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Livestock feed encompasses both human edible and human inedible components. Human edible feed components may become less available for livestock. Especially for proteins, this calls for action. This review focuses on using alternative protein sources in feed and protein efficiency, the expected problems, and how these problems could be solved. Breeding for higher protein efficiency leading to less use of the protein sources may be one strategy. Replacing (part of) the human edible feed components with human inedible components may be another strategy, which could be combined with breeding for livestock that can efficiently digest novel protein feed sources. The potential use of novel protein sources is discussed. We discuss the present knowledge on novel protein sources, including the consequences for animal performance and production costs, and make recommendations for the use and optimization of novel protein sources (1) to improve our knowledge on the inclusion of human inedible protein into the diet of livestock, (2) because cooperation between animal breeders and nutritionists is needed to share knowledge and combine expertise, and (3) to investigate the effect of animal-specific digestibility of protein sources for selective breeding for each protein source and for precision feeding. Nutrigenetics and nutrigenomics will be important tools.
Marinus Te Pas; Teun Veldkamp; Yvette de Haas; André Bannink; Esther Ellen. Adaptation of Livestock to New Diets Using Feed Components without Competition with Human Edible Protein Sources—A Review of the Possibilities and Recommendations. Animals 2021, 11, 2293 .
AMA StyleMarinus Te Pas, Teun Veldkamp, Yvette de Haas, André Bannink, Esther Ellen. Adaptation of Livestock to New Diets Using Feed Components without Competition with Human Edible Protein Sources—A Review of the Possibilities and Recommendations. Animals. 2021; 11 (8):2293.
Chicago/Turabian StyleMarinus Te Pas; Teun Veldkamp; Yvette de Haas; André Bannink; Esther Ellen. 2021. "Adaptation of Livestock to New Diets Using Feed Components without Competition with Human Edible Protein Sources—A Review of the Possibilities and Recommendations." Animals 11, no. 8: 2293.
Feed management decisions are an important element of managing greenhouse gas (GHG) and nitrogen (N) emissions in livestock farming systems. This review aims to a) discuss the impact of feed management practices on emissions in beef and dairy production systems and b) assess different modelling approaches used for quantifying the impact of these abatement measures at different stages of the feed and manure management chain. Statistical and empirical models are well-suited for practical applications when evaluating mitigation strategies, such as GHG calculator tools for farmers and for inventory purposes. Process-based simulation models are more likely to provide insights into the impact of biotic and abiotic drivers on GHG and N emissions. These models are based on equations which mathematically describe processes such as fermentation, aerobic and anaerobic respiration, denitrification, etc. and require a greater number of input parameters. Ultimately, the modelling approach used will be determined by a) the activity input data available, b) the temporal and spatial resolution required and c) the suite of emissions being studied. Simulation models are likely candidates to be able to better explain variation in on-farm GHG and N emissions, and predict with a higher accuracy for a specific mitigation measure under defined farming conditions, due to the fact that they better represent the underlying mechanisms causal for emissions. Integrated farm system models often make use of rather generic values or empirical models to quantify individual emissions sources, whereas combining a whole set of process-based models (or their results) that simulates the variation in GHG and N emissions and the associated whole farm budget has not been used. The latter represents a valuable approach to delineate underlying processes and their drivers within the system and to evaluate the integral effect on GHG emissions with different mitigation options.
Latifa Ouatahar; André Bannink; Gary Lanigan; Barbara Amon. Modelling the effect of feeding management on greenhouse gas and nitrogen emissions in cattle farming systems. Science of The Total Environment 2021, 776, 145932 .
AMA StyleLatifa Ouatahar, André Bannink, Gary Lanigan, Barbara Amon. Modelling the effect of feeding management on greenhouse gas and nitrogen emissions in cattle farming systems. Science of The Total Environment. 2021; 776 ():145932.
Chicago/Turabian StyleLatifa Ouatahar; André Bannink; Gary Lanigan; Barbara Amon. 2021. "Modelling the effect of feeding management on greenhouse gas and nitrogen emissions in cattle farming systems." Science of The Total Environment 776, no. : 145932.
C. van Bruggen; Wageningen Ur Library; A. Bannink; C.M. Groenestein; J.F.M. Huijsmans; L.A. Lagerwerf; H.H. Luesink; M.B.H. Ros; G.L. Velthof; J. Vonk; T. van der Zee; Wias; Wimek. Emissies naar lucht uit de landbouw berekend met NEMA voor 1990-2019. Emissies naar lucht uit de landbouw berekend met NEMA voor 1990-2019 2021, 1 .
AMA StyleC. van Bruggen, Wageningen Ur Library, A. Bannink, C.M. Groenestein, J.F.M. Huijsmans, L.A. Lagerwerf, H.H. Luesink, M.B.H. Ros, G.L. Velthof, J. Vonk, T. van der Zee, Wias, Wimek. Emissies naar lucht uit de landbouw berekend met NEMA voor 1990-2019. Emissies naar lucht uit de landbouw berekend met NEMA voor 1990-2019. 2021; ():1.
Chicago/Turabian StyleC. van Bruggen; Wageningen Ur Library; A. Bannink; C.M. Groenestein; J.F.M. Huijsmans; L.A. Lagerwerf; H.H. Luesink; M.B.H. Ros; G.L. Velthof; J. Vonk; T. van der Zee; Wias; Wimek. 2021. "Emissies naar lucht uit de landbouw berekend met NEMA voor 1990-2019." Emissies naar lucht uit de landbouw berekend met NEMA voor 1990-2019 , no. : 1.
C. van Bruggen; Wias; A. Bannink; C.M. Groenestein; J.F.M. Huijsmans; L.A. Lagerwerf; H.H. Luesink; G.L. Velthof; J. Vonk; Wimek. Emissies naar lucht uit de landbouw,1990-2018 : Berekeningen met het model NEMA. Emissies naar lucht uit de landbouw,1990-2018 : Berekeningen met het model NEMA 2020, 1 .
AMA StyleC. van Bruggen, Wias, A. Bannink, C.M. Groenestein, J.F.M. Huijsmans, L.A. Lagerwerf, H.H. Luesink, G.L. Velthof, J. Vonk, Wimek. Emissies naar lucht uit de landbouw,1990-2018 : Berekeningen met het model NEMA. Emissies naar lucht uit de landbouw,1990-2018 : Berekeningen met het model NEMA. 2020; ():1.
Chicago/Turabian StyleC. van Bruggen; Wias; A. Bannink; C.M. Groenestein; J.F.M. Huijsmans; L.A. Lagerwerf; H.H. Luesink; G.L. Velthof; J. Vonk; Wimek. 2020. "Emissies naar lucht uit de landbouw,1990-2018 : Berekeningen met het model NEMA." Emissies naar lucht uit de landbouw,1990-2018 : Berekeningen met het model NEMA , no. : 1.
J. Vonk; E.J.M.M. Arets; A. Bannink; C. van Bruggen; C.M. Groenestein; J.F.M. Huijsmans; L.A. Lagerwerf; H.H. Luesink; M.B.H. Ros; M.J. Schelhaas; T. van der Zee; G.L. Velthof; Forest And Landscape Ecology Alterra - Vegetation; Wias; Pe&rc; Wimek. Referentieraming van emissies naar de lucht uit landbouw en landgebruik tot 2030, met doorkijk naar 2035 : Achtergronddocument bij de Klimaat- en Energieverkenning 2020. Referentieraming van emissies naar de lucht uit landbouw en landgebruik tot 2030, met doorkijk naar 2035 : Achtergronddocument bij de Klimaat- en Energieverkenning 2020 2020, 1 .
AMA StyleJ. Vonk, E.J.M.M. Arets, A. Bannink, C. van Bruggen, C.M. Groenestein, J.F.M. Huijsmans, L.A. Lagerwerf, H.H. Luesink, M.B.H. Ros, M.J. Schelhaas, T. van der Zee, G.L. Velthof, Forest And Landscape Ecology Alterra - Vegetation, Wias, Pe&rc, Wimek. Referentieraming van emissies naar de lucht uit landbouw en landgebruik tot 2030, met doorkijk naar 2035 : Achtergronddocument bij de Klimaat- en Energieverkenning 2020. Referentieraming van emissies naar de lucht uit landbouw en landgebruik tot 2030, met doorkijk naar 2035 : Achtergronddocument bij de Klimaat- en Energieverkenning 2020. 2020; ():1.
Chicago/Turabian StyleJ. Vonk; E.J.M.M. Arets; A. Bannink; C. van Bruggen; C.M. Groenestein; J.F.M. Huijsmans; L.A. Lagerwerf; H.H. Luesink; M.B.H. Ros; M.J. Schelhaas; T. van der Zee; G.L. Velthof; Forest And Landscape Ecology Alterra - Vegetation; Wias; Pe&rc; Wimek. 2020. "Referentieraming van emissies naar de lucht uit landbouw en landgebruik tot 2030, met doorkijk naar 2035 : Achtergronddocument bij de Klimaat- en Energieverkenning 2020." Referentieraming van emissies naar de lucht uit landbouw en landgebruik tot 2030, met doorkijk naar 2035 : Achtergronddocument bij de Klimaat- en Energieverkenning 2020 , no. : 1.
Rumen sensors provide specific information to help understand rumen functioning in relation to health disorders and to assist in decision-making for farm management. This review focuses on the use of rumen sensors to measure ruminal pH and discusses variation in pH in both time and location, pH-associated disorders and data analysis methods to summarize and interpret rumen pH data. Discussion on the use of rumen sensors to measure redox potential as an indication of the fermentation processes is also included. Acids may accumulate and reduce ruminal pH if acid removal from the rumen and rumen buffering cannot keep pace with their production. The complexity of the factors involved, combined with the interactions between the rumen and the host that ultimately determine ruminal pH, results in large variation among animals in their pH response to dietary or other changes. Although ruminal pH and pH dynamics only partially explain the typical symptoms of acidosis, it remains a main indicator and may assist to optimize rumen function. Rumen pH sensors allow continuous monitoring of pH and of diurnal variation in pH in individual animals. Substantial drift of non-retrievable rumen pH sensors, and the difficulty to calibrate these sensors, limits their application. Significant within-day variation in ruminal pH is frequently observed, and large distinct differences in pH between locations in the rumen occur. The magnitude of pH differences between locations appears to be diet dependent. Universal application of fixed conversion factors to correct for absolute pH differences between locations should be avoided. Rumen sensors provide high-resolution kinetics of pH and a vast amount of data. Commonly reported pH characteristics include mean and minimum pH, but these do not properly reflect severity of pH depression. The area under the pH × time curve integrates both duration and extent of pH depression. The use of this characteristic, as well as summarizing parameters obtained from fitting equations to cumulative pH data, is recommended to identify pH variation in relation to acidosis. Some rumen sensors can also measure the redox potential. This measurement helps to understand rumen functioning, as the redox potential of rumen fluid directly reflects the microbial intracellular redox balance status and impacts fermentative activity of rumen microorganisms. Taken together, proper assessment and interpretation of data generated by rumen sensors requires consideration of their limitations under various conditions.
J. Dijkstra; S. van Gastelen; K. Dieho; K. Nichols; A. Bannink. Review: Rumen sensors: data and interpretation for key rumen metabolic processes. Animal 2020, 14, s176 -s186.
AMA StyleJ. Dijkstra, S. van Gastelen, K. Dieho, K. Nichols, A. Bannink. Review: Rumen sensors: data and interpretation for key rumen metabolic processes. Animal. 2020; 14 (S1):s176-s186.
Chicago/Turabian StyleJ. Dijkstra; S. van Gastelen; K. Dieho; K. Nichols; A. Bannink. 2020. "Review: Rumen sensors: data and interpretation for key rumen metabolic processes." Animal 14, no. S1: s176-s186.
In mitigating greenhouse gas (GHG) emissions and reducing the carbon footprint of dairy milk, the use of generic estimates in inventory and accounting methodology at farm level largely ignores variation of on-farm GHG emissions. The present study aimed to implement results of an extant dynamic, mechanistic Tier 3 model for enteric methane (CH4) (applied in Dutch national GHG inventory) in order to capture variation in enteric CH4 emission, and in faecal N and organic matter (OM) digestibility, ultimately required to predict manure CH4 and ammonia emission. Tier 3 model predictions were translated into calculation rules that could easily be implemented in an annual nutrient cycling assessment tool including GHG emissions, which is currently used by Dutch dairy farmers. Calculations focussed on (1) enteric CH4 emission, (2) apparent faecal OM digestibility and (3) apparent faecal N digestibility. Enteric CH4 was expressed in CH4 yield indicated with the term emission factor (EF; g CH4/kg DM) for individual dietary components and feedstuffs. Factors investigated to cover predicted variation in EF value included the level of feed intake, the type of roughage fed (proportions of grass silage and maize silage) and the quality of roughage fed. A minimum number of three classes of roughage type (i.e. 0. 40% and 80% maize silage in roughage DM) appeared necessary to obtain correspondence between interpolated EF values from EF lists and Tier 3 model predictions. A linear decline in EF value with 1% per kg increase in DM intake is adopted based on model simulations. The quality of roughage was represented by the effect of maturity of harvested grass or of the whole plant maize at cutting, based on a survey of modelling as well as experimental work. Also, predictions were assembled for apparent faecal OM digestibility which could be used in national inventory and in farm accounting. Apparent faecal N digestibility (as a major determinant of predicted urinary N excretion) was predicted, to support current Dutch national ammonia emission inventory and to correct the level of N digestibility in farm accounting. Compared to generic values or values retrieved from the Dutch feeding tables, predicted OM and N digestibility and enteric CH4 are better rooted in physiological principles and better reflect observed variation under experimental conditions. The present results apply for conditions with fairly intensive grassland management in temperate regions.
A. Bannink; R. L. G. Zom; K. C. Groenestein; Jan Dijkstra; L. B. J. Sebek. Applying a mechanistic fermentation and digestion model for dairy cows with emission and nutrient cycling inventory and accounting methodology. Animal 2020, 14, s406 -s416.
AMA StyleA. Bannink, R. L. G. Zom, K. C. Groenestein, Jan Dijkstra, L. B. J. Sebek. Applying a mechanistic fermentation and digestion model for dairy cows with emission and nutrient cycling inventory and accounting methodology. Animal. 2020; 14 ():s406-s416.
Chicago/Turabian StyleA. Bannink; R. L. G. Zom; K. C. Groenestein; Jan Dijkstra; L. B. J. Sebek. 2020. "Applying a mechanistic fermentation and digestion model for dairy cows with emission and nutrient cycling inventory and accounting methodology." Animal 14, no. : s406-s416.
L.B. Šebek; Lr - Animal Nutrition; J.A. De Boer; A. Bannink; Lr - Veehouderij En Omgeving; Wias. De Kringloopwijzer, het voerspoor en methaanemissie op het melkveebedrijf : Prestaties van een reken- en managementinstrument voor sturing van de enterische methaanemissie. De Kringloopwijzer, het voerspoor en methaanemissie op het melkveebedrijf : Prestaties van een reken- en managementinstrument voor sturing van de enterische methaanemissie 2020, 1 .
AMA StyleL.B. Šebek, Lr - Animal Nutrition, J.A. De Boer, A. Bannink, Lr - Veehouderij En Omgeving, Wias. De Kringloopwijzer, het voerspoor en methaanemissie op het melkveebedrijf : Prestaties van een reken- en managementinstrument voor sturing van de enterische methaanemissie. De Kringloopwijzer, het voerspoor en methaanemissie op het melkveebedrijf : Prestaties van een reken- en managementinstrument voor sturing van de enterische methaanemissie. 2020; ():1.
Chicago/Turabian StyleL.B. Šebek; Lr - Animal Nutrition; J.A. De Boer; A. Bannink; Lr - Veehouderij En Omgeving; Wias. 2020. "De Kringloopwijzer, het voerspoor en methaanemissie op het melkveebedrijf : Prestaties van een reken- en managementinstrument voor sturing van de enterische methaanemissie." De Kringloopwijzer, het voerspoor en methaanemissie op het melkveebedrijf : Prestaties van een reken- en managementinstrument voor sturing van de enterische methaanemissie , no. : 1.
Mammary gland utilization of AA and other metabolites in response to supplemental energy from protein (PT) and supplemental energy from fat (FT) was tested in a 2 × 2 factorial arrangement using a randomized complete block design. Fifty-six Holstein-Friesian dairy cows were adapted during a 28-d control period to a basal total mixed ration consisting of 34% grass silage, 33% corn silage, 5% grass hay, and 28% concentrate on a dry matter (DM) basis. Experimental rations were fed for 28 d immediately following the control period and consisted of (1) low protein, low fat (LP/LF), (2) high protein, low fat (HP/LF), (3) low protein, high fat (LP/HF), and (4) high protein, high fat (HP/HF). To obtain the high-protein (HP) and high-fat (HF) diets, intake of the basal ration was restricted and supplemented isoenergetically [net energy (MJ/d) basis] with 2.0 kg/d rumen-protected protein (soybean + rapeseed, 50:50 mixture on a DM basis) and 0.68 kg/d hydrogenated palm fatty acids on a DM basis. Arterial and venous blood samples were collected on d 28 of both periods. Isoenergetic supplements (MJ/d) of protein and fat independently and additively increased milk yield, PT increased protein yield, and FT increased fat yield. A PT × FT interaction affected arterial concentration of all essential AA (EAA) groups, where they increased in response to PT by a greater magnitude at the LF level (on average 35%) compared with the HF level (on average 14%). Mammary gland plasma flow was unaffected by PT or FT. Supplementation with PT tended to decrease mammary clearance of total EAA and decreased group 1 AA clearance by 19%. In response to PT, mammary uptake of total EAA and group 2 AA increased 12 and 14%, respectively, with significantly higher uptake of Arg, Ile, and Leu. Energy from fat had no effect on mammary clearance or uptake of any AA group. The mammary gland uptake:milk protein output ratio was not affected by FT, whereas PT increased this ratio for EAA and group 2 AA. Arterial plasma insulin concentration decreased in response to FT, in particular on the HP/HF diet, as indicated by a PT × FT interaction. Arterial concentrations of nonesterified fatty acids, triacylglycerol, and long-chain fatty acids increased in response to FT, and concentrations of β-hydroxybutyrate and acetate decreased in response to FT only at the HP level. Mammary clearance and uptake of triacylglycerol and long-chain fatty acids increased in response to FT. Energy from PT and FT increased lactose yield despite no change in arterial glucose concentration or mammary glucose uptake. Mammary-sequestered glucose with PT or FT was used in the same amount for lactose synthesis, and a positive net mammary glucose balance was found across all treatments. Results presented here illustrate metabolic flexibility of the mammary gland in its use of aminogenic versus lipogenic substrates for milk synthesis.
K. Nichols; H. Van Laar; A. Bannink; J. Dijkstra. Mammary gland utilization of amino acids and energy metabolites differs when dairy cow rations are isoenergetically supplemented with protein and fat. Journal of Dairy Science 2019, 102, 1160 -1175.
AMA StyleK. Nichols, H. Van Laar, A. Bannink, J. Dijkstra. Mammary gland utilization of amino acids and energy metabolites differs when dairy cow rations are isoenergetically supplemented with protein and fat. Journal of Dairy Science. 2019; 102 (2):1160-1175.
Chicago/Turabian StyleK. Nichols; H. Van Laar; A. Bannink; J. Dijkstra. 2019. "Mammary gland utilization of amino acids and energy metabolites differs when dairy cow rations are isoenergetically supplemented with protein and fat." Journal of Dairy Science 102, no. 2: 1160-1175.
This study tested the effects of energy from glucogenic (glucose; GG) or lipogenic (palm olein; LG) substrates at low (LMP) and high (HMP) metabolizable protein levels on whole-body energy and N partitioning of dairy cattle. Six rumen-fistulated, second-lactation Holstein-Friesian dairy cows (97 ± 13 d in milk) were randomly assigned to a 6 × 6 Latin square design in which each experimental period consisted of 5 d of continuous abomasal infusion followed by 2 d of rest. A total mixed ration consisting of 42% corn silage, 31% grass silage, and 27% concentrate (dry matter basis) was formulated to meet 100 and 83% of net energy and metabolizable protein requirements, respectively, and was fed at 90% of ad libitum intake by individual cow. Abomasal infusion treatments were saline (LMP-C), isoenergetic infusions (digestible energy basis) of 1,319 g/d of glucose (LMP-GG), 676 g/d of palm olein (LMP-LG; major fatty acid constituents are palmitic, oleic, and linoleic acid), or 844 g/d of essential AA (HMP-C), or isoenergetic infusions of 1,319 g/d of glucose + 844 g/d of essential AA (HMP-GG) or 676 g/d of palm olein + 844 g/d of essential AA (HMP-LG). The experiment was conducted in climate respiration chambers to determine energy and N balance in conjunction with milk production and composition, nutrient digestibility, and plasma constituents. Infusion of GG and LG decreased dry matter intake, but total gross energy intake from the diet plus infusions was not affected by GG or LG. Furthermore, GG or LG did not affect total milk, protein, or lactose yields. Infusing GG or LG at the HMP level did not affect milk production differently than at the LMP level. Infusion of GG stimulated energy retention in body tissue, increased plasma glucose and insulin concentrations, decreased lipogenic metabolites in plasma, and decreased milk fat yield and milk energy output. Nitrogen intake decreased and milk N efficiency increased in response to GG, and N retention was not affected. Infusion of LG tended to increase metabolizable energy intake, increased milk fat yield and milk energy output, increased plasma triacylglycerides and long-chain fatty acid concentrations, and had no effect on energy retention. Infusion of LG decreased N intake but did not affect milk N efficiency or N retention. Compared with the LMP level, the HMP level increased dry matter intake, gross and metabolizable energy intake, and total milk, fat, protein, and lactose yields. Milk energy output increased at the HMP level, and protein level did not affect total energy retention. Heat production increased at the HMP level, but only when GG and LG were infused. The HMP level increased N intake, milk N output, and plasma urea concentration, tended to increase N retention, and decreased milk N efficiency. Regardless of protein level, GG promoted energy retention and improved milk N efficiency, but not through increased milk protein yield. Infusion of LG partitioned extra energy intake into milk and had no effect on milk N efficiency.
K. Nichols; J. Dijkstra; H. Van Laar; S. Pacheco; H.J. Van Valenberg; A. Bannink. Energy and nitrogen partitioning in dairy cows at low or high metabolizable protein levels is affected differently by postrumen glucogenic and lipogenic substrates. Journal of Dairy Science 2019, 102, 395 -412.
AMA StyleK. Nichols, J. Dijkstra, H. Van Laar, S. Pacheco, H.J. Van Valenberg, A. Bannink. Energy and nitrogen partitioning in dairy cows at low or high metabolizable protein levels is affected differently by postrumen glucogenic and lipogenic substrates. Journal of Dairy Science. 2019; 102 (1):395-412.
Chicago/Turabian StyleK. Nichols; J. Dijkstra; H. Van Laar; S. Pacheco; H.J. Van Valenberg; A. Bannink. 2019. "Energy and nitrogen partitioning in dairy cows at low or high metabolizable protein levels is affected differently by postrumen glucogenic and lipogenic substrates." Journal of Dairy Science 102, no. 1: 395-412.
The current inventory of N emission from cow excreta relies on fecal N digestibility data in Dutch feeding tables, assuming additivity of dietary ingredients to obtain diet values (CVB model). Alternatively, fecal N digestibility can be estimated by a dynamic, mechanistic model of digestion in the gastrointestinal tract, currently used as Tier 3 for enteric methane prediction in the Netherlands (Tier 3 model). Estimates of in situ rumen degradation characteristics for starch, neutral detergent fiber (NDF) and crude protein used as an input for the Tier 3 model were based on Dutch feeding tables (the protein evaluation system). Both methods were evaluated on independent dataset on fecal N digestibility that was constructed from peer-reviewed papers on N balance data for dairy cows published since 1999 (54 trials, 242 treatment means). Results indicate that observed apparent fecal N digestibility (67.0 ± 6.77%) was systematically over-predicted in particular by the CVB model (73.8 ± 4.35%) compared to the Tier 3 model (69.8 ± 4.52%). For the dataset including only observations from Dutch trials the observed fecal N digestibility (70.4 ± 7.33%) was also systematically over-predicted by the CVB model (76.4 ± 5.27%) but not by the Tier 3 model (69.7 ± 5.81%). Mixed model analysis with study as random factor indicated the slope of the regression between observed and predicted fecal N digestibility to be smaller than 1, in particular for the CVB model (CVB model slope varied between 0.405 and 0.560 and Tier 3 model slope between 0.418 and 0.657). The over-prediction by the CVB model with 6–7%-units of digestibility will lead to an over-predicted ammoniacal N excretion (urinary N) in the ammonia inventory, and biased estimation of N mitigating potential of nutritional measures. The present study demonstrates the benefit of using the Tier 3 model to predict the average level of apparent fecal N digestibility compared to the CVB model. The general estimates of in situ rumen degradation characteristics for starch, NDF and crude protein used as input for the Tier 3 model seemed applicable for the Dutch trials but less so for the non-Dutch trials.
André Bannink; Wouter J. Spek; Jan Dijkstra; Leon B. J. Šebek. A Tier 3 Method for Enteric Methane in Dairy Cows Applied for Fecal N Digestibility in the Ammonia Inventory. Frontiers in Sustainable Food Systems 2018, 2, 1 .
AMA StyleAndré Bannink, Wouter J. Spek, Jan Dijkstra, Leon B. J. Šebek. A Tier 3 Method for Enteric Methane in Dairy Cows Applied for Fecal N Digestibility in the Ammonia Inventory. Frontiers in Sustainable Food Systems. 2018; 2 ():1.
Chicago/Turabian StyleAndré Bannink; Wouter J. Spek; Jan Dijkstra; Leon B. J. Šebek. 2018. "A Tier 3 Method for Enteric Methane in Dairy Cows Applied for Fecal N Digestibility in the Ammonia Inventory." Frontiers in Sustainable Food Systems 2, no. : 1.
3-Nitrooxypropanol (NOP) is a promising methane (CH) inhibitor. Recent studies have shown major reductions in CH emissions from beef and dairy cattle when using NOP but with large variation in response. The objective of this study was to quantitatively evaluate the factors that explain heterogeneity in response to NOP using meta-analytical approaches. Data from 11 experiments and 38 treatment means were used. Factors considered were cattle type (dairy or beef), measurement technique (GreenFeed technique, C-Lock Inc., Rapid City, SD; sulfur hexafluoride tracer technique; and respiration chamber technique), dry matter (DM) intake, body weight, NOP dose, roughage proportion, dietary crude protein content, and dietary neutral detergent fiber (NDF) content. The mean difference (MD) in CH production (g/d) and CH yield (g/kg of DM intake) was calculated by subtracting the mean of CH emission for the control group from that of the NOP-supplemented group. Forest plots of standardized MD indicated variable effect sizes of NOP across studies. Compared with beef cattle, dairy cattle had a much larger feed intake (22.3 ± 4.13 vs. 7.3 ± 0.97 kg of DM/d; mean ± standard deviation) and CH production (351 ± 94.1 vs. 124 ± 44.8 g/d). Therefore, in further analyses across dairy and beef cattle studies, MD was expressed as a proportion (%) of observed control mean. The final mixed-effect model for relative MD in CH production included cattle type, NOP dose, and NDF content. When adjusted for NOP dose and NDF content, the CH-mitigating effect of NOP was less in beef cattle (-22.2 ± 3.33%) than in dairy cattle (-39.0 ± 5.40%). An increase of 10 mg/kg of DM in NOP dose from its mean (123 mg/kg of DM) enhanced the NOP effect on CH production decline by 2.56 ± 0.550%. However, a greater dietary NDF content impaired the NOP effect on CH production by 1.64 ± 0.330% per 10 g/kg DM increase in NDF content from its mean (331 g of NDF/kg of DM). The factors included in the final mixed-effect model for CH yield were -17.1 ± 4.23% (beef cattle) and -38.8 ± 5.49% (dairy cattle), -2.48 ± 0.734% per 10 mg/kg DM increase in NOP dose from its mean, and 1.52 ± 0.406% per 10 g/kg DM increase in NDF content from its mean. In conclusion, the present meta-analysis indicates that a greater NOP dose enhances the NOP effect on CH emission, whereas an increased dietary fiber content decreases its effect. 3-Nitrooxypropanol has stronger antimethanogenic effects in dairy cattle than in beef cattle.
J. Dijkstra; A. Bannink; J. France; E. Kebreab; S. van Gastelen. Short communication: Antimethanogenic effects of 3-nitrooxypropanol depend on supplementation dose, dietary fiber content, and cattle type. Journal of Dairy Science 2018, 101, 9041 -9047.
AMA StyleJ. Dijkstra, A. Bannink, J. France, E. Kebreab, S. van Gastelen. Short communication: Antimethanogenic effects of 3-nitrooxypropanol depend on supplementation dose, dietary fiber content, and cattle type. Journal of Dairy Science. 2018; 101 (10):9041-9047.
Chicago/Turabian StyleJ. Dijkstra; A. Bannink; J. France; E. Kebreab; S. van Gastelen. 2018. "Short communication: Antimethanogenic effects of 3-nitrooxypropanol depend on supplementation dose, dietary fiber content, and cattle type." Journal of Dairy Science 101, no. 10: 9041-9047.
K. Nichols; A. Bannink; S. Pacheco; H.J. Van Valenberg; J. Dijkstra; H. Van Laar. Feed and nitrogen efficiency are affected differently but milk lactose production is stimulated equally when isoenergetic protein and fat is supplemented in lactating dairy cow diets. Journal of Dairy Science 2018, 101, 7857 -7870.
AMA StyleK. Nichols, A. Bannink, S. Pacheco, H.J. Van Valenberg, J. Dijkstra, H. Van Laar. Feed and nitrogen efficiency are affected differently but milk lactose production is stimulated equally when isoenergetic protein and fat is supplemented in lactating dairy cow diets. Journal of Dairy Science. 2018; 101 (9):7857-7870.
Chicago/Turabian StyleK. Nichols; A. Bannink; S. Pacheco; H.J. Van Valenberg; J. Dijkstra; H. Van Laar. 2018. "Feed and nitrogen efficiency are affected differently but milk lactose production is stimulated equally when isoenergetic protein and fat is supplemented in lactating dairy cow diets." Journal of Dairy Science 101, no. 9: 7857-7870.
Ruminant production systems are important contributors to anthropogenic methane (CH4) emissions, but there are large uncertainties in national and global livestock CH4 inventories. Sources of uncertainty in enteric CH4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH4 emission factors. There is also significant uncertainty associated with enteric CH4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF6) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes.
A.N. Hristov; E. Kebreab; M. Niu; J. Oh; A. Bannink; A.R. Bayat; T.M. Boland; A.F. Brito; D.P. Casper; L.A. Crompton; J. Dijkstra; M. Eugène; P.C. Garnsworthy; N. Haque; A.L.F. Hellwing; P. Huhtanen; M. Kreuzer; B. Kuhla; P. Lund; J. Madsen; C. Martin; P.J. Moate; S. Muetzel; C. Muñoz; N. Peiren; J.M. Powell; C.K. Reynolds; A. Schwarm; K.J. Shingfield; T.M. Storlien; M.R. Weisbjerg; D.R. Yáñez-Ruiz; Z. Yu. Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models. Journal of Dairy Science 2018, 101, 6655 -6674.
AMA StyleA.N. Hristov, E. Kebreab, M. Niu, J. Oh, A. Bannink, A.R. Bayat, T.M. Boland, A.F. Brito, D.P. Casper, L.A. Crompton, J. Dijkstra, M. Eugène, P.C. Garnsworthy, N. Haque, A.L.F. Hellwing, P. Huhtanen, M. Kreuzer, B. Kuhla, P. Lund, J. Madsen, C. Martin, P.J. Moate, S. Muetzel, C. Muñoz, N. Peiren, J.M. Powell, C.K. Reynolds, A. Schwarm, K.J. Shingfield, T.M. Storlien, M.R. Weisbjerg, D.R. Yáñez-Ruiz, Z. Yu. Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models. Journal of Dairy Science. 2018; 101 (7):6655-6674.
Chicago/Turabian StyleA.N. Hristov; E. Kebreab; M. Niu; J. Oh; A. Bannink; A.R. Bayat; T.M. Boland; A.F. Brito; D.P. Casper; L.A. Crompton; J. Dijkstra; M. Eugène; P.C. Garnsworthy; N. Haque; A.L.F. Hellwing; P. Huhtanen; M. Kreuzer; B. Kuhla; P. Lund; J. Madsen; C. Martin; P.J. Moate; S. Muetzel; C. Muñoz; N. Peiren; J.M. Powell; C.K. Reynolds; A. Schwarm; K.J. Shingfield; T.M. Storlien; M.R. Weisbjerg; D.R. Yáñez-Ruiz; Z. Yu. 2018. "Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models." Journal of Dairy Science 101, no. 7: 6655-6674.
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.
H. J. van Lingen; J. G. Fadel; A. Bannink; Jan Dijkstra; J. M. Tricarico; David Pacheco; D. P. Casper; E. Kebreab. Multi-criteria evaluation of dairy cattle feed resources and animal characteristics for nutritive and environmental impacts. Animal 2018, 12, s310 -s320.
AMA StyleH. J. van Lingen, J. G. Fadel, A. Bannink, Jan Dijkstra, J. M. Tricarico, David Pacheco, D. P. Casper, E. Kebreab. Multi-criteria evaluation of dairy cattle feed resources and animal characteristics for nutritive and environmental impacts. Animal. 2018; 12 ():s310-s320.
Chicago/Turabian StyleH. J. van Lingen; J. G. Fadel; A. Bannink; Jan Dijkstra; J. M. Tricarico; David Pacheco; D. P. Casper; E. Kebreab. 2018. "Multi-criteria evaluation of dairy cattle feed resources and animal characteristics for nutritive and environmental impacts." Animal 12, no. : s310-s320.
We previously reported 2 experiments with rumen-cannulated Holstein-Friesian dairy cows showing that during the transition period, rumen papillae surface area, and fractional absorption rate of volatile fatty acids (VFA) increase after calving. However, supplemental concentrate during the dry period and rate of increase of concentrate allowance during lactation affected papillae surface area, but not VFA absorption. Here we report the changes in gene and protein expression in rumen papillae related to tissue growth and VFA utilization. The lactation experiment treatment consisted of a rapid [RAP; 1.0 kg of dry matter (DM)/d; n = 6] or gradual (GRAD; 0.25 kg of DM/d; n = 6) increase of concentrate allowance (up to 10.9 kg of DM/d), starting at 4 d postpartum (pp). The dry period experiment treatment consisted of 3.0 kg of DM/d of concentrate (n = 4) or no concentrate (n = 5) during the last 28 d of the dry period. Real-time quantitative PCR analysis of rumen papillae showed that the expression of apoptosis-related genes was neither affected by day nor its interaction with treatment for both experiments. Expression of epithelial transporter genes was not affected by day or treatment in the lactation experiment, except for NBC1. In the dry period experiment, expression of MCT1, NBC1, DRA, NHE2, NHE3, and UT-B generally decreased after calving. A day and treatment interaction was observed for ATP1A1 in the dry period experiment, with greater expression at 18 and 8 d antepartum for concentrate than no concentrate. Generally, expression of VFA metabolism-related genes was not affected by day or its interaction with treatment. In the lactation experiment, immunoblotting of 5 selected genes showed that protein expression of DRA and PCCA was greater at 16 d pp compared with 3 and 44 d pp. Expression of NHE2 was greater, and that of ATP1A1 lower, at 16 and 44 d pp compared with 3 d pp, suggesting alterations in intracellular pH regulation and sodium homeostasis. Both MCT1 and PCCA protein were upregulated by RAP from 3 to 16 d pp, indicating modulations in VFA metabolism. Our data suggests that VFA absorption and metabolic capacity changed little per unit of surface area during the transition period, and suggests that a change in mitosis rate rather than apoptosis rate is associated with the increased ruminal VFA production, resulting in tissue growth. A significant but weak correlation between the examined gene and protein expression levels was observed only for PCCA, indicating that care must be taken when interpreting results obtained at either level.
K. Dieho; J. Van Baal; L. Kruijt; A. Bannink; J. T. Schonewille; David Carreño; W.H. Hendriks; J. Dijkstra. Effect of supplemental concentrate during the dry period or early lactation on rumen epithelium gene and protein expression in dairy cattle during the transition period. Journal of Dairy Science 2017, 100, 7227 -7245.
AMA StyleK. Dieho, J. Van Baal, L. Kruijt, A. Bannink, J. T. Schonewille, David Carreño, W.H. Hendriks, J. Dijkstra. Effect of supplemental concentrate during the dry period or early lactation on rumen epithelium gene and protein expression in dairy cattle during the transition period. Journal of Dairy Science. 2017; 100 (9):7227-7245.
Chicago/Turabian StyleK. Dieho; J. Van Baal; L. Kruijt; A. Bannink; J. T. Schonewille; David Carreño; W.H. Hendriks; J. Dijkstra. 2017. "Effect of supplemental concentrate during the dry period or early lactation on rumen epithelium gene and protein expression in dairy cattle during the transition period." Journal of Dairy Science 100, no. 9: 7227-7245.
The high contribution of postruminal starch digestion (up to 50%) to total-tract starch digestion on energy-dense, starch-rich diets demands that limitations to small intestinal starch digestion be identified. A mechanistic model of the small intestine was described and evaluated with regard to its ability to simulate observations from abomasal carbohydrate infusions in the dairy cow. The 7 state variables represent starch, oligosaccharide, glucose, and pancreatic amylase in the intestinal lumen, oligosaccharide and glucose in the unstirred water layer at the intestinal wall, and intracellular glucose of the enterocyte. Enzymatic hydrolysis of starch was modeled as a 2-stage process involving the activity of pancreatic amylase in the lumen and of oligosaccharidase at the brush border of the enterocyte confined within the unstirred water layer. The Na-dependent glucose transport into the enterocyte was represented along with a facilitative glucose transporter 2 transport system on the basolateral membrane. The small intestine is subdivided into 3 main sections, representing the duodenum, jejunum, and ileum for parameterization. Further subsections are defined between which continual digesta flow is represented. The model predicted nonstructural carbohydrate disappearance in the small intestine for cattle unadapted to duodenal infusion with a coefficient of determination of 0.92 and a root mean square prediction error of 25.4%. Simulation of glucose disappearance for mature Holstein heifers adapted to various levels of duodenal glucose infusion yielded a coefficient of determination of 0.81 and a root mean square prediction error of 38.6%. Analysis of model behavior identified limitations to the efficiency of small intestinal starch digestion with high levels of duodenal starch flow. Limitations to individual processes, particularly starch digestion in the proximal section of the intestine, can create asynchrony between starch hydrolysis and glucose uptake capacity.
J.A.N. Mills; J. France; J.L. Ellis; L.A. Crompton; A. Bannink; M.D. Hanigan; Jan Dijkstra. A mechanistic model of small intestinal starch digestion and glucose uptake in the cow. Journal of Dairy Science 2017, 100, 4650 -4670.
AMA StyleJ.A.N. Mills, J. France, J.L. Ellis, L.A. Crompton, A. Bannink, M.D. Hanigan, Jan Dijkstra. A mechanistic model of small intestinal starch digestion and glucose uptake in the cow. Journal of Dairy Science. 2017; 100 (6):4650-4670.
Chicago/Turabian StyleJ.A.N. Mills; J. France; J.L. Ellis; L.A. Crompton; A. Bannink; M.D. Hanigan; Jan Dijkstra. 2017. "A mechanistic model of small intestinal starch digestion and glucose uptake in the cow." Journal of Dairy Science 100, no. 6: 4650-4670.
The rumen microbes can adapt to feed additives, which may make the decrease in enteric CH4 production upon feeding an additive a transient response only. This study investigated alternate feeding of 2 CH4 mitigating feed additives with a different mode of action on persistency of lowering CH4 production compared with feeding a single additive over a period of 10 wk. Four pairs of cows were selected, and within pairs, cows were randomly assigned to either the control (AR-AR) or the alternating (AR-LA) concentrate treatment. The AR concentrate contained a blend of essential oils (Agolin Ruminant, AGOLIN SA, Bière, Switzerland; 0.17 g/kg of dry matter) and the LA concentrate contained lauric acid (C12:0; 65 g/kg of dry matter). A basal concentrate without Agolin Ruminant and lauric acid was fed during the pretreatment period (2 wk). Thereafter, the cows assigned to the AR-AR treatment received the AR concentrate during all 10 treatment weeks (5 periods of 2 wk each), whereas cows assigned to the AR-LA treatment received AR and LA concentrates rotated on a weekly basis. Methane emission was measured in climate respiration chambers during periods 1, 3, and 5. From period 3 onward, dry matter intake and milk protein concentration were reduced with the AR-LA treatment. Milk fat concentration was not affected, but the proportion of C12:0 in milk fat increased upon feeding C12:0. Molar proportions of acetate and propionate in rumen fluid were lower and higher, respectively, with the AR-LA than with the AR-AR treatment. Methane yield (g/kg of dry matter intake) and intensity (g/kg of fat- and protein-corrected milk yield) were not affected by treatment. Methane yield and intensity were significantly lower (12 and 11%, respectively) in period 1 compared with the pretreatment period, but no significant difference relative to pretreatment period was observed in period 3 (numerically 9 and 7% lower, respectively) and in period 5 (numerically 8 and 4% lower, respectively). Results indicate a transient decrease in CH4 yield and intensity in time, but no improvement in extent or persistency of the decline in CH4 due to rotational feeding of essential oils and C12:0 in lactating dairy cows.
G. Klop; Jan Dijkstra; K. Dieho; W.H. Hendriks; A. Bannink. Enteric methane production in lactating dairy cows with continuous feeding of essential oils or rotational feeding of essential oils and lauric acid. Journal of Dairy Science 2017, 100, 3563 -3575.
AMA StyleG. Klop, Jan Dijkstra, K. Dieho, W.H. Hendriks, A. Bannink. Enteric methane production in lactating dairy cows with continuous feeding of essential oils or rotational feeding of essential oils and lauric acid. Journal of Dairy Science. 2017; 100 (5):3563-3575.
Chicago/Turabian StyleG. Klop; Jan Dijkstra; K. Dieho; W.H. Hendriks; A. Bannink. 2017. "Enteric methane production in lactating dairy cows with continuous feeding of essential oils or rotational feeding of essential oils and lauric acid." Journal of Dairy Science 100, no. 5: 3563-3575.
Changes in rumen microbiota and in situ degradation kinetics were studied in 12 rumen-cannulated Holstein Friesian dairy cows during the dry period and early lactation. The effect of a rapid (RAP) or gradual (GRAD) postpartum (pp) rate of increase of concentrate allowance was also investigated. Cows were fed for ad libitum intake and had free access to a mixed ration consisting of chopped wheat straw (dry period only), grass silage, corn silage, and soybean meal. Treatment consisted of either a rapid (1.0 kg of dry matter/d; n = 6) or gradual (0.25 kg of dry matter/d; n = 6) increase of concentrate allowance (up to 10.9 kg of dry matter/d), starting at 4 d pp. In whole rumen contents, bacterial community composition was assessed using samples from 50, 30, and 10 d antepartum (ap), and 3, 9, 16, 30, 44, 60, and 80 d pp, and protozoal and archaeal community composition using samples from 10 d ap, and 16 and 44 d pp. Intake of fermentable organic matter, starch, and sugar was temporarily greater in RAP than GRAD at 16 d pp. Bacterial community richness was higher during the dry period than during the lactation. A rapid increase in concentrate allowance decreased bacterial community richness at 9 and 16 d pp compared with a gradual increase in concentrate allowance, whereas from 30 d pp onward richness of RAP and GRAD was similar. In general, the relative abundances of Bacteroidales and Aeromonadales were greater, and those of Clostridiales, Fibrobacterales, and Spirochaetales were smaller, during the lactation compared with the dry period. An interaction between treatment and sampling day was observed for some bacterial community members, and most of the protozoal and archaeal community members. Transition to lactation increased the relative abundance of Epidinium and Entodinium, but reduced the relative abundance of Ostracodinium. Archaea from genus Methanobrevibacter dominated during both the dry period and lactation. However, during lactation the abundance of the methylotrophic Methanomassiliicoccaceae and Methanosphaera increased. The in situ degradation of organic matter, neutral detergent fiber, starch, and crude protein was neither affected by treatment nor by transition from the dry period to lactation. Results show that the composition of the rumen microbiota can change quickly from the dry period to the lactation period, in particular with a rapid increase in fermentable substrate supply postpartum, but this was not associated with changes in rumen degradation kinetics.
K. Dieho; B. Van Den Bogert; G. Henderson; A. Bannink; Javier Ramiro-Garcia; Hauke Smidt; Jan Dijkstra. Changes in rumen microbiota composition and in situ degradation kinetics during the dry period and early lactation as affected by rate of increase of concentrate allowance. Journal of Dairy Science 2017, 100, 2695 -2710.
AMA StyleK. Dieho, B. Van Den Bogert, G. Henderson, A. Bannink, Javier Ramiro-Garcia, Hauke Smidt, Jan Dijkstra. Changes in rumen microbiota composition and in situ degradation kinetics during the dry period and early lactation as affected by rate of increase of concentrate allowance. Journal of Dairy Science. 2017; 100 (4):2695-2710.
Chicago/Turabian StyleK. Dieho; B. Van Den Bogert; G. Henderson; A. Bannink; Javier Ramiro-Garcia; Hauke Smidt; Jan Dijkstra. 2017. "Changes in rumen microbiota composition and in situ degradation kinetics during the dry period and early lactation as affected by rate of increase of concentrate allowance." Journal of Dairy Science 100, no. 4: 2695-2710.
D. Warner; A. Bannink; B. Hatew; H. Van Laar; J. Dijkstra. Effects of grass silage quality and level of feed intake on enteric methane production in lactating dairy cows. Journal of Animal Science 2017, 95, 3687 .
AMA StyleD. Warner, A. Bannink, B. Hatew, H. Van Laar, J. Dijkstra. Effects of grass silage quality and level of feed intake on enteric methane production in lactating dairy cows. Journal of Animal Science. 2017; 95 (8):3687.
Chicago/Turabian StyleD. Warner; A. Bannink; B. Hatew; H. Van Laar; J. Dijkstra. 2017. "Effects of grass silage quality and level of feed intake on enteric methane production in lactating dairy cows." Journal of Animal Science 95, no. 8: 3687.