000			03361nab|a22004217a|4500
999			_c62463 _d62455
001			62463
003			MX-TxCIM
005			20220920151106.0
008			200822s2020||||xxk|||p|op||||00||0|eng|d
022			_a0014-4797
022			_a1469-4441 (Online)
024	8		_ahttps://doi.org/10.1017/S0014479720000125
040			_aMX-TxCIM
041			_aeng
100	1		_aLark, R.M. _913487
245	1	0	_aLongitudinal analysis of a long-term conservation agriculture experiment in Malawi and lessons for future experimental design
260			_aCambridge (United Kingdom) : _bCambridge University Press, _c2020.
500			_aPeer review
500			_aOpen Access
520			_aResilient cropping systems are required to achieve food security in the presence of climate change, and so several long-term conservation agriculture (CA) trials have been established in southern Africa – one of them at the Chitedze Agriculture Research Station in Malawi in 2007. The present study focused on a longitudinal analysis of 10 years of data from the trial to better understand the joint effects of variations between the seasons and particular contrasts among treatments on yield of maize. Of further interest was the variability of treatment responses in time and space and the implications for design of future trials with adequate statistical power. The analysis shows treatment differences of the mean effect which vary according to cropping season. There was a strong treatment effect between rotational treatments and other treatments and a weak effect between intercropping and monocropping. There was no evidence for an overall advantage of systems where residues are retained (in combination with direct seeding or planting basins) over conventional management with respect to maize yield. A season effect was evident although the strong benefit of rotation in El Niño season was also reduced, highlighting the strong interaction between treatment and climatic conditions. The power analysis shows that treatment effects of practically significant magnitude may be unlikely to be detected with just four replicates, as at Chitedze, under either a simple randomised control trial or a factorial experiment. Given logistical and financial constraints, it is important to design trials with fewer treatments but more replicates to gain enough statistical power and to pay attention to the selection of treatments to given an informative outcome.
526			_aMCRP _bFP1
546			_aText in English
650		7	_aClimate-smart agriculture _2AGROVOC _92419
650		7	_aDiversification _2AGROVOC _93027
650		7	_aSustainable agriculture _2AGROVOC _92327
650		7	_aZero tillage _2AGROVOC _91753
700	0		_aIvy Sichinga Ligowe _96054
700	1		_aThierfelder, C. _gSustainable Intensification Program _gSustainable Agrifood Systems _8INT2939 _9877
700	1		_aMagwero, N. _915371
700	1		_aNamaona, W. _915372
700	1		_aNjira, K. _915373
700	1		_aSandram, I. _915374
700	1		_aChimungu, J.G. _915375
700	0		_aPatson Cleoups Nalivata _96055
773	0		_gv. 56, no. 4, p. 506-527 _dCambridge (United Kingdom) : Cambridge University Press, 2020. _x0014-4797 _tExperimental Agriculture _wu444498
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/20938
942			_cJA _n0 _2ddc