Presented by Blümmel, M.1, Garg, M.R.,2 Jones, C.1, Baltenweck, I.1 and Staal, S. at the Indian Animal Nutrition Association XI Biennial Conference, Patna, India, 19-21 November 2018

1. Animal nutrition approaches for profitable livestock
operations and sustainable rural livelihoods
Blümmel, M.1, Garg, M.R.,2 Jones, C.1, Baltenweck, I.1 and Staal, S.1
International Livestock Research Institute
National Dairy Development Board-2, India
Indian Animal Nutrition Association XI Biennial Conference, Patna, India, 19-21 November 2018

2. Structure of Presentation
• Feed costs as challenge to livestock producers and
therefore animal nutritionist
• Improving economics of feeding through animal nutrition
approaches
• Feed resourcing and feeding at the interface where
positive and negative effects from livestock are
negotiated
• Feed interventions and wider livelihood implication

3. Share of feed costs in total costs of dairy
production
(Hemme et al. 2013)

4. Global and Indian Feed Price Development
(IFCN, 2018)

5. Feed Price and Milk Farm Gate Price
Developments in India
(GAIN Report IN7123, 2018)

6. Feed Costs as Challenge
• Feed costs already the major input cost into livestock
production
• Global and India feed prices diverge to the detriment of
the latter
• Feed prices in India rise faster than farm gate prices of
produce, producing a scissor effect

7. Improving economics of feeding through
animal nutrition approaches
• Importance of feed quality –price relations, develop a
culture to combine both information
• Improve feed biomass quality: support plant breeding,
upgrading ligno-cellulosic biomass
• Improving on-farm feeding, matching and balancing
nutrients and animal performance

8. Feed quality –price relations
Variations in prices in 65 compound and concentrate feeds
collected in Bihar in 2015 accounted for by CP, NDF,
ADF, ADL, IVOMD,ME and Fat using
stepwise multiple regression
(Singh et al. 2016)
Feed quality traits Partial R2 Total R2 P < F
Metabolizable Energy 0.155 0.155 0.001
Crude Protein 0.076 0.231 0.02
Feed dependent estimates to produce on additional kg of milk
ranged from 10.3 to 24.5 IRs

9. Forages and (in)attention to their quality:
a study of Co FS 29
Trait Mean Range
Forage fresh yield (kg/ha/cut) 34 126 15 157 - 61 282
Forage dry yield (kg/ha/cut) 5 951 2 242 - 9 500
Forage N (%) 2.00 1.55 - 2.22
Forage IVOMD (%) 49.1 42.3 - 53.4
Highly successful for example in
Mulkanoor Woman Dairy Co-operative!
But do we need to settle for a mean
IVOMD of below 50% in a green forage ?
Ramachandra et al, unpublished

10. Variations in forage quality in 84 forage gene
bank accessions of Napier from a single cut
Trait Mean Range
Leaf Stem
Crude protein (%) 16.5 5.9 to 23.6 6.4 to 20. 9
IVOMD (%) 62.1 53.7 to 68.0 54.1 to 73.0
ME (MJ/kg DM) 8.6 7.8 to 9.7 7.8 to 10.4
(Jones et al., 2018)

11. Breeding advance in dual purpose maize stover fodder quality
relative to different sorghum stover traded in rainfed India
4 5 .0 4 7 .5 5 0 .0 5 2 .5 5 5 .0 5 7 .5 6 0 .0
2 .8
3 .0
3 .2
3 .4
3 .6
3 .8
4 .0
4 .2
S to v e r in v itro digestibility (% )
Stoverprice(IR/kgDM)
L o w q u a lity
s o rg h u m sto ve r
H ig h q u a lity
s o rg h u m sto ve r
M e a n IV O M D (ra n g e 5 5 .2 to 5 7 .9 % )
o f 1 1 a d v a n c e d d u a l p u rp o s e m a ize
b re e d in g lin e s g e n e ra te d
d u rin g th e p ro je c ts
M e a n IV O M D (ra n g e 5 3 .6 to 5 6 .0 % )
o f 1 1 e xp e rim e n ta l h e a t to le ra n t d u a l
p u rp o s e m a iz e h y b rid s g e n e ra te d
d u rin g th e p ro je c ts
B lü m m e l e t a l. (2 0 1 4 a )

12. Leveraging spin-off technologies from 2nd generation
for deconstructing ligno-cellulosic biomass
• 10 – 50 Billion tons biomass annually
and about 4 Billion tons are from
crop residues
• Billions of $ investment to leverage
for different steps along the value
chain starting from collection of high
bulk low density feed stocks to bio-
manufacturing and de novo synthesis
of enzymes
• Dissolve boundaries between food-
feed-fodder, livestock species and
even animal and human nutrition
• Potential game changer technologies

13.  Efficient harvest and collection of high volume-low density
biomass
 Balance central versus decentralized approach
 Optimize physical form-transport-susceptibility to pre- treatment-
voluntary feed intake
 Swell and disrupt hemicellulose-cellulose-lignin matrix
 Partially hydrolyze xylan structure
 Increase surface and porocity of fiber structure
 Unclear benefit for ruminant nutrition, more research with new
enzymes/enzyme cocktails needed
 Demand/potential for monogastric nutrition
 “One pot” complete enzymatic conversions
Biomass: Straws and Stovers
Ethanol Fermentation
Distillation
Pre-treatment
Pre- treated Biomass
Pentoses
Rumen microbial
digestion
External Enzymes
GLUCOSE
LivestockNutrition
Sucrose Juice or
Molasses
Yeast
Ethanol
Stillage
Ruminants
Monogastrics
EthanolPathway
Figure 1: Process steps in second generation bio-fuel technology of interest to livestock nutrition(Blümmel et al.,2014)

14. Leveraging 2nd generation biofuel
technologies
Steam Explosion Treatment
[Nagarjuna Fertilizer]
Ammonia Fiber Expansion (AFEX)
[Michigan Biotechnology Institute]
2-Chemical Combination Treatment
[Indian Institute for Chemical Technology,
joint patent application with ILRI under
consideration]

15. Spin-off technology n In vitro GP after 48 h
(ml/200 mg)
True IVOMD after 48 h
(%)
U T U T
Steam Treatment 4 48.6 53.6 62.9 71.8
AFEX Treatment 10 42.9 51.5 65.1 84.4
2CC Treatment 11 39.7 66.7 55.9 94.1
Summary of effects of steam, ammonia fiber expansion and 2CC treatment on in
vitro gas production (GP) and true in vitro digestibility-1 (IVOMD) after 48 h of
incubation. U = untreated; T = Treated
-1The average difference between true and apparent IVOMD is about 12.9 percentage units (van Soest, 94).
Increments in digestibility were similar independent of expression as apparent or true digestibility.
Blümmel et al. (2018)

16. Intake and weight gain in sheep fed complete diets consisting of
70% untreated and steam and 2CCT treated rice straw
-
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
OMI(g/kgLW)
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)

17. Would rice straw with a digestibility of more than 80% still
burn?

18. Improve feed biomass quality: support plant
breeding, upgrading ligno-cellulosic biomass
Improving economics of feeding through
animal nutrition approaches• Co-operation of animal nutrition and plant improvement
can contribute significantly to more feed biomass with
higher fodder quality
• Potential game changer technologies to be harvested
from 2nd generation biofuel - animal nutritionists
need to be the driver!

19. Improving on-farm feeding, matching and
balancing nutrients and animal performance
performance
nimal nutrition approaches
Ration Balancing: a comprehensive approach of NDDB to apply
animal nutrition principles to improve on-farm feeding:
• Increase in production
• Increase in economics of dairy and its components
• Positive associated effects

20. Summary of key dairy productivity variables
after implementing ration balancing (RB)
feeding, matching and balancing nutrients
and animal performance
nimal nutrition approaches
Impact on Cows (n=1.74 million) Buffalo (n=1.05 million)
Mean Range Mean Range
Milk production before RB kg/d) 9.1 7.9 to 15.6 7.8 5.6 to 11.4
Milk production after RB (kg/d) + 0.85 0.40-3.10 + 0.42 0.15-2.20
Milk fat (% units) + 0.3 0.1-1.5 + 0.3 0.1-1.8
Feed costs (IRs / kg Milk) - 1.8 0.5-3.5 - 1.1 0.4-3.2
Milk efficiency (kg FCM/kg DMI) + 0.2 0.58 to 0.78 + 0.13 0.53 to 0.66
Reduction in CH4 (% / kg Milk) -18 11-24 -16 10-20
Daily benefit per animal* (IRs /d) + 25 15-40 + 25 10-35
* In animals yielding about 8 to 10 kg/d

21. Improving on-farm feeding, matching and
balancing nutrients and animal
performance
nimal nutrition approaches
• Ration Balancing applied to millions of dairy animals had significant positive
effect on key dairy productivity variables
• The comprehensive approach of NDDB to apply animal nutrition principles to
improve on-farm feeding has general appeal to LMC countries –
South to South collaborative opportunities
• A serious study is warranted (and facilitated) to understand if current findings
describe ceiling values for what is achievable through on-farm
targeted feed interventions

22. Feed resourcing and feeding and
environmental foot prints
Structure of Presentation
• Feed production and water requirements for feed
production
• Feed characteristics and greenhouse gas emissions
• Intensification and reduction of feed requirements and
environmental foot prints

23. Life cycle analysis of irrigation water use in dairy
production in Gujarat in India
S. Gujarat W. Gujarat N. Gujarat
B CB B CB LC B CB LC
Milk kg/d 1.87 2.90 4.72 6.39 4.08 3.82 5.14 4.0
Liter H2O drinking water 39 32 41 34 28 52 49 38
Liter H2O feed 5970 5510 7730 8790 6680 11760 11630 7060
Liter H2O per kg of milk 3226 1887 2041 1724 1667 4546 2941 2941
Data adapted from Singh et al., 2004
B = Buffalo; CB = cross breed; LC = Local cow
H2O requirement for production of 1 kg of Milk
Gujarat: 3 400 l Global: 1 000 l

24. Climatic and water
data
•Min and Max-
Temperature ( oC)
•Humidity (%)
•Rain fall
•Wind speed ( km day-1)
•Sunshine (hrs day-1)
•Radiation (Mj m-2 day-1)
•Volume of water per
irrigation and number of
irrigation
Crops and soil parameters
•Soil type and structure
•Crop types and
management practices (
food and fodder crops)
•Length of growing period
for different stages of
development
•Soil types
Examples of tools
and procedures
•Budget (Raes et al.,
2006)
•CropWat (FAO 1998;
Allen et al., 1998)
Total evapotranspired
water by feed sources
type (m3 ha-1)
Conversion factors,
HI, feed use factor (as
structured in Table 4)
Feed Dry Matter (kg m-
3)
Land use
land cover
(ha) as
structured in
Table 4
Feed resources by
types (Kg ha-1)
A simplified framework to combine feed resources data
base and water input requirement estimates
NIANP FeedBase ConceptNIANP FEEDBASE
(Blummel et al, 2014b)

25. 100 150 200 250 300 350 400
17.5
22.5
27.5
32.5
37.5
42.5
47.5
52.5
57.5
62.5
67.5
high propionate
high acetate
Microbial biomass produced per kg feed digested (g/kg)
CH4(l)producedperkgfeeddigested
Methane production from 1 kg of feed truly digested in the
rumen in dependence of SCFA proportion and Efficiency of
Microbial Production
(modified from Blümmel and Krishna 2003)

26. Feed requirement in dependency of per dairy
animal productivity: c. 70 M dairy, 82 Mt milk
3.6
6.0
9.0
12.0
15.0
0
2 5
5 0
7 5
1 0 0
A ve ra g e d a ily m ilk y ie ld (kg )
Relativefeedrequirement(MJME)withincreasing
productivityandcorrespondingreductionin
numbersofdairyanimals:2005equals100
R e la tiv e fe e d re q u ire m e n ts (M E M J)
P ro p o rtio n o f fe e d (M E M J ) u s e d fo r m a in te n a n c e
(Blummel et al, 2013 calculated from data of Anandan et al. 2009)

27. Effect of producing the same amount of milk with
fewer dairy animals on methane production
0 .0 2 .5 5 .0 7 .5 1 0 .0 1 2 .5 1 5 .0 1 7 .5
0
1
2
3
4
5
6
D a ily m ilk p ro d u c tio n p e r a n im a l (k g )
Methaneannuallyproduced(Tg)
(Blummel et al., 2013 calculated from data of Anandan et al. 2009)

28. Feed resourcing and feeding and
environmental foot prints
Structure of Presentation
• Feed sourcing is the driving factor for livestock water
productivity
• With awareness, animal nutritionist can estimate water
requirement and design water use efficient rations
• Ration choice and design effect SCFA proportion and EMP
and both effect enteric CH4 production
• Intensification has potentially an overriding effect on
feed requirement and total and proportional
CH4 production

29. Feed interventions and wider livelihood
implications
• Feed interventions, feeding and labor
• Limitations to improvement of feed resources on-farm
• Need to increase affordable off-farm produced feed
• Win-win situation through production of affordable off-
farm produced feed

30. Labor implication of feed interventions

31. Cost of Milk Production in India
0
10
20
30
40
50
60
70
IN-2AS
IN-6AS
IN-2GU
IN-8GU
IN-2KA
IN-6KA
IN-2OD
IN-5OD
IN-2UP
IN-4UP
IN-2HA
IN-20HA
IN-60CF
IN-300CF
USD/100kgmilk(ECM)
Quota costs Opportunity costs Cost P&L - non milk returns Milk price
IFCN, 2018

32. Labor input per dairy animal on 4 farms in India with
differing numbers of animals and land sizes
(modified from
0
1 0 0
2 0 0
3 0 0
4 0 0
5 0 0
6 0 0
7 0 0
8 0 0
9 0 0
1 0 0 0
Hours/head/year
F 1 [2 /0 ] F 2 [4 /3 .7 ] F 3 [2 2 /4 .8 ] F 4 [3 7 /0 ]
(m o d ifie d fro m H e m m e e t a l., 2 0 0 3 )

33. Gender Role in Dairy Production
Activities Men Women
Livestock/ Dairy Animal treatment Fodder collection
Breeding Feeding
Feed purchase Watering
Delivery of milk/marketing Cleaning shed
Sweet manufacturing Milking
Delivery of milk/marketing
Care of sick animals
Total labor hours for
dairy
0.5-1 hours 4-5 hours
2-3 hrs. for feeding tasks
(Source: Kumaraswamy et al., 2014. A gendered assessment of the Mulukanoor Women’s Cooperative Dairy value chain, Telangana, India;
Ravichandran et al., 2018. Determinants of women’s participation and control over dairy income from dairy cooperatives: Evidence from Bihar and Telangana
villages, India)

34. More off-farm produced feed and its
implication for wider rural livelihood
implicationsForages as a cash crop
• Simple, low biophysical and socio economic investment
• Highly competitive for example with vegetables
Fodder marketing, service provision
• Fodder collection and transactions
• Chopping, grinding
• Silage, hay making
Feed processing
• Mineral and other supplements
• Total mixed rations

35. Conclusions
• Increase the economic benefit from ASF production by decreasing feed
costs and/or increasing ASF production,
• Decrease the environmental footprint of ASF production
• Reduce labour requirements and drudgery involved in feed resourcing and
feeding
• Provide opportunities for micro, small and medium enterprises (MSME) in
feed production, marketing and processing

36. Conclusions
However to achieve this we need to work within a wide
disciplinary and institutional framework:
• Economists and socio-economists
• Natural resource management
• Plant improvement
• Key life science actors
• Development actors, NGOs
• Private sector
• Policy makers

37. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
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