Field-scale study of rumen function, efficiency and emissions in dairy cows The 1000 cow study. Phil Garnsworthy
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1 Field-scale study of rumen function, efficiency and emissions in dairy cows The 1000 cow study Phil Garnsworthy
2 1000 cow study
3 Animal Phenotypes Feed intake & Diet composition Rumen VFA & NH 3 & Methane Milk yield & composition Digestibility & Nitrogen excretion Blood samples Rumen microbiome Animal genotype
4 Work Package 3 - Phenotypes Aim: to provide phenotypic data and samples of rumen fluid, faeces and blood for 1,000 cows UK (UNOTT) 400 cows Italy (UNICATT) 400 cows Sweden (SLU) 100 cows Finland (MTT/Luke) 100 cows
5 Measurements and samples required Cow data Milk yield, live weight Milk composition Blood samples Methane Rumen samples Feed intake Digestibility During milking/greenfeed Respiration Chambers Rumen sample probe Direct measurement / Alkanes Direct or AIA / indf
6 SOP 9 - Collection of ruminal fluid The instrument: oro-ruminal probe and a suction pump
7 Feed intake - The Alkane Method We cannot measure intake directly on commercial farms Odd-chain alkanes are naturally present in feeds Even-chain alkane fed at fixed or known rate per day Intake estimated from faecal ratios of even to odd chain alkanes
8 Metabolic chambers in Minkiö Dairy Research Barn High pressure blowers Cow inside chamber Sampling pump and analyzers
9 Methane (ppm) Online measurement of methane during milking Cow 441 Means Peak 4203 ppm Interval 57 s Cow 273 Means Peak 1601 ppm Interval 50 s Time (s) & InveN2Ory 2 ResearCH 4 Synthesis
10
11 Variability among cattle in chambers 2x variation in CH 4 at same DMI 2x variation in DMI at same CH 4 Reading University report for DairyCo
12 1000-cow study Results so far UK 407 Italy 410 Holsteins Maize + Grass silage/ hay diets Sweden 100 Finland 100 Red & White Grass silage diets
13 ** Preliminary Data **
14 ** Preliminary Data **
15 ** Preliminary Data **
16 ** Preliminary Data **
17 ** Preliminary Data **
18 Is methane related to intake on farms?
19 Are low methane emitters more efficient?
20 Digestibility, methane and efficiency Methane varies from 2% to 12% of Gross Energy intake (IPCC value 6.5%) Average cow (33 kg milk/d) consumes Gross Energy 370 ; Metabolisable Energy 230 MJ/d 12% CH 4 compared with 2% CH 4 = +23 MJ ME = +4.5 kg milk OR = digestibility = -0.5 kg milk
21 Digestibility and methane
22 Milk N/N intake Nitrogen intake, production and nitrogen use efficiency Milk protein yield N intake Nousiainen et al., 2004
23 Nitrogen efficiency
24 Nitrogen efficiency
25 Is methane related to rumen VFA?
26 Is methane related to rumen microbes?
27 Archaea vary with farm and date
28 First Data Analysis (Emma Gregson) Random Effects: Country Farm Sampling Date Farm/Month
29 Residual Correlations Intake and Milk Methane production was correlated with dry matter intake and energy-corrected milk yield
30 Residual Correlations Milk components Methane production was correlated with live weight and yield of all milk components except urea
31 Residual Correlations - Blood None of the recorded blood parameters are correlated with methane production or Archaea (except haptoglobulin)
32 Residual Correlations Volatile Fatty Acids Methane production was correlated with acetate and butyrate (+) propionate and valerate (-)
33 Residual Correlations Microbes Methane production was correlated with several genera / species
34 Best phenotype model (so far) Response variate: METHANE Fixed model: Constant + Milk_PUFA_Y + DMI + LW + RP + Milk_SFA_Y Random model: FARM + FARM.PERIOD Number of units: 987 (29 units excluded due to zero weights or missing values) % Methane Variation Propionate 7.4 LW 5.1 DMI 6.1 Milk PUFA yield 2.4 Milk SFA yield 10.0
35 Microbe phenotype model Response variate: PROPIONATE Fixed model: Constant + B_Bact + B_Fibr + B_Firm + B_Prot + F_Neoc Random model: FARM + FARM.PERIOD Number of units: 930 (86 units excluded due to zero weights or missing values) % Propionate Variation +/- Fungi, genus Neocallimastix Bacteria, phylum Firmicutes Bacteria, phylum Proteobacteria Bacteria, phylum Fibrobacteres Bacteria, phylum Bacteroidetes
36 Conclusions 1000 cows was a big challenge We have a good range in values for all phenotypes Within countries, and overall, data are normally distributed CH 4 emissions (g/d and g/kg DMI) vary widely between cows CH 4 is not necessarily related to efficiency, so genetic selection for low emitters needs caution Variation could be due to genetics, physiology, behaviour is this reflected in the rumen microbiome or cow genome?
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