Aim:  Isolation and characterization of a bacterial isolate (strain FP10) from banana rhizosphere with innate potential as fungal antagonist and microbial adjuvant in micropropagation of banana. Methods and Results:  Bacterium FP10 was isolated from the banana rhizosphere and identified as Pseudomonas aeruginosa based on phenotypic, biochemical traits and sequence homology of partial 622‐bp fragment of 16S ribosomal DNA (rDNA) amplicon, with the ribosomal database sequences. Strain FP10 displayed antibiosis towards fungi causing wilt and root necrosis diseases of banana. Production of plant growth hormone, indole‐3‐acetic acid (IAA), siderophores and phosphate‐solubilizing enzyme in FP10 was determined. Strain FP10 tested negative for hydrogen cyanide, cellulase and pectinase, the deleterious traits for plant growth. Screening of antibiotic genes was carried out by polymerase chain reaction using gene‐specific primers. Amplification of a 745‐bp DNA fragment confirmed the presence of phlD, which is a key gene involved in the biosynthesis of 2,4‐diacetylphloroglucinol (DAPG) in FP10. The antibiotic produced by FP10 was confirmed as DAPG using thin layer chromatography, high performance liquid chromatography and Fourier transform infrared and tested for fungal antibiosis towards banana pathogens. Procedures for encapsulation of banana shoot tips with FP10 are described. Conclusions:  Strain FP10 exhibited broad‐spectrum antibiosis towards banana fungi causing wilt and root necrosis. DAPG by FP10 induced bulb formation and lysis of fungal mycelia. Encapsulation of banana shoot tips with FP10 induced higher frequency of germination (plantlet development) than nontreated controls on Murashige and Skoog basal medium. Treatment of banana plants with FP10 enhanced plant height and reduced the vascular discolouration as a result of Fusarium oxysporum f. sp. cubense FOC. Significance and Impact of the Study:  Because of the innate potential of fungal antibiosis by DAPG antibiotic and production of siderophore, plant‐growth‐promoting IAA and phosphatase, the strain FP10 can be used as biofertilizer as well as a biocontrol agent.

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Machining processes have emerged as an important requirement in product design concepts, manufacturing applications, and the overall functional aspects of the product. For machining a component, it is important to understand the characteristics of work material in order to choose the appropriate cutting tool and to fix a set of machining parameters to achieve optimum output. This article presents the details of experiments conducted for machining Inconel 718, by turning process, with two different coated carbide tool inserts (KC5525 and HK150), with an objective of optimizing the process. Furthermore, four different analytical models were developed, validated, and compared to exhibit their performance in establishing the input–output relationship. A set of input machining parameters were chosen to yield a higher material removal rate (MRR), coupled with a moderate surface finish. Experimental data were generated for the chosen set of input parameters and the resultant output parameter and the machining performance of the two tool inserts was compared. With the above experimental data, Analytical models were developed, using genetic programming (GP), artificial neural networks (ANN), adaptive neuro‐fuzzy inference system (ANFIS) and the mathematical regression models with an objective of minimizing the surface roughness while turning Inconel‐718. The effect of machining parameters on the surface roughness was evaluated and the optimum machining condition for minimizing the surface roughness was determined; further the order of influencing input parameters was brought out. Prediction accuracy of the four models was established and the above models were validated, using the different set of experimental data. Comparison of performance of the four models is discussed, extent of prediction accuracy of each model is brought out and the advantages, disadvantages, and limitations of the four models are outlined in this article. This shall be a reference to the machinists to choose appropriate cutting parameters to meet the surface finish requirements demanded by the product designers.

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