Cotton yield decrease in Côte d’Ivoire are important because of the climate change and pest infestations. The target of this survey is to analyze the spatio-temporal dynamics of Intra-Seasonal Descriptors (ISD) of rainfall and the annual mean infestation levels (MILs) of two pests, Helicoverpa armigera and Jacobiella facialis, as well as their interactions. The analysis datas are mainly constituted of annual rainfall and entomological data of H. armigera and J. facialis covering the period 1971-2016. The spatio-temporal distributions of rainfall ISDs and pest MILs were statistically analyzed, mapped, and their interactions determined using Instat+ and Surfer 11 software. Outcomes showed an interannual variability in rainfall ISDs, with coefficients of variation exceeding 30%. For H. armigera, MIL peaks shifted from the South and Center (1995–2000) to the Center-East and North-East (2011–2016), with an overall declining trend in MILs, attributable to the adoption of the Insecticide Resistance Management Program (IRMP) in 1999. However, a recent increase in peak levels suggests that climatic conditions particularly reduced cumulative rainfall and fewer rainy days favor its development. Regarding J. facialis, MILs increased from 3 to 16 infested plants per 30 plants, due to the IRMP’s limited focus on this pest, with the infestation hotspot shifting from the North (1995-2000) to the North-East and Center-East (2011-2016). These results demonstrated the relevance of integrating climatic conditions into pest management strategies.
The increasing rainfall variability in West Africa is a great challenge for crop productivity in small-scale farming systems, thus jeopardizing food security. Rainfed rice is particularly sensitive to inconsistent rainfall, especially during the reproductive stage. It is, therefore, necessary to develop management practices suited to the change of rainfall pattern over the growth seasons. In this study, the modeling technology with the rice model ORYZA (v3) was used to identify appropriate rainfed rice growing seasons for a better adaptation of farmers to climate variability. The potential yields, the favorable sowing periods, the optimum sowing dates, and the attainable yields of two contrasted cultivars were determined. After successfully calibrating and validating the model, it predicted potential yields of 5.5 to 6.5 tons/ha for the early maturing variety WAB56-104 (90-100 days), while potential yields of 4 to and 5.5 tons/ha was predicted for the late maturing variety CG14 (115-125 days). In rainfed conditions, two favorable sowing periods were identified from the model scenario analysis. The first period spans from late February to late April and the second from late July to early September. Farmers can double their actual yield of 1.5 tons/ha if they follow the recommended sowing dates and good agricultural practices. Indeed, the yield of 3.5 tons/ha was found with the variety WAB 56-104 sown on around 16 April in San-Pedro and around 2 April in Dimbokro. The yield of 3 tons/ha for the variety CG14 could be achieved if the sowing is done on around 18 March in San-Pedro and around 21 March in Dimbokro.