Socio-economic factors that affect livestock herd size : a case study of smallholder cattle farmers in Lepelle-Nkumpi municipality, Limpopo

Abstract

The study was conducted at Lepelle-Nkumpi Municipality in the Limpopo Province of South Africa. The main objective of the study was to determine the socio-economic factors affecting cattle herd size in the study area. The research was quantitative in approach and used a proportionate stratified sampling technique that adopted the method proposed by Krejcie and Morgan to determine a sample size of two hundred and sixty- one (261) smallholder cattle farmers. Respondents were interviewed through a questionnaire to answer objectives of the study. Collected data were captured and analysed using the Statistical Package for Social Sciences (SPSS). SPSS was used to obtain descriptive statistics (the frequency, percentages, mean, variance, standard deviation, cross-tabulation) and OLS multiple linear regression model. Descriptive statistics results revealed that draught; practical knowledge; no/less grazing land; maintenance; water circulation; getting good breeding stock; poor market prices; small grazing land; stock theft; insufficient or no breeding stock and pest/parasites were prevailing factors affecting cattle herd size in Lepelle-Nkumpi Municipality. Most of the farmers stated that they would like their livestock to increase by (94.8%). OLS multiple linear regression results revealed significant variables such as age; household size; sales per year; livestock keeping and planted pasture. The study revealed a link between significant independent variables, which will help smallholder cattle farmers to alleviate their vulnerability to cattle herd size and age. This study recommends that smallholder livestock farmers should be provided with extension services, training, and stakeholder engagement to provide subsidies, and ensuring that distribution of policies are provided with equal benefits. Furthermore, this study recommend that farmers should plant pastures and practise camp system to avoid overgrazing and overstocking, while planting pastures would help them to minimise costs and increase forage for feeding livestock. Moreover, greater consideration in creating farmers assortations to support and monitor farmers should be encouraged.

Thuto ye e dirilwe masepaleng wa Lepelle-Nkumpi ka Profenseng ya Limpopo ka Afrika Borwa. Maikemišetšo a magolo a nyakišišo e be e le go laetša mabaka a ekonomi ya leago ao a amago bogolo bja mohlape wa dikgomo mo lefelong la nyakišišo. Nyakišišo e be e le ya boleng gomme e šomišitše thekniki ya go tšea mehlala ya go lekana ya stratified yeo e amogetšego mokgwa wo o šišintšwego ke Krejcie le Morgan go laetša bogolo bja sampole ya balemirui ba dikgomo ba makgolo a mabedi le masometshela-tee (261). Ba arabetšego ba ile ba botšološišwa ka lenaneopotšišo, go araba maikemišetšo a nyakišišo. Datha ye e kgobokeditšwego e ile ya thopša le go sekaseka ka go šomiša sephuthelwana sa dipalopalo sa mahlale a leago. SPSS e ile ya šomišwa go hwetša dipalopalo tše di hlalošago (maqhubu, diphesente, magareng, phapano, go fapoga ga maemo, sefapano-tabulation) le mohlala wa OLS multiple linear regression. Dipoelo tša dipalopalo tše di hlalošago di utollotše gore go goga; tsebo e šomago; ga go/naga ya phulo ye nnyane; tlhokomelo; go dikološwa ga meetse; go hwetša setoko se sebotse sa tswadišo; ditheko tše di fokolago tša mmaraka; naga ye nnyane ya phulo; bohodu bja setoko; go se lekane goba go se be le setoko sa tswadišo le disenyi/diphelakadingwe e be e le mabaka ao a bego a ama bogolo bja mohlape wa dikgomo ka mmasepaleng wa Lepelle-Nkumpi. Bontši bja balemirui ba boletše gore ba rata gore diruiwa tša bona di oketšege ka (94.8%). Dipoelo tša OLS multiple linear regression di utollotše diphetogo tše bohlokwa tša go swana le mengwaga; bogolo bja lapa; thekiso ka ngwaga; go hlokomela diruiwa le mafulo a bjetšwego. Thuto e utolotše kgokagano magareng ga diphetogo tše bohlokwa tše di ikemetšego tšeo di tlago thuša balemirui ba dikgomo ba balemirui ba bannyane go fokotša go hlaselega gabonolo ga bona go bogolo bja mohlape wa dikgomo le mengwaga. Thuto e šišinya gore balemirui ba diruiwa ba bannyane ba swanetše go fiwa ditirelo tša katološo, tlhahlo, le go tsenela bakgathatema go aba dithušo tša ditšhelete, le go netefatša gore kabo ya melawana e fiwa ka mehola ya go lekana. Thuto, go feta fao, e šišinya gore Balemirui ba swanetše go bjala mafulo le go itlwaetša tshepedišo ya kampa go efoga go fula kudu le go swara diruiwa go feta tekano, mola go bjala mafulo go be go tla ba thuša go fokotša ditshenyegelo le go oketša furu ya go fepa diruiwa. Go feta fao, hlohleletša go ela hloko kudu go hloleng mehuta ya balemirui go thekga le go hlokomela balemirui.