13 Grain Processing
Processing grains increase the availability of starch in the rumen, which results in an improved digestibility of the feedstuff. The improved digestibility reduces energy losses and increases rate of passage, which can subsequently reduce CH4 emissions directly (Hristov et al., 2013). Grain processing can also effect CH4 production by increasing feed efficiency, leading to increased animal performance and decreased number of days until harvest. One study compared precision processing, a process of setting roller width to match kernel size, to a conventional processing, leaving roller width the same for all kernel sizes, of barley and observed an improvement in animal performance (Yang et al., 2012). It was observed that by precision processing the barley, there was a 25-day reduction in days on feed, which saved 163 kg of feed per head throughout the feeding period (Yang et al., 2012). Reducing the amount of feed consumed reduces total CH4 produced because DMI and CH4 emissions are highly correlated. Additionally, reducing days on feed could have a significant impact on CH4 production by reducing the total carbon footprint (CFP; kg of CO2 equivalent per kg of product produced) of the beef industry (Hristov et al., 2013).
Branine, M. E. 1987. Effects of grain and monensin on ruminal fermentation, forage intake and digestibility, digesta kinetics and performance in beef steers grazing native range or winter wheat pasture. Ph.D. Diss. New Mexico State University, Las Cruces.
In studies of other tannin-containing legumes, the fatty acid composition of blood plasma predicted trends in the fatty acid composition of intramuscular fat (Vasta et al., 2009). At the end of the 2013 grazing season, the blood plasma of cows on the grass treatment was significantly higher in trans-vaccenic acid (TVA), the precursor of conjugated linoleic acid (CLA; 18:2c9t11) in intramuscular fat. trans-Vaccenic acid is produced in the rumen via biohydrogenation of mono- and polyunsaturated substrates, including both linoleic and linolenic acids; linolenic acid is more efficiently converted to TVA than linoleic acid (Bauman et al., 2003). In cattle on a feedlot diet in 2013, TVA was significantly lower than for steers on any pasture treatment. Cattle fed on pastures and in the feedlot in 2013 were slaughtered, and subjected to carcass evaluation. The meat from these cattle was used in sensory panels and was evaluated for quality characteristics. The results of these studies will be reported in other publications.
correlated with the increase in stocking rate (McCarthy et al. 2014). Research indicated that an increase in stock- ing rate results in increased grazing intensity, which will subsequently result in lower daily herbage allowance (McCarthy et al. 2011). Changes in seasons from wet to dry meant that available forage material is fibrous and is not palatable, hence lowering DMI. Nguni cattle minim- ise energy loss in the dry season through deliberate voluntary anorexia and feeding during the cooler hours of the day (Scholtz 2011). The cattle are also bulky grazers unlike other breeds, which are selective grazers. This causes Nguni cattle to, minimally, lose condition, during periods when feed resources are scarce. Boran cattle have survived in challenging Afri- can terrain for a long period to evolve and have attri- butes that allow them to manage situations where forage is in short supply. The animals store fat deposits during the periods when feed resources are abundant and later on use them when the forage availability is low (Berman 2011). Such mechanisms could have contributed to maintenance of body con- dition scores at optimal levels in this study.
Beef growth (i.e. 0 to 21 months) under grazing and indoor fatten- ing (i.e. 22 to 25 months) data for Local Yellow×Red Sindhi (B. indicus; Lai Sind; LSD), and 1/2 Limousin (LS), 1/2 Drought Master (DS), and 1/2 Red Angus (RS) cattle were obtained from a household farming study  conducted in the EaKar District of the DakLak Province of Vietnam between September 2007 and December 2010. Animals in each breed (n = 4; [16,17]) were subject to the same measurement variables (dry matter intake [DMI], live weight [LW], and carcass characteristics). Conse- quently, the size of the declared differences between the treatments accounted for the variation between and within animals as well as throughout the time of the initial experimental programme [16,17]. This represented the current situation and the reference- starting point for developing simulations using the digestion and metabolism ruminant model to determine variations on growth performance, meat productivity and estimates of entericmethaneemissions related to alternative feeding scenarios.
Land 2018, 7, 26 4 of 9
All cows were fed a partial mixed ration (PMR) containing forage and concentrates ad libitum, with additional concentrates fed whilst milking. Of the 12 farms studied, half the farms allowed the cows access to grass (PMR + grazing) during the day. Dry matter intake of individual cows was predicted from their milk yield and live weight using the equation by MAFF [ 20 ] as: Dry matter intake (kg/day) = 0.025 × live weight (kg) + 0.1 × milk yield (kg/day). Records on the composition of diet and forage (Table 2 ) and concentrate feeds (Table 3 ) were obtained from each farm, with feed samples analysed by a commercial analytical laboratory (Sciantec Analytical Services, Cawood, UK). Cows used in this study were mainly Holstein-Friesian breed and remained on the same feeding regime throughout the measurement period.
The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher’s version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.
Animals used. The work described was conducted in accordance with the requirements of the UK Animals (Scientific Procedures) Act 1986 and with the approval of the Aberystwyth University Animal Welfare and Ethical Review Board. Measurements were made on mature barren ewes of four different breed types: Welsh Mountain, Scottish Blackface, Welsh Mule (Welsh Mountain × Border Leicester) and Texel (n = 8 per breed). The Welsh Mountain and Scottish Blackface are hardy hill breeds commonly used in extensive production systems on mar- ginal grasslands. Cross-bred ewes such as the Welsh Mule are larger and more prolific, and are generally used in more intensive production systems based on improved pasture. The Texel breed is a large meat breed valued for its carcass characteristics. Animals were selected from their respective flocks on the basis of LW and uniformity of body condition score 33 . All animals were drenched with an anthelmintic prior to the start of each experiment.
All cows were fed a partial mixed ration (PMR) containing forage and concentrates ad libitum, with additional concentrates fed whilst milking. Of the 12 farms studied, half the farms allowed the cows access to grass (PMR + grazing) during the day. Dry matter intake of individual cows was predicted from their milk yield and live weight using the equation by MAFF  as: Dry matter intake (kg/day) = 0.025 × live weight (kg) + 0.1 × milk yield (kg/day). Records on the composition of diet and forage (Table 2) and concentrate feeds (Table 3) were obtained from each farm, with feed samples analysed by a commercial analytical laboratory (Sciantec Analytical Services, Cawood, UK). Cows used in this study were mainly Holstein-Friesian breed and remained on the same feeding regime throughout the measurement period.
A drawback of Audsley et al.’s first-derivative approach is the assumption that some marginal pasture lands are cur- rently only productive when used for cattlegrazing (Foley et al., 2011), thus grazing lands are not contributing to LUC from the consequential perspective. But alternatively, re- cent analysis suggests grazing lands could also be used to power horse-based transportation (in the developing world) or for cellulosic biofuels, and thus have other uses and trade- offs (Liska and Heier, 2013); this would suggest pasture graz- ing should be attributed consequential ILUC emissions. Also, Audsley et al.’s approach does not capture increased soil car- bon storage in pasture (compared to cropland) or address the impact of substitute products which may have an identi- cal land area footprint, but different land use change impacts. Yet, this approach appears to be the most consistent with at- tributional LCA principles since it does not over-count and is not dependent on situational conditions. A second-derivative consequential framework, however, could be more insightful if needed to inform agricultural policy (Dumortier et al., 2012).
5. Genomic prediction of feed intake
Feed costs represent half of the total costs of dairy production (EU, 2011). Therefore, one way to increase profitability of dairy production is to reduce feed costs by improving feed efficiency (Veerkamp, 1998, de Haas et al., 2012). Optimization of dairy cattle breeding goals for feed efficiency requires the availability of breeding values for DMI, as this is an important component of feed efficiency. In order to estimate accurate DMI breeding values, a large number of records is required; however, DMI is a labor-intensive and expensive-to-measure trait, which is not recorded in relation to commercial herds, meaning that the amount of available data is limited. The difficulty in recording DMI has hampered direct selection for DMI previously, since an insufficient number of records was available on daughters of progeny-tested bulls. This difficulty might be overcome by jointly using predictor traits (Veerkamp and Brotherstone, 1997, Berry and Crowley, 2013, Manzanilla-Pech et al., 2016) and genomic information (Meuwissen et al., 2001). A readily available predictor trait is fat and protein corrected milk (FPCM), while live weight (LW) is another that is easier and cheaper to record than DMI itself. LW can also be very accurately predicted from linear-type traits (Koenen and Veerkamp, 1998, Banos et al., 2012, Haile-Mariam et al., 2014). Both FPCM and LW are known to be highly correlated with DMI (Korver, 1988, Van Arendonk, 1991, Veerkamp and Brotherstone, 1997, Veerkamp, 1998, Liinamo et al., 2012). Ideally, breeding values for feed intake across the whole productive lifetime of cows should be predicted, but historical DMI data in the Netherlands has mainly covered the first lactation. Furthermore, linear-type traits, which are used to predict LW, are only recorded during the first lactation. It is well known that DMI and LW are traits, which vary across lactations (Veerkamp and Thompson, 1999, Berry et al., 2006). For this reason, it is important to investigate the impact of using data for genomic prediction in Lactation 1 alone, or using data combined from multiple lactations when predicting feed intake in Lactation 1 or in the first three lactations.
Ammonia Emission Estimates
The EF values derived from the literature and used in the model are given in Tables 5 and 6. Our selection of EF data from the literature gave priority to field measure- ments based on mass balances or micrometrological methods, or to values from reviews that were frequently cited by others. The specific values of EF we used were generally consensus or median values based on a number of references. The EF values for landspreading were computed using regression models (Misselbrook et al. 2005) that were derived from large data sets. The values presented in Table 6 were computed from these models for national median conditions, and were subsequently modified slightly among the Ecoregions for temperature and rainfall effects. The estimates of N excretion and NH3 emission, differentiated by animal type and stage from housing to landspreading (Table 7), indicate that cows are the major source, and this is consistent with their relative biomass: cows make up about 55% of the total beefcattle biomass compared with only 25% for steers and heifers combined (Table 7). However, cows only cause 42% of the total NH3 emissions because much of their N excretion is done on pasture where EF values are low. Total emissionsfrom heifers (2.7 kg yr 1 ) were slightly lower than for steers (3.4 kg yr 1 ) because the heifers include replacement in addition to slaughter heifers, and the replacement heifers are on pasture longer than are the steers.
Because the feed trial took place during the dry season, we were limited in our supply of fresh manure and were only able to measure emissions during the dry season. We did add 20 mm of precipitation 2 wk after application to mimic a rain event, which resulted in an increase in emission rates. This, along with changes to fodder quality and therefore manure quality as well, suggests that the emission factors may change if measurements are made throughout the year rather than during just one season. A pre- vious study found higher emissions during the “summer,” when temperatures were higher than during a cooler “winter” period in Brazil (Mazzetto et al., 2014). Also, deposition rates and feces properties are not constant throughout the year (Rufino et al., 2006; Schlecht et al., 2006). Given that the ad libitum diet with additional protein supplementation was a better quality diet than many African cattle receive during the dry season, it is likely that annual field emissions are lower than what we suggest here, although additional investigation is required to verify these assumptions. Excreta emissions on pasturelands, however, are typ- ically very low in comparison to enteric CH 4 emissions (Jarvis et
on the subsequently growth rate of the Limousin calves when pastured on the silage aftermath in the autumn. The figures for cow weight change over the summer period revealed a significant interaction between management system and year. Output in terms of lamb and calf liveweight gain per unit area of improved pasture were calculated, and combined to give the total output. The SPP system had the lowest overall output. The highest overall yield was recorded on the S/C6L SN system, with the S/C12L SN similar to that of the S/C6L PP. Further research is required to profile the chemical composition of native plant species in greater detail, and to investigate the extent to which nutrient use efficiency can be manipulated by altering the balance of different plant species within the diet. There is also a need to explore how environmental factors, including soil status and climatic conditions, influence the chemical composition of such plants, in order to better predict the nutritional value of vegetation at different sites. This information, together with corresponding vegetation survey data, would give a robust rationale for the development of grazing plans for specific sites that optimise the efficiency of use of nutrients available.
Here, the arboreal community was not negatively impacted by heavy grazing, but this may not be the case elsewhere, depending on the extent of tree clearing, fire, and other indirect impacts on arboreal habitats. Tree clearing, often associated with grazing, is a major threat to arboreal fauna (Gibbons and Lindenmayer 2002; Parsons et al. 2017). Indirectly, long-term soil compaction, may suppress new tree growth (Fischer et al. 2004) and grazing can interact with browsing by large native herbivores, resulting in changes to arboreal structure (Ogada et al. 2008; Pringle 2008). Fischer et al. (2009) suggest that current grazing management styles are leading to major tree declines. As keystone structures, loss of trees will have major impacts on the distribution and biodiversity across vast regions of the world (Manning et al. 2006). Both dead and living trees, and the accumulation of course woody debris, are prime habitat for diverse animal communities (Whiles and Grubaugh 1996). Even damaged trees increase structural complexity, and can increase occupancy of arboreal lizards (Pringle 2008). Unlike other areas used for livestock grazing, the Wambiana Grazing Trial has not been cleared within the last 100 years and therefore has many old, overstory trees. Additionally, fire is not regularly used to suppress woody growth at this location. While open-canopy woodlands such as the Wambiana Grazing Trial have naturally sparse tree cover, the trees that are present support a wide variety of wildlife, especially old trees with hollows and flaking bark (Gibbons and Lindenmayer 2002; Bryant et al. 2012).
Pregnancy: Estimating the energy demands of pregnancy is complicated by many factors, notably the incidence of multiple births (the energy demand of twins is less than twice the energy demand of a single foetus), and the loss of lambs due to miscarriages, stillbirths, and early lamb mortality. However, most pregnancies result in a single lamb. By assuming that the energy demand of a single foetus applies to all lambs born, these complications tend to offset each other - i.e., the extra ‘efficiency’ of multiple births, is offset by the ‘inefficiency’ of lambs lost to miscarriages, stillbirths and early mortality. Consequently, if the number of live lamb births is known, it is reasonable to take this to be the same as the number of pregnancies. If the number of lambs reared to weaning is the only available estimate of lambs born, then this number could be taken as the number of pregnancies, adjusted by an estimate of lamb survival from birth to weaning. Adjustments can also be made for seasons of high lamb mortality such as might result from adverse weather or poor grazing conditions. The AFRC assesses the energy retained by the conceptus (foetus plus placenta and other associated tissues) during each day of the pregnancy. Integrating these throughout the gestation period (148 days) provides an expression for the energy cost (NE required ) of a single-foetus pregnancy:
Models developed on the EU database and model evaluations are presented in Table 3. The internal EU model evaluations based on EU observations and model comparisons across different categories followed a trend similar to the intercontinental prediction models. Adding NDF to DMI improved model accuracy compared to using either DMI or GEI alone or adding EE to DMI (Table 3). A model with dietary concentrations without DMI did not perform as well as models in previous categories. Models using ECM and milk composi- tion performed better than those using MY only. When all predictors were available for selection, DMI, dietary EE, dietary NDF, MF, and BW were selected and had a similar performance (RMSPE = 14.6%, Equation 23) as the DMI + NDF. Once again, if DMI was taken out, prediction accuracy became worse (RMSPE = 15.8%, Equation 24). Similar to RMSPE, evaluation through CCC and MAE also indicated that models using DMI + NDF and all variables had better prediction accuracy compared to the other models (CCC = 0.72 and 0.72, respectively; Table 3) and (MAE = 44.9 and 44.5 g/day, respectively; Figure 2). In addition, the intercontinental and EU models had similar overall performance for predicting enteric CH 4 production of EU
Orlando A Aguilar 1* , Ronaldo Maghirang 2 , Steven L Trabue 3 , Charles W Rice 4 and Larry E Erickson 5
Pen surface amendments for mitigatingemissions of greenhouse gases (GHGs), such as nitrous oxide (N 2 O), methane (CH 4 ), and carbon dioxide (CO 2 ), frombeefcattle feedlots, were evaluated under controlled laboratory conditions. Amendments were organic residues (i.e., sorghum straw, prairie grass, woodchip), biochar from those organic residues and frombeefcattle manure, and activated carbon. Manure samples were collected from several randomly selected pens from two beefcattle feedlots in Kansas and used in the experiments, either as dry (0.10 g · g −1 wet basis water content) or moist (0.35 g · g −1 wet basis). For each amendment, four different treatment levels (i.e., amounts of material) were placed on top of manure samples in glass containers and analyzed for GHG emissions using a photo-acoustic infrared multi-gas analyzer. From measured concentrations, emission rates were determined. For the dry manure conditions, all amendment materials showed significant reduction of N 2 O and CO 2 emissions compared to the control (i.e., no amendment). For the moist manure conditions, none of the amendments showed significant effects on GHG emissions during the first 8 days; at days 10 and 15 after application, however, the biochar materials performed significantly better than the control (i.e., no surface amendment) in reducing N 2 O and CH 4 emissions. No significant difference was observed in GHG emissions when the amendments were placed on top or mixed within the top surface layer of the manure.