare ground exposure To optimise grazing livestock nutrition, it is necessary to know both the available dry matter yield and the nutritive characteristics of pasture at the farm-scale in near real time. Previous studies have shown the potential of using field spectrophotometers that measure the reflectance of light across the visible to near infrared spectrums to gather information on pasture dry matter yield (DMY) and nutritive characteristics. This study sought to calibrate and validate new mathematical models for ten parameters including dry matter yield and nine nutritive characteristics of relevance to ruminant nutrition. As a part of the analysis process, two innovative approaches were tested: the use of a hybrid modelling approach where partial least squares regression (PLSR) outputs were used as support vector regression (SVR) inputs; and, the inclusion of covariate data. These approaches were compared with traditional stand-alone PLSR and SVR modelling approaches without covariates. The study was undertaken in six predominantly perennial ryegrass pastures on a single farm in the temperate zone of South-Eastern Australia. A total of 204 pasture samples were scanned with a field spectrophotometer over several spring growth stages in late 2019 and subsequently analysed by wet chemistry to obtain reference nutritive values. The raw reflectance spectra were initially pre-processed using a variety of techniques and then used to test the four kinds of chemometric models. In cross validation, hybrid models showed a superior fit for all variates in comparison to the other model types tested. However, the differential was reduced in independent validation where, out of 10 best-performing models for dry matter yield and key nutrient properties, six were produced by the hybrid modelling, three from SVR and one from PLSR. For every hybrid model that was built, adding covariate(s) consistently improved model performance but the increase was small (a reduction in normalised root mean square error (RMSE) of -0.36 % on average for all properties considered). The best performing models were comparable with other published literature with normalised RMSE of prediction ranging from 1.7 – 23.1 % (a mean of 9.7%). Well-predicted variates included metabolisable energy, digestible energy, DMY, and crude protein. Fibre fractions, ash and dry matter were less well-predicted but still had acceptable normalised RMSE values (< 10 %) while carbohydrate fractions were the poorest predicted variates. It was concluded that hybrid modelling in chemometric analyses can modestly improve accuracy and shows promise as an alternative to more traditional approaches. Using covariates also improved accuracy, but the additional time and effort to gather such information outweighed the minor benefits of inclusion. [ABSTRACT FROM AUTHOR]

• Accurate seasonal predictions of ryegrass cultivar DM yields using LMMs. • Base AR 37 and Bealy NEA2 were the best performing cultivars based on annual ranking. • Seasonal variability was found to be larger than genotypic variability. • An antedependence of order 3 was the best residual covariance structure for harvests. With over 60 commercial perennial ryegrass cultivars available on the market in Australia, selecting cultivars with high dry matter (DM) yield and economic profitability requires accurate estimates of their DM yield across target environments. This study, using data from multi-environment multi-harvest (MEMH) trials conducted in south-eastern Australia, derived accurate seasonal predictions of DM yield of these cultivars using linear mixed models (LMM). Base AR37 and Bealy NEA2 were found to be the best performing cultivars in most of the seasons in the target south-eastern Australian environments. Seasonal variability was found to be larger than genotypic variability as usually is the case in multi-environment trials. We have provided details of the LMM methodology used, along with ASReml-R code, to enable others to apply it in similar studies with appropriate changes as required for dataset used. The statistical theory underlying this methodology has also been briefly described in an Appendix for interested readers. [ABSTRACT FROM AUTHOR]