Bioinformatics

Biography

Biography: Dago Dougba Noel

Abstract

Several studies showed the importance of rhizobacteria (P. fluorescens) associated to natural fertilizer improving cereal production in poor and arid soils. However, agriculture crops prediction by statistical models remains an adequate system to assess the performance of bio-fertilizer used in farming practices. Indeed, the large amount of data to process in this context allowed the integration of computers in the statistical analysis schemes. Computational statistic can be defined as the explicit impact of computers on statistical methodology. Here,we developed a bioinformatics pipeline in R bio-statistic environment assessing the relationship between previous analyzed rhizobacteria (P. fluorescens) treatments (T0: treatment without any rhizobacteria and any foliar bio-fertilizer, T1: treatment with only rhizobacteria, T2: treatment with both rhizobacteria and foliar bio-fertilizer and T3: treatment with only foliar bio-fertilizer)and their potential influences on growth and yield parameters of both maize and soybean cereal varieties in arid soil in the north of Côte d'Ivoire. Then, the present survey basing on the computational statistic approach, highlighted a strong difference between the four considered rhizobacteria treatments impacting the two analyzed cereal crops and development process (p-values < 0.05). Moreover, the same analysis suggested a positive and selective effect of rhizobacteria (P. fluorescens) combined with foliar bio-fertilizer on both quantitative and qualitative production of analyzed cereal crop varieties. Indeed, we were able to demonstrate the differences between maize and soybean crops replying torhizobacteria (P. fluorescens) bio-fertilizer treatments. Further, the present developed pipeline showed that the two analyzed varieties of soybean (green and yellow soybean) were differentially influenced by the different rhizobacteria treatments as opposed to maize plant varieties (p-value < 0.05). Finally our findings evidenced that disregarding analyzed parameters and cereal varieties, treatment T2 having the recommended dose of rhizobacteria P. fluorescens+ foliar fertilizer compost recorded the best performance improving both maize (Zea mays. L) and soybean (Glycine max) cereals cultivation in arid region. In conclusion this study demonstrated the key role of rhizobacteria (P. fluorescens) combined with foliar bio-fertilizer improving cereal production in soil with low fertility aptitude, adjusting the concordance between both growth and yield parameters.