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On-farm nutrition and management interventions to reduce enteric CH4 (eCH4) emission, the most abundant greenhouse gas from cattle, may also affect volatile solids and N excretion. The objective was to jointly quantify eCH4 emissions, digestible volatile solids (dVS) excretion and N excretion from dairy cattle, based on dietary variables and animal characteristics, and to evaluate relationships between these emissions and excreta. Univariate and Bayesian multivariate mixed-effects models fitted to 520 individual North American dairy cow records indicated dry matter (DM) intake and dietary ADF and CP to be the main predictors for production of eCH4 emissions and dVS and N excreta (g/day). Yields (g/kg DM intake) of eCH4 emissions and dVS and N excreta were best predicted by dietary ADF, dietary CP, milk yield and milk fat content. Intensities (g/kg fat- and protein-corrected milk) of eCH4, dVS and N excreta were best predicted by dietary ADF, dietary CP, days in milk and BW. A K-fold cross-validation indicated that eCH4 and urinary N variables had larger root mean square prediction error (RMSPE; % of observed mean) than dVS, fecal N and total N production (on average 24.3% and 26.5% v. 16.7%, 15.5% and 16.2%, respectively), whereas intensity variables had larger RMSPE than production and yields (29.4%, 14.7% and 14.6%, respectively). Univariate and multivariate equations performed relatively similar (18.8% v. 19.3% RMSPE). Mutual correlations indicated a trade-off for eCH4v. dVS yield. The multivariate model indicated a trade-off between eCH4 and dVS v. total N production, yield and intensity induced by dietary CP content.
The automation of existing in vitro gas production methods (Beuvink et al., 1992) and the development of new ones (Theodorou et al., 1994) have created a need for suitable mathematical models to describe and interpret cumulative gas production profiles. Ideally a function is required which is capable of modelling a range of shapes with no inflexion point and also a range of sigmoidal shapes in which the inflexion point is variable. Several models have been proposed to describe gas production profiles (e.g. Blümmel and Ørskov, 1993; Beuvink and Kogut, 1993; Schofield et al ., 1994), sometimes blending empiricism with a more mechanistic view based on a compartmental scheme. The primary objectives of this paper are to present a unifying analysis of this area, pointing out compartmental interpretations of some of the candidate models and to link the gas production technique to animal performance by determining the extent of ruminal degradation for each model.
In protein evaluation systems for ruminants, the microbial protein supply is calculated from the amounts of rumen degradable organic matter and nitrogen (N) using empirical equations. A variable part of the rumen synthesized microbial protein does not reach the duodenum but is recycled within the rumen (review Firkins, 1996). Since energy is required for its re-synthesis and degraded microbial protein is subject to deamination, the efficiency of substrate conversion into microbial protein in the rumen is affected by microbial recycling. Rumen protozoa have a major impact upon this recycling through engulfment of micro-organisms and autolysis. In vitro, bacterial protein breakdown is proportionately reduced by some 0·9 upon removal of protozoa (Wallace and McPherson, 1987). Defaunation of the rumen increases the efficiency of microbial protein synthesis in vivo significantly (review Jouany et al., 1988).
To investigate socio-economic differences in changes in fruit and vegetable intake between 2004 and 2011 and explore the mediating role of financial barriers in this change.
Respondents completed a self-reported questionnaire in 2004 and 2011, including questions on fruit and vegetable intake (frequency per week), indicators of socio-economic position (education, income) and perceived financial barriers (fruits/vegetables are expensive, financial distress). Associations were analysed using ordinal logistic regression. The mediating role of financial barriers in the association between socio-economic position and change in fruit and vegetable intake was studied with the Baron and Kenny approach.
Longitudinal GLOBE study.
A total of 2978 Dutch adults aged 25–75 years.
Respondents with the lowest income in 2004 were more likely to report a decrease in intake of cooked vegetables (P-trend<0·001) and raw vegetables (P-trend<0·001) between 2004 and 2011, compared with those with the highest income level. Respondents with the lowest education level in 2004 were more likely to report a decrease in intake of fruits (P-trend=0·021), cooked vegetables (P-trend=0·033), raw vegetables (P-trend<0·001) and fruit juice (P-trend=0·027) between 2004 and 2011, compared with those with the highest education level. Financial barriers partially mediated the association between income and education and the decrease in fruit and cooked vegetable intake between 2004 and 2011.
These results show a widening of relative income and educational differences in fruit and vegetable intake between 2004 and 2011. Financial barriers explained a small part of this widening.
The high contribution of postruminal starch digestion (>50%) to total tract starch digestion on certain energy dense diets (Mills et al. 1999) demands that limitations to small intestinal starch digestion are identified. Therefore, a dynamic mechanistic model of the small intestine was constructed and evaluated against published experimental data for abomasal carbohydrate infusions in the dairy cow. The mechanistic structure of the model allowed the current biological knowledge to be integrated into a system capable of identifying restrictions to dietary energy recovery from postruminal starch delivery.
A non-invasive method is proposed for determining the extent of degradation in the rumen, based on the gas production technique and mathematical modelling. The exercise involves developing both a statistical model and a kinetic model (France et al., 2000). The statistical model shifts (or maps) the gas accumulation profile obtained using a faecal inoculum to a rumen gas profile, thus obviating the need for rumen sampling. The kinetic model determines the extent of degradation in the rumen from the shifted profile. It is presented as a generalised mathematical function, allowing any one of a number of alternative equation forms to be selected.
To calculate the extent of ruminal degradation based on the gas production technique, equations were derived to describe gas production profiles from substrate degradation (France et al. submitted). This derivation demonstrated that if the yield of gas (Y; ml/g degradable OM) produced during the course of incubation varies significantly, then the calculated extent of degradation is not correct. Variation in Y may occur due to variation in the yield of individual volatile fatty acids (VFA) produced. The objective of this simulation study was to examine the impact of variation in individual VFA production and consequently in yield of gas on the extent of ruminal degradation.
Gas production profiles were simulated based on a generalized Mitscherlich (GM) equation (see France et al. submitted) for three substrates (soluble sugars, starch, fibre) that differ in degradation rate and VFA production profile (see Table 1).
Dietary intervention to reduce methane emissions from lactating dairy cattle is both environmentally and nutritionally desirable due to the importance of methane as a causative agent in global warming and as a significant loss of feed energy. This investigation involved the development of a dynamic mechanistic model of whole rumen function (Dijkstra et al. 1992), with the objective to simulate whole-animal methane emissions for a range of dietary inputs.
Agriculture in general, and dairy production in particular, has been identified as one of the major sources of greenhouse gas emissions and other environmental pollutants such as nitrogen (N) (as ammonia, N and Nitrous oxides, and N leaching). Availability of cheap sources of protein has led to increased consumption of protein supplements. However, the protein is often utilised inefficiently and excess nitrogen is excreted particularly in urine, which has much more potential to pollute the environment. One of the obvious ways of reducing pollution is by evaluating the pollution potential of diets and formulating more balanced rations. A few technical mathematical models have been published but rarely do they consider more than one pollutant at a time. The objective of the present study was to develop a decision support system (DSS) by first integrating mechanistic models of N (Kebreab et al., 2002) and methane (Mills et al., 2001) with a rumen model (Dijkstra, 1994) and then develop a graphical user interface (GUI) for ease of use and analysis of outputs.
This study investigated the relationships between methane (CH4) emission and fatty acids, volatile metabolites (V) and non-volatile metabolites (NV) in milk of dairy cows. Data from an experiment with 32 multiparous dairy cows and four diets were used. All diets had a roughage : concentrate ratio of 80 : 20 based on dry matter (DM). Roughage consisted of either 1000 g/kg DM grass silage (GS), 1000 g/kg DM maize silage (MS), or a mixture of both silages (667 g/kg DM GS and 333 g/kg DM MS; 333 g/kg DM GS and 677 g/kg DM MS). Methane emission was measured in climate respiration chambers and expressed as production (g/day), yield (g/kg dry matter intake; DMI) and intensity (g/kg fat- and protein-corrected milk; FPCM). Milk was sampled during the same days and analysed for fatty acids by gas chromatography, for V by gas chromatography–mass spectrometry, and for NV by nuclear magnetic resonance. Several models were obtained using a stepwise selection of (1) milk fatty acids (MFA), V or NV alone, and (2) the combination of MFA, V and NV, based on the minimum Akaike’s information criterion statistic. Dry matter intake was 16.8±1.23 kg/day, FPCM yield was 25.0±3.14 kg/day, CH4 production was 406±37.0 g/day, CH4 yield was 24.1±1.87 g/kg DMI and CH4 intensity was 16.4±1.91 g/kg FPCM. The observed CH4 emissions were compared with the CH4 emissions predicted by the obtained models, based on concordance correlation coefficient (CCC) analysis. The best models with MFA alone predicted CH4 production, yield and intensity with a CCC of 0.80, 0.71 and 0.69, respectively. The best models combining the three types of metabolites included MFA and NV for CH4 production and CH4 yield, whereas for CH4 intensity MFA, NV and V were all included. These models predicted CH4 production, yield and intensity better with a higher CCC of 0.92, 0.78 and 0.93, respectively, and with increased accuracy (Cb) and precision (r). The results indicate that MFA alone have moderate to good potential to estimate CH4 emission, and furthermore that including V (CH4 intensity only) and NV increases the CH4 emission prediction potential. This holds particularly for the prediction model for CH4 intensity.
The adaptation of dairy cows to methane (CH4)-mitigating feed additives was evaluated using the in vitro gas production (GP) technique. Nine rumen-fistulated lactating Holstein cows were grouped into three blocks and within blocks randomly assigned to one of three experimental diets: Control (CON; no feed additive), Agolin Ruminant® (AR; 0.05 g/kg dry matter (DM)) or lauric acid (LA; 30 g/kg DM). Total mixed rations composed of maize silage, grass silage and concentrate were fed in a 40 : 30 : 30 ratio on DM basis. Rumen fluid was collected from each cow at days −4, 1, 4, 8, 15 and 22 relative to the introduction of the additives in the diets. On each of these days, a 48-h GP experiment was performed in which rumen fluid from each individual donor cow was incubated with each of the three substrates that reflected the treatment diets offered to the cows. DM intake was on average 19.8, 20.1 and 16.2 kg/day with an average fat- and protein-corrected milk production of 30.7, 31.7 and 26.2 kg/day with diet CON, AR and LA, respectively. In general, feed additives in the donor cow diet had a larger effect on gas and CH4 production than the same additives in the incubation substrate. Incubation substrate affected asymptotic GP, half-time of asymptotic CH4 production, total volatile fatty acid (VFA) concentration, molar proportions of propionate and butyrate and degradation of organic matter (OMD), but did not affect CH4 production. No substrate×day interactions were observed. A significant diet×day interaction was observed for in vitro gas and CH4 production, total VFA concentration, molar proportions of VFA and OMD. From day 4 onwards, the LA diet persistently reduced gas and CH4 production, total VFA concentration, acetate molar proportion and OMD, and increased propionate molar proportion. In vitro CH4 production was reduced by the AR diet on day 8, but not on days 15 and 22. In line with these findings, the molar proportion of propionate in fermentation fluid was greater, and that of acetate smaller, for the AR diet than for the CON diet on day 8, but not on days 15 and 22. Overall, the data indicate a short-term effect of AR on CH4 production, whereas the CH4-mitigating effect of LA persisted.
A Fresnel zone plate (sometimes called a Fresnel-Soret zone plate) is an image formation device consisting of a large number of concentric circular rings which are alternatively transparent and opaque for the radiation concerned.
At the Institute of Applied Physics TNO-TH at Delft a strongly off-plane grating mounting has been developed for the soft X-ray wavelength region. In this mounting a parallel beam is incident on the grating surface nearly parallel to the grooves. We found herewith a remarkable improvement of the grating efficiency compared with the grazing incidence perpendicular to the grooves. The focal distance is nearly independent on the wavelength, so scanning of the spectrum can be provided by a simple rotation of the cylindrical grating around the central groove. The exit slit and the detector have fixed positions. The lightspot on the detector cathode does not move and has a moderate size; a standard detector can be used.
Grass silage is typically fed to dairy cows in temperate regions. However, in vivo information on methane (CH4) emission from grass silage of varying quality is limited. We evaluated the effect of two rates of nitrogen (N) fertilisation of grassland (low fertilisation (LF), 65 kg of N/ha; and high fertilisation (HF), 150 kg of N/ha) and of three stages of maturity of grass at cutting: early maturity (EM; 28 days of regrowth), mid maturity (MM; 41 days of regrowth) and late maturity (LM; 62 days of regrowth) on CH4 production by lactating dairy cows. In a randomised block design, 54 lactating Holstein–Friesian dairy cows (168±11 days in milk; mean±standard error of mean) received grass silage (mainly ryegrass) and compound feed at 80 : 20 on dry matter basis. Cows were adapted to the diet for 12 days and CH4 production was measured in climate respiration chambers for 5 days. Dry matter intake (DMI; 14.9±0.56 kg/day) decreased with increasing N fertilisation and grass maturity. Production of fat- and protein-corrected milk (FPCM; 24.0±1.57 kg/day) decreased with advancing grass maturity but was not affected by N fertilisation. Apparent total-tract feed digestibility decreased with advancing grass maturity but was unaffected by N fertilisation except for an increase and decrease in N and fat digestibility with increasing N fertilisation, respectively. Total CH4 production per cow (347±13.6 g/day) decreased with increasing N fertilisation by 4% and grass maturity by 6%. The smaller CH4 production with advancing grass maturity was offset by a smaller FPCM and lower feed digestibility. As a result, with advancing grass maturity CH4 emission intensity increased per units of FPCM (15.0±1.00 g CH4/kg) by 31% and digestible organic matter intake (33.1±0.78 g CH4/kg) by 15%. In addition, emission intensity increased per units of DMI (23.5±0.43 g CH4/kg) by 7% and gross energy intake (7.0±0.14% CH4) by 9%, implying an increased loss of dietary energy with advancing grass maturity. Rate of N fertilisation had no effect on CH4 emissions per units of FPCM, DMI and gross energy intake. These results suggest that despite a lower absolute daily CH4 production with a higher N fertilisation rate, CH4 emission intensity remains unchanged. A significant reduction of CH4 emission intensity can be achieved by feeding dairy cows silage of grass harvested at an earlier stage of maturity.
The in situ degradation of the washout fraction of starch in six feed ingredients (i.e. barley, faba beans, maize, oats, peas and wheat) was studied by using a modified in situ protocol and in vitro measurements. In comparison with the washing machine method, the modified protocol comprises a milder rinsing method to reduce particulate loss during rinsing. The modified method markedly reduced the average washout fraction of starch in these products from 0.333 to 0.042 g/g. Applying the modified rinsing method, the fractional degradation rate (kd) of starch in barley, oats and wheat decreased from on average 0.327 to 0.144 h−1 whereas for faba beans, peas and maize no differences in kd were observed compared with the traditional washing machine rinsing. For barley, maize and wheat, the difference in non-fermented starch in the residue between both rinsing methods during the first 4 h of incubation increased, which indicates secondary particle loss. The average effective degradation of starch decreased from 0.761 to 0.572 g/g when using the new rinsing method and to 0.494 g/g when applying a correction for particulate matter loss during incubation. The in vitro kd of starch in the non-washout fraction did not differ from that in the total product. The calculated ratio between the kd of starch in the washout and non-washout fraction was on average 1.59 and varied between 0.96 for oats and 2.39 for maize. The fractional rate of gas production was significantly different between the total product and the non-washout fraction. For all products, except oats, this rate of gas production was larger for the total product compared with the non-washout fraction whereas for oats the opposite was observed. The rate of increase in gas production was, especially for grains, strongly correlated with the in vitro kd of starch. The results of the present study do not support the assumption used in several feed evaluation systems that the degradation of the washout fraction of starch in the rumen is much faster than that of the non-washout fraction.
The current longitudinal study investigated the role of home language and outside home exposure in the development of Dutch and Frisian vocabulary by young bilinguals. Frisian is a minority language spoken in the north of the Netherlands. In three successive test rounds, 91 preschoolers were tested in receptive and productive vocabulary in both languages. Results showed a home language effect for Frisian receptive and productive vocabulary, and Dutch productive vocabulary, but not for Dutch receptive vocabulary. As for outside home exposure, an effect was found on the receptive vocabulary tests only. The results can be explained by the amount of L2-input that participants received. The Dutch input is higher for participants with Frisian as home language compared to the Frisian input for participants with Dutch as home language. The conclusions lead to further implications for language professionals working in language minority contexts.
In the classic in situ method, small particles are removed during rinsing and hence their fractional degradation rate cannot be determined. A new approach was developed to estimate the fractional degradation rate of nutrients in small particles. This approach was based on an alternative rinsing method to reduce the particulate matter loss during rinsing and on quantifying the particulate matter loss that occurs during incubation in the rumen itself. To quantify particulate matter loss during incubation, loss of small particles during the in situ incubation was studied using undegradable silica with different particle sizes. Particulate matter loss during incubation was limited to particles smaller than ~40 μm with a mean fractional particulate matter loss rate of 0.035 h−1 (first experiment) and 0.073 h−1 (second experiment) and an undegradable fraction of 0.001 and 0.050, respectively. In the second experiment, the fractional particulate matter loss rate after rinsing in a water bath at 50 strokes per minute (s.p.m.) (0.215 h−1) and the undegradable fraction at 20 s.p.m. (0.461) were significantly larger than that upon incubation in the rumen, whereas the fractional particulate matter loss rate (0.140 and 0.087 h−1, respectively) and the undegradable fraction (0.330 and 0.075, respectively) after rinsing at 30 and 40 s.p.m. did not differ with that upon rumen incubation. This new approach was applied to estimate the in situ fractional degradation rate of insoluble organic matter (OM) and insoluble nitrogen (N) in three different wheat yeast concentrates (WYC). These WYC were characterised by a high fraction of small particles and estimating their fractional degradation rate was not possible using the traditional washing machine rinsing method. The new rinsing method increased the mean non-washout fraction of OM and N in these products from 0.113 and 0.084 (washing machine method) to 0.670 and 0.782, respectively. The mean effective degradation (ED) without correction for particulate matter loss of OM and of N was 0.714 and 0.601, respectively, and significant differences were observed between the WYC products. Applying the correction for particulate matter loss reduced the mean ED of OM to 0.676 (30 s.p.m.) and 0.477 (40 s.p.m.), and reduced the mean ED of N to 0.475 (30 s.p.m.) and 0.328 (40 s.p.m.). These marked reductions in fractional degradation rate upon correction for small particulate matter loss emphasised the pronounced effect of correction for undegraded particulate matter loss on the fractional disappearance rates of OM and N in WYC products.
A mechanistic model (COWPOLL) was used to estimate enteric methane (CH4) emissions from beef production systems in Chile. The results expressed as a proportion of gross energy intake (GEI) were compared with enteric fermentation data reported in the last Chilean greenhouse gases inventory, which utilized an earlier the Intergovernmental Panel on Climate Change Tier 2 approach. The simulation analysis was based on information from feedstuffs, dry matter intake (DMI), body weight (BW) and average daily gain (ADG) of steers raised and finished at two research facilities located in Central and Southern Chile, as well as three simulated scenarios for grass-based finishing systems in Southern Chile. Data for feedlot production systems in the central region were assessed by considering steers fed a forage : concentrate ratio of 23 : 77 using maize silage and wheat straw as roughage sources during the stages of backgrounding and fattening. Average DMI were 7·3±0·62 and 9·2±0·55 kg/day per steer for backgrounding and fattening, respectively, whereas ADG were 1·1±0·22 and 1·3±0·37 kg/day for backgrounding and fattening. For the Southern Chilean fattening production systems, the forage : concentrate ratio was 56 : 44 with ryegrass pasture as the sole forage source. In this case, average DMI was 9·97±0·51 and ADG was 1·1±0·24 kg/day per steer. Two of the grass-based scenarios used the same initial BW information as that used for the Central and Southern Chilean systems, but feedlot diets were replaced by ryegrass pasture. The third grass-based scenario used an initial BW of 390 kg. In all the grass-based scenarios an ADG of 0·90 kg/day, with maximum DMI estimated as a proportion of BW (0·01 of NDF, kg/kg BW), was assumed. The results of the simulation analysis showed that emission factors (Ym; fraction of GEI) ranged from 0·062 to 0·079 of GEI. Smaller values were associated with finishing systems that included a lower proportion of forage in the diet due to higher propionate production, which serves as a sink for hydrogen in the rumen. Cattle finished in feedlot systems had an average of 0·062 of GEI lost as CH4, whereas grass-based cattle had losses of 0·079 of GEI. Enteric CH4 emissions for the systems using grass-based and concentrate diets were 261 and 159 g/kg weight gain, respectively. The Chilean CH4 inventory employs a fixed Ym of 0·060 to estimate enteric fermentation for all cattle. This value is lower than the average Ym obtained in the current simulation analysis (0·071 of GEI), which results in underestimation of enteric CH4 emissions from beef cattle. However, these results need to be checked against field measurements of CH4 emissions. Implementation of mechanistic models in the preparation of national greenhouse gas inventories is feasible if appropriate information is provided, allowing dietary characteristics and regional particularities to be taken into consideration.
In view of environmental concerns with regard to phosphorus (P) pollution and the expected global P scarcity, there is increasing interest in improving P utilization in dairy cattle. In high-producing dairy cows, P requirements for milk production comprise a significant fraction of total dietary P requirements. Although variation in P content of milk can affect the efficiency of P utilization for milk production (i.e. the fraction of ingested P that is incorporated in milk), this variation is poorly understood. It was hypothesized that the P content of milk is related to both milk protein and milk lactose content, but not necessarily to milk fat content. Three existing experiments comprising individual animal data on milk yield and fat, protein, lactose and P content of milk (in total 278 observations from 121 cows) were analysed to evaluate this hypothesis using a mixed model analysis. The models including the effects of both protein and lactose content of milk yielded better prediction of milk P content in terms of root-mean-square prediction error (RMSPE) and concordance correlation coefficient (CCC) statistics than models with only protein included as prediction variable; however, estimates of effect sizes varied between studies. The inclusion of milk fat content in equations already including protein and lactose did not further improve prediction of milk P content. Equations developed to describe the relationship between milk protein and lactose contents (g/kg) and milk P content (g/kg) were: (Expt 1) P in milk=−0·44(±0·179)+0·0253(±0·00300)×milk protein+0·0133(±0·00382)×milk lactose (RMSPE: 5·2%; CCC: 0·71); (Expt 2) P in milk=−0·26 (±0·347)+0·0174(±0·00328)×milk protein+0·0143 (±0·00611)×milk lactose (RMSPE: 6·3%; CCC: 0·40); and (Expt 3) P in milk=−0·36(±0·255)+0·0131(±0·00230)×milk protein+0·0193(±0·00490)×milk lactose (RMSPE: 6·5%; CCC: 0·55). Analysis of the three experiments combined, treating study as a random effect, resulted in the following equation to describe the same relationship as in the individual study equations: P in milk=−0·64(±0·168)+0·0223(±0·00236)×milk protein+0·0191(±0·00316)×milk lactose (RMSPE: 6·2%; CCC: 0·61). Although significant relationships between milk protein, milk lactose and milk P were found, a considerable portion of the observed variation remained unexplained, implying that factors other than milk composition may affect the P content of milk. The equations developed may be used to replace current fixed milk P contents assumed in P requirement systems for cattle.