Improving the value of maize as livestock feed to enhance the livelihoods of maize-

livestock farmers in East Africa

CIMMYT/ILRI/NARS Joint Project

2005-2009

BMZPresentation: CGIAR Systemwide Livestock Programme

Livestock Policy Group, 1 December 2009

ILRI

International Livestock Research Institute

Background:● maize is grown on about 5 million hectares in Ethiopia,

Kenya and Tanzania.

● maize grain provides on average for one third of the daily calories in the diets

● maize is often grown in crop-livestock farming systems where maize stover can contribute to livestock feeding

● livestock rearing contributes to household nutrition, cash income, asset building and employment.

Justification:

● shortage of arable land and water resources● shrinking and deteriorating common property● increasing demand for fodder● further pressure on feed resources

increasing use of crop residues as fodder

Maize stover for animal fodder…

Current maize breeding programs:

● Breeding programs focus on improved grain yield, and resistance/tolerance to biotic & abiotic stresses

● stover traits are usually neglected in cultivar selection

● stover quality and quantity in cereals is highly genotype dependent

Project Goal

● to investigate the potential of dual-purpose maize to enhance the livelihoods of resource poor crop-livestock farmers of East Africa where the concentration of mixed smallholders is highest and agricultural systems are undergoing further intensification

Objectives:● To understand the influence of livestock related factors on

farmers choice of maize cultivars.

● To identify superior dual-purpose maize cultivars from existing maize germplasm for diverse agro-ecological zones.

● To define opportunities and strategies for further genetic enhancement towards dual-purpose maize.

● To develop new tools for quick and economical on-field assessments of stover fodder value in crop improvement work.

● To propose additional selection criteria for variety releasing agents that take into consideration stover quality.

Project partners: ● ILRI M Blummel, Salvador Fernandez Mario Herrera Ashenafi Mengistu

● CIMMYT S. Twumasi-Afriyie H De Groote, W Mwangi, D Watson

● EIAR, OARI, MAFS-Tz, KARI Gudeta N, Demissew A, Dagne W, Birhanu T Md. Hassena, Getachew D P Matowo, S Lyimo, G Sonda J Kang’ara

● Haramaya U, Sokoine UA Bekabil Fufa, Habtaamu Zeleke Evelyn Lazaro

Influence of livestock related factors on farmers choice of maize cultivars

• CIMMYT and ILRI household data combined to determine potential areas for impact of improved food-feed-maize in AEZs and countries

– 8 contrasting maize-livestock scenarios identified based on differences in:• Human population• Cattle density• Available feed resource characteristics

– 3 study sites chosen in Ethiopia; 2 in Tanzania

Cattle numbers, human population and feed resources in Ethiopia

[Source: Mario Herrero, ILRI]

low potential feed deficits

Potentially 25% from maizelowest potential feed deficits

Potentially 30% from maizeV. high potential feed deficits

Potentially 35% from maize

Hai High pop./high cattle/low feed

resources Use of thinnings, strippings Cut and carry dry stover (zero

grazing)

Moshi High pop./high cattle/high feed

resources Feed dry stover in situ

Maize-Livestock Systems in NZ, Tanzania

Use of stover in contrasting scenarios(PRAs in Bako and Awassa)

● Much diversity in the way maize stover is used as fodder depends on availability of grazing land

● Stover becomes important as cropping expands onto grazing land Bako: grazing land available

livestock freely graze crop residues after harvest. Awassa: pastureland scarce

dry stover transported & stored at homestead sold in market (green cob production), green stover cut and sold

● Farmers recognize differences among maize varieties in the quality of their stover as livestock feed.

Maize attributes identified by farmers that determine choice of maize cultivars

Food criteria Feed criteria Agronomic criteria Other criteria

Taste of main dishes

Nutritional quality

Quality of ‘ferso’

Sweet green cob

Flour mix-ability

Digestibility

Taste of kolo, mullu

Flour yield

Fermentation of the dough

Thin bark of the stalk

Thin stalk

Soft stalk

Wet stalk

Green leaf

Sweet stalk

Stover biomass

Number of tillers

Yield by volume

Yield by weight

Cob size

Grain size

Number of ear per plant

Plant height

Drought tolerance

Disease tolerance

Pest resistance

Weed resistance

Uniformity (plant and color of tassel)

Ear filling

Husk cover

Duration

Seed color

Seed re-use

Cash investment

Labor investment

Market price

Seed availability

Fertilizer

Importance of maize attributes by gender and maize/livestock scenario

Rank Male Female Ambo Bako Hawasa

1 YIELD YIELD YIELD YIELD YIELD2 2 FOOD 4 2 FOOD3 FOOD 2 2 FOOD 24 4 4 COB SIZE 6 65 COB SIZE COB SIZE FOOD COB SIZE 46 6 6 7 4 COB SIZE7 8 10 6 10 STOVER8 7 11 10 11 89 STOVER 15 STOVER 16 17

10 10 19 11 8 1511 11 STOVER 8 7 SWEET STK12 12 17 15 STOVER 2013 WET STALK 8 SWEET STK WET STALK 1214 SWEET STK 7 WET STALK 19 1915 15 SWEET STK 12 17 1016 16 16 18 12 1117 17 12 16 15 718 18 20 20 SWEET STK WET STALK19 19 WET STALK 19 18 1820 20 18 17 20 16

Attribute by Gender Attribute by Maize/Livestock Scenario

FO

OD

T

RA

ITS

FE

ED

TR

AIT

S

Farmers’ evaluation of maize varieties with respect to major attributes

Improved variety Local variety

Rank BH660 BH540 Burre BH660 AMH800 Orome BH540 Tabor

1 YIELD 15 2 YIELD 3 15 3 YIELD2 2 4 11 7 4 2 2 33 3 9 12 3 STOVER 12 9 STOVER4 4 3 STOVER STOVER 9 WET STK 15 125 5 2 WET STK 9 YIELD 11 7 76 6 YIELD 4 6 2 STOVER STOVER 157 7 5 13 WET STK 7 3 4 58 STOVER STOVER 3 4 12 5 11 WET STK9 9 12 6 11 14 14 12 1410 WET STK 7 9 12 15 6 YIELD 911 11 WET STK 5 2 13 4 WET STK 412 12 6 7 14 11 13 6 213 13 11 14 5 6 9 5 1114 14 14 15 15 5 7 14 615 15 13 YIELD 13 WET STK YIELD 13 13

AwassaBako Ambo

Factors influencing farmers’ choice of maize varieties

● Experience in maize production● Sex of the farmer ● Farmer’s education level ● Family size of a household ● Total livestock holding of a household ● Total land holding of a household ● Perception of inputs & credit availability ● Walking time to nearest market ● Walking time to nearest all-weather road ● Participation in extension training ● Study area where a farmer resides ● Demand for food attribute ● Demand for green cob attribute ● Demand of large stover biomass ● Demand for sweet stalk ● Demand for yield attribute ● Demand for good price at market

● Choice of improved varieties: Access to fertilizer

+ Land holding

+ Gender (male)

+ Access to road

−

● Choice of local varieties: Access to seed

− Land holding

− Gender (male)

− Extension training

− Demand for food & yield

+

● Stover biomass & sweetness did NOT influence choice

Variable Y=Local only Y=IV only Y=IV-Local

FAMSIZE 0.016 -0.008 -0.008

EXPYEAR 0.012*** -0.007 -0.005

TLU -0.012 0.003 0.009

ACCROAD 0.112**-

0.094* -0.018

MARKET -0.063 0.000 0.063

LAND

-0.108*** 0.082*** 0.025

ST_AREA

-0.660*** 0.385*** 0.275***

SEX

-0.231** 0.232* -0.001

EDU 0.041 -0.101 0.060

FERT -0.043 0.396*** 0.439***

SEED

-0.209** 0.068 0.141

CREDIT 0.127 0.126

-0.253***

EXTN -0.306* -0.102 0.408***

FOODd

-0.180** 0.107 0.074

ISHETd 0.234** 0.087

-0.322***

BIOMSd -0.104 -0.063 0.167*

SWTSd 0.159 -0.093 -0.066

YIELDd

-0.300*** 0.178 -0.178

PRICEd -0.141 0.153 -0.012

Livestock production potential of maize stover and its prediction by laboratory traits

• a range of maize cultivars grown in 2003 (DZ), 2004 (DZ) and 2005 (Ambo) and fed to sheep

• intake and LWG by sheep measured

• samples analyzed for a wide range of chemical, in vitro and morphological traits (collectively called lab-traits)

• simple and multi-variate regressions used to relate lab to animal data

• lab traits validated for Near Infrared Spectroscopy calibration

Fernandez-Rivera et al, unpublished

Sheep performance on maize stover based-diets

Cultivar Years Intake Weight gain (g/d)

A 511 2005 43.3 18.5

BH 140 2004/2004 47.2 27.9

BH 540 2004 44.0 26.3

BH 542 QPM 2004/2005 51.5 37.8

BH 660 2004/2005 44.6 23.5

GIBE 1 2005 46.7 30.3

KATUMANI 2004/2005 47.5 34.9

KULENI 2005 45.7 33.6

PHB 3253 2004/2005 45.3 27.9

SYN 1 2004/2005 46.2 25.6

SYN 2 2004/2005 45.1 29.4

SYN 32 2004/2005 45.8 30.0

LSD 3.5 10.5

P < 0.001 0.04Fernandez-Rivera et al, unpublished

Correlation between livestock productivity and lab quality traits in 71 individual treatments

Traits 2004 + 2005 2003 2004

R P>F R P>F R P>F

Nitrogen 0.08 0.50 -0.26 0.22 0.40 <0.01

In vitro digestibility

0.29 0.01 -0.06 0.80 0.04 0.80

Cell wall (NDF) -0.24 0.04 -0.50 0.01 -0.19 0.20

Cellulose (ADF) -0.21 0.09 -0.66 <0.01 -0.53 <0.01

Lignin (ADL) -0.22 0.07 -0.58 <0.01 -0.48 <0.01

Fernandez-Rivera et al, unpublished

Correlation between livestock productivity and lab quality traits in 71 individual treatments

Traits 2004 + 2005 2003 2004

R P>F R P>F R P>F

Nitrogen 0.08 0.50 -0.26 0.22 0.40 <0.01

In vitro digestibility

0.29 0.01 -0.06 0.80 0.04 0.80

Cell wall (NDF) -0.24 0.04 -0.50 0.01 -0.19 0.20

Cellulose (ADF) -0.21 0.09 -0.66 <0.01 -0.53 <0.01

Lignin (ADL) -0.22 0.07 -0.58 <0.01 -0.48 <0.01

Fernandez-Rivera et al, unpublished

Correlation between livestock productivity and morphological quality traits

Traits2004

R P > F

Plant height -0.15 0.31

Stem diameter -0.12 0.40

Number of leaves -0.01 0.94

Leaf length -0.04 0.81

Leaf width 0.01 0.94

Fernandez-Rivera et al, unpublished

• Better understanding of some of the morphological assessments required since they are linked to farmers perception and preliminary screening

New tools for quick & economical on-field assessment of stover fodder value for

breeders

Qualitative trait prediction in plant breeding based on Near Reflectance Infrared Spectroscopy (NIRS)

Non-destructivec. 200 samples/d

>30 traits

Physico-chemicalc. 60 000 US $CalibrationValidation

NIRS equations sharable across compatible instruments

Blind-prediction of pertinent laboratory traits by stationary Near Infrared Spectroscopy (NIRS)

Laboratory trait R2 nNitrogen 0.91 220

Metabolizable energy 0.88 220

In vitro digestibility 0.87 220

Cell wall (NDF) 0.88 220

Kinetics (rate) of fermentation 0.91 220

U Hohenheim field NIRS instrument

Comparison of blind-prediction of maize stover lab quality traits by field and stationary NIRS

Laboratory trait R2 Field R2 Stationary

Nitrogen 0.79 0.95

Cell wall (NDF) 0.83 0.93

In vitro digestibility 0.82 0.88

Montes et al. (2008)

• However, sample preparation and presentation problematic

VariableField NIRS (chopped

maize stover)Stationary NIRS

(ground maize stover)

R2 SEP R2 SEP

Stover Nitrogen 0.44 0.16 0.92 0.06

Cell wall (NDF) 0.79 3.3 0.95 1.68

In vitro digestibility

0.89 2.9 0.95 2.0

Conclusion

• While predictive accuracy of field NIRS is less than of stationary NIRS it can be used for screening

• Mobility needs to be further increased

• Currently stationary lab NIRS more suitable for support of multidimensional crop improvement

• Main constraint remains sample preparation

Genetic Variability in Maize Stover Quality and Its Relation to Primary Traits

● Two highland trials: Ambo, Holeta and Kulumsa ARC 12 & 22 hybrids

● Two mid-altitude trials: Bako, Hawassa and Jimma ARC 63 entries; 16 inbred lines

● Two trials planted in Tanzania (Selian ARI and Hai) 56 genotypes

● Measurements: grain and stover yield stover fodder quality traits (CP, NDF, ADF, ADL, OM, TIOMD, NDFD,

N, ME, IVOMD)

Phenotypic correlation between food and feed traits in 63 maize hybrids evaluated at 3 sites

LSR SY N NDF ADF ME IVOMD

GY 0.07 0.76** -0.28* 0.02 0.17 -0.09 -0.08

LSR -0.19 0.07 0.20 0.17 0.02 0.02

SY -0.33** 0.03 0.09 -0.13 -0.13

N -0.67** -0.19 0.67** 0.70**

NDF 0.37** -0.52** -0.55**

ADF -0.13 -0.12

ME 1.00**

● High genetic variability observed among: Highland crosses Mid-altitude crosses Mid-altitude inbred lines

● GY & SY positively and strongly correlated possibility for simultaneous increase

● SY & GY not correlated with quality traits possibility to improve GY & SY w/o

affecting quality

● BUT stover quality traits SHOULD be incorporated as evaluation criteria: During inbred line development Hybrid performance evaluation

Heritability, heterosis and CA in maize SY and quality

● Important to design future breeding strategies for the development of food-feed maize genotypes. Therefore:

Estimate heritability for stover feed quality traits in maize hybridsDetermine level of heterosis for GY, SY and quality Determine the relative importance of GCA and SCA

● Preponderance of additive gene effects most traits can be improved with simple selection Recurrent selection needed for complex traits like GY & SY

● Heterosis:increasing effect on: ADF (acid detergent fiber), ADL (acid detergent lignin), DCRY (digestible crop residue yield) decreasing effect on: nitrogen (N), metabolisable energy (ME) and in vitro organic matter digestibility (IVOMD).

Conclusions

Implications of genetic variability and farmers’ choice on maize stover quality for breeding

programs and variety release criteria

Some Principles● Current release criteria with focus on grain remain important● Stover traits are additional criteria not substituting criteria● Go for win-win situations● Facilitate optimization of whole plant utilization (also beyond fodder)

Some Approaches ● Map demand areas/AEZs to decide on weighing criteria● Use stepwise approach, e.g., include stover yield as weighted

criteria according to demand areas/AEZs● Phenotype submitted cultivars for variations in food-feed traits

(hub?)Conclusions● Need to include diverse participants in the food-feed value chain● From exploration to implementation > 5 years● Stepwise process probably biomass yield

in addition to grain as 1st step

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