best practice endline survey report: uganda coffee farm
TRANSCRIPT
Best practice endline survey report: Uganda coffee farm college cohort 2018 Implemented by TechnoServe
FEBRUARY 2021
Best Practice Endline Survey Report
Uganda Coffee Farm College Cohort 2018
Implemented by TechnoServe
www.laterite.com
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EXECUTIVESUMMARY..................................................................................................................4INTRODUCTION...............................................................................................................................7RESEARCHDESIGN.........................................................................................................................8HOUSEHOLDDEMOGRAPHICS.................................................................................................11AGRONOMYBESTPRACTICES..................................................................................................12REJUVENATION...........................................................................................................................................................16PRUNING........................................................................................................................................................................17INTEGRATEDPESTANDDISEASEMANAGEMENT(IPDM)....................................................................18SAFEUSEOFPESTICIDES.......................................................................................................................................19COFFEENUTRITION..................................................................................................................................................20WEEDING.......................................................................................................................................................................22MULCHING.....................................................................................................................................................................23SOILEROSIONCONTROL........................................................................................................................................24SHADEMANAGEMENT.............................................................................................................................................25RECORDKEEPING......................................................................................................................................................26
OTHERAGRONOMYPRACTICES..............................................................................................27COFFEEDRYING..........................................................................................................................................................27COFFEEPLANTING....................................................................................................................................................27INTERCROPPING.........................................................................................................................................................29
HOUSEHOLDCHARACTERISTICS............................................................................................30HOUSEHOLDCOMPOSITIONANDFARMERAGE.........................................................................................30EDUCATION...................................................................................................................................................................31EMPLOYMENTSTATUS–OUTSIDETHECOFFEEFARM..........................................................................32PAIDLABORANDCHILDLABOR.........................................................................................................................32LANDOWNERSHIP....................................................................................................................................................33COFFEEPRODUCTION..............................................................................................................................................34ASSETOWNERSHIP...................................................................................................................................................35
PERCEPTIONS&IMPACT...........................................................................................................37THEMEOFINTEREST:GENDER...............................................................................................39FINANCIALDECISIONS(INCOME&SAVINGS)..............................................................................................39FOODDECISIONS........................................................................................................................................................42ALLDECISIONS............................................................................................................................................................44
TABLEOFCONTENTS
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COFFEEFARMRESPONSIBILITY.........................................................................................................................45INTRA-HOUSEHOLDLABOURDISTRIBUTION..............................................................................................46
FINANCIALPROFILE....................................................................................................................47INCOMEDISTRIBUTION..........................................................................................................................................47SAVINGS..........................................................................................................................................................................48
VULNERABILITYPROFILE.........................................................................................................49FINANCIALSHOCKS..................................................................................................................................................49FOODSHORTAGES.....................................................................................................................................................49HOUSEHOLDDIET......................................................................................................................................................50PROGRESSOUTOFPOVERTYINDEX.................................................................................................................51MULTI-DIMENSIONALPOVERTYINDEX.........................................................................................................52
APPENDICES..................................................................................................................................54
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The TechnoServe Coffee Farm College Program, supported by Stichting Coffee Agronomy
Training,KeurigDrPepper,JacobsDouweEgberts(JDE),andEnveritas,isafour-yeartraining
program that aims to improve incomes for 30,000 coffee farming households in Central and
WesternUgandabyincreasingtheircoffeefarmproductivity.Thiswillbeachievedbypromoting
improvedcoffeeagronomicpracticesatthefarmlevelthroughatwo-yearstructuredandfarm-
basedtrainingprogramandtheimprovementofcoffeefarmers'accesstorecommendedinputs.
TheprogramworkedwithfarmersintheSembabuledistrictfromAugust2018toendofOctober
2020,deliveringatotalof20trainingsessions.Farmershavebeentrainedon14topicsdesigned
toincreaseyieldsandimprovecoffeequalitywhichinturnwillincreasefarmerincomeandlead
to improved socio-economic outcomes for their families. There was some disruption to the
trainingcausedbyCOVID-19,withgrouptrainingstoppedfromthemiddleofMarch,andoneto
onehouseholdon-farmtrainingdeliveredtotheendoftheprogram.Giventhaton-farmtraining
tooktwotothreemonthstoreachallhouseholds,despiteashortextensiontotheprogram,two
plannedreviewmoduleswerenotdelivered.A total of 8,262 households registered in this
cohortandattendedatleastonetraining.Ofthese,6,916farmersfrom6,161households(75%
ofregisteredhouseholds)canbeconsideredas“trained”havingattendedatleastseven(50%)of
the14topics,and39%oftrainedfarmersarewomen.Thetargetforthe2018Cohortis6,000
householdstrained.
Farmerswere assessed on ten agronomy best practices: record keeping, weeding, coffeenutrition,safeuseofpesticides,integratedpestanddiseasemanagement(IPDM),erosioncontrol,
shademanagement, rejuvenation, pruning, andmulching. Adoption of these best practices is
based on rules developed by TechnoServe based on their experience and expertise in coffee
farming.
Figure1.PercentageofHouseholdsAdoptingeachBestPractice
EXECUTIVESUMMARY
AGRONOMYBESTPRACTICEADOPTIONSUMMARY
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AsshowninFigure1,baselineadoptionoftheagronomybestpracticeswaslow.Nohouseholdswere adopting safe use of pesticides and a negligible share of householdswere adopting the
nutritionandrecordkeepingbestpracticesatbaseline.
Theresultsoftheendlinesurveyshowanincreaseinadoptionofbestpracticeswitheightoutofthetenbestpracticeshavingastatisticallysignificantincrease.Mulchingwastheonlybestpracticethatshowedadecreasedadoptionratefrom10%offarmersmulchingduringthe
baselinetoonly4%duringtheendline,andsafeuseofpesticidesremainedat0%.Overall,the
shareofhouseholdsthatadoptedhalf(five)ormorebestpracticesincreasedfrom6%atbaseline
to33%atendline.Inaddition,70%ofhouseholdssawatleastonenewbestpracticeadopted,
andalmosthalf(48%)sawatleasttwonewbestpracticesadopted,sincebaseline.
Thekeydriversofyieldimprovementareexpectedtobepruning,rejuvenation,weedingandpestanddiseasemanagement.Althoughsoilhealthandnutritionareimportant,thesoilsinSembabulearefertileandhighinorganicmatter,unlikelytobelimitingyieldformostfarms.
Asoilandleafsurveyconductedbytheprogramshowedthatsoilswereabletosustainyieldsof
3kilogramsofcherrypertreewithouttheadditionoffertilizer.
Householdmembers.Householdshavesixmembersonaverage,fourofwhicharechildren(0to18years).Overall,thelevelofeducationismoderate,with84%ofthewomenand90%ofthe
menhavingreceivedsomelevelofformaleducation.Aquarter(25%)ofmalefarmerseitherhave
hademploymentinthepastorarecurrentlyemployedoutsideoftheircoffeefarmscomparedto
just16%ofthewomen.
Land Ownership. At endline, farmers own a self-reported mean of 2.1 hectares of totalagriculturalland,0.9hectaresofwhichisplantedwithcoffee,withanaverageof992coffeetrees.
HouseQuality.Thebuildingqualityofthefarmers’housesintheSembabuledistrictisgood,withthemajorityofhouseshaving improvedroofs,walls,and floors.Over four-fifths (85%)of the
householdshaveaccesstoelectricity,eitherfromthemainlineorsolarpanels.
WASH. Access to water, sanitation, and hygiene has increased, but remains limited. 12% ofhouseholdshaveaccesstoanimprovedtoilet,upfromjust7%atbaseline.Only26%ofthehouses
haveanimprovedwatersource,animprovementfrom17%atbaseline.
Assets.Manyhouseholdshavetheirownmeansoftransport–68%ofhouseholdsownabicycle,39%ownamotorcycle, and4%owna car.Mosthouseholds (95%)have at least onemobile
phone. Most households have some livestock, with 70% of households owning at least one
chicken.
CoffeeIncome.Atendline,coffeehouseholdswerehighlydependentoncoffee,with60%ofthehouseholdsreportingthatmorethanhalfoftheirtotalhouseholdincomecomesfromcoffee.This
isan increase fromthebaseline,wheremajorityofhouseholds(64%)reportedcoffee income
representedbetween25-50%ofincome.
HOUSEHOLDCHARACTERISTICSSUMMARY
FINANCIALPROFILESUMMARY
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Savings.Mosthouseholds(86%)wereusingatleastonesavingsmethodatendline,comparedtoonly50%atbaseline.Thisincreasewasdrivenbyhouseholdsjoininginformalsavinggroups.
Shocks&Shortages.Amajorityofthehouseholdsatendline(70%)reportedtheyhavebeenaffectedbyatleastoneseriousfinancialshockinthepastyearandlessthanhalf(40%)reported
havingsufferedfromafoodshortageinthepastyear.Thisisanimprovementcomparedtothe
baseline,whenahighershareofhouseholdsreportedfinancialshocksandfoodshortages.
Poverty.UsingtheProgressoutofPoverty(PPI)andMulti-DimensionalPoverty(MPI)indices,householdswereassessedontheirpovertyprofilesatendline.Only17%ofthehouseholdswere
likelytofallbelowtheinternational$1.90/day2011PPPpovertylineusingthePPI,amuchlower
proportioncomparedtoruralhouseholdsinCentralUganda(22%).UsingtheMPI,two-thirds
(66%) of the households are considered multidimensionally poor, compared to 55% of the
householdsnation-wide.
Farmerperceptionsonyield,time,andincome.Coffeefarmersoverwhelminglyself-reportedincreasesincoffeeyields,timespentworkingoncoffee,andincomefromcoffee,sincejoiningthe
CoffeeFarmCollege inAugust2018.81%ofhouseholdsreportedexperiencingan increase in
yield sinceattending training, and40%acknowledged this increasewassubstantial.For time
spentworkingoncoffee,84%ofhouseholdsreportedspendingmoretimeoncoffee,with31%
statingthisincreasewashigh.Finally,57%ofhouseholdsreportedexperiencinganincreasein
income,with13%statingthisincreasewashigh.
Contactmodalities.Farmerswereaskedabouttheusefulnessofadditionalvisits,phonecalls,andSMSmessagesfromTechnoServefarmertrainers.Onascalefrom0to10,visitswereseenas
the most useful modality (mean score of 7.4), followed by phone calls (7.3), and then SMS
messages(6.8).
PERCEPTIONSSUMMARY
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InOctober2020,thetwo-yearCoffeeFarmCollege,whichbeganinAugust2018,endedinthe
SembabuledistrictoftheCentralregionofUganda.Throughoutthecourseofthisprogram,Coffee
FarmCollegefarmersweretrainedon14topicstosustainablyimprovetheircoffeeyieldsand
supporttheirhouseholds.
Thisreportanalyzesdatafromanendlinesurveyof581householdsconductedinOctoberand
Novemberof2020tomeasuretherateofadoptionofagronomyBestPractices(BPs)aftertwo
years of the program and collect information on household characteristics. The survey was
conductedbothatthefarmandthehouseholdlevel.
This report hasbeen createdwith a strong emphasis on learning about theprofiles of coffee
farmersintheSembabuledistrictofUganda.Weexploretherelationbetweenattendanceinthe
trainingprogramandbestpracticeadoption,aswellashouseholdcharacteristicswhichcouldbe
influencing participation and adoption. We also explore intra-household gender relations
includingdecision-makingandlabourroleswithinhouseholds.Theseinsightswillhelpinform
thetrainingcontentandtheongoingimplementationoftheFarmCollegeinothercohorts.
Figure2.Mapofsurveyedhouseholds,colouredbyparish(Courtesy:OpenStreetMapcontributors&Tableau)
INTRODUCTION
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LateriteLtd., adata, research, andadvisory firm, led thedevelopmentof the researchdesign,
supportedsurveydevelopmentandimplementation,andconductedtheanalysisforthisstudy.
AteamofeightenumeratorsweremanagedbyTechnoServetoconductthesurveyusingtablets.
DesignandSampleSelection
Overalldesign.Thisisatwotime-periodstudy(baselineandendline)trackingatotalof600households before and after the start of the Coffee Farm College trainings delivered by
TechnoServeinUganda’sSembabuleDistrict.Allhouseholdsincludedinthesamplearefarmers
that signed-up during sensitization to participate in the program. This study does not use a
counterfactual.
Samplingstrategy.Thedesignforthisstudyisbasedonaone-stageclusteredrandomsamplingmethod,withstratificationattheparishlevel:
• Stratification:thesamplewasstratifiedover15parishesacrossthreesub-countiesinthe
SembabuledistrictofUganda.
• Clustering:withineachparish,40householdswererandomlyselectedfromFarmCollege
sign-uplistscreatedduringtraininggroupformation.
Variablesof interest.Thisstudyfocusesonthreesetsofvariables:(i) farmerandhouseholdcharacteristics, including data on demographics, diet, assets, and labour; (ii) coffee-related
characteristics, including farm-based observations of agronomy best practices; and (iii)
participation levels in theprogram.Households showedvaryingdegreesof attendance in the
trainingsessionsconductedoverthetwoyears.
Hypotheses.Themainhypothesisunderlyingtheresearchdesignisthathighattendancefarmers(i.e. the farmers thatattendhalformoreof the training topicsessions)willbemore likely to
experienceanincreaseintheadoptionofagronomybestpracticesbytheendoftheCoffeeFarm
College. In addition, our prior experience is that households with better socio-economic
indicatorsatbaselinewillbemorelikelytoattendthetrainingsessionsandthusmorelikelyto
adopt agronomy practices. Consequently, we will seek to measure the relative best practice
adoption amongst the different attendance groups and also examine socio-economic
characteristics of these farmers to understand some of the determinants of adoption. It is
importanttonotethatassociationsbetweenattendanceandadoptionofagronomybestpractices
willnotconstituteevidenceofimpact;rather,suchassociationsareexpectedsymptomsthatwe
would observe in the casewhere the program did have an effect on adoption of coffee best
practices.
BestPracticeBaselineandEndlineSurveys
SurveyCompletion.HouseholdswerevisitedinSeptemberandOctober2018forthebaselinesurvey,and inOctoberandNovember2020 for theendlinesurvey. Inbothsurveys,datawas
collected on demographics, diet, assets, and labour. In addition, farm-based agronomy best
practiceswereobserved.Theoverallrateofsurveycompletionatbaselinewas100%with600
households interviewed. The overall rate of survey completion at endlinewas 97%,with 19
householdseitherrefusingtobesurveyed,orunabletobesurveyed.Thedatawasweightedusing
inverse probability weights. These weights were determined by taking the inverse of the
probabilityofsamplingeachhouseholdsigned-upwithinaparish.
RESEARCHDESIGN
HHDESIGN
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MatchingtoAttendance.HouseholdsthatparticipatedinthebaselinesurveyandattendedtheCoffee Farm College are identified via a baseline farmer tracking survey and via in-house
matching.Intotal,464(77%)ofthebaselinehouseholdsinthesamplewerematchedbeforethe
startoftheendlinesurvey.Duringtheendlinedatacollection,anadditional38householdswere
matchedtotheirattendancerecords,foratotalof502(86%)matchedhouseholds.Households
thatarenotmatchedareconsideredasnotattendingCoffeeFarmCollege.
Survey Sections. The surveys included two main sections. The first section covered thedemographic and socio-economic status of each household. With regard to demographics,
farmerswereaskedabouttheirmaritalstatus,age,education,employmentstatus,andhousehold
size.Therespondentswerealsoaskedtoprovidearecountofeachchildlivinginthehousehold,
theirage,andeducationstatus.Intermsofsocio-economiccharacteristics,farmerswereasked
aboutlandandassetownership,incomesources,nutritionaldiet,andfinancialshocks.Therewas
alsoastrongemphasisoncoffeetreeownershipandproduction;farmerswereaskedaboutthe
numberof coffee treesownedand themethodsandquantitiesof coffee soldduring themost
recentcoffeeharvestseason.
Thesecondsection focusedon theagriculturalpractices thatwere taughtduringCoffeeFarm
College. First, farmers were asked to show records on coffee sold and costs incurred in the
productionofcoffee.Farmerswerethenaskedaseriesofquestionsandobservationsregarding
pesticides, including products used on the coffee farm and howpesticidesweremanaged, to
determinewhether the farmerswere using these products safely. Finally, the data collectors
requestedwhethertheycouldvisitfarmers’maincoffeefieldtodeterminetheimplementation
ratesofthegoodagriculturalpracticesattheendoftheCoffeeFarmCollege.Thisappraisement
wasprimarilybasedondirectobservationofthecoffeefieldbythedatacollectors.
Additional Questions at Endline. In the endline survey, additional questions around intra-household decision-making and gender relations were added, as well as questions around
householdperceptionsoftheTechnoServeCoffeeFarmCollegeanditsimpactoncoffeeyields,
timespentoncoffeeproduction,andincomeearnedfromcoffee.
10BestPractices.Overall farmerswereassessedon their1) recordkeeping,2)weeding,3)coffeenutrition,4)integratedpestanddiseasemanagement(IPDM),5)safeuseofpesticides,6)
erosion control, 7) shade management, 8) rejuvenation, 9) pruning, and 10) mulching best
practices.
BestPracticeRules.Eachbestpracticewasassessedusingspecificrulesbasedonagronomicbestpracticesforcoffeefarming.Coffeehouseholdsmeetingtheseruleswereconsideredtohave
adoptedthebestpractice. In thisendlinereport,differentruleswereusedthanatbaseline in
ordertobeconsistentwithotherTNSreports.Assuch,baselineresultsreportedinthisendline
reportdiffertothoseinthebaselinereport,astheyhavebeenrecalculatedusingdifferentrules.
Appendix5documentsthesechanges.
Endline Sample. The analysis of best practices and household characteristics has beenstructuredaroundtheentireendlinesampleof581coffee-farminghouseholds.
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Thereportcontinueswithasummaryofthemainhouseholdcharacteristicsandaprofileofthe
average Sembabule coffee farming household participating in the Coffee Farm College. This
profileisfollowedbyadetaileddescriptionoftheagriculturalpracticeendlinesurveyresultsand
adetaileddescriptionoftheselectedhouseholdcharacteristics.
Picture1.Coffeetreeloadedwithcoffee,SembabuleDistrict
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HOUSEHOLDDEMOGRAPHICS
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Farmerswereassessedon10agronomybestpractices (BP): rejuvenation,pruning,mulching,
coffeenutrition,intercropping,weeding,shademanagement,erosioncontrol,integratedpestand
diseasemanagement(IDPM),safeuseofpesticides,andrecordkeeping.
Table1.BestPracticeAdoptionRatesatBaselineandEndlineIncludesallsurveyedhouseholdsatendline,bothattendingandnon-attending Baseline Endline 2018 2020
No. of Households 581 581 Best Practices % Adoption Rate % Adoption Rate Shade Management*** 51% 67% Weeding*** 40% 64% IPDM*** 40% 61% Erosion Control*** 38% 57% Rejuvenation*** 29% 55% Pruning*** 16% 46% Coffee Nutrition*** 3% 17% Record Keeping*** 2% 4% Mulching*** 10% 4% Safe Use of Pesticides 0% 0% Average # of best practices adopted *** (out of 10) 2 BPs 4 BPs
Households adopting 5 or more best practices ***
6% 33%
Households adopting 2 or more additional best practices at endline compared to baseline
N/A 48%
Notesforinterpretingthetableofresultspresentedabove:
§ Thestars(*) indicatethesignificancelevelofbestpracticeadoptiondifferencesbetweenbaselineandendline,usingalogitregressionwithsamplingprobabilityweighing,clusteredattheparishlevel.
§ ***Significantatthe1%level,**significantatthe5%level,and*significantatthe10%level.§ SafeUseofPesticidesisdefinedforasamplesizeof421householdsatbaselineand419householdsat
endline,asallnon-usersofpesticideareconsideredas“NotApplicable”.§ Thepercentagesareweightedusingsamplingprobabilityweights.
Adoptionofbestpracticesvariedwidelyatbothbaselineandendline,asshowninTable1.Theendline survey results show a statistically significant increase in the average number of best
practicesadopted,from2atbaselineto4atendline,and48%ofhouseholdsadoptedtwoormore
additionalbestpracticeswhencompared tobaseline.Allbestpractices (excludingsafeuseof
pesticides) reported a statistically significant change in adoption rate, eight practices in an
increasingdirectionandonepractice inadecreasingdirection (mulching).Thepercentageof
householdsadoptingatleasthalf(5)ofthebestpracticesincreasedfrom6%atbaselineto34%
atendline.
Forthepracticeswherefarmersscoredrelativelywell:
AGRONOMYBESTPRACTICES
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ShadeManagementiscommoninmixedcoffeefarmingsystems,suchasthoseinUganda,withhigh numbers of fruit trees, such as bananas in the coffee fields, resulting in relatively high
adoption of the shademanagement best practice (67%at endline). Almost half (48%) of the
householdshadgoodshadelevelsatendline(>20%shade)and40%ofhouseholdshadplanted
shadetreesinthepastthreeyears,whichwillprovideshadeintime.
Weeding canhaveadramatic impactoncoffeeyield.CoffeeFarmCollege taught farmers theimportance of weeding under the canopy by hand-pulling, using a panga, or mulching. The
trainingalsoexplainedwhyweedingbydiggingunderthecanopyisbadforcoffee.Adoptionof
theweedingbestpracticeincreasedfrom40%to64%frombaselinetoendline.Thiswasledby
asignificant increase in thepracticeofpullingweedsbyhandaswellasbyadecrease in the
practiceofweedingbydigging.
IPDMadoptionincreasedfrom40%adoptionatbaselineto61%atendline.CoffeeFarmCollegetaughthouseholdshowtouseculturalmethods,suchascrophygiene,traps,goodnutrition,etc.
toreducetheincidenceofpestsanddiseases,ratherthanreactivelymanagingthepestordisease
once the tree has been infected. At endline farmers reported knowing more methods for
preventingbothtwigborersandcoffeewiltdisease(CWD).
Figure3.PercentageofhouseholdsadoptingeachBPatBaselineandEndline
TherearenumerousBestPracticeswherefarmerscontinuetohavelowadoption:
SafeUseofPesticidescontinuestobeaconcern,withnohouseholdspassingthebestpractice,despite72%ofthefarmersusingatleastonetypeofpesticideinthepast12months.Almostall
households(99%)failedfornotusingtheminimumappropriatepersonalprotectiveequipment
(mask,goggles,andgloves).
CoffeeNutritionpracticescontinuetobepoor,with50%offarmsnotusinganyfertilizer,and17%usingthewrongfertilizers,suchasUreaandCANinsteadofNPK(25:05:05or22:06:12),
DAP,compost,ormanureandzincfoliarfeeds.
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Mulchingwas theonlybestpractice that reportedsignificantdecrease inoverall adoptionatendline (4%) compared to baseline (10%). While the use of mulch increased from 16% of
households applyingmulch to19%at endline, thebest practice formulching requires a2cm
minimumthickness,whichthehouseholdsdidnotmeet.
Figure4showsthatonly6%ofthehouseholdswereadoptinghalf(five)ormoreofthe10BPsatbaseline.Atendline,thisfigureincreasedto33%.Atendlinemosthouseholdswereadopting
threetofivebestpractices.
Figure4.DistributionofnumberofBPsadoptedatBaselineandEndline
Figure5showsthat70%ofhouseholdssawanimprovementofatleastonenewbestpracticeadoptedsincebaseline,andalmosthalf(48%)sawanimprovementoftwoormorebestpractices.
Figure5.ChangeinnumberofBPsadoptedcomparedtoBaseline
Understanding the overall adoption rate of best practices of coffee-farming households at
baselineandendlineiscriticaltoobservetheeffectoftheprogram,butitisequallyinteresting
from a programmatic perspective to investigate the correlations between attendance to the
TechnoServeCoffeeFarmCollegeandbestpracticeadoption.
10%
21%
27%
23%
13%
5%
1% 0%1%
5%
15%
20%
25%22%
9%
2%
0 1 2 3 4 5 6 7
Perc
enta
ge o
f hou
seho
lds
Number of BPs Adopted
Distribution of Number of BPs Adopted: Baseline and EndlineAll Households (n = 581)
Baseline(2018)
Endline(2020)
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Thissub-sectionanalyzesbestpracticeadoptionatendlineforthe502householdsthatcouldbe
matchedwith attendance records to themonthlyCoffee FarmCollege trainings.1 It compareshouseholdswhohaveattendedmorethanhalfofthetrainingtopics(7outof13)2,the“TrainedHouseholds”, to households who attended less than seven topics (1 to 6 topics) the LowAttendanceHouseholds.
Foracomparisonofthecharacteristicsoftrainedandlowattendancehouseholds,pleaserefertoAppendix1.Foracomparisonofbestpracticeadoptionbytrainingoneachspecifictopic,pleaserefertoAppendix2.Foradoptionratesfornon-attendinghouseholds,pleaserefertoAppendix3.Fortheparisheswithhighestadoptionrates,pleaserefertoAppendix4.Table2.LowAttendancevs.TrainedHouseholds:BestPracticeAdoptionRatesbyTrainingAttendanceLevelsatEndline Low Attendance
Households Trained
Households Overall Average Overall Average No. of Households 63 443 Shade 60% 66% Weeding 58% 65% IPDM 58% 64% Erosion Control* 72% 57% Rejuvenation 53% 54% Pruning 50% 46% Coffee Nutrition 16% 18% Record Keeping 4% 5% Mulching 5% 4% Safe Use of Pesticides 0% 0% Average # of best practices adopted (out of 10) 4 BPs 4 BPs
Households adopting more than half (5) of the best practices
26% 35%
Notesforinterpretingthetableofresultspresentedabove:
§ Thesignificancelevelofbestpracticeadoptiondifferencesbetweenbaselineandendlinewasestimatedusingalogitregressionwithsamplingprobabilityweighing,clusteredattheparishlevel.
§ SafeUseofPesticides is defined fora sample sizeof419households, asall non-usersofpesticideareconsideredas“NotApplicable”.
§ Thepercentagesareweightedusingsamplingprobabilityweights.
Ofthehouseholdsthatcouldbematchedtoattendance,88%,(443outof506)hadattendedat
leastseventopicsoftheCoffeeFarmCollege,andwithinthese443households,75%attended
11–13topics–indicatingahighattendancerate.Ofthe63householdsinthe“LowAttendance”group,60%attended4orfewertopics.Householdsinthe“Trained”grouphavehigheradoptionratesin6ofthe10BPsandloweradoptionratesin4BPs.However,onlyoneofthesedifferences
wasfoundtobestatisticallysignificant-erosioncontrol,whichislowerfortrainedfarmers.Other
thanthis,householdsattendingmorethan7trainingtopicsisnotassociatedwithgreaterbest
1Thebaselinesamplewasrandomlydrawnfromthosethatsigned-upaspotentialprogramparticipants,ratherthanfromattendancesheets.Farmerswerethenmatchedtotheirattendancerecordsanditisassumedthatifnotmatchedtotheattendancerecordsthatthehouseholddidnotattendtraining.2Atthetimeofwriting,attendancedataisavailableuntilAugust2020anddoesnotincludethelasttrainingonsustainablefarming.
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practiceadoptiononanyoftheother9bestpracticeswhencomparedtohouseholdsattending
fewer than7 training topics.Whencompared tobaseline,however,householdswhoattended
trainingshaveimprovedbestpracticeadoption.
Rejuvenationadoption increasedsignificantly from29%at
baselineto55%atendline–thesecondmostimprovedbest
practice after pruning. As seen in Figure 6 the maindeterminantofthisincreaseinadoptionwasthereductionin
thenumberofstemsfrom5ormore,downto3or4main
stems.Atbaseline,47%ofhouseholdsaveraged5ormore
mainstems.Atendline,thisfigurewasjust23%,indicatinga
significantdecrease.
FarmersinUgandatypicallyrejuvenatetheircoffee,butnot
systematically.Theywillallownewsuckerstogrowatany
timeandoftenhaveupto10mainstems,allofdifferentages,
someolderthaneightyears.TheCoffeeFarmCollegetaught
farmersabouttheimportanceofrejuvenatinginasystematic
way,maintaining youngmain stems (less than eight years
old) and keeping nomore than fourmain stems, although
twoorthreeareideal.
Whenaskedwhyfarmersdecidedtorejuvenatetheircoffee
farm, 70% mentioned that learning and practicing this
activity in the training session led to their decision to
rejuvenate.25%mentionedthatthetrainervisitingtheirfarmwaswhatledtotheirdecision,and
28%mentionedseeingtheimpactinthedemonstrationplotasthereasonforrejuvenating.
Figure6.NumberofMainStemsatBaselineandEndlineMaximumoffourmainstemsrecommended
REJUVENATION
Picture2.Rejuvenatedcoffeetree
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Pruningwasthemostimprovedbestpracticewithanincreasefrom16%atbaselineto46%at
endline. This increase was due to an increase in the number of pruning methods used, as
householdsaveragedlessthan2methodsatbaseline,andmorethan3methodsatendline.
TheCoffeeFarmCollegetaughtfoursimplepruning
methods: remove the dead branches, the branches
touchingtheground,theunwantedsuckers,andthe
cross-overbranchesinordertoopenthetreecentres.
Pruningopensupthetreetolightandaircirculation,
bothprerequisitesforgoodfloweringandlowdisease
and pest incidence. Adoption of the pruning best
practice required the trees to be pruned using a
minimumofthreeofthefourmethodsthattheCoffee
FarmCollegetaught.
AsshowninFigure6,therewasincreaseintheusageof three of the four pruning methods between
baseline and endline. The opening tree centres
methodincreasedfrom21%adoptionatbaselineto
71%atendline.Twoothermethodsimprovedbyat
least18percentagepoints,andonemethod(removal
of unwanted suckers) decreased by 10 percentage
points.
Figure7.PruningMethodsUsed–Baselinev.Endline
21%
51% 50%
29%
71%
41%
68%55%
Centres opened Unwanted suckers removed Dead branches removed Branches touching the groundremoved
Perc
enta
ge o
f hou
seho
lds
Pruning Methods
Pruning Methods Used: Baseline and EndlineAll Households (581)Baseline
(2018)Endline(2020)
PRUNING
Picture3.Apartiallyprunedcoffeetree
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IPDMadoptionincreasedfrom40%adoptionatbaselineto61%atendline.Thisimprovement
wasdrivenbyanincreaseintwigborerandcoffeewiltdisease(CWD)preventionmethods.At
baseline,farmersknew1.7methodsonaverageforpreventingtwigborers,and0.5methodson
averageforpreventingCWD.Atendline,theseincreasedto1.9methodsfortwigborerprevention
and0.7methodsforCWDprevention–amodestincrease.
Theuseofpesticides– insecticides, fungicides,andherbicides– ismoderatelyhighinUganda
(72%).Manyfarmersaresimplyunawareofalternativepestanddiseasecontrolmethods.The
CoffeeFarmCollegetaughthouseholdshowtouseculturalmethods,suchascrophygiene,traps,
goodnutrition,etc.toreducetheincidenceofpestsanddiseases,ratherthanreactivelymanaging
thepestordiseaseoncethetreehasbeeninfected.
As IPDMmethodscannotallbeeasilyobserved, thesurveyused twoknowledgequestions to
assesshouseholdknowledgeonmanagingacommonpest,TwigBorerandacommondisease,
CoffeeWilt.
Figure8andFigure9showthechangeinknowledgeofthevariousmanagementmethodsforCWDandTwigBorer infestations.After training, the percentage of farmers not knowing any
methodsdecreased,andfewerfarmersreportedincorrectmethods.Therewasalsoanincrease
inknowledgearoundthemostcrucialpractices,theuprooting,removal,andburningofinfested
twigsandtrees,whichmorethantwo-thirdsofhouseholdscorrectlyidentifiedasamethodat
endlineforbothCWDandTwigBorers.
Figure8.CoffeeWiltDiseaseManagementMethodsKnown
INTEGRATEDPESTANDDISEASEMANAGEMENT(IPDM)
19
Figure9.CoffeeTwigBorerManagementMethodsKnown
DuetothehighuseofpesticidesinUganda(72%reportedusingpesticidesatendline),safeuse
of pesticides is an important best practice. Unfortunately, as was the case at baseline, no
householdspassedthisbestpractice.Thisfailureisprimarilyduetooneofthefiveelementsof
safepesticideuse–theuseofpersonalprotectiveequipment(PPE)–specificallymasks,goggles,
andgloves.Figure10belowdisplaysthesefiveelementsandshowswherefarmersinSembabuledistricthaveimprovedandwheretheyarestillfallingshort. Figure10.ElementsofSafePesticideUse–Baselinevs.EndlineAllfiveelementsrequiredtobeconsideredsafe.
Safe pesticide usage requires adoption of awide array of elements. The Coffee FarmCollege
taughtfarmersaboutthehazardsofusingpesticides:howtoreadpesticidelabels,whichPPEto
use, the safety procedures for purchasing pesticides, transportation, storage, and disposal of
pesticidecontainers.
10%2%
79%70%
12%1% 1% 0%
7%1%
87%80%
10%4% 1% 0%
No methodsknown
Incorrectmethods
mentioned
Removeinfested twigs
Burn infestedtwigs
Removeunwantedsuckers
Spraypesticidescontaining
imidachloprid
Spray otherpesticides
Reduceshade
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Twig Borer Management Methods: Baseline and EndlineAll Households (n = 581)
Baseline(2018)
Endline(2020)
SAFEUSEOFPESTICIDES
20
Whenusingpesticides,farmersshouldwearPPEtostopanypossiblerouteofentryintothebody
bywearingamask,goggles,gloves,spraysuit,andboots.Glovesareespeciallyimportantashands
canbeexposedtotheundilutedproductwhenmixingpesticides.Farmersareconsideredtobe
usingpesticidessafelywhenthey:i)havebeentrainedonhowtousepesticidessafely,ii)donot
storepesticidesinsidetheirhomesandinalockedstoreoutsideoftheirhome,iii)weargoggles,
amask,andglovesataminimum, iv)discardpesticidecontainersbyburningthem,returning
them to a contractor, or returned to the source, andv)donotusebannedpesticides suchas
Parathion,Carbofuran,orDieldrin.
Despite significant improvements in safe storage, disposal, and training received, 99% of
householdsfailedthePPErequirement.Figure11showsthisinmoredetailbyhighlightingthespecificitemsofPPEthatarelacking.Masks,gloves,andgogglesareallrequiredtopass,yetall
threeoftheseitemshaveverylowlevelsofadoptionatendline(17%,13%,4%respectively).
Furtherinvestigationisrequiredinconsultationwithconcernedstakeholderstounderstandif
pooradoptionofPPEisanissueofavailabilityorcost,similarlowadoptionratesareseenin
othercountriesinEastAfrica.
Figure11.PersonalProtectiveEquipmentUse–Baselinev.Endline
AdoptionofthecoffeenutritionBPincreasedfrom3%atbaselineto17%atendline.50%offarms
surveyedatendlinearenotusinganyfertilizer(includingcompostormanure),and17%areusing
thewrongfertilizers,suchasUreaandCANinsteadofNPK(25:05:05or22:06:12),DAP,compost,
ormanureandzincfoliarfeeds.
Generally, the soils in Uganda are some of the best in East Africa; the soil and leaf survey
conducted at baseline indicated which nutrients were lacking and provided parish-specific
recommendations,bothtocorrectthesoilsandfeedthecoffeetrees.Usingjustnutrientsavailable
inthesoilcoffeetreescanproduceupto3kilogramsofcherrypertree.Forfarmerswhowishto
improveyieldsfurtherandarenotaimingfortheorganicmarket,theuseofadditionalnutritional
products can increase yields. Coffee Farm College farmers were taught the importance of
balancedcoffeenutrition,makingandapplyingorganicproductssuchascompostandmanureas
wellasapplicationofcertainformulationsofNPK,atthecorrectrate(usingameasure)andin
35%
3% 4%
38%
1% 1% 1%
37%
17%13%
61%
4% 6% 3%
No protectionused
Mask Gloves Boots Goggles Spray suit Hat
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Protective Equipment Used: Baseline and EndlineHouseholds applying pesticides (n = 419)
Baseline(2018)
Endline(2020)
COFFEENUTRITION
21
the correct place, under the tree canopy where the
feeder roots grow, in order to prevent fertilizer
wastage.
Thecoffeenutritionbestpracticerequiresthattrees
shownosignsofnutrientdeficienciesandfarmsapply
atleastonerecommendednutritionalproductwhich
canincludecompostormanure(countedasone),NPK,
DAP,limeorzincfoliarfeed.
Atendlinehalfofhouseholds(48%)didnotuseany
nutritionalproducts,includingcompostormanureon
their farms, and 5% of farms showed nutritional
deficiencies. Only 27% of farms used compost or
manure,aslight increase fromthebaseline. 21%of
farms used a recommended formulation of NPK, up
from7%atbaseline.Acombined13%offarmsused
NPK17:17:17(6%notrecommended),CAN(7%not
recommended) or Urea (4% not recommended).
Figure12displayssomeoftheimprovementsmadesince the baseline and also highlights the need for
increaseduseofappropriatenutrition.
Intermsofapplication,42%offarmsusinggranularfertilizersdidnotuseameasuretoapply
fertilizer, and thus do not know the amount given to each tree. All households applied the
fertilizerinthecorrectplace,whichisunderthetree,anddidnotbroadcastitoverthefield.This
isanimprovementfromthebaseline,where2%ofthehouseholdsapplyinggranularfertilizers
broadcastedthefertilizeralloverthefield.
Figure12.FertilizerUsedinthePrevious12Months–Baselinevs.Endline
Forcomposting,therewasanincreaseincompostingseenonthefarmfrom7%ofhouseholds
makingcompost(eithercompostpit,heap,ormanureheap)atbaselineto14%atendline.This
assessmentonlyaccounts forcompostormanureheapsseenduringtheendlinevisit, theuse
during the rest of the year shown in Figure 12 is self-reported, indicating the difference innumbers.
Picture4.Nitrogendeficiencyshowingasyellowleaves
22
Compostorcompostedmanureisaslowrelease,naturalfertilizerreturningkeynutrientstothe
soiltohelpmaintainsoilqualityandfertility.Inaddition,compostbringsorganicmattertothe
soilwhichhelpstoretainmoistureandfeedsmicroandmacro-organisms.CoffeeFarmCollege
teachesfarmerstomakecompostheaps,whencomparedtomakingcompostinapit,heapsare:
easier to turn,donotgetwaterloggedandwillproducecompost faster.Figure13 shows thedistributionofthethreecompostmethodsforsurveyedfarmers,anddepictsthechangesfrom
baselinetoendline.
Figure13.TypeofCompostSeenonFarm–Baselinevs.Endline
Adoptionoftheweedingbestpracticeincreased
from40%to64%frombaselinetoendline.This
wasledbyasignificantincreaseinthepracticeof
pullingweedsbyhand(fromjust3%atbaseline
to59%atendline)aswellasbyadecreaseinthe
practice of weeding by digging, which can
damage the feeder roots. Figure 14 highlightssomeoftheseimprovements.
Weedscanhaveadramatic impactonyield, so
theareaunderthetreecanopy,whichisthemain
feederrootzone,shouldbekeptasweed-freeas
possible throughout the season. This can be
difficultduringtherains,giventhatweedgrowth
israpidintropicalclimates.CoffeeFarmCollege
taughtfarmerstheimportanceofweedingunder
the canopy by hand-pulling using a panga or
mulchingwithslashing,and intercroppingwith
beans as options for between the rows. Coffee
Farm College also explained why weeding by
diggingunderthecanopyisbadforthecoffee,as
it damages the feeder roots and can introduce
CoffeeWiltDisease.
7%
2% 2% 3%
14%
0%
6% 7%
Yes, HH is making compost Layered compost heap Pile of boma manure Compost pitOverall Type of Compost Seen
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Compost Seen by Type: Baseline and EndlineAll Households (n = 581)
Baseline(2018)
Endline(2020)
WEEDING
Picture5.Coffeetreeweededbydigging.
23
Adoptionofweedingrequiresthati)thefarmerpullweedsbyhand,orusesaslasherorpangato
weedunderthetreecanopy,ii)thefarmerweedsatleasttwiceperyear,andiii)therearenoor
limitedweedsunderthetreecanopylessthan30cmtall.
Wherepossible,observationsweremadetoassesstheweedingstatus,andotherquestionssuch
asfrequencyofweedingwereaskedofthefarmers.Atendline,16%ofhouseholdsfailedbecause
theywereexclusivelyweedingbydiggingunderthecanopy.Another16%ofhouseholdsfailed
becausemanyweedswereobservedbytheenumeratorunderthecanopyand8%ofhouseholds
failedbecauseweedshadreachedheightsofmorethan30cmunderthecanopy.
Figure14.WeedingMethodsUsed–Baselinevs.Endline
The mulching best practice decreased in
adoption rate from baseline to endline.
However, this decrease was despite the fact
the percentage of farms applying mulch
actually increased, from 16% at baseline to
19%atendline.AsFigure15 illustrates, thereason for the failure is attributed to the
thicknessofthemulchapplied,whichmustbe
morethan2cmtobeconsideredfullyadopted.
Only4%offarmsadheredtothisstandard.
Mulching has many benefits including the
suppression ofweeds, reduction ofmoisture
loss from the soil, reduction of soil
temperatures, and increase of soil organic
matter. Mulching is especially important if
shadelevelsarelow.CoffeeFarmCollegetaughtfarmersaboutthebenefitsofmulchingandhow
tomulch.Adoptionofmulchingrequiresthatthereisatleast2cmthickmulchapplied.
Whileoverall adoptionof thisbestpracticedecreased for this cohort, future trainings should
focusontheimportanceofmulchthicknesstoreapthebenefitsofmulching.
MULCHING
Picture6.Awellmulchedtree.
24
Figure15.MulchApplicationandThickness–Baselinevs.Endline
Adoptionofsoilerosioncontrolbestpracticeincreasedfrom
38%atbaselineto57%atendline.Ahouseholdisconsidered
fully adopted if they employ one or more erosion control
methodsonthefarm.Thisincreaseinadoptionistherefore
attributed to the increased use of certain methods,
specifically trenches and water traps (counted as one),
mulch, and stabilizing grasses. Figure 16 illustrates theimprovementsincebaselineonthesevariousmethods.
Soil erosion results in the loss of top-soil, leaving roots
exposed and resulting in a loss of soil fertility, ultimately
impacting yield. Coffee Farm College taught farmers the
importanceoferosioncontrol insoilmanagement,evenon
fields without slopes, where wind erosion can take place.
Farmers learned various techniques to reduce soil erosion
including planting stabilizing grasses, applyingmulch, and
terracingonsteepslopes.
Afterreceivingtraining,thenumberoffarmersnotusingany
form of erosion control decreased by 19%. The preferred
methodforfarmersinSembabuleDistrictweretrenchesand
watertraps,followedbymulch.
Figure16.ErosionControlMethodsSeen–Baselinevs.Endline
62%
25%16%
1% 1%
43% 45%
19%
4% 0%
No erosion control seen Trenches and water traps Mulch Stabilizing grasses TerracesPerc
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Erosion Control Methods Seen: Baseline and EndlineAll households (n = 581); multiple select option
Baseline(2018)
Endline(2020)
SOILEROSIONCONTROL
Picture7.Watertrap
25
Adoption of shade management best
practiceincreasedfrom51%atbaseline
to 67% at endline. At baseline, 23% of
householdshadashade levelof20%or
more,atendline,thisincreasedto48%of
households.
Shadeiscommoninmixedcoffeefarming
systems, such as those in Uganda, with
high numbers of fruit trees, such as
bananas in the coffee fields, resulting in
relativelyhighadoptionoftheshadebest
practice. Almost half (48%) of the
households had good shade levels at
endline (>20% shade) and 40% of
households had planted shade trees in
thepast threeyears,whichwill provide
shadeintime.
ShadeisimportantforRobustacoffee,whichevolvedinthetropicalforestsofUgandaandCongo.Ideally,shadelevelsshouldbebetween20-40%.Below20%,coffeetreeswillbesubjectedtohigh
temperaturesandhighlevelsofmoisturelossfromboththeleavesandthesoil.However,very
high levelsofshadecanresult inreduced floweringandthereforeyields.CoffeeFarmCollege
taughtfarmersabouttheimportanceofshademanagement,theidealshadetreevarieties,and
plantingtechniques.Adoptionofshademanagementrequiresthatmorethan20%ofthefarmis
coveredbyshadeorthatshadetreeshavebeenplantedinthelastthreeyears,eveniftheyare
notcurrentlyprovidingtherequiredshadelevels.
Figure17illustratesthemostcommonshadetreesinthecoffeefieldswerefruittrees:69%offarmshadbananas, significant increasefrom47%atbaseline,and22%of farmshadplanted
otherfruittreessuchasmangooravocado.Althoughtheselargefruittreesgivehighshadelevels,
and have other socio-economic benefits such as enhancing household diet and providing
additional income, the farm can only accommodate a limited number of them. Only 6% of
households had indigenous trees in the farm,while just 1%had planted exotic varieties like
grevillea,whicharegenerallyconsideredunsuitable.
Figure17.ShadeTreeTypes–Baselinevs.Endline
2%
47%
32%
13%1%
69%
22%
6%
Exotic trees(e.g., Grevillea)
Banana Other fruit trees(e.g., mango, avocado)
Indigenous trees(e.g., Albizia)
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Shade Tree Types: Baseline and EndlineAll households (n = 581)
Baseline(2018)
Endline(2020)
SHADEMANAGEMENT
Picture8.Bananaplantsinacoffeefarm
26
Figure18illustratestheshadelevelsfoundoncoffeefarmsinSembabuleDistrictatbaselineandendline. It shows there has been an increase in shade levels since baseline, with 49% of
householdshavingatleasta20%shadelevel,andfewerhouseholdshavingnoshade.
Figure18.ShadeLevel–Baselinevs.Endline
Adoptionoftherecordkeepingbestpractice
increasedslightlyfrom2%atbaselineto4%
atendline.TheCoffeeFarmCollegeprogram
provided a three-year pictorial record card
(as illustrated inPicture9) at the February
2019trainingandtrainedfarmersonhowto
keep financial records and calculate profit.
However,duringdatacollection,only5%of
thehouseholdspresentedarecordbookand
only4%hadwrittenrecordsonit.
Duringdatacollection,enumeratorsreported
that farmers were often times reluctant to
show their record cards as they had not
started using them. Additionally, some data
collectorsmightnothavewaitedlongenough
forfarmerstobringtheirrecordcardsduring
the interview. This, combinedwith the fact
that 68% of the households attended the
February2019training,ledLateriteandTechnoServetofollowuponhouseholdsthatattended
anyCoffeeFarmCollegetrainingtounderstandwhethertheyhadreceivedarecordbook.
Theteammanagedtoreach420of500householdstargetedbyphone,andofthese,62%stated
tohavereceivedarecordbookfromTechnoServe,bringingtherateofrecordbookownershipto
50%forallhouseholds.TechnoServewasnotabletofollowupinpersonwiththe163households
whostatedtheyhadkeptfarmrecordsintheirbooks.Thesehouseholdsarenotincludedinthebestpracticeadoptioncalculationinthisreport,whichmaythereforeunderestimatetheadoption
ofrecordkeeping.
Atendline67%ofhouseholdsknewhowtocalculatefarmprofitandloss,comparedtoonly32%
atbaseline.
RECORDKEEPING
Picture9.CoffeeFarmCollegerecordcardandfarmer'srecordbook.
27
Thefollowingpracticesareimportantagronomicpracticesforcoffeefarming;however,theydo
notapplytoallcoffeehouseholdssurveyed.Therefore,theyarenotconsideredkeybestpractices,
butwerearestillmonitoredduringtheendlinesurvey.
87% of households met the criteria for coffee
drying;however,atthetimeoftheendlinesurvey,
only 55 households (9%) were actively drying
coffee. Of these, the vast majority were drying
coffeecorrectlyontarpaulinoraplasticsheeton
theground.Eightofthesehouseholdsweredrying
the coffee onbare ground,which could result in
contamination from the soil and isn’t
recommended..
Proper coffee drying is crucial to produce
improvedqualitycoffeeandminimizetheriskof
contamination. As harvesting season had nearlyfinished when the survey was conducted,
households in Sembabule self-reported their
coffee-dryingpractices.Correctcoffeedryingwas
assessed based on whether (i) the farmer is
currentlydryingcoffeeonaplastictarpaulinoron
an elevated bed or (ii) the farmer is not drying
coffee,butplanstodosoinatarpaulinorontables.
Ofthe526householdsnotcurrentlydrying,88%
plantodryonatarpaulinorplastic,and3%plan
to dry on the bare ground. Coffee Farm College
promotedtheuseofplastictarpaulinsorraisedbedsfordryingcoffeetopreventcontamination
from drying the cherry on the bare ground. The training also stressed the importance of
harvesting red cherry, turningduringdrying, andusinggood storage techniques to avoid the
developmentofmouldorfurthercontamination.
Goodcoffeeseedlingsandcorrectplantingareessentialforahealthycoffeetreeandfuturehigh
production. The Ugandan Government’s Operation Wealth Creation (OWC) program, in
collaborationwiththeUgandaCoffeeDevelopmentAuthority(UCDA),hasprovidedseedlingsto
farmerssince2015.Duringthebaselinesurvey,41%ofcoffeehouseholdsreportedplantingnew
coffeeseedlings in thepast12months.Atendline,58%ofhouseholds reportedplantingnew
seedlings.
OTHERAGRONOMYPRACTICES
COFFEEDRYING
COFFEEPLANTING
COFFEEDRYING
Picture10.Coffeedryingonatarpaulin
28
AsillustratedinFigure19,therearenumerouselements to consider for proper coffee
planting: (i) the variety of coffee is elite or
clonalwithCoffeeWiltDiseaseresistance;(ii)
the new seedlings come from certified
nurseries (UCDA or Government); (iii) the
farmerappliedanapprovednutritionproduct;
(iv) seedlings look healthy; (v) the seedlings
wereplantedinrowsthreemetersapart;and
(vi) for seedlings taller than60cm, the stems
are bent to initiate sucker production. If
suckers are taller than 30cm, the best four
suckershavebeenselected.
While households improved on four of the
elements above, they regressed in two
elements.Inparticular,thecriteriaonsourcing
seedlings from certified nurseries saw the
sharpestdecreasefrom78%atbaselinetojust
49% at endline. At endline, farmers opted to
source seeds from non-certified sources,
including 16% who grew the seedling
themselves,and9%whousedseedlingsgrown
by neighbours. In addition, only 39% of
householdsappliedanapprovedfertilizertotheseedlings.Additionally,therewasasignificant
increaseintheuseofEliteorCWDresistantvarietiescomparedtobaseline,whichisapositive
step.
Figure19.ElementsofProperCoffeePlanting–Baselinevs.Endline
Picture11.Ayoungcoffeetree
29
Intercroppinghastwokeybenefits:diversificationofincomeandusageasacovercropduring
therainstoreducetheincidenceofsoilerosion.WiththewiderspacingassociatedwithRobusta
coffee,itispossibletointercropbetweentherowsofmaturecoffeetrees.
The intercropping is practiced correctly if farmers are intercropping their coffee trees with
legumes,suchasbeans,orfruittrees,suchasbananas.Farmersshouldnotusemaize,cassava,
creepers–suchaspumpkin,rootsandtubers,orgroundnuts–orothercropsonthecoffeefield,
whichareeithergreedycrops(maize)orwouldrequirethefieldtobedugforharvest.Thesurvey
observedallcropsusedandnotthemaincropsointerpretationofthefindingsisdifficult, for
exampleonemaizeplantinafieldofbeanswouldbeacceptable.
Figure20illustratesthecropsseenasanintercrop.Therewasanincreasedobservationofmaizeasanintercrop,seenat44%offarmsatendlinecomparedtojust11%atbaseline.Intercropping
usingsuitablecropslikebananaandlegumesalsoincreasedsignificantlyandtheuseofcassava
(another unsuitable crop) decreased between baseline and endline. For the small percentage
(4%)ofcoffeefarminghouseholdsinSembabulenotgrowinganyintercrops,thispracticewas
consideredas“notapplicable”.
Figure20.Inter-CroppingVarieties–Baselinevs.Endline
INTERCROPPING
30
The following section covers demographic, socio-economic, and financial information on the
entireendlinesampleof581households.
HouseholdComposition:Householdshave,onaverage,sixmembers,fourofwhicharechildren(0to18years).Bothfemaleandmalecoffeefarmersarelikelytobeintheirforties,withamean
ageof42 forwomenand48 formen.Of themale farmers,9%are less than30yearsof age,
whereas21%offemalefarmersarelessthan30andcanbeconsidered“youth”.
Figure21.DistributionofHouseholdSizeatEndline
Figure22.DistributionofNumberofChildrenatEndline
HOUSEHOLDCHARACTERISTICS
HOUSEHOLDCOMPOSITIONANDFARMERAGE
31
Figure23.MedianandMeanAgeDistributionbyGender
Overall,thelevelofeducationismoderate,with84%ofthewomenand90%ofthemenhaving
receivedsomelevelofformaleducation.Menareslightlybettereducated,as22%ofthemale
farmers have education above the primary level (either Secondary or above Secondary),
comparedtoonly19%forthewomen.
Figure24.LevelofEducationbyGender
Forchildrenaged6–14,99%ofbothboysandgirlswereenrolledinformaleducationatendline.
Thisisaslightincreasefromthebaselineforboys,where95%wereenrolled.Forchildrenaged
15–18,therehasbeenasignificantincreaseinschoolenrolmentsincethebaselineforbothboys
and girls. At baseline, just 76% of girls 15–18 were enrolled in school. At endline this rate
increasedto92%.Similarly,forboys,atbaselineenrolmentlevelsfor15–18yearoldsweremuch
lower(70%)comparedtoendline(83%).
EDUCATION
32
Figure25.ChildEducationbyGenderandAge
Aquarter(25%)ofthemalefarmerseitherhavehademploymentinthepastorarecurrently
employedoutsidetheircoffeefarmscomparedtojust16%ofthewomen.Thereisasignificant
increaseinmenwhoarecurrentlyemployedatendline(9%),comparedtobaseline(3%).
Figure26.EmploymentStatusbyGenderatEndline
Atendline,overhalf(59%)ofthefarmershadhiredpaidlabourtoworkonthecoffeefarminthe
past 12months. The average reportedwage for an eight-hourwork daywas 8,525Ugandan
Shillings,equivalentto$2.30USD.Thisisanincreasefrombaseline,wheretheaveragewagewas
reportedtobe7,887UgandanShillings,equivalentto$2.00USD.Thenationalminimumwagein
Ugandais130,000UgandanShillingspermonth,approximately5,909UgandanShillingsperday
;therefore,thewagesearnedonthecoffeefarmsareslightlyabovethemonthlyminimumwage.
Ofthe476householdswithschool-agedchildren(6-14yearsold),75%reportthattheirchildren
workinthecoffeefields.Forthese476households,4%ofhouseholdsreportedthatfarmwork
sometimesinterferedwithaccesstoeducationfortheirownchildren,especiallyduringharvest.
Lessthan1%(4farms)ofhouseholdsreportedhiringlabourbelow14yearsofage.
EMPLOYMENTSTATUS–OUTSIDETHECOFFEEFARM
PAIDLABORANDCHILDLABOR
33
Farmersownaself-reportedmeanof2.1hectaresoftotalagriculturalland,0.9hectaresofwhich
isplantedwithcoffee,withanaverageof992coffeetrees.Toaccountforoutliersduetoself-
reporting,the1stand99thpercentilesofthestatisticshavebeentrimmed.Themedianfortotallandis1.4hectares,with0.8hectaresofcoffeeland,and750coffeetrees.Two-thirds(66%)of
coffeetreeswereplantedafter2000,and68%ofhouseholdsstatedthattheyplannedtoplant
morecoffeeoverthenext12months.
Figure27.DistributionofTotalFarmSizeinHectares
Figure28.DistributionofNumberofCoffeeTrees
LANDOWNERSHIP
34
Figure29.DistributionofYearofPlanting
Production data was collected in kilograms of cherry, kiboko (sun dried cherry), and FAQ
(parchment)producedinthe2020harvestseason.Thisdataisself-reported,andcanbeseenas
aguidelineonly,givenlimitedrecordkeepingandthetendencytoroundyieldstothenearest100
kg.AsreportedinFigure30,anegligibleproportionofthefarmers(1%)reportednotsellinganycoffeein2020,whilethemajoritysoldcherry(64%).One-third(34%)offarmerssoldFAQ,while
27%soldkiboko.Additionally,2%ofhouseholdspre-soldtheircoffeepriortoharvest.Compared
tobaseline,thepercentageofhouseholdssellingFAQhasnearlydoubled,from18%atbaseline
to34%atendline.FAQfetcheshigherpricesthantheotherforms,sothisincreaseisapositive
finding.
Figure30.TypeofCoffeeSold
Atendline,themeanself-reportedyieldpertreewas2.0kgcherryequivalentwithamedianyieldof1.6kgcherryequivalentpertree.Thisisupfrombaseline,wherethemeanself-reportedyieldpertreewas1.3kgcherryequivalent,withamedianof0.9kgcherryequivalent.
Giventhemedianfarmhas750coffeetreesatendline,anestimatedfarmproductionwouldbe
about1,200kgofcherryequivalent.Soldaskiboko(600kg),thiswouldearnthehouseholdabout
$360USD.Conductingthesamecalculationusingmeansinsteadofmedians,householdswouldearnabout$595USD.
COFFEEPRODUCTION
35
Assumptionsforyieldpertreecalculations:
• 1kgofkiboko=2kgofcherry
• 1kgofFAQ=4kgofcherry
• 1kgofkiboko=$0.60USD
• 1stand99thpercentilesweretrimmedtoaccountformistakesinself-reporteddata
Householdsown,onaverage,8ofthe23surveyedassets.Thisisanincreasefromanaverageof
6assetsatbaseline.Thetopfivelargestimprovementssincebaselinehavecomefromaccessto
electricity(+17percentagepointsfrombaseline),ownershipofpropershoes(+14),ownership
oftelevision(+11),ownershipofatleastonepig(+9),andaccesstoimprovedwatersource(+7).
Twotransportationassets,–bicyclesandmotorcycles–decreasedsincethebaselineby5and1
percentagepointsrespectively.However,thisispartiallyoffsetbyanincreasedownershipofcars
ortrucks(+2).
HouseQuality:Thebuildingqualityof the farmers’houses in theSembabuledistrict isgood.Almosteveryhousehold(99%)hasimprovedroofs(corrugatedironortinsheets),85%ofthe
houseshaveaccesstoelectricity,mostlyfromsolarpanels,whichisupfromjust68%atbaseline.
Morethanhalf(56%)ofthehouseshavecementsealedfloors.
WaterandSanitation:12%ofthefarmershaveaccesstoanimprovedtoilet3,upfromjust7%atbaseline.Only26%ofthehouseshaveanimprovedwatersource,4yetthisisanimprovementfromjust17%atbaseline.Childrenareresponsibleforcollectingwaterin66%ofhouseholdsand
the average time to complete the return journey to collectwaterwas 39minutes. For some
households,thistookaslongasthreehours.
Livestock:Mosthouseholdshavesomelivestock,with70%ofhouseholdsowningatleastonechicken,48%owningatleastonepig,19%owningatleastonecow,and35%owningatleastone
goatorsheep.
Communication:Ownershipof communicationdevices ishighamong farmers in Sembabule.Almost all households (95%) own at least onemobile phone,which ismost usually used for
calling(99%),mobilebanking(61%),sendingandreceivingmessages(51%).Mosthouseholds
(84%)alsoownradios,whileamuchlowerproportion(28%)ownatelevision.
Transport:Manycoffeehouseholdsowntheirownmeansoftransport,68%ofhouseholdsownabicycle,and39%ownamotorcycle,with4%owningacar.
3Improvedaccesstosanitationconsistsofventilatedimprovedpits,flushtoilets,orcompostingtoiletsthatarenotsharedwithotherhouseholds. 4Improvedwateraccessconsistsofhavingaccesstoaprotecteddugwellorspring,tubewell,watertank,orapublicorprivatetap.Ifthewatersourceisnotatthehouse,itshouldnotbemorethana30-minuteroundtrip.
ASSETOWNERSHIP
36
Figure31.HouseholdOwnershipofAssetsatEndline
37
TohelpTechnoServeimprovetheprogramandassessitsimpactonfarmhouseholds,questions
wereaskedaboutfarmerperceptionsoftheFarmCollege.
ContactModalities(Message,Call,Visit)Toassesstheusefulnessofthevariouswaysfarmersarecontactedandtrained,farmerswere
askedtoscoreeachmodality(messages,calls,visits)from0–10onusefulness,with10beingthe
mostusefuland0beingnotatalluseful.Figure32reportsthefindings,showingthatonaveragevisitswereseenasthemostusefulmodalitywithanaveragescoreof7.4,,followedbyphonecalls
(7.3),andthenmessages(6.8).Note thatallof thecallsconductedwereduringtheCOVID-19
lockdownperiod,whichmayimpactresponsesforperceivedusefulnessastheyweretheprimary
modalityusedinthatperiod.
Figure32.PerceivedUsefulnessofTNSContactModalities(Meanof0-10scale)
PerceptionsonYieldChangeFarmers at endlinewere asked to rate the change in coffee yield that they experienced since
joiningCoffeeFarmCollege.AsseeninFigure33,81%ofhouseholdsreportedexperiencinganincrease in yield since attending training, and 40% said this increasewas large. Only 8% of
households reported a decrease in yields since training, and 10% reported no change. Figure33.PerceptionofYieldChangesinceattendingTNStraining
PERCEPTIONS&IMPACT
38
PerceptionsonTimeSpentonCoffeeProductionDuringendline,farmerswereaskedtoratethechangeintimespentoncoffeeproductionsince
joiningCoffeeFarmCollege.AsseeninFigure34,84%ofhouseholdsreportedexperiencinganincreaseintimespent,with31%sayingthisincreasewashigh.Thisislikelyduetotheincreased
attentiontobestpracticeadoption,asmanywerenotadoptingbestpracticesatbaseline.Only
6%ofhouseholdsreportedadecreaseintimespentoncoffeesincethetraining.
Figure34.PerceptionofTimeSpentonCoffeesinceattendingTNStraining
PerceptionsonCoffeeIncomeFarmersatendlinewereaskedtoratethechangeinincomefromcoffeesincejoiningCoffeeFarm
College.AsseeninFigure35,57%ofhouseholdsreportedexperiencinganincreaseinincome,with 13% saying this increasewas high. 17% reported having lost income since the start of
training,and24%reportednochange.GiventheendlinewasconductedduringtheCOVID-19
pandemic,when incomeswere already low formany farmers, it is possible that the farmers
reportingalossofincomesincethetrainingsareareflectionofthepandemic,andnotnecessarily
theimpactoftheCoffeeFarmCollege.Nevertheless,itappearsthatthemajorityofparticipating
coffee farmers in Sembabule District perceive the program to have generated a positive
contributiontoincome,whichisaprimarygoaloftheCoffeeFarmCollege.
Figure35.PerceptionofIncomeChangefromCoffeesinceattendingTNStraining
39
In the endline survey, additional questions relating to intra-household decision-making and
gender relationswere added to help understand howwomen’s participation in the program
translates to intrahousehold relations (e.g., gender roles andpreferences,decision-makingon
incomeandsavings,decision-makingonfoodpurchases).
Threequestionsguidedtheresearch:
• Howarewomenabletotranslatetheirparticipationintheinterventionintotheirability
tonegotiateintrahouseholdrelationstomakedecisionsovertheuseofincome?
• Howcanweunderstandthedifferentrolesandpreferencesofmenandwomentoplan
interventionsthatmeettheobjectivesandaimsoftheprogram?
• Howarewereachingandmeetingtheneedsofdifferentwomenthroughtheprogram?
InordertounderstandhowwomencantranslateparticipationintheCoffeeFarmCollegeinto
theirabilitytonegotiateintrahouseholdrelations,questionsondecision-makingonincomeand
savingswereasked.
Figure36reportstheprimarydecision-makeronincomedecisionsforbothcoffeeincomeandnon-coffeeincome.Itshowsthatmakingdecisionsjointly(bothmanandwomanequally)isthe
most commonway households in Sembabule District make decisions on both coffee income
(29%)andnon-coffeeincome(33%).However,whenhouseholdsdonotmakedecisionsjointly,
both coffee income and non-coffee income decisions are primarily made by men. Men are
involvedatleastequallyin80%ofcoffeeincomedecisions,comparedtojust48%ofwomen.For
non-coffeeincome,womenplayamoreprimaryroleastheyareinvolvedatleastequallyin57%
ofhouseholds.However,menarestillthemajoritydecision-makersonnon-coffeeincome,with
77%ofhouseholdsincludingmenatleastequallyinthesedecisions.
Itisimportanttonotethat5%ofhouseholdsatendlinearesingle-adultfemalehouseholds,and
13% of households are single-adult male households, which are indicated below. In these
households,decisionsaremadebyonlywomenoronlymen,asitistheonlyoption.
Figure36.Decision-makeronCoffeeandNon-CoffeeIncome
THEMEOFINTEREST:GENDER
FINANCIALDECISIONS(INCOME&SAVINGS)
40
Figure 37 reports the primary decision-maker on decisions for both major and minorexpenditures. Major expenditures include expenses including: 1) house construction and
renovation;2)payingschoolfees;3)buyingabicycleormotorbike;4)goingonareligioustrip;
or5)purchasinglargeappliancesforthehouse.Minorexpendituresincludeexpensessuchas:1)
foodpurchasesfordailyconsumption;2)rural-urbantransport;3)buyinghouseholditemslike
soapandcosmetics,charcoal,andfirewood;or4)kerosenepurchases.
Men tend to make sole decisions regarding major expenditures of the household. The most
commonwayforcoffeehouseholdstomakeminorexpendituredecisionsisjointly(bothmanand
womanequally) (23%). Formajor expenditures,men are involved at least equally in80%of
households,comparedtojust45%ofwomen.Forminorexpenditures,however,womenplaya
leadingrole,aswomenare involved in thesedecisionsat leastequally in65%ofhouseholds,
comparedtojust57%formen.
Again,itisimportanttonotethat5%ofhouseholdsatendlinearesingle-adultfemalehouseholds,
and13%ofhouseholdsaresingle-adultmalehouseholds,whichare indicatedbelow. Inthese
households,decisionsaremadebyonlywomenoronlymen,asitistheonlyoption.
Figure37.Decision-makeronMajorandMinorExpenditures
Figure38 reports theprimarydecision-makeronsavingsdecisions,andshowsthat themostcommondecisionmakersonsavingsaremenbythemselves(33%).Jointdecision-making(both
manandwomanequally)wasalsocommon(28%).Overall,menareinvolvedinsavingsdecisions
atleastequallyin74%ofhouseholds,comparedtojust54%forwomen.
Again,itisimportanttonotethat5%ofhouseholdsatendlinearesingle-adultfemalehouseholds,
and13%ofhouseholdsaresingle-adultmalehouseholds.Inthesehouseholds,decisionswould
bemadebyonlywomenoronlymen,asitistheonlyoption.
41
Figure38.Decision-makeronSavings
Enumeratorswerethenaskedtoobservewhoansweredthequestiontogaugeintra-household
genderrelations.Figure39disaggregatestheinformationbasedonwhoansweredthequestionandshowsastrongbiastowardsthegenderofthepersonresponsiblefordecision-making.For
example, in the 116 households where women are the sole decision-makers on savings, the
woman answered the question in 92%of the cases, suggesting thatwomen are speaking for
themselveswhenitrelatestosomethingtheyareresponsiblefor.Asimilarpatternwasobserved
with male participants, where the vast majority of men answered when they were solely
responsible fordecisionsonsavings.For jointdecisionhouseholds(eitherequallyor inpart),
bothmenandwomenparticipatedinansweringthequestion,butmenmoresothanwomen.
Figure39.Decision-makeronSavings,bywhoansweredthequestion
42
Inordertofurtherunderstandtherolesofmenandwomeninthehousehold,questionsregarding
foodpurchasedecisionsandcropproductionparticipationwerealsoasked.Figure40reportstheprimarydecision-makerforbothfoodpurchaseandcropproductionparticipationdecisions.
Forfoodpurchasedecisions,itismostcommonformentomakethesedecisionsbythemselves(30%).Menareinvolvedatleastequallyinfoodpurchasedecision-makingin69%ofhouseholds,
comparedtojust48%forwomen.
Forcropproductionparticipationdecisions,itismostcommonforhouseholdstomakethesedecisionsjointlyandequally(39%).Womenareinvolvedinthesedecisionsatleastequallyin
79%ofhouseholdsatendline,comparedto60%formen.
Figure40.Decision-makeronFoodPurchaseandCropProductionParticipation
Again,afteraskingthesequestionsonfoodproductiondecisions,theenumeratorswereaskedto
observe who answered the questions to gauge intra-household gender relations. Figure 41disaggregatestheinformationbasedonwhoansweredthequestionandagainshowsastrong
biastowardsthegenderofthepersonresponsiblefordecision-making.Forexample,inthe177
householdswheremenaretheonlydecision-makersonfoodpurchases,themanansweredthe
questionin70%ofthecases.Asimilarandevenmorepronouncedpatterninseenwithwomen,
wherethevastmajorityofwomenansweredwhentheyweresolelyresponsiblefordecisionson
foodpurchases.Forjointdecisionhouseholds(eitherequallyorinpart),bothmenandwomen
participatedinansweringthequestion,butmenmoresothanwomen.
FOODDECISIONS
43
Figure41.Decision-makeronFoodPurchaseDecisions,bywhoanswered
AsimilaranalysiswasconductedoncropproductionparticipationdecisionsinFigure42.Again,there isastrongbias towardsthegenderof thepersonresponsible fordecision-making,with
womenandmenspeaking for themselveswhentheyareresponsible,andanswering together
whenthereisjointresponsibility.
Figure42.Decision-makeroncropproductionparticipation,bywhoanswered
44
Figure43 providesa summaryof all of thedecisionsaskedabout in theendline survey, andhighlightsthemostcommonanswer.Itshowsthatjoint-decisionmakingisverycommonwith
menmakingslightlymoredecisionsthanwomenforsomedecisioncategories.However,there
arestillasignificantpercentageofhouseholdswherewomenare leadingthedecision-making
process.
Figure43.Summaryofdecision-makingacrosssevendecisions
Tofurtherassessoveralldecision-makingacrossalltypesofdecisions(income,savings,food),
Figure44analyzesthehouseholdswheremen,women,orbothareinvolvedatleastequallyinall decisions. In 41% of householdsmen are involved at least equally in all decisionswhere
questionswereasked(income,savings, food). In29%ofhouseholdswomenwere involvedat
leastequallyinalldecisions.In32%ofhouseholds,bothmenandwomenwereinvolvedatleast
insomepartinalldecisions.Thesefindingsreinforcethatmenareoveralltheprimarydecision-
makersinSembabuleDistrict,butthatjointdecision-makingandfemale-decisionhouseholdsare
verycommonaswell.
Figure44.Decision-makingbygenderacrossalldecisions(income,savings,food)
Thesefindingshighlightthatwomenandmenareresponsiblefordifferentdecisionswithinthe
household,andthatmanydecisionsaremadejointly.Bothwomenandmenfeelfreetoanswer
thequestionsabouttheirdecision-makingwhentheyareresponsible,andallowtheirpartnerto
answerwhen theyareresponsible.For jointdecision-makinghouseholds,men tend tobe the
primaryquestionrespondent,butwomenalsocontributeaconsiderableamount.
ALLDECISIONS
45
Inordertofurtherassessrolesandresponsibilitiesonthefarm,respondentswereaskedwhois
most responsible for thecoffee farm. Inaddition,at theendof thesurvey,enumeratorswere
asked to recordwhich respondent (man orwoman) answered themajority of the questions
throughoutthesurvey.Figure45 illustratesthatmenareprimarilyresponsibleforthecoffeefarm(44%)andwerealsotheprimaryrespondenttothemajorityofsurveyquestions(53%).
Figure45.CoffeeFarmResponsibilityandQuestionAnsweringatEndline
Toassessthisfurther,Figure46depictswhoansweredthemajorityofthequestionsthroughouttheentireendlinesurvey,dependingonwhoisresponsibleforthefarm.Similartothedecision-
makinganalysis,astrongbiastowardsthegenderofthemostresponsiblefarmerwasfound.That
is,whenwomenweremostresponsible,womenoverwhelmingly(93%)answeredthequestion.
Asimilarpatternwasfoundformen.Thisfurthersuggeststhatwomenareempoweredenough
to:a)beresponsibleforthecoffeefarm;b)answerquestionsontheirresponsibility.Italsoshows
thatmenandwomenallowtheirpartnerstoanswerfortheirownwork,asignofcooperative
intra-householdgenderrelations.
Figure46.CoffeeFarmResponsibility,bywhoansweredthequestions
COFFEEFARMRESPONSIBILITY
46
Toassessgenderroleswithrespecttocoffeeproduction,questionswereaskedonthegender
responsibilityforfourcoffeefarmingpractices:pruning,harvesting,weeding,andplanting.
Figure47reportsthefindings,andshowsthatmenandwomenhavedifferentresponsibilitieson the farm.Men are highly involved in all four practices, but are least involved in planting.
Womenareprimarilyinvolvedinharvestingandweeding,andmuchlessinvolvedinpruningand
planting.Harvestingandweeding,beinglesstechnicalskills,arealsotheactivitieswhereother
householdmembers(oftenchildrenaged6–14)aremostinvolved,andalsotheactivitieswhere
hiredlabourisused.
Figure47.GenderresponsibilityforPruning,Weeding,Planting,andHarvesting
Tofurtherassesstheintensityoflabourrequiredfromeachgender,Figure48reportsthemeannumberactivitieswhereeachmemberisinvolved,andshowsthatmenareinvolvedin2.8ofthe
4activitiesonaverage,comparedto2.2forwomen.However,thismetricdoesnotcapturethe
timespentoneachactivity,whichwouldbeatruertestofintensityoflabour.
Figure48.MeanNumberofResponsibilitiesbyGender
INTRA-HOUSEHOLDLABOURDISTRIBUTION
47
This section is dedicated to understanding the income profile of households. Examining the
financial profile of a household is useful to understand the wealth and vulnerability of the
household.
A major program goal of Farm College is to increase incomes and reduce poverty through
increasedcoffeeproductionandsales.Figure49showsthedependenceofhouseholdsoncoffeeforincomebasedonself-reporteddata.
Figure49.PortionofTotalHouseholdIncomefromCoffee
In 2020, coffee households were highly dependent on coffee, with 60% of the households
reportingthatmorethanhalfoftheirtotalhouseholdincomecomesfromcoffee.Thisisashift
frombaseline,where themajority of households (64%) recorded coffee income representing
between 25% and 50% of income. The COVID-19 pandemic may be a factor in this shift as
households may have lost other sources of income and are more dependent on coffee. As
reportedinFigure50,othermajoreconomicactivitiesintheareaare:1)thesaleofmaize,beans,andbananas(57%)2)runningpersonalbusinesses(16%);3)thesaleoflivestock(8%).
Figure50.OtherIncomeSourcesatEndline
FINANCIALPROFILE
INCOMEDISTRIBUTION
48
For any household, savings are an important shield against financial shocks and coffee price
volatility.14%ofthehouseholdsreportedthattheydonotuseanymethodofsavings.Thisis
downdramaticallyfrom51%atbaseline,whichappearstobedrivenbyariseinmembershipto
informalsavingsgroups.
Farmerswereaskedabouttheirmainsavingmethods,whichisreportedinFigure51.47%ofthe farmersmentioned informalsavinggroupsas theirmainsavingsmethod,updramatically
fromjust18%atbaseline.13%offarmersuseformalsavingsgroups(e.g.,SACCOs),andonly7%
ofthehouseholdsuseformalsavingbankaccountsastheirsavingmethod.Thesameproportion
of households (7%) report fattening of livestock as their main saving mechanism. A lower
proportionoffarmers(5%)useamobilemoneyaccountforsavings.
Figure51.SavingMethodsUsedatEndline
SAVINGS
49
This section explores the vulnerability of households by studying the financial shocks and
incidenceoffoodshortagesfacedbyfarmersinSembabule.
Ashockorcrisisisdefinedasanyeventthatleadstoaseriousreductioninthefarmer’sasset
holdings,causingthehouseholdincometofallsubstantiallyorresultinasignificantreductionin
food consumption. A majority of the households at endline (70%) reported they have been
affectedbyatleastoneseriousfinancialshockorcrisisduringthelastyear.Atbaseline,thisfigure
was80%.
Householdsintheendlinesurveyreportedanaverageof1.4financialshocksinthelastyear,with
themostcommonbeingaserioushealthproblemordeath(51%),drought(30%),andlowcoffee
yields(27%).Figure52reportstheremainingmostcommonshocks.Figure52.TopFinancialShocksFacedbyHouseholds
Foodshortagescanbedebilitatingforhouseholds,adverselyaffectingtheirhealthandabilityto
workontheirfarms.Atendline,235households(40%)reportedfacingfoodshortagesoverthe
lastyear,eachforanaverageofonemonth.Thisisdownconsiderablyfrombaseline,when65%
experiencedfoodshortagesforanaverageoftwomonths.Figure53belowdepictsthemonthsof the year in which food shortages were most common, and shows August to October
experiencing the most food shortages. The peak came in September, when 65% of the 235
householdswhoexperiencedshortage,wenthungry.
VULNERABILITYPROFILE
FINANCIALSHOCKS
FOODSHORTAGES
50
Figure53.Mainmonthsoffoodshortagefor235householdsfacingfoodshortage
In order to combine data from a large number of individual food groups, a single indexwas
constructedusingamethodpromotedbytheFoodandAgricultureOrganizationoftheUnited
Nations(FAO2011).Thehouseholddietarydiversityscore(HDDS)reflects, inasnapshot,the
economicabilityofahouseholdtoaccessavarietyoffoods.Studieshaveshownthatanincrease
indietarydiversityisassociatedwithsocio-economicstatusandhouseholdfoodsecurity.
TheHDDStakes integervaluesbetween0and12; thehigherthescore, thebetter thedietary
diversity. The average household in the endline survey has a HDDS score of 8, indicating a
moderatedietarydiversityformostfarminghouseholds.
Themostfrequentfoodgroupsconsumedbysampledfarmerswerepulsesorlegumessuchas
beansorpeas(97%),fruits(93%),rootsandtubers(92%),andspicesorcondiments(99%).A
largemajorityofthehouseholdsalsoconsumedvegetables(86%),oilsorfats(82%),sugaror
honey(73%)andmilkproducts(73%).Consumptionofcerealsfellfrom77%atbaselinetojust
60% at endline. A lower percent of households (13%) reported having consumed meat
(predominantlybeef), fish (24%),andeggs (15%). Matooke,a stapledish inmostofUganda
consistingofmashedstarchybanana,wasoneofthemostwidelyconsumedfooditemsatendline,
withmorethanhalf(77%)ofthehouseholdsreportinghavingeatenthisdishduringthepast24
hours.Otherpopulardishesincludeboiledormashedcassava(38%)andugali(33%).
HOUSEHOLDDIET
51
Figure54.MainTypesofFoodConsumed
This sectionprovidesabriefoverviewof twopovertyassessment tools– theProgressoutof
Poverty Index (PPI) and the Multi-Dimensional Poverty Index (MPI). The purpose of these
povertyassessmenttoolsistounderstandtherelativepovertyprofileofthefarmersinvolvedin
theFarmCollegeprogram.
ThePPIisapovertymeasurementtoolcomprisedofacountry-specificsurveywith10simple,
easy-to-answermultiple-choicequestions.5ItwasdevelopedbyGrameenBankandmanagedbyInnovationsforPovertyAction(IPA).ItisprimarilyusedbyNGOs,socialenterprises,andafew
foundations and has been customized for 61 developing countries to date, including Uganda
(Schreiner2011).
Thetotalscorethatahouseholdcanachieverangesbetween0(mostlikelytobebelowapoverty
line)and100(leastlikelytobebelowapovertyline).ThePPIscoringcanbeusedtoestimate
threebasicquantities.First,thepovertylikelihoodofahousehold,whichistheprobabilitythata
householdhasper-adultorequivalentper-capitaconsumptionbelowapovertyline.Second,the
PPI scorecanestimate thepoverty rateofagroupofhouseholdsatapoint in timeusing the
averagescoresofeachhousehold.Third, it canestimate thechanges in thepovertyratesofa
groupofhouseholdsbetweentwopointsintime.
TheSimplePovertyScorecard(Schreiner2011),usedtomeasurethepovertylikelihoodof
farmersinCentralUganda,isbasedonindicatorsrelatedtothehouseholdcomposition(suchas
thenumberofhouseholdmembers),education(suchasthelevelofeducationofa
woman/wife),housingquality(suchasthewallandroofmaterialsofthehouse),andthe
ownershipofdurableassets(suchasmobilephoneorshoeownership).Foradetailed
descriptionofthequestionsusedtobuildthepovertyprofileofFarmCollegecoffeefarmers,
pleasereferto
Appendix6.
5FormoreinformationonthePovertyProbabilityIndex,visithttps://www.povertyindex.org/about-us.
POVERTYANALYSIS
PROGRESSOUTOFPOVERTYINDEX
52
TheresultsofthissectioncomparethePPP-basedpovertyrateofcoffeefarmersinSembabuleto
theUgandaNationalHouseholdSurvey2016((UBOS)2018),anationallyrepresentativesurvey
covering7,500householdscountry-wide.
Figure55belowshowstheresultsofthePPIanalysisforSembabuleDistrictfrombothbaselineandendline.Theregionalvaluesdonotchangebetweenbaselineandendlineasthesamesurvey
isused.ThePPIvalueforaregionrepresentsthepercentageofagivenpopulationthatlivesbelow
thepovertylineindicated.
Figure55.PPI-BasedPovertyRate
Asillustratedabove,PPI-basedpovertyhas fallensincebaseline inallcategoriescomparedto
nationalandregionalaverages.Thatis,thehouseholdsbelongingtothe2018cohortoftheFarm
Collegeareinabetterpositionintermsofpovertylevels,whenusingPPIcalculations.Only17%
ofthehouseholdsatendlinearelikelytofallbelowthe$1.90/day2011PPPpovertyline,which
isdownfrom26%atbaseline,andnowlessthanCentralRegionaverages(22%).Atthenational
povertylinelevel,only1%ofSembabulehouseholdssurveyedfallbelowthepovertyline.
The globalMPI is an internationalmeasure of poverty that complements traditional income-
basedpovertymeasuresbycapturing thedeprivations thateachperson faceswithrespect to
education,health,andlivingstandards. ItwasdevelopedandmanagedbytheOxfordPoverty&HumanDevelopmentInitiativeandsupportedbyUNDP.ItisprimarilyusedbyUNDP(Human
DevelopmentReport),WorldBank,andotherlargeinstitutions,andcoversover100countries.6
Understandingthemultiplefacetsofpovertylikelackofeducation,healthdeprivation,andpoor
standardsoflivingiscriticaltotrulyassessingtherelativepovertyofthebeneficiaries.TheMPI
tool provides a multi-dimensional perspective of the relative poverty of farmers. Note that
incidence refers to percentage of people that are multi-dimensionally poor/deprived, andintensity refers to proportion of indicators in which these poor people are deprived. The
6Formoreinformation,visit:http://hdr.undp.org/en/content/multidimensional-poverty-index-mpi
MULTI-DIMENSIONALPOVERTYINDEX
53
TechnoServeMPIwasadapted7 to theendline surveyandcompares thedataof the surveyedhouseholds to that of the Uganda 2016 Demographic and Health Survey (Uganda Bureau of
Statistics,2018).
TheresultsinFigure56showthat,onaverage,thecoffeehouseholdsinthe2018cohortofCoffeeFarmCollegeareworseoffthanthenationalandregionalaverages.66%ofthehouseholdsare
consideredmulti-dimensionallypoorcomparedto55%ofthehouseholdsnation-wide,and31%
of the households in the Central Region of Uganda. However, this is slightly improved since
baseline,where69%ofhouseholdswereconsideredpoor.
Figure56.MultidimensionalPoverty–IncidenceandIntensity
Figure 57 shows the contribution of the different indicators to overall poverty. The maincontributorforthefarmersinthe2018CohortoftheFarmCollegeisthenutritioncomponent,as
more than a quarter of the households (28%) have an HDDS score below or equal to 8, the
thresholdfordeprivationinnutrition.
7ThemainchangeistheuseofaHouseholdDietaryDiversityIndex(HDDS)insteadofusingBodyMassIndex(BMI)basedonscoresfor calculating nutritional deprivation. Numerous studies using cross-sectional data for sub-Saharan African and South Asiancountriesshowadirectlinkbetweendietarydiversityandthenutritionaladequacyofadiet(HoddinottandYohannes,2002;Ogle,2001;Bhargava,2015;Hatloyetal.,1998).Also,ArimondandRuel(2004)showthatdietarydiversitydoespredictheight-for-weightz-scores(HAZ),weight-for-age(WAZ)z-scores,andundernutrition–theverymeasuresusedintheglobalMPI.WhilethisMPImaynotbecompletelycomparablewiththeglobalone,theHDDSweemployedprovidessimilarinformationatmuchlowerdatacollectioncost,henceitsuseisjustified.
54
Figure57.ContributionofeachIndicatortoOverallPoverty
Appendix1.CharacteristicsofAdoptingHouseholds
Acomparisonofthecharacteristicsof(i)householdsadoptingfourormorebestpractices–High
Adopters,tothose(ii)householdswhohaveimplementedthreeorfewerbestpractices–Low
Adopters,revealsthatthetwogroupsareslightlydifferent.Differencesarestatisticallysignificant
for women’s age, women’s education, men’s literacy rates, land planted with coffee, asset
ownership,andfinancialshocksfaced.Thatis,highadoptionhouseholdsarestatisticallydifferent
thanlowadoptionhouseholdsinthefollowingways:
1%significancedifferences• Womeninhighadoptionhouseholdsareyoungeronaverage(age40)comparedtolow
adoptionhouseholds(age44).
• Women inhighadoptionhouseholdshavemore formaleducation(88%),comparedtolowadoptionhouseholds(82%).
• Menhavehigherratesofliteracyinhighadoptionhouseholds(91%),comparedtolowadoptionhouseholds(82%).
• Low adoption households have less land planted with coffee trees (0.8 hectares)comparedtohighadoptionhouseholds(1.2hectares)
• Highadoptionhouseholdsownmoreassets(9)comparedtolowadoptionhouseholds(8)
5%significancedifferences• Highadoptionhouseholdsweremorelikelytohavefacedafinancialshockinthelastyear.
Table3.AverageCharacteristicsofLowandHighBestPracticeAdoptingHHsStatisticallysignificantdifferencesarehighlightedingreen.
Low Adoption Households
High Adoption Households
Adopting less than 4 BPs
Adopting 4 or more BPs
No. of Households 384 197 Number of household members 6 7 Number of children 4 4
APPENDICES
55
Age of woman*** 44 40 Age of man 48 47 Formal education rate – women*** 82% 88% Formal education rate – men 89% 92% Literacy rate – women 75% 80% Literacy rate – men*** 82% 91% Total agricultural land (hectares) 2.0 2.2 Land planted with coffee (hectares)*** 0.8 1.2 % Faced financial shocks in last year** 67% 77% % Faced food shortages in last year 38% 43% Asset Ownership (number of assets)*** 8 9 Coffee majority of income 59% 62% HH Dietary Diversity Score 8.0 8.2 Thestars(*)representthesignificancelevelofthedifferencebetweenthehighadoptionandlowadoptiongroups.***Significantatthe1%level,**Significantatthe5%level,*Significantatthe10%level.
Appendix2.BestPracticeAdoptionbyTrainingonEachSpecificTopic
Acomparisonofbestpracticeadoptionrateswasconductedforhouseholdsthatwereconsidered
trainedonaspecifictopic(sometimesthisrequiredattendanceatmultipletrainings)–AttendedTrainingonTopic–andthosewhowerenottopictrained–DidNotAttendTrainingonTopic.Noneofthedifferenceswerefoundtobestatisticallysignificant.
Table4.Bestpracticeadoptionbytrainingoneachspecifictopic Not Trained on
Specific Topic Trained on
Specific Topic
Overall Average Overall Average Shade 64% 66% Weeding 59% 65% IPDM 63% 63% Erosion Control 60% 59% Rejuvenation 47% 56% Pruning 44% 47% Coffee Nutrition 19% 17% Record Keeping 2% 5% Mulching 6% 4% Safe Use of Pesticides 0% 0% Average # of best practices adopted (out of 10) 4 BPs 4 BPs
Thestars(*)representthesignificancelevelofthedifferencebetweenthehighadoptionandlowadoptiongroups.***Significantatthe1%level,**Significantatthe5%level,*Significantatthe10%level.
56
Appendix3.BestPracticeAdoptionbyNon-AttendingHouseholds
Acomparisonofbestpracticeadoptionrateswasalsoconductedforthe79householdswhodid
notattendCoffeeFarmCollege.Table5reportstheseratesaswellastheadoptionratesandalsoreports the rates for Low Attending Households (less than 7 topics attended) and TrainedHouseholds(morethan7topicsattended).
Table5.Bestpracticeadoptionfornon-attendinghouseholdsatendline
Non-Attending Households
Low Attend. Households
Trained Households
Overall Average Overall Average Overall Average No. of Households 79 63 443 Shade 78% 60% 66% Weeding 62% 58% 65% IPDM 42% 58% 64% Erosion Control 44% 72% 57% Rejuvenation 61% 53% 54% Pruning 42% 50% 46% Coffee Nutrition 16% 16% 18% Record Keeping 2% 4% 5% Mulching 2% 5% 4% Safe Use of Pesticides 0% 0% 0% Average # of best practices adopted (out of 10)
3 BPs 4 BPs 4 BPs
Households adopting more than half (5) of the best practices
29% 26% 35%
Appendix4.BestPracticeAdoptionbyParishComparisonofhouseholdsfromthe15parishesshowsthatthereisavariationinbestpracticeadoptionbetweentheparishes–seeTable6.HighestAdoptingParishes
• Nsoga–Nsogaaveragedthemostamountofbestpracticesadopted(4.3),andthesecondmosthouseholdsadopting5+bestpractices(45%)• Mateete–38%offarmersinMateeteareadoptingmorethan5bestpractices,andhouseholdsaverage4.2bestpractices• Nakagongo–46%offarmersareadoptingmorethan5bestpractices(mostofallparishes);householdsaverage3.9bestpractices
LowAdoptingParishes
• Kasambya–only22%offarmersareadopting5ormorebestpractices,andtheyscorethelowestaveragebestpracticesatendline(3.4).• Lugusulu–farmersatendlineaveragedjust3.3bestpractices,thelowestofanyparish.
Table6.BestPracticeAdoption,byParishForeachbestpractice,thetwohighestadoptingparishesarehighlightedingreen,andthetwolowestadoptingparishishighlightedinred.(n=581)
Kabale Kasam- bya
Kasambya Lwebitakuli Kayunga Kido-
kolo Kinywa-
mazzi Lugus
ulu Lwebita-
kuli Mabindo Man- yama Mateete Mitete Naka-
gongo Naka- senyi Nsoga
No. of households Record Keeping 0% 6% 5% 7% 6% 0% 3% 6% 5% 8% 5% 3% 8% 5% 5% Safe Use of Pesticides 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Weeding 72% 64% 54% 73% 64% 65% 60% 71% 67% 82% 58% 61% 59% 54% 61% IPDM 46% 47% 56% 56% 69% 51% 55% 65% 62% 53% 68% 74% 64% 74% 79% Rejuvenation 49% 58% 56% 68% 69% 43% 53% 53% 49% 45% 53% 45% 77% 59% 61% Pruning 41% 44% 38% 46% 61% 43% 35% 49% 49% 50% 30% 65% 62% 44% 58% Nutrition 8% 8% 10% 5% 6% 27% 20% 24% 15% 21% 40% 26% 13% 10% 16% Mulching 8% 3% 5% 5% 6% 8% 3% 0% 5% 3% 5% 0% 3% 0% 0% Erosion 51% 47% 59% 51% 56% 68% 40% 47% 64% 63% 73% 61% 54% 51% 76% Shade 82% 61% 64% 54% 50% 76% 63% 57% 74% 55% 88% 71% 54% 64% 71% Adopted 5+ BPs 21% 22% 21% 32% 42% 35% 30% 27% 41% 34% 38% 42% 46% 38% 45% Sum BPs (Endline) 3.6 3.4 3.5 3.7 3.9 3.8 3.3 3.7 3.9 3.8 4.2 4.1 3.9 3.6 4.3 Sum BPs (Baseline) 1.8 1.5 1.9 2.3 1.9 2.6 2.1 2.3 2.5 2.0 3.0 2.6 2.6 2.2 2.8
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Appendix5.BestPracticeRuleChangessinceBaselineIn thebaselinereport,bestpracticeswerescoredusinganew,morecomplexrulemethodology,combining feedback fromHRNS.Atendline, thedecisionwasmadetorevertbacktothestandardTNSruleswhichareconsistentwithallothercountriesaswellastheprogramproposal.ThisendlinereportusesthesestandardTNSrules,andhasconvertedallbaselineresultstotheseusualrules.Table7displaystheoriginalbaselinerulesaswellastheusualTNSrulesusedatendline,anddescribesthedifferencebetweenthetwomethodologies.AdiscussionwillbeheldwiththewiderUCATteamontherulesinlightofthefindings.
Table7.RuleschangessinceBaselinetoreverttousualTNSrules
Original Baseline Rule Updated Rule at Endline (Usual TNS Rules) Comment
10 Best Practices Adopted if: Adopted if:
Record Keeping
1. Farmer has a Record Book AND 2. This has records of either coffee sold OR hired labour costs or other costs
1. Farmer has a Record Book AND 2. This has records of either coffee sold OR hired labour costs or other costs
No change. Already consistent with usual TNS rules.
Safe Use of Pesticides
N/A if farmer has not sprayed pesticide. If farmer has sprayed pesticide: 1. Farmer has been trained on how to safely use pesticide AND 2. Famer is not storing pesticide OR farmer stores pesticide outside the house and the store is locked AND 3. Farmer used masks googles and gloves at a minimum OR contractor used masks goggles and gloves items AND 4. Containers not washed and re-used for other purposes AND not thrown into the fields or compound
N/A if farmer has not sprayed pesticide. If farmer has sprayed pesticide: 1. Farmer has been trained on how to safely use pesticide AND 2. Famer is not storing pesticide OR farmer stores pesticide outside the house and the store is locked AND 3. Farmer used masks googles and gloves at a minimum OR contractor used masks goggles and gloves items AND 4. Containers not washed and re-used for other purposes AND not thrown into the fields or compound
No change. Already consistent with usual TNS rules.
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AND not thrown into the rubbish pit AND not buried AND not thrown into pit latrine/toilet 5. No banned pesticides used
AND not thrown into the rubbish pit AND not buried AND not thrown into pit latrine/toilet 5. No banned pesticides used
Weeding
1. Farmer has pulled weeds by hand, used a slasher under the tree canopy, used a panga to weed under the tree canopy, dug under the tree canopy, or applied herbicides AND 1.1. Farmer has NOT exclusively dug under the tree canopy exclusively AND 2. Farmer weeds twice or more per year AND 3. There are few OR no weeds AND 4. If there are few weeds, they are less than 30cm tall AND 5. Weeds have not reached the flowering stage
1. Farmer has pulled weeds by hand, used a slasher under the tree canopy, used a panga to weed under the tree canopy, dug under the tree canopy, or applied herbicides AND 1.1. Farmer has NOT exclusively dug under the tree canopy exclusively AND 2. Farmer weeds twice or more per year AND 3. There are few OR no weeds AND 4. If there are few weeds, they are less than 30cm tall
Weed flowering criteria was removed in order to be consistent with usual TNS rules in other countries and cohorts.
IPDM
1. Farmer can name at least 4 out of 9 IPDM methods AND 2. Farmer mentions uprooting and burning infested trees for CWD AND 3. Farmer mentions removing and burning infested twigs for CTB
1. Farmer can name at least 3 out of 9 IPDM methods
Reverted to usual TNS rules which require 3 out of 9 methods, and do not specify conditions on specific methods.
Rejuvenation
1. Most trees have 4 main stems or less AND 2. The oldest trees are 8 years old or younger OR
1. Most trees have 4 main stems or less AND 2. The oldest main stems are 8 years or younger
Reverted to usual TNS rule for rejuvenation, which requires 4 or fewer main stems and main stems 8 years or younger.
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1. At least one tree is older than 8 years AND 2. The oldest main stems are 8 years or younger AND 3. Most trees have 4 main stems or less AND 4. At least 25% of the farm has been rejuvenated AND 5. Suckers are less than 30cm tall OR Suckers are more than 30cm tall AND there are 4 or less suckers
Pruning
1. Trees have been pruned using 4 of the 5 methods listed
1. Trees have been pruned using 3 of the 4 methods listed
Reverted to usual TNS rule for pruning, which requires 3 methods to be seen. In addition, the responses choosing the option “Broken / unproductive stems and/or branches removed” were removed, as this option is not typically given in any other countries or cohorts. As such, the usual TNS rule of 3 of 4 methods is used.
Coffee Nutrition
1. Nearly all leaves are dark green AND 2. At least two of the following are used: compost or manure (counted as 1), NPK, Foliar Feeds, Lime and DAP. If foliar feed is used only count if this is zinc/boron based AND 3. IF fertilizer is applied to the soil, the fertilizer has been applied using a measure, and is not broadcast
1. Nearly all leaves are dark green AND 2. At least one of the following are used: compost or manure (counted as 1), NPK, Foliar Feeds, Lime and DAP. If foliar feed is used only count if this is zinc/boron based AND 3. IF fertilizer is applied to the soil, the fertilizer has been applied using a measure, and is not broadcast
Reverted to usual TNS rule for good soils (based in soil survey results since the baseline) where organic production is common, which requires one product be used, instead of two.
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Mulching
1. Farmer has applied mulch AND 2. Mulch applied on up to 25% of the farm AND 3. Mulch is more than 2cm thick
1. Farmer has applied mulch AND 2. Mulch is more than 2cm thick
Reverted to usual TNS rules which do not include the 25% farm proportion criteria.
Erosion Control
1. At least two erosion control methods seen 1. At least one erosion control methods seen Reverted back to usual TNS rules which requires just one erosion control method seen. In addition, the options of trenches and water traps were combined into one single option, as trenches are not typically an option under TNS rules.
Shade
1. There is 20% shade or more OR 2. There is less than 20% shade but shade trees have been planted in the last 3 years
1. There is 20% shade or more OR 2. There is less than 20% shade but shade trees have been planted in the last 3 years
No change. Already consistent with usual TNS rules.
Other Agronomy Practices
Composting
Originally considered a BP No longer considered a BP Not usually considered a standalone BP as it is included under Coffee Nutrition. This is consistent with TNS rules in other countries and cohorts.
Intercropping
Originally considered a BP No longer considered a BP Not usually considered a standalone BP under usual TNS rules. Question was changed.
Coffee Planting Not considered a BP Not considered a BP No change Coffee Drying Not considered a BP Not considered a BP No change
Appendix6.MPIandPPIScorecardsFigure58.MPIScorecard
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Figure59.PPIScorecard
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(UBOS),UgandaBureauofStatistics.2018.“UgandaNationalHouseholdSurvey2016.”Kampala.FAO.2011.“GuidelinesforMeasuringHouseholdandIndividualDietaryDiversity.”
KenyaNationalBureauofStatistics.2015.KenyaDemographicandHealthSurvey2014.Rockville,MD,USA:KenyaNationalBureauofStatistics.
KenyaNationalBureauofStatistics.2013.KenyaIntegratedHouseholdBudgetSurvey2005-06.Nairobi:KenyaNationalBureauofStatistics.
Schreiner,Mark.2011.“SimplePovertyScorecard®Poverty-AssessmentToolKenya.”SimplePovertyScorecard,11March.
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