Integrated Soil Water and Nutrient Management and Dry ... - Icrisat

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years, ranging from 23 to 87. On average a household has access to 3.1 ha, ranging from 0.4 to 9.7 ha. To identify factors determining household differentiation and evaluate how they interact with characteristics of extension services and result in the observed performance, factor analysis was first carried out. Nonmetric variables were included using dummy variables. The procedure extracted 8 factors with Eigen values greater than 1. The scree test showed that only the first three factors are significant and these were retained for further analysis. To interpret the factors the VARIMAX method was used to obtain orthogonal rotation of factors (Table 8). After rotating the factor axes, the variables with high statistically significant loadings on Factor 1 included number of members working on Table 8. VARIMAX-rotated component analysis factor matrix, southern Zimbabwe, 2001/02 Variable 1 2 3 Uniqueness Croplabo 0.68808 -0.03725 -0.11600 0.51170 Hhldsize 0.64468 -0.10472 -0.14982 0.55098 Cultivat 0.62445 0.06450 -0.05644 0.60272 Farmarea 0.55666 -0.42858 0.02962 0.50557 Ploughs 0.55132 0.11087 -0.39051 0.53126 Draftcat 0.54917 0.33146 -0.26302 0.51937 Harrows 0.53369 0.31335 -0.18665 0.58215 Carts 0.48901 0.18710 -0.42028 0.54923 Agehead 0.47972 -0.43676 0.10874 0.56728 Sprayer 0.41106 0.12300 -0.08316 0.80899 Cattle 0.40906 0.35568 -0.40408 0.54288 Animlabo 0.33750 -0.08203 -0.20594 0.83695 Barrow 0.31904 0.32160 -0.36185 0.66385 Hmaway 0.21931 0.22782 0.00940 0.89991 Bicycle 0.16970 0.53035 -0.17856 0.65804 Goats 0.16375 0.26193 -0.63383 0.50284 Farmsize 0.15742 0.18713 -0.22334 0.89032 Dmale 0.14784 -0.53857 -0.43818 0.49608 Sheep 0.14030 0.02323 -0.32833 0.87197 Cash 0.13402 0.22958 -0.05455 0.92635 Donkeys 0.09599 -0.06032 -0.84658 0.27045 Draftdon 0.07610 -0.09583 -0.84546 0.27023 Deffem 0.07135 0.67665 0.35021 0.41441 Radio -0.00317 0.53887 -0.33226 0.59921 35
crops, household size, cultivators, farming experience, ploughs, draft cattle, harrows, carts, and age of household head. We identify Factor 1 as capturing well-resourced households with full set of farm equipment. Variables that load very high on Factor 2 include de facto female head, radio, bicycle, cattle, draft cattle, wheelbarrows, harrows, goats and cash in the positive direction and farming experience, age of household head, and male head husband resident in the negative direction. We identify Factor 2 as capturing average households, mostly de facto female-headed households with access to salaried incomes and remittances, cash for investing in farming and consumer durables such as radio and bicycles. Variables that have significant loadings on Factor 3 are mostly negatively associated with donkeys, draft donkeys, goats, male-head husband resident, carts, cattle, ploughs, wheelbarrow, radio, sheep and draft cattle. Therefore we interpret Factor 4 as reflecting poorly resourced mostly de jure female-headed households. Focus group discussions with farmers revealed that they recognize three household typologies based on community-derived wealth criteria such as ownership of draft animals and farm equipment, land-holding size, farming knowledge, and access to salaried incomes and remittances. These include wealthy, average and poor households. Wealthy households have adequate draft animals to inspan and a full set of equipment, including ploughs, harrows, cultivators, and carts. They are generally male-headed households with a resident husband and have access to pension, business income, or salaried employment in the rural area. They have grown-up children whose education is complete, and who are assisting them. They do not have major expenses such as school fees and health costs. Some can afford to hire local casual laborers and full-time workers to help with farming tasks. Average households have inadequate animals and equipment for inspanning. They share draft animals and implements and combine with others. They are mostly femaleheaded households with husbands away or male-headed households with retired or elderly household heads. Poor households have access to land but do not have draft animals and farm implements. They have to hire draft power from other farmers. They often sell labor for weeding and harvesting and herding cattle; collect insects and natural resource products and sell them and ask for help. Some poor households brew beer, breed poultry, make clay pots to sell, and exchange human labor for animal draft services. These are usually female-headed households. 36
Page 2 and 3: Citation: Citation: Rusike J, Heinr
Page 4 and 5: The opinions expressed in this publ
Page 6 and 7: Synthesis Synthesis of Workshop Out
Page 8 and 9: • Increased crop and variety dive
Page 10 and 11: udgets are now activity- and perfor
Page 12 and 13: Appendix Introduction Background an
Page 14 and 15: The farmers decided on the experime
Page 16 and 17: Table 1. Manzimahle Farmer Field Sc
Page 18 and 19: egistered to become members of the
Page 20 and 21: The farmers appreciated the fact th
Page 22 and 23: The groups discussed problems affec
Page 24 and 25: • Fuel shortage • Low mileage r
Page 26 and 27: • Pre-planting tied ridges are no
Page 28 and 29: completed in all FFS. Installation
Page 30 and 31: wider options available and whether
Page 32 and 33: for the whole country. Provincial t
Page 34 and 35: • Participating farmers liked sha
Page 36 and 37: • There is high staff turnover of
Page 38 and 39: Responses of farmers and extension
Page 42 and 43: Government extension officers and N
Page 44 and 45: Table 11. Allocation of government
Page 46 and 47: Impact of Master Farmer, Farmer Fie
Page 48 and 49: Compared to the control group, the
Page 50 and 51: Empowerment Farmers were asked whet
Page 52 and 53: farmer-to-farmer visits, a sense of
Page 54 and 55: to the majority of farmers, conduct
Page 56 and 57: This study conducted a comparative
Page 58 and 59: Participants Alibaba, S Provincial
Page 60 and 61: Makumbe, Willie Senior Agricultural
Page 62 and 63: Ndebele, Crispen Crop Research Offi
Page 64 and 65: Tsikisayi, Sylvester Director ZFU P
Page 66: ICRISAT-Patancheru (Headquarters) P

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