African Journal of
Microbiology Research

  • Abbreviation: Afr. J. Microbiol. Res.
  • Language: English
  • ISSN: 1996-0808
  • DOI: 10.5897/AJMR
  • Start Year: 2007
  • Published Articles: 4900

Full Length Research Paper

Predicting maize and soybean crops dry biomass through rhizobacteria microorganisms activity on foliar bio-fertilizer in an arid agro-climate: A multiple linear regression analysis

Noel Dougba Dago
  • Noel Dougba Dago
  • Unité de Formation et de Recherche (UFR) des Sciences Biologiques, Département de Biochimie-Génétique, Université Peleforo Gon Coulibaly BP 1328 Korhogo, Côte d’Ivoire.
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Nafan Diarrassouba
  • Nafan Diarrassouba
  • Unité de Formation et de Recherche (UFR) des Sciences Biologiques, Département de Biochimie-Génétique, Université Peleforo Gon Coulibaly BP 1328 Korhogo, Côte d’Ivoire.
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Martial Didier Yao Saraka
  • Martial Didier Yao Saraka
  • Unité de Formation et de Recherche (UFR) des Sciences Biologiques, Département de Biochimie-Génétique, Université Peleforo Gon Coulibaly BP 1328 Korhogo, Côte d’Ivoire.
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Jean-Luc Aboya Moroh
  • Jean-Luc Aboya Moroh
  • Unité de Formation et de Recherche (UFR) des Sciences Biologiques, Département de Biochimie-Génétique, Université Peleforo Gon Coulibaly BP 1328 Korhogo, Côte d’Ivoire.
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Inza Jesus Fofana
  • Inza Jesus Fofana
  • Unité de Formation et de Recherche (UFR) des Sciences Biologiques, Département de Biochimie-Génétique, Université Peleforo Gon Coulibaly BP 1328 Korhogo, Côte d’Ivoire.
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Lamine Baba-Moussa
  • Lamine Baba-Moussa
  • Faculté des Sciences et Techniques, Laboratoire de Biologie et de Typage Moléculaire en Microbiologie, Université d’Abomey-Calavi, Cotonou, Benin.
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Adama Coulibaly
  • Adama Coulibaly
  • Unité de Formation et de Recherche (UFR) des Sciences Biologiques, Département de Biochimie-Génétique, Université Peleforo Gon Coulibaly BP 1328 Korhogo, Côte d’Ivoire.
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  •  Received: 22 May 2018
  •  Accepted: 04 September 2018
  •  Published: 14 September 2018

Abstract

After previously showing rhizobacteria Pseudomonas fluorescence and foliar bio-fertilizer mixture as a suitable practice in improving maize and soybean crops development and dry biomass, this study thus embark on predicting the above-mentioned plants dry biomass feature through their yield and growth parameters by assessing P. fluorescence activities on foliar bio-fertilizer in an arid agro-climate. For this purpose, several scripts and functions from our previous computational statistic pipeline, developed in R programming environment were partially used for statistical survey. Several multiple linear regression models have been achieved aimed at understanding the links between maize and soybean crops (i) dry biomass, (ii) yield and (iii) growth features as well as highlights the synergic roles of rhizobacteria microorganisms and foliar bio-fertilizer on that relationship. Findings, revealed as expected, a significant difference in term of crops development between plants from seeds without treatment and those from seeds under (i) rhizobacteria, (ii) rhizobacteri + foliar bio-fertilizer mixture and (iii) foliar bio-fertilizer treatments (p<0.05). Also, yield parameters exhibited a substantial variability reacting to rhizobacteria microorganism as well as to rhizobacteria microorganism + foliar bio-fertilizer mixture as opposed to growth features. Hence, the present results clearly showed significant difference between rhizobacteria microorganism and foliar bio-fertilizer activities impacting both maize and soybean crops yield and growth features (p<0.05). Indeed, findings suggested a selective impact of rhizobacteria microorganisms (P. fluorescence) on processed plants yield features. The same findings  exhibited P. fluorescence and foliar bio-fertilizer mixture, as adjusting the synergy between both processed crops growth and yield parameters by improving dry biomass feature (p= 0.17). Finally, this study emphasized rhizobacteria microorganism’s activities on foliar bio-fertilizer in an arid agro-climate low fertile soil as a weighty promoter improving maize and soybean crops dry biomass by normalizing the relationship concerning growth and yield features.

 

Key words: Rhizobacteria (Pseudomonas fluorescence), growth and yield parameters, dry biomass, maize (Zea mays. L.) and soybean (Glycine max), computational statistic.