Optimization of Culture Conditions for Zinc Phosphate Solubilization by Aspergillus sp. Using Response Surface Methodology

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Ramesh, VetukuriSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Växtskyddsbiologi,Department of Plant Protection Biology (author)

Optimization of Culture Conditions for Zinc Phosphate Solubilization by Aspergillus sp. Using Response Surface Methodology

Article/chapterEnglish2022

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2022-01-10
Springer Science and Business Media LLC,2022
,2024

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LIBRIS-ID:oai:slubar.slu.se:115683
https://res.slu.se/id/publ/115683URI
https://doi.org/10.1007/s42729-021-00709-4DOI

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Language:English
Summary in:English

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Subject category:art swepub-publicationtype

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Zinc (Zn) is an essential trace element for plant growth and development, but Zn deficiency is common in many types of soil, due to either low total Zn concentrations or low availability of soluble, plant-accessible forms. In the latter cases, harnessing microorganisms' potential to solubilize Zn can play an important eco-friendly role in sustainable agriculture. However, micro-organisms' in vitro solubilization potential is strongly influenced by their culture medium's composition, which must therefore be optimized when screening and applying microorganisms as biofertilizers. In order to have modeling effects of varying levels of a carbon source (fructose, 5-30 g L-1), a nitrogen source (ammonium sulfate, 2-10 g L-1), and zinc phosphate (Zn-3(PO4)(2), 2-15 g L-1) on Aspergillus-mediated Zn release from the zinc phosphate, a central composite design (CCD) experiment with 20 combinations of surface variables and surface response method was used. The resulting model had high predictive ability (R-2 = 0.9454), and showed that the Zn-3(PO4)(2) and (NH4)(2)SO4 concentrations were the first and second most important factors for amounts of Zn released, respectively. The results also indicated that 14.6 g L-1 fructose, 10 g L-1 (NH4)(2)SO4, and 15 g L-1 Zn-3(PO4)(2) was the optimal combination for maximizing Zn release under our culture conditions. It concluded that the study highlights the utility of response surface modeling for optimizing multiple cultivation variables when screening microbial taxa for solubilizing Zn, or maximizing other microbial activities.

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Kushwaha, Sandeep KumarSwedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för växtförädling,Department of Plant Breeding,National Institute of Animal Biotechnology(Swepub:slu)104885 (author)
Sveriges lantbruksuniversitetVäxtskyddsbiologi (creator_code:org_t)
Sveriges lantbruksuniversitet

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In:Journal of Soil Science and Plant Nutrition: Springer Science and Business Media LLC22, s. 1009-10180718-95080718-9516

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