Designing cotton ideotypes for the future: Reducing risk of crop failure for low input rainfed conditions in Northern Cameroon
Climate change is threatening the ability to grow cotton (Gossypium hirsutum L.) under low input rainfed production areas in Sub-Saharan Africa. In Northern Cameroon, yield has been declining due to unsuitable cropping practices such as sub-optimal planting dates, along with an absence in genetic gain. The aim of this study was to use a cropping system model (DSSAT CSM-CROPGRO-Cotton) to identify the best cultivars (ideotypes) for Northern Cameroon that are adapted to low input rainfed productions systems for 2050 under RCP4.5 and RCP8.5. Calibration and evaluation of the CSM-CROPGRO-Cotton were performed with field observations for two cultivars (Allen Commun and L484). For RCP4.5 and RCP8.5, 50 replications for 2050 were generated based on an ensemble of 17 Global Circulating Models. In total, 3125 virtual cultivars representing existing genetic variability for phenology, morphology and photosynthesis were simulated. Thereafter, they were evaluated for performance under the projected future climate based on potential yield and the resilience of yield to sub-optimal planting date. The widely cultivated cultivar L484 will be unsuitable under projected future climate, due to boll opening during the middle of the rainy season (median: 10/09 under RCP4.5 and 12/09 under RCP8.5). None of the ideotypes tested could optimize both yield and resilience (Pearson correlation <−0.82). However, compared to the current cultivar L484, two virtual ideotypes were identified: (a) “Ideo_sub” had a wide planting window, especially in the 10 worst replications of 2050, up to +5 days in RCP8.5; (b) “Ideo_Pot” had a high potential yield trait with low resilience to sub-optimal planting date, in the 10 worst replications of 2050, +530 kg ha−1 in RCP4.5 and +591 kg ha−1 in RCP8.5. Both ideotypes had an earlier anthesis date, a longer reproductive duration, and increase in the maximum photosynthetic rate. Therefore, breeding programs should consider these traits suggested by this system analysis using a crop simulation model for the identification of suitable cultivars under the projected future climate.
| Summary: | Climate change is threatening the ability to grow cotton (Gossypium hirsutum L.) under low input rainfed production areas in Sub-Saharan Africa. In Northern Cameroon, yield has been declining due to unsuitable cropping practices such as sub-optimal planting dates, along with an absence in genetic gain. The aim of this study was to use a cropping system model (DSSAT CSM-CROPGRO-Cotton) to identify the best cultivars (ideotypes) for Northern Cameroon that are adapted to low input rainfed productions systems for 2050 under RCP4.5 and RCP8.5. Calibration and evaluation of the CSM-CROPGRO-Cotton were performed with field observations for two cultivars (Allen Commun and L484). For RCP4.5 and RCP8.5, 50 replications for 2050 were generated based on an ensemble of 17 Global Circulating Models. In total, 3125 virtual cultivars representing existing genetic variability for phenology, morphology and photosynthesis were simulated. Thereafter, they were evaluated for performance under the projected future climate based on potential yield and the resilience of yield to sub-optimal planting date. The widely cultivated cultivar L484 will be unsuitable under projected future climate, due to boll opening during the middle of the rainy season (median: 10/09 under RCP4.5 and 12/09 under RCP8.5). None of the ideotypes tested could optimize both yield and resilience (Pearson correlation <−0.82). However, compared to the current cultivar L484, two virtual ideotypes were identified: (a) “Ideo_sub” had a wide planting window, especially in the 10 worst replications of 2050, up to +5 days in RCP8.5; (b) “Ideo_Pot” had a high potential yield trait with low resilience to sub-optimal planting date, in the 10 worst replications of 2050, +530 kg ha−1 in RCP4.5 and +591 kg ha−1 in RCP8.5. Both ideotypes had an earlier anthesis date, a longer reproductive duration, and increase in the maximum photosynthetic rate. Therefore, breeding programs should consider these traits suggested by this system analysis using a crop simulation model for the identification of suitable cultivars under the projected future climate. |
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