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V2 PAR PROCESS: GHANA AND BURKINA 
             FASO
Team composition

                        ILRI, IWMI, WUR        Burkina Team
   Ghana Team




Agronomist ‐1 ARI
Nutritionists‐2 ARI                       Agronomist
Economists‐2 UDS,ARI                      Nutritionists
Agro‐climatologist‐1                      Economists
SARI                                      Agro‐climatologist
Process of PAR design
  PRA  Team            IPs Looking for         PAR Team
Getting started         things to try     Designing experiment


                          Analysis of               Treatments
  Secondary data          constraints           Number of farmer 
    Community           Prioritization            experimenters 
 identification and       Rain water                 identified
       entry            management               Resources, roles 
  Identification of        strategies            and time frame
    constraints         Technical and             Other studies 
                         institutional               identified
                          constraints              PAR protocol
                          understood                 indicators

        Tools
     Community                Tools                    Tools
     workshops            IP meetings               IP meetings
   Questionnaire            Pair wise             Team meetings
   Team meetings             ranking
      Trainings               Group 
                          discussions
Process contd.

Design of PAR        Trying out
 Sustaining        Data collection    Analysis
  process           Monitoring




                         IP




                      Sharing  
                     ressults
                     Learning
Identified institutional constraints and possible 
                      action
Constraints              Actions
High cost of fertilizers IP to discuss, feed 
                         evidence‐based studies to 
                         IPs
Bushfires                IPs to discuss
Inadequate knowledge in  Training (MoFA),NGOs and 
handling agro‐chemicals  agro‐chemical companies
Inadequate storage       IPs to discuss communal 
facilities               storage facilities
Identified technical constraints and possible 
                    solutions
Constraints                 Technological solutions
Drought                     Use of Tied ridges and 
                            contour bunds
Low soil fertility          Use of organic and 
                            inorganic manure
Lack of animal feed in dry  50% and 100% crop 
season                      residue harvest  and feed 
                            strategies developed
Animal                      Prophylactic treatment of 
diseases/mortalities        small ruminants
THANK YOU!
Please stay for more on the AR 
            protocols
V2 ACTION RESEARCH PROTOCOL: GHANA
                  BACKGROUND
 Innovation platforms, took roots from the
Participatory Rural Appraisal (PRA) and were built
around key crop‐livestock value chains in the Lawra
and Tolon/Kumbungu districts. They identified
constraints, opportunities and strategies at various
levels along each value chain, and these formed the
basis for formulating, in a participatory approach,
the PAR protocol.
Objectives of the PAR
The objectives of the PAR, which are similar
to the research questions are:
Which are the best integrated rainwater
management strategies and how would they
work in each recommendation domain?
Will integration of organic and inorganic
fertilizer for maize‐soybean intercrop,
supplementary feeding and prophylactic
treatment     lead    to     increased farm
productivity and profitability?
Hypothesis


Better integration of crop‐livestock and rain
water management increases overall farm
productivity and profitability
Design of the experiment
Of the constraints identified at IP which require
technological solutions the project communities
agreed to use the following interventions:
Contour bunds
Tied ridges
Application of organic and/or inorganic fertilizers to
experimental plots
Supplementary feeding of small ruminants
Prophylactic treatment of small ruminants
Issues addressed
Rainwater management
Soil fertility improvement
Livestock feeding
The treatments
            Soil water           Soil fertility              Supplementary
            management           management                  feeding
Treatment
            Tied      Contour    Organic       Inorganic     50% crop    100% crop 
            ridges    bunds      manure        fertilizers   residue     residue 
                                 4t/ha         NPK 15‐       harvest     harvest
                                               15‐15, SA     (Gp. 1      (Gp. 2 
                                                             farmers)    farmers)

T1

T2          √                    √                           √           √

T3                    √          √                           √           √

T4          √                    √             √             √           √

T5                    √          √             √             √           √

ALL FARMERS WILL SOW MAIZE/SOYBEAN INTERCROP
Order of experiment
                 Agronomic
Number of farmer experimenters‐
16/location
Plot size‐0.5acre/farmer
Completely randomized block design
Subplots 15
Measuring 10mx10m
3 replicates
Livestock feeding experiment

T1: Free range (farmer practice)
T2: Confinement + cereal‐legume residue 
T3:  Confinement + cereal‐legume residue 
+concentrate
Order of experimentation

For the raining season flock management will 
be Monitored.
Feeding trials will start from January to April
Number of farmer experimenters‐6/location
Total no. of sheep/location‐30
All animals will be given prophylactic 
treatment
Response variables
 Net grain yield (maize and soybean)
 Soil nutrient content (moisture, pH. NPK, C 
 etc.)
 Crop residue yield (bulk DM, stem/leaf ratios)
 Cost of production
 Small ruminant manure yield (quantity, 
 quality),housing management
 Feed intake
 Weight gains, total gain, growth rate
 Feed conversion ratio
Mortality rate
Statistical analysis


Each response variable will be subjected to
statistical analysis using the GENERAL ANOVA
of GENSTAT RELEASE 10.3 DISCOVERY
EDITION 4 with 5% level of significance
Field activities to date
Activity                 Start date   Status      Remarks
Farmer /AEA training     15/04/2012   Completed
on protocol
Soil sampling            14/05/2012   Completed
Procurement of seed      20/05/2012   Completed
material
Ploughing                04/06/2012   Completed

Field layout (marking    10/06/2012   Completed
out subplots)
Weighing out organic     12/06/2012   Completed
manure
Field layout (tied       12/06/2012   Completed
ridging & contour 
bunds)
Sowing at                25/06/2012   Completed   Lawra district not 
Tolon/Kumbungu                                    started‐no rains
District
Field layout demonstration at farmer training
Tied ridges demonstrated on the ground at farmer 
training session
Field layout demonstration to project farmers
Soil sample collection
Soil samples 
Weighing of organic manure
Contour bund
Tied ridges being made
Tied ridges being made
Women putting manure into pans
Tied ridges 
Women carrying head pans full of manure to the fields
THANK  YOU!
Please don’t go away. Stay 
  for more from Burkina 
          Faso!
V2 ACTION RESEARCH PROTOCOL
         Burkina Faso




                              33
Background: 

Research protocol builds on :
• PRA
• IPs meetings 
with regard to crop and livestock value chains 

The action research addresses the constraints linked to 
water, crop and livestock management.
                                                           34
Objectives: 
▪ Assess agricultural production (crop yields, animal weight 
gain), water productivity and nutrient flows in smallholder 
crop‐livestock farms of the Volta Basin, for different levels of 
integration, different agroecological zones and different levels 
of access to rainwater management technologies;

▪ Assess trade‐offs in using water for crops or for livestock, 
through alternative uses of crop residues.
                                                             35
Hypothesis
(i) Agricultural production (crop yields, animal weight gain and 
    milk production), water productivity and nutrient use efficiency 
    are higher in farms where water, crops and livestock 
    management are integrated in a sustainable manner.

(ii) The increase in agricultural production (crop yields, animal 
      weight gain and milk production), water productivity and 
      nutrient use efficiency due to integration has greater impact on 
      food security and farmers livelihood in water scarce areas 
      compared to areas with higher access to water. 

                                                                   36
37
38
FACTORS STUDIED
RHT: Stone rows; Stone rows + Zai; grass strip; control

Fertilization: Mineral fertilizer, OM+fertiliser; control

Animal feeding: Pasture+crop residues; pasture+crop
residues+industrial by‐products; pasture (control)

Crops: cereal; legume (improved seeds)
Animals: sheep; goat
12 farmers per village (4 villages per district, 2 districts)
Plot size: 0.25 ha per crop type                                39
Measurements
Soil: Bulk density, pH, nutrients (NPK), OM, texture, field 
capacity, wilting point.

Climate: rainfall, air Temperature, air humidity, radiation, 
wind speed.

Manure & Compost: nutrient contents, water content 

                                                           40
Measurements
Crop: planting date, fertilizer application date, harvesting 
date, yield, biomass production, nutrient contents, forage 
quality.

Livestock: weight gain, feed water content, deaths, sales, 
births, quantity of crop residues fed.

Pasture: floristic composition, herbage yield, forage 
quality, nutrient contents.
                                                          41
Measurements
Economic evaluation: date and nature of farming activities, 
labour, costs and benefits, market information (prices and 
outlet). 




                                                          42
STATISTIC ANALYSIS
ANOVA ; multivariate analysis, correlations

Using GENSTAT




                                              43
THANK YOU!



             44

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