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THE CONTRIBUTION OF EXOGENOUS ENZYMES TO SUSTAINABLE (RESPONSIBLE) ANIMAL PRODUCTIONGilson A. GomesGlobal Technical Manager, AB Vista
Oliver KinseyGlobal Services Manager, AB Vista
Christine YoungAccount Manager, AB Sustain
OUTLINE1. Introduction2. Exogenous Enzymes3. Enzymes Benefits in Practice4. Conclusions
LIVESTOCK: WE ARE RESPONSIBLE TO PROVIDE GOOD QUALITY PROTEIN FOR THE POPULATION
Zuidhof, et al. Poultry Science 93, 2970–2982 (2014).
PER CAPITA MEAT COMSUMPTION
6.52 6.49 6.41 6.45 6.51 6.50 6.48 6.47 6.47 6.48 6.48 6.48 6.48 6.50
12.5 12.6 12.5 12.3 12.3 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.1
13.2 13.3 13.7 13.8 13.9 13.8 13.9 13.9 14.0 14.0 14.0 14.1 14.1 14.1
1.70 1.70 1.72 1.73 1.73 1.75 1.76 1.79 1.81 1.83 1.85 1.86 1.87 1.88
13 14 15 16 17 18 19 20 21 22 23 24 25 26
Kg m
eat p
er c
apita
Year
Beef Pork Poultry Sheep
Source: OECD-FAO Agricultural Outlook (Edition 2017)
POPULATION VS CROPS
Source: OECD-FAO Agricultural Outlook (Edition 2017)
y% (2017) = 1.32x - 1843
y% (2017) = 1.00x - 1928
y% (2017) = 0.83x - 1581
y% (2017) = 0.96x - 1843 2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
2012 2014 2016 2018 2020 2022 2024 2026 2028
Mill
ions
of t
onne
s (Co
rn, W
heat
, Soy
)
Glo
bal P
opul
atio
n (B
illio
ns o
f peo
ple)
Year
Population Corn Wheat Soybean
PRODUCING ANIMALS IS JUST GETTING LESS ENVIRONMENTALLY
FRIENDLY…SWEDEN (1986)
DENMARK (1999)
EUROPEAN UNION (2006)
USA (2016)
BRAZIL (2016)
LIVESTOCK PRODUCTION: WE ARE THE ONES TO BLAME FOR GLOBAL
ENVIRONMENTAL ISSUES
IF WE DON’T DO OUR HOMEWORK…
Market Forces and Food Technology Will Save the World, Bruce Friedrich, TEDx
WE ARE IN THE RIGHT DIRECTION…
…”Microbial phytase has been used successfully to control P excretion”……”Nitrogen control can be achieved through amino acid supplementation and protein restriction in the diet”……” Supplementation with carbohydrasesreduces output of excreta as well as N”…
Paik, I. K. Asian-Australasian Journal of Animal Sciences 14, 384–394 (2001).
EXOGENOUS ENZYMES
HISTORY OF FEED ENZYMES
• 1984: 1st Glucanase commercially available
• 1990: 1st Phytase commercially available
• 2008: Protease commercially available
PHYTATE-P CONTENT IN FEED INGREDIENTSPh
ytic
P, (%
)
0.000.200.400.600.801.001.201.401.601.80
> 100,000 samples testedSource: AB Vista
PHYTASE
MORE P THAN
NEEDED
POLUTION
NELSON ’70s
PHYTASE ’90s
P COST
0.10%avP
0.12%avP
0.14%avP
0.15%avP
PHYTATE AND AMINO ACID DIGESTIBILITY
Ilea
l am
ino
acid
dig
estib
ility
Cowieson et al. (2017)
Meta analysis on 24 independent publications
THERE IS A LARGE VARIATION IN NSP CONTENT IN FEEDSTUFF
0
10
20
30
40
50
60
Rice
(n=4
)W
heat
flou
r (n=
1)Co
rn g
lute
n m
eal (
n=6)
Cook
ed c
orn
(n=3
)Co
okie
/Cra
cker
resi
due
(n=7
)So
rghu
m (n
=30)
Pear
l mill
et (n
=10)
Cass
ava
(n=1
)Co
rn (n
=153
)Q
uino
a (n
=2)
Bake
ry m
eal (
n=3)
Whe
at (n
=55)
DDGS
, ric
e (n
=1)
Pea
(n=2
)Pe
anut
mea
l, ex
pelle
r (n=
3)Br
oken
cor
n (n
=1)
Bake
ry c
ooki
e m
eal (
n=2)
Cott
on se
ed m
eal (
n=1)
Full
fat s
oya
(n=2
6)Fe
rmen
ted
soyb
ean
(n=1
)Se
sam
e M
eal (
n=1)
Oat
(n=1
)Pe
anut
mea
l (n=
4)Co
rn g
erm
mea
l, de
fat (
n=1)
Rice
bra
n (n
=9)
Sesa
me
mea
l, ex
pelle
r (n=
1)So
ybea
n m
eal (
n=66
)Ba
rley
(n=2
0)G
uar m
eal (
n=3)
Soyb
ean
mea
l, ex
pelle
r (n=
2)So
y pr
otei
n co
ncen
trat
e (n
=1)
Whe
at m
idds
(n=1
)Ca
nola
mea
l (n=
10)
Rice
bra
n, d
efat
(n=3
)Co
rn g
erm
mea
l (n=
2)DD
GS, c
orn
(n=1
8)Su
nflo
wer
mea
l (n=
5)Al
mon
d hu
lls (n
=1)
Cass
ava
bran
(n=4
)W
heat
bra
n (n
=18)
DDGS
, whe
at (n
=1)
Corn
glu
ten
feed
(n=4
)Co
conu
t exp
elle
r (n=
1)Pa
lm k
erne
l mea
l (n=
4)Co
conu
t res
idue
(n=1
)Co
rn c
ob (n
=1)
Beet
pul
p (n
=1)
Soya
hul
ls (n
=8)
% A
S IS
BAS
IS
Arabinose Xylose Fuccose Galactoronic Acid Galactose Glucoronic Acid Mannose Rhamnose Glucose (Soluble) Glucose (Insoluble)
AB Vista Internal Data, 2018 (n>500 samples)
ENERGY COST
NEGATIVE CORRELATION BETWEEN FIBRE MEASUREMENTS AND DE SHOWS HIGHER
FIBRE CONTENT, REDUCED ENERGY
Correlation factor>0.24 : P<0.01
Nutrient dig vs Energy value
65% to 92% (mean 81%)Negatively affected by fibre
(1993) J. Noblet, J.M. Perez. Prediction of digestibility of nutrients and energy values of pig diets from chemical analysis
ENZYMES BENEFITS IN PRACTICE
30.7
a
60.0
b
21.1
4b
1.29
4a
22.7
b
60.5
b
21.0
4b
1.26
2b
22.5
b
61.6
a
22.1
0a
1.27
3b
21.5
c
59.0
c
21.1
0b
1.21
9c
60%65%70%75%80%85%90%95%
100%105%110%
P efficiency (gP/bird)
Lys efficiency (gLys/bird)
Calorie Conversion(Mcal/bird)
Cost (EUR/bird)
PC IC NC NC+QB/EXT
UTILIZING PHYTASE IN COMBINATION WITH XYLANASE TO OPTIMIZE MINERALS, ENERGY AND AMINO ACIDS UTILIZATION
AND LOWER FEED COSTS OF BROILERS
NC+MMN
27.7
a
50.5
b
13.8
3b
1.03
1a
21.2
b
50.5
b
13.6
2b
0.97
6b
20.8
b
53.2
a
14.7
0a
0.99
6b
19.2
c
49.0
b
13.5
8b
0.92
5c
60%65%70%75%80%85%90%95%
100%105%110%
P efficiency (gP/bird)
Lys efficiency (gLys/bird)
Calorie Conversion(Mcal/bird)
Cost (USD/bird)
PC IC NC NC+QB/EXT
UTILIZING PHYTASE IN COMBINATION WITH XYLANASE TO OPTIMIZE MINERALS, ENERGY AND AMINO ACIDS
UTILIZATION AND LOWER FEED COSTS OF BROILERS
NC+MMN
CARBON FOOTPRINT
2.35a 2.30ab 2.36a 2.23b
- 500/9600 - MMN
PositiveControl
IndustryControl
Min+AA's+EMA
2.58b 2.48bc 2.75a 2.40c2.00
2.10
2.20
2.30
2.40
2.50
2.60
2.70
2.80
2.90
3.00
- 500/9600 - MMN
PositiveControl
IndustryControl
Min+AA's+EMA
kg C
O2/
kg c
arca
ss
UTILIZING PHYTASE IN COMBINATION WITH XYLANASE TO OPTIMIZE MINERALS, ENERGY AND AMINO ACIDS
UTILIZATION AND LOWER FEED COSTS OF PIGS
374b
965b
510a
22.8
7b
375b
968b
375b
22.3
0bc
422a
1080
a
386b
24.0
6a
381b
971b
347b
21.6
7c
0%
20%
40%
60%
80%
100%
120%
140%
160%
Calorie conversion,Mcal/pig*
Lys efficiency, g/pig* P efficiency, g/pig* Cost/pig, €
Resu
lts a
s re
lativ
e to
IC fe
d pi
gs
PC IC NC MMN
Quantum Blue 2018 Pigs Spain 817
CARBON FOOTPRINT
1.10
1.12
1.14
1.16
1.18
1.20
1.22
1.24
1.26
1.28
PC IC NC NC+MMN
Kg C
O2e
/Kg
BW
TARGETED USE OF ENZYMES ALLOWS THE REDUCTION IN FEED COST AND CO2E
934.3
869.8
904.0
845.2
263.8
253.1
287.2
275.0
80%
85%
90%
95%
100%
105%
110%
115%
Conventional MMN Conventional MMN
Least Cost Least CO2e
Diff
eren
ce, %
(Rel
ativ
e to
con
vent
iona
l Lea
st C
ost)
CO2e EUR/t
