Initiating Sustainable AgriculturalSystems Through ConservationAgriculture in Mozambique: PreliminaryExperiences from SIMLESADias, D.J1, Nyagumbo, I2* and Nhantumbo, N.S3, Tomo, A4Instituto de Investigação Agrária de Moçambique (IIAM) email@example.comCIMMYT, International Maize and Wheat Improvement Centre, Box MP163, Mt.Pleasant, Harare, Zimbabwe, firstname.lastname@example.org;Instituto Superior Politécnico de Manica, Faculdade de Agricultura,email@example.com
Contents of the presentation• Introduction• Materials and Methods• Results and Discussions- Implementation- Challenges encountered- Future Outlook
1. Introduction• Mozambique is a Southern African country with an estimated population of 21 million people• Poverty levels are high and literacy levels are estimated to be around 48 % (AGRA-JIMAT, 2010)• On average only 4.9 % of arable land area (36 million ha) is cultivated• Major crops are maize (78% households), cassava (34.3%), groundnut (22%) , pigeon pea (18.9%) and cowpea (10.9% households)
Introduction•Mozambique has almost 85% of the ruralpopulation practicing low external inputsubsistence agricultural systems•The use of conservation agriculture and adoptionof best practices has a strong potential to boostyields and sustain food security.•CA promoted in Mozambique since the late1990s by Sassakawa Global 2000 and others butstill a long way to go for meaningful adoption.
Contd.• CIMMYT, IIAM and other partners since August 2010, have been implementing SIMLESA, a research initiative aimed at promoting a sustainable intensification of maize–legume cropping systems for food security in Eastern and Southern Africa.• Objective of this paper is to highlight experiences gathered during this first season of implementation focussing on the successes, challenges, lessons learnt and insights on the future.
Materials and Methods Exploratory CA trials were established in 6 communities distributed within three provinces (Manica, Tete and Sofala) of Mozambique (see map). A criteria for selection was based on attributes such as:1. Agro-ecology,2. Accessibility,3. Potential to boost yields using CA,4. Potential for maize legume systems5. Availability of secondary data including meteorological data.
Testing sites Angonia (R10) Angonia (R10) (Communities of (Communities of Ciphole and Ciphole and Cabango) Cabango) Gorongoza (R4) Gorongoza (R4) Community of Community of Canda-sede)) Canda-sede Manica (R10&R4) Community of Chinhadombwe) Sussundenga (R4) Community of Sussundeng-sede R10: Community of Rotanda
The process• 1 week CA training for ext staff on CA concepts and principles• Community awareness meetings• Election of 6 trial host farmers per community using secret ballots after agreeing on key attributes for hosts• CA initiatives were supervised and monitored by the local extension staff.
The process Contd……..• Farmers consulted on maize-legume treatments in each community during community awareness meetings• Small survey carried out to profile host farmers in July/Aug 2011.
Perceptions of host farmers regarding what they think were reasons for being selected to host trialsReason for being selected Frequency Percenthard worker 18 51ability to run trials and experience from other 8 23trialss/he is trustworthy 2 6very active/ willing to learn/ good fields 7 20
Previous experience hosting other trials 28.6 % have never participated in any research trials before 71.4 % have hosted other research/ extension trials before
Table 2. Key attributes of trial host farmersVariable Mean Standard deviationPeriod of residence in the community 35.1 17.5(yrs)Family size ( no. of persons) 8 3.4Age of household head (years) 45.5 12.7No. of years in school (years) 6 3.3Contribution of labour in own farm 84.3 31.2Land size (ha) 4.8 3.6
Gender characteristics of hosts• The selection to host trials differed from site to site and depended very much on cultural habits with some gender biases.• In Manica and Tete sites, the process was more supportive of women with one to three women being selected to host trials per site and an average of two women participating in CA committees (Table 3).
Table 3: Gender characteristics of CA trial host farmers and research committees by communityProvince/District Farmers selected to Farmers in Local Total host trials by Research community Committees Male Female Male FemaleSofala: Gorongosa- 6 0 5 0 11CandaManica: Chinhadombwe 5 1 3 2 11Manica: Sussundenga 5 1 3 2 11SedeManica: Sussundenga- 5 1 2 3 11RotandaTete: Angonia-Cabango 3 3 3 2 11Tete:Angonia-Chiphole 5 1 2 3 11
Contd.• In contrast, in Gorongosa no women featured on any role!• Although meant to ensure ownership and identification with the project the approach in some situations e.g. Gorongosa, led to selection of the same people already hosting trials from other initiatives.
Contd.• This problem only corrected after lengthy discussions.• Research committees selected to manage the trials were also completely dysfunctional in some communities but very instrumental in others.
Contd.• Farmers were motivated by the resources availed to them through the project such as inputs and equipment (Jab planters, direct seeders) which they considered as very useful tools due to their ability to make the sowing easier and less time consuming.• There were complaints over bad functionality, unavailability on the local market and the high cost of the equipment were major constraints to famers interested in adopting the initiatives
Implementation:The initiative found that success on implementation starkly depended on:1. Motivation of the local extension worker as well as the interest of the local farmers.2. The quality of CA implemented, highly depended on the extension workers knowledge, motivation, resources put at their disposal and their workload or commitment to other initiatives .3. The existence of other projects with different approaches also led to confusion among both the extension staff and farmers.
Quality of CA management % applying residues by Weed Maize Quality of No. of flowering management by average ExtensionSite farmers stage mid Season yield (kg/ha) support 1 excellent, 2Chiphole 6 100 good; 3 average 3371 Very good 1 very good; 3 good; 1 average; 1Kabango 6 83 poor 4384 Very good 3 excellent; 2Sussunden average, 1 latega 6 83 planted 1997 Very good 2 good, 3 average,Rotanda 6 100 1 late planted 2458 averageGorongos 2 good, 2 average,a 6 83 2 very bad 1075 average 1 excellent, 4 very
Exploratory trials achievements so farCommunity Trials established Trials harvested % Success rateManica 6 5 80%Sussundenga 6 6 100%Rotanda 6 6 100%Gorongosa 6 6 100 %Kabango 6 5 80%Chiphole 6 6 100%• Rainfall: Rainfall recording erratic in most situations.•Generally legumes were lost in most communities•Socio-economic data poorly collected eg labour,
Challenges encountered:The first six months of implementation revealed complex challenges:1. The unavailability of residues1. Termite infestation was also a deterrent to residue application for example in Manica.2. Weed management also proved a serious challenge with some farmers calling for the use of pre- emergence herbicides in addition to glyphosate while others avoided hand/hoe weeding on plots treated with herbicides.
Contd.1. Jab planters and direct seeders were considered very useful tools provided they were properly manufactured.2. Training of extension agents/ farmers was also another challenge with some lacking hands-on practical experience.
Future Outlook1. Extension agents should be very well trained to understand the concepts and practices of CA.2. The project should also consider using farmers from previous projects that succeeded in using CA to train other farmers.3. Exchange visits were an effective dissemination and training tool equipping them with practical skills based on ‘seeing is believing’.4. Efforts to be taken to reach more farmers by working with other partner organizations through Innov Plats.5. Improve regular monitoring and assistance to frontline implementation teams
Summary• SIMLESA has made a good start in Moambique and there is potential to move forward as we build on previous experience from the farmers• Lessons learnt from the first season on gender imbalances and other key drivers for success will be used to inform future programming of activities in the next season and beyond.• The SIMLESA framework could provide an effective framework for scaling up technologies