000			04562nab|a22004577a|4500
001			69572
003			MX-TxCIM
005			20251123184651.0
008			251121s2025||||ne |||p|op||||00||0|eng|d
022			_a0378-4290
022			_a1872-6852 (Online)
024	8		_ahttps://doi.org/10.1016/j.fcr.2025.109988
040			_aMX-TxCIM
041			_aeng
100	1		_aKamara, A. Y. _96761
245	1	0	_aEvaluation and application of the CROPGRO – Cowpea model for simulating appropriate sowing window and planting density of cowpea varieties across contrasting environments
260			_aNetherlands : _bElsevier B.V., _c2025.
500			_aPeer review
500			_aOpen Access
520			_aContext: Cowpea [Vigna unguiculata (L.) Walp.] is an important legume crop in sub-Saharan Africa where its grain and fodder are valued for food and feed. Grain yields are, however, low due to several biotic and abiotic constraints. Several improved stress-tolerant varieties and complementary agronomic management technologies have been developed to enhance its productivity and sustainability. Cropping simulation models are useful tools for evaluating the deployment of crop varieties and management options for target locations. While the CSM-CROPGRO model in DSSAT has been used to simulate the performance of several legume crops, only a few studies have evaluated and used the relatively new CSM-CROPGRO-cowpea model for use in West Africa. Objectives: The objectives of this study were to (i) evaluate the performance of the CSM-CROPGRO-Cowpea model in simulating the cowpea growth and yields in contrasting environments (ii) use the model to assess the optimal sowing window and planting density of cowpea varieties across contrasting environments in the savannas of Nigeria. Methods: Here, we used comprehensive savanna-wide datasets to calibrate and validate the CSM-CROPGRO-cowpea model for savannah environments. The evaluated model was then applied to assess the yield performance of cowpea varieties with varying plant densities and six sowing windows across four sites considering 36 growing seasons. Results: The model accurately simulated cowpea phenology (RMSE 0.58–0.67 day; nRMSE 1.36–1.46 %; d-index > 0.90 for days to flowering, RMSE 0.82–1.73 days; nRMSE 1.09–2.29 %; d-index 0.88–0.99 for days to physiological maturity), grain yield (RMSE 86–121 kg ha−1; nRMSE 3.66–6.14 %; d-index > 0.90) and total dry matter (RMSE 260–295 kg ha−1; nRMSE 4.79–10.73 %; d-index = 0.87–0.95). The long-term simulation results indicate that SAMPEA 9 showed no response to sowing density beyond 13.3 plants m–2 across all locations, likely due to interplant competition at higher densities. In contrast, the simulated yield of SAMPEA 14 and FUAMPEA 1 increased as plant density increases from 13.3 to 40 plants m⁻². In northern Guinea savanna, sowing could be delayed until July 14 at Demsa and July 29 at Zaria for all tested varieties. In the Sudan savanna AEZ (SS), sowing should be done between July 1 and 14 for all varieties, beyond which there will be a significant reduction in yield. Conclusion: Except for SAMPEA 9, the simulated optimum planting density for all the varieties is 40 plants m–2 in all AEZ, while the sowing window was dependent on location and AEZ. The variety SAMPEA 9 was the most yield-stable variety across the tested environments and did not require planting density above the current industry recommendations of 13.3 plants m−2. This study could fill the knowledge gap in understanding optimal cowpea management opportunities needed to maximize productivity and strengthen cropping resilience.
546			_aText in English
650		7	_aDecision support _2AGROVOC _916361
650		7	_aTechnology transfer _2AGROVOC _96415
650		7	_aCowpeas _2AGROVOC _95144
650		7	_aPlant population _2AGROVOC _91211
650		7	_aSowing _2AGROVOC _91801
650		7	_aVarieties _2AGROVOC _91303
650		7	_aEnvironment _2AGROVOC _91098
700	1		_aSolomon, R. _96830
700	1		_aTofa, A. I. _96828
700	1		_aGarba, I. I. _96764
700	1		_aEseigbe, O.B. _940619
700	1		_aJibrin, J. M. _96760
700	1		_aOmoigui, L. _96833
700	0		_aKamaluddin Tijjani Aliyu _8001714253 _gSustainable Agrifood Systems _937565
700	1		_aAdeleke, M.A. _937571
700	1		_aBebeley, J.F. _940620
700	1		_aJerome, H.P. _940621
773	0		_tField Crops Research _gv. 331, art. 109988 _dNetherlands : Elsevier B.V., 2025. _x0378-4290 _wG444314
942			_cJA _n0 _2ddc
999			_c69572 _d69564