Winning solutions for climate-smart dairy animal nutrition in India
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Presented by Jimmy Smith, With contributions from: Habibar Rahman, KSV Prasad, Ravi Devulapalli, Chris Jones, Padmakumar V. at the NDDB Animal Nutrition Research Advisory Committee meeting, May 2021
Winning solutions for climate-smart dairy animal nutrition in India
Better lives through livestock
Winning solutions for climate-smart dairy animal
nutrition in India
Jimmy Smith, Director General
With contributions from: Habibar Rahman, KSV Prasad, Ravi Devulapalli, Chris Jones, Padmakumar V.
International Livestock Research Institute (ILRI)
NDDB Animal Nutrition Research Advisory Committee meeting
May 2021
Acknowledgement: Much of the work of ILRI and partners in India on crop residues as
livestock feed included in this presentation was led and pioneered by the late Dr Michael
Blümmel.
2
Overview
Context: dairy demand, production and feed sources
Challenges
Opportunities: More and better feed solutions
Environmental implications
5
Dairy demand in India
0
50000
100000
150000
200000
250000
2010 2030 2050
000
M
tonnes
Source: Impact model predictions under moderate climate change in 2050 with assumption of
moderate economic and population growth, with thanks to Dolapo Enahoro (ILRI)
8
Dairy cattle feed rations, regional averages
0
10
20
30
40
50
60
70
80
90
100
NA RUSS WE EE NENA ESEA OC SA LAC SSA
%
total
dry
matter
feed
intake
Region
Fresh grass Hay Legumes and silage Crop residues Sugarcane tops Leaves
Bran Oilseed meals Wet distilleries grain Grains Molasses Pulp
Regions: NA (North America), RUSS (Russian Federation), WE (Western Europe), EE (Eastern Europe), NENA (Near East and North Africa), ESEA
(East and Southeast Asia), OC (Oceania), SA (South Asia), LAC (Latin America and the Caribbean) and SSA (Sub-Saharan Africa)
9
Challenges
Meet increasing future demand for dairy: produce more
Without increasing emissions/environmental impacts
Coping with climate change and climate variability
Starting from today’s situation:
Many small / medium farms
Local feed resources
Main feed: low quality crop residues
11
Opportunity: more and better feed options from crop residues
• Small changes in crop residue quality have a significant impact on milk
production
‘..a 1% increase in digestibility of sorghum stover fed to dairy cows leads to a 6-8
% increase in milk production…’
• Improve feed quality: Inclusion of feed quality parameters in crop
breeding required:
• Demonstration that quality variations were present
• That these did not jeopardize grain yields
• Easy ways of assessment allow for inclusion in crop breeding and selection
programs
• Improve feed utilization through processing
12
Stover fodder trait analysis in new sorghum cultivar release
testing in India 2002 to 2008
(Blümmel et al. 2010)
Yes! Stover quality varies significantly and does not affect
grain yield
34 37 40 43 46 49 52 55 58 61 64
0
3000
6000
9000
12000
15000
18000
21000
24000
27000
30000
Kharif: y = -5466 + 373x; P < 0.0001; r=0.39
Rabi: y = -2775 + 165x; P < 0.0001; r=0.28
Stover in vitro organic digestibility (%)
Stover
yield
(kg/ha)
Sorghum
13
Non-evasive
c. 200 samples/d
>30 traits
Physico-chemical
c. 60 000 US $
Calibration
Validation
NIRS equations sharable across
compatible instruments
Measurement and development of equations using NIRS: easy, quick
assessment of feed quality parameters without feeding trials
Qualitative feed trait
prediction in plant
breeding based on
Near Infrared
Spectroscopy (NIRS)
15
Block Premium Block Low
CP 17.2 % 17.1%
ME (MJ/kg) 8.46 MJ/kg 7.37 MJ/kg
DMI 19.7 kg/d 18.0 kg/d
DMI per kg LW 3.8 % 3.6 %
Milk Potential* 15.5 kg/d 9.9 kg/d
Modified from Anandan et al. (2009a)
* 21 and 14 kg/d in crossbred cattle
Comparisons of feed blocks based on lower (47%) and higher (52%)
digestible sorghum stover and tested with commercial dairy buffalo
farmers in India
16
Steam
explosion
treatment
2-chemical
combination
treatment
0 1 2 3 4 5 6 7 8 9 1 0
1 8
2 0
2 2
2 4
2 6
2 8
3 0
3 2
3 4
3 6
3 8
4 0
4 2
4 4
4 6
W e e k s o f e x p e rim e n ta tio n
O
M
I
(g
/k
g
L
W
)
T M R w ith 2 C C tre a te d rice s tra w
T M R w ith ste a m tre a te d rice s tra w
T M R w ith u n tre a te d rice stra w l
x = 3 4 .1
x = 3 9 .9
x = 28.3
+ 3 .9 2 k g L W G
+ 6 .1 2 k g L W G
+ 1 .6 6 k g L W G
R e s p o n s e o f s h e e p fe d to ta l m ix e d ra tio n s c o n ta in in g 7 0 % o f u n tre a te d , 2 C C T
tre a te d a n d s te a m tre a te d ric e s tra w
( Unpublished ILRI-IICT data)
Improve feed utilization through processing:
Leveraging spin-off technologies from 2nd generation for deconstructing
ligno-cellulosic biomass
2-CCT = 2-Chemical Combination Treatment; developed by ILRI with
the Council of Scientific and Industrial Research-Indian Institute of Chemical Technology
17
Environmental implications
The win-win opportunity:
- Improved nutrition from better feed quality
(together with health and appropriate genetics
interventions)
- Less animals to meet demand
- Less enteric emissions
- Economic benefits for farmers – more
nutrients go to growth not emissions
A particular case in India: rice straw
Emission factors and IPCC
18
Regional variation in cattle milk production and GHG
emissions
Gerber, P.J., Steinfeld, H., Henderson,
B., Mottet, A., Opio, C., Dijkman, J.,
Falcucci, A. & Tempio, G.
2013. Tackling climate change through
livestock – A global assessment of
emissions and mitigation
opportunities. Food and Agriculture
Organization of the United Nations
(FAO), Rome.
20
The win-win opportunity
Emission intensity and milk yield
FAO and GDP. 2018. Climate change
and the global dairy cattle sector – The
role of the dairy sector in a low-carbon
future. Rome. 36 pp. Licence: CC BY-NC-
SA- 3.0 IGO
Doubling milk
yield through
better feeding,
could reduce
India’s total
methane
emissions by
25%
21
Would rice straw with a digestibility of more than 60% still
be burnt?
Possible with 2-CC
treatment?
22
Mean in vitro digestibility in rice straw traded in Kolkata relative
to available variation in digestibility
32.5 35.0 37.5 40.0 42.5 45.0 47.5 50.0 52.5
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
AROMATICS
HYBRIDS
INDICA
NPT
Released
varieties
Mean digestibility (range 34.5 to 41.5%)
in rice straw traded in Kolkatta
In vitro organic matter digestibility (%)
Grain
yield
(kg/ha)
22
Rice
23
Measuring and mitigating emissions
It’s all mostly about the feed:
• Intake and digestibility
o70-80% of variability in enteric GHGEs
oVery difficult to measure intake in
smallholder situations
oKey assumptions about estimating intake violated
(esp. ad lib intake)
• Enteric methane and manure emissions
• Focus on reducing intensities (amount per kg
product)
24
Enteric and manure emissions: multiple approaches
Enteric methane
Manure
Emission factor calculations: take account of local
situation and diet variations
‘gold standard’ chambers for emission
measurement: eg measure impacts of sub-
maintenance diets
Breed and diet impact on N2O emissions from
manure
Updated IPCC guidelines (2019) based on
assessments of N2O emission factors and CH4
emissions (much lower) for manure on pastures
25
Climate Change Impacts on Livestock
• Heat stress has direct impacts on livestock yields
• Many forage yields will also be affected as temperatures increase
• As climate variability and extremes increase
• Pasture yields will change
• Disease vectors will change
• Production systems will change
26
https://bovidiva.com/
India’s dairy sector?
Commit to net zero
dairy?
Or carbon neutral
dairy?
Make a commitment
Speak up
http://www.livestockdialogue.org/eve
nts/events/webinars/net-zero-
pathways-to-low-carbon-dairy/en/
https://www.dairyglobal.net/Market-trends/Articles/2021/2/Indias-dairy-sector-remains-strong-and-steady-709298E/ : Production 180 million tonnes by 2022 (NDDB)
Livestock: On our plates or eating at our table? A new analysis of the feed/food debate
Anne Mottet, Cees de Haan, Alessandra Falcucci, Giuseppe Tempio, Carolyn Opio, Pierre Gerber http://dx.doi.org/10.1016/j.gfs.2017.01.001
Kristjanson P.M. and Zerbini E. 1999. Genetic Enhancement of Sorghum and Millet Residues Fed to Ruminants. An ex ante assessment of returns to research. ILRI Impact Assessment Series 2. ILRI (International Livestock Research Institute), Nairobi, Kenya. 52pp.
What would these different milk potential mean for livestock water productivity? To estimate this….