to SNV (2008), the Eastern Province has more than 49% of all the cattle
population in Rwanda but is challenged by prolonged drought as it is the first
region with high risk of drought (MIDMAR, 2014, Bazimenyera
et al., 2014).).  Dairy production
plays an important role in the area both as a food source and for cash
generation.  Cattle for instance,
contribute 30% of the total household income of which 89% is from the sale of
milk.  The main cattle breeds kept are
crossbreed between exotic (mainly jersey and Holstein) and local East African
Shorthorn.  Milk productivity per
lactating animal in the area is normally between 3 and 10 kg per day in the dry
season, and 5 and 15 kg per day in the wet season.  The dominant system of dairy production is
zero grazing system (Cut and Carry system).

Farmer interviews and

The study will target smallholder farmers in zero-grazing
dairy production system, who keep cattle in a common cow shed.
 A comprehensive list of common cow sheds
will be obtained from the Girinka coordinator and District Animal Resources Officer
(DARO).  The list will be used to draw up
a sample framework for the formal survey.  Five (5) farms (common sheds) from each
district will be randomly selected for interview.  This will give a total number of 35 farms in
the seven districts.  Interviews will be
conducted using a structured questionnaire and it will start in March 2018.  The data to collect are classified in social
demographic information about the shed manager, members, herd status (age
category, sex, breeds) animal welfare, health management and feeds and feeding
(types of grasses used, quantity and varieties of Napier used, the way Napier
grass is grown, available land, used conservation techniques and storage,
Challenges/ season, best forage, needs in forages, their awareness on Napier
grass new varieties and manure management.

Feeding management monitoring

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the 5 selected farms per district for interview, one will be randomly selected
for feeding monitoring.  The feed will be
monitored in a total of seven sheds over one-week period in March, May, August
and October 2018.  March and August are
dry season months associated with feed scarcity while May and October are the
peaks of the rainy season when feeds are more widely available.  From each shed, 10 for a total of 70 cows will
be selected for feed monitoring.  A 50 kg
spring scale with units of 0.5 kg will be used for weighing feeds at each farm.
 Samples of various varieties of feed
will be pooled separately and subsampled each week for chemical analysis.  Refusals will be weighed every afternoon,
accumulated weekly, subsampled and prepared for chemical analysis.  The types of feeds offered to cattle during
the exercise will be classified into: Napier grass; weeds (roughage cut from
road sides and cropland); fibrous crop residues; fodder legumes; other forages
grass and commercially processed feeds (concentrates) which included dairy
meal, wheat or rice bran and pollard (a by-product from the oil extraction
process from maize grain).  The daily
milk yield from each lactating cow in monitored sheds will be measured by
farmers using a scale and recorded in an exercise book for the duration of the
study.  The collection of Milk samples will
be done in every season and kept in cold storage.

Feed samples processing
and nutrient analysis

Feed samples
will be dried at 65 °C to constant weight and ground to pass through a 1 mm
screen before analysis.  Chemical
proximate analysis of feed will be done by wet chemistry (AOAC, 1995) for dry
matter (DM), total N (To be calculated as N × 6.25.), neutral detergent fibre
(NDF), acid detergent fibre (ADF) and total condensed tannins.

Pasture yield and
residual hay estimation

biomass yield of the pasture will be estimated by placing an exclusion cage per
each monitored farm (seven in total) and extrapolating the yield to the area of
the pasture.  Banana pseudo-stems and
legume trees in the diet will be estimated from farmer recall.  Maize Stover biomass will be estimated by
applying farmer recall of grain yield to a harvest index (0.41) (Remison & Fajemisin, 1982).
For forage pasture, the cutting intervals will be taken.  The soil samples from the pasture will be
taken and rainfall conditions data considered.

Milk samples analysis

Milk samples
will be analyzed for butterfat (BF) using Gerber method (Kleyn et al.,
2001) and milk density (FAO, 1998) by New Kenya Co-operative Creameries (KCC),
Kapsabet.  The Richmond’s formula (Bector
& Sharma, 1980) will be used to calculate milk solid non-fat (SNF) from BF
and density.


energy content (ECM) will be calculated from equation by Tyrell

(g ? (kg milk) )+0.0205SNF(g?(kg milk) )-0.236

Data analysis

from the field exercise and chemical analyses of the feed samples will be
statistically analyzed using R (R, 1985).  Standard deviations and means will be
calculated for numbers of cattle per cow shed, areas of fodder crops grown, are
of Napier grown, quantities of roughage, hay and concentrates offered to cattle
during rainy and dry seasons, folder conservation techniques and general
management.  Analyses of Variance (ANOVA)
will be carried out to test for differences between farms, districts and
between seasons, in quantities of roughage and concentrates offered, and in
chemical composition of feeds and milk.  During the rainy season, the daily refusal
quantity and quality, pasture production and herd size will be used to estimate
the hay quantity and quality that can be made from the overproduction.

Objective 2

enteric methane emissions from common cow sheds in Eastern province of Rwanda
across seasons using Tier II method.

Estimation of Enteric CH4

general approach of IPCC Tier 2 will be used to estimate enteric methane
emission.  This approach integrates the
animal activity performance, production data and metabolizable energy
requirements (MER) to compute the daily methane production (DMP) and emission
factor (EF).  Live weights of each cow in
the seven selected farms will be estimated through heart girth measurements using
a ‘Weighband’ (Dalton Supplies Limited, Nettlebed, UK) at the start of the

DMP: daily methane production and DMI: Dry matter
intake Mean

for each class of animal in each season will be calculated.  This will be then used to calculate an annual
enteric methane EF (CH4kg/head/year):


emission factor


the Methane gas analyses, a multiple
linear regression model and analysis of variance (ANOVA) will be utilized.  Descriptive statistics (mean and standard
error of means (SEM)) will be calculated for live-weight, live-weight change,
daily milk yield, total metabolizable energy requirements (MER), DMI and DMP
for each district and season.  The linear
regression model fitted tested the association of methane emissions with dry
matter digestibility and the impact of milk production on energy required for
lactation and total metabolizable energy.  The dependent variables will be daily methane

Yi = ?0 + ?1X1,1 + ?2 X1,2+ ?


Yi =

?0, =
constant, ?1
and ?2=
regression parameters, X1,1 = dry matter digestibility, X1,2=
daily milk production, ? = random

The effect of district and season on DMD and DMP, will
be analysed using ANOVA fitting season (SR, HD, LR and CD) and districts as
factors in a general linear model in the form:

Yijk= ? + ?i + ?j
+ ?ij with i= 1, 2, 3,4,5,6,7 and j= 1, 2, 3, 4


Yijk= DMD/
DMP, ?= overall mean, ?i= level
effect of district, ?j=level effect of season (SR, HD, LR or CD). ?ij= random


Objective 3

Determine the
effect of Napier grass (Pennisetum purpureum) supplemented with the hay of
Clitoria ternatea and Calliandra spp as protein and tannin source on methane
emission, nitrogen and milk quality in lactating cattle.

The study will be carried
out during the dry season in the Eastern province of Rwanda described
above.  Twelve (12) lactating cows will
be purposively selected from the seven farms where the feeding is
monitored.  The selection criteria will
be the use of Napier grass as basal diet by the owner, no use of concentrates,
being from 1st to 3rd lactation, crossbreed, dewormed
against endoparasites and sprayed against ectoparasites, and having
approximately the same live weight.  The
experimental animals will be weighed for initial milk yield and body weight.  Cows will be divided into six groups of two animals
each.  The animals from each group will
be randomly assigned to six dietary treatment.

Feeds and experimental diets

Clitoria will established at
the onset of long rains (April) without fertiliser application in the pasture
of the university of Rwanda (Eastern Province) and harvested after attaining
50–60% flowering.  Calliandra and mineral
licks will be respectively purchased from farmers and local supplier.  The hays of Clitoria and Calliandra will be
made and stored.

The control diet consisted
of Napier grass fed ad libitum as usual and 60g of a mineral lick daily.  The other five treatments consisted of the
control supplemented with 2kg (DM) of Clitoria and/or Calliandra hay.
Considering the daily DMI of 10 Kgs, cows will be getting 80% (8kg (DM)) of the
basal diet (Napier grass) and 20 % (2kg (DM)) of legumes (Clitoria and/ or
Calliandra) as protein supplement.

The six groups of lactating cows will be allocated to
the six dietary treatments (table 1) in a 6×6 Latin-square design.  The
basal diet will be offered after the half of the supplement had been
consumed.  In late afternoon the other remaining
half of supplement will be offered.  Each
experimental period will last for 10 days, consisting of 5 days of adaptation
to the respective diet, 5 days of measurement and collection. Each animal
received the six diets in a different sequence.  The grass quantity will be measured as well as
the refusal.  The milk samples will be
also taken for analysis.  Data will be collected for a period of 60
days including the adaptation period of cows to diets.

Table 2:
Different diet treatments


Basal diet (Napier
grass) %

Clitoria hay %

Calliandra hay %



























In vivo apparent diet digestibility

During data collection of
each diet, total daily faecal output for two consecutive days per experimental
animal will be collected in individual buckets as it was dropped.  The faeces will be weighed, and weights will
be recorded.  Samples will be used for dry
matter determination and ashing.  These
values will be used to determine the amount of dry matter and organic matter in
the faeces, that will help to calculate the percent DM and OM digestibility of
the diets as described by Abdulrazak (1995).

Forage and
milk sample analysis

The forages samples from
each treatment will be taken for proximate analysis. Tannins will be determined
according to the methods described by Abdulrazak and Fujihara (1999).

Milk samples
will be analyzed for butterfat (BF), milk density and non-fat (SNF) using the
method described in objective 1.

model and analysis

following statistical linear model will be used:


yij is the response due to ith treatment and jth
animal; µ is overall mean; ti is the effect of ith treatment
and eij is a random error component.

will be subjected to analysis of variance (ANOVA), using the General linear model
(GLM) procedures of Statistical Analysis Systems (SAS, 1987).  Means will be separated using the least
significant difference (LSD).



the in vivo digestibility and methane gas production of the hay made of Clitoria ternatea and Calliandra spp with and without the
Polyethylene glycol (PEG) added.

hay with and without the polyéthylène
glycol ((PEG-6000) added will be analyzed for digestibility,
gas production (GP) characteristics and methane production.  Samples will be of five types of mixture of Clitoria
and Calliandra.  The proportions of the
two legumes will be: 4:0,3:1,2:2, 1:3 and 0. 
six replicates will be done from each mixture type.  Samples will be dried in forced oven, and
ground and analyzed for nutrient composition. 
The PEG will be added in three replicates of each type.  In vitro GP and in vitro organic
matter digestibility (IVOMD) will be determined using rumen fluid collected,
strained and anaerobically prepared.  A
semi-automated system will be used to measure GP by incubating the sample in a
shaking incubator at 39°C.

The net gas volume data were
fitted to the model p =a +b(1-e-ct) (Menke and Steingass,

a, the gas production from the immediately soluble fraction (mL); b, the gas
production from the insoluble fraction (mL); c, the gas production rate
constant for the insoluble fraction (mL/h); a+b, potential gas production (mL);
t, incubation time (h); y, gas produced at time “t”.

effect on microorganism evolution will also be determined.

Objective 5

Evaluate the effect of
high yielding Napier ecotypes, Calliandra and Clitoria on methane emission,
nitrogen and energy balance in growing lambs  

study will be conducted at BecA-ILRI Hub (Nairobi).  It will consist of feeding trials of
different diets on growing lambs.  Diets will
consist of different proportions of dried, leafy Napier grass, the herbaceous
legume Clitoria and the foliages of the tannin-rich shrub legume Calliandra.  Napier grass cultivar to be used in the study
will be two high nutritious ecotypes from Rwanda.

forages will be used to form six diets: one pure Napier grass diet and five
diets consisting of 80% Napier grass and 20% legumes (on dry matter (DM) basis).
 The legume part of the diets will consist
of Clitoria or Calliandra separately or combined in ratios of: 3:1,2:2, 1:3.

castrated, male lambs of 3 months of age of the same breeds will be weighted, allocated
to the six dietary treatments in a 6X6 Latin-square design.  Each experimental period will last for 16
days, consisting of 7 days of adaptation to the respective diet, 7 days of collection
and measurement of growth and nitrogen related parameters, and 2 days of
quantitative measurement of gaseous exchange in dual open-circuit respiratory

animal will receive the six diets in a different sequence with a daily forage
DM allowance of 60 g per kg of metabolic BW (BW 0.75).  The diet sample will be taken for proximate

were weighed directly before feeding in the morning, at the beginning and the
end of each experimental and adaptation periods.  The food refusal will be recorded during the
experimental period. Faeces and urine will be collected for more analysis. 4 h
after feeding, rumen fluid and blood samples will be taken.


refusals and faeces will be analysed for DM, total ash (to calculate organic
matter (OM)), NDF and ADF, feeds also for ADL, all by standard methods (AOAC,
1990).  NDF will be analysed without the
addition of sodium sulphite, and values of NDF and ADF will be corrected for
ash content.  Extractable and fibre-bound
CT will be determined according to the procedure suggested by Terrill et al.
(1992) as modified by Barahona et al. (2003).  Nitrogen and C content will be determined in
feeds, refusals, fresh faeces and urine. 
Gross energy (GE) contents of feeds, refusals and lyophilised faeces
will be assessed.  Ciliate protozoa and
bacteria will be microscopically enumerated.  Determination of VFA will
be performed by HPLC.  Blood plasma
concentration of urea will be determined. Oxygen, carbon dioxide and methane from
each lamb will be quantified.

and statistical analysis

and N concentrations will be used to calculate urinary energy (Hoffmann
and Klein, 1980).  Methane energy loss
and energy expenditure will be calculated from the gaseous exchange data (heat
production) by the equations of Brouwer (1965) but corrected for the
carbon dioxide emitted from fermentation (Chwalibog et al., 1996).

H= (3.866 x O2) +(1.200 x CO2) –
(0.518 x CH4)- (1.431 x N)

where H = heat production (kcal), O2, CO2
and CH4 represent volumes of oxygen consumed and of carbon dioxide
and methane produced in litres and N: urine nitrogen (g).

body energy retention (RE) will be calculated as metabolizable energy (ME) minus
energy expenditure. Body fat energy will be calculated as the difference
between RE and the energy retained in protein.

GLM procedure of SAS (version 9.1.3; 2006; SAS, Cary, NC, USA) will be used for
analysis of variance with diet, animal and experimental periods as sources of


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