Bradyrhizobium as the Only Rhizobial Inhabitant of Mung Bean (Vigna radiata) Nodules in Tropical Soils: A Strategy Based on Microbiome for Improving Biological Nitrogen Fixation Using Bio-Products

The mung bean has a great potential under tropical conditions given its high content of grain protein. Additionally, its ability to benefit from biological nitrogen fixation (BNF) through association with native rhizobia inhabiting nodule microbiome provides most of the nitrogen independence on fertilizers. Soil microbial communities which are influenced by biogeographical factors and soil properties, represent a source of rhizobacteria capable of stimulating plant growth. The objective of this study is to support selection of beneficial bacteria that form positive interactions with mung bean plants cultivated in tropical soils, as part of a seed inoculation program for increasing grain yield based on the BNF and other mechanisms. Two mung bean genotypes (Camaleão and Esmeralda) were cultivated in 10 soil samples. Nodule microbiome was characterized by next-generation sequencing using Illumina MiSeq 16S rRNA. More than 99% of nodule sequences showed similarity with Bradyrhizobium genus, the only rhizobial present in nodules in our study. Higher bacterial diversity of soil samples collected in agribusiness areas (MW_MT-I, II or III) was associated with Esmeralda genotype, while an organic agroecosystem soil sample (SE_RJ-V) showed the highest bacterial diversity independent of genotype. Furthermore, OTUs close to Bradyrhizobium elkanii have dominated in all soil samples, except in the sample from the organic agroecosystem, where just B. japonicum was present. Bacterial community of mung bean nodules is mainly influenced by soil pH, K, Ca, and P. Besides a difference on nodule colonization by OTU sequences close to the Pseudomonas genus regarding the two genotypes was detected too. Although representing a small rate, around 0.1% of the total, Pseudomonas OTUs were only retrieved from nodules of Esmeralda genotype, suggesting a different trait regarding specificity between macro- and micro-symbionts. The microbiome analysis will guide the next steps in the development of an inoculant for mung bean aiming to promote plant growth and grain yield, composed either by an efficient Bradyrhizobium strain on its own or co-inoculated with a Pseudomonas strain. Considering the results achieved, the assessment of microbial ecology parameters is a potent coadjuvant capable to accelerate the inoculant development process and to improve the benefits to the crop by soil microorganisms.

Kinetic modelling of phenol co-oxidation using horseradish peroxidase

Phenol is an industrial pollutant and its removal from industrial wastewaters is of great importance. In order to design optimised phenol removal procedures by using horseradish peroxidase-based systems, there are some points that have to be dealt with. One of the most important issues is the need for reliable kinetics as this is one of the difficulties found during process scale-up. Although simplified kinetics can be used for limited ranges of operating conditions, they are not usually reliable for the description of varying process conditions. The present work describes the implementation of a kinetic model, based on a mechanism, for the co-oxidation of phenol and 4-aminoantipyrine (Am-NH2), which is used as a chromogen agent, with hydrogen peroxide as the oxidant. The model covers not only the variation of the concentrations of all the species involved, but also the effect of temperature in the reaction. The estimation of kinetic rate constants and activation energies for the various steps in the mechanism is performed with a single optimisation procedure, and all the experimental results are described using a unique set of parameters, which, thus, is valid over an extended range of operating conditions. The mechanism allowed the determination of a reliable kinetic model which is appropriate for the range of experimental conditions used. The computational model was also tested with an independent set of experiments with different conditions from the ones for which the parameters were estimated.