000			02128nab|a22003137a|4500
999			_c63858 _d63850
001			63858
003			MX-TxCIM
005			20211006075047.0
008			202101s2021||||xxk|||p|op||||00||0|eng|d
022			_a1756-5529
022			_a1756-5537 (Online)
024	8		_ahttps://doi.org/10.1080/17565529.2021.1930507
040			_aMX-TxCIM
041			_aeng
100	1		_aMujeyi, A. _95746
245	1	0	_aAdoption patterns of Climate-Smart Agriculture in integrated crop-livestock smallholder farming systems of Zimbabwe
260			_aUnited Kingdom : _bTaylor and Francis, _c2021.
500			_aPeer review
520			_aThis paper maps adoption patterns and determinants of Climate-Smart Agriculture (CSA) technologies. A multivariate analysis approach that combined principal component analysis (PCA) and cluster analysis was employed and findings showed that patterns of CSA varied across household typologies. Resource endowed, experienced farmers have a high use of crop rotation and minimum tillage that require more resources while resource-constrained clusters shunned those. Double hurdle model results showed that adoption of CSA is significantly affected by distance to the tarred road, access to weather information, livestock income share and ownership of transport asset. Adoption intensity is significantly affected by the sex of household head, labour size, frequency of extension contact, credit access, access to weather forecasts, off-farm income, distance to input and output markets, number of traders and asset ownership. The study recommends policies that ensure access to credit and weather forecasts coupled with frequent access to extension services.
546			_aText in English
650		7	_aInnovation adoption _gAGROVOC _2 _91160
650		7	_aHouseholds _2AGROVOC _92743
650		7	_aClimate-smart agriculture _2AGROVOC _92419
651		7	_2AGROVOC _94496 _aZimbabwe
700	1		_aMudhara, M. _912299
700	1		_aMutenje, M. _8INT3348 _9929 _gSocioeconomics Program
773	0		_tClimate and Development _dUnited kingdom : Taylor and Francis, 2021. _x1756-5529 _gIn press
942			_cJA _n0 _2ddc