In the present work, we studied the effect of critical electrogalvanizing parameters on the quality of electrodeposited Zn films. The current density, electrodeposition time, and ZnCl2 concentration of electrolyte were optimized to maximize current efficiency and brightness, and also, to minimize the surface roughness. Importantly, regression models of the response variables were developed. These models could help industrial applications by providing definitive process conditions to obtain Zn coatings at a desired thickness, roughness and brightness with a high current efficiency. First, preliminary studies were conducted to determine the initial levels of the designated factors. Then, the optimization was conducted through the Central Composite Design by Design-Expert (trial version). Upon completion of the optimization, analysis of variance was also performed. The optimum values of current density, coating duration and ZnCl2 concentration were determined as 3.7 A/dm 2 , 4.4 minutes, and 50 g/L, respectively, at a thickness of 6 m. Finally, a set of Zn films were deposited at this optimum conditions. The characterization of these films showed that the experimental results were in good accordance with model predictions, providing a bright (L*=83.69) and smooth (Ra=0.75 µm) coating with excellent adhesion to steel substrate (pull-off strength > 29.4 MPa) at a current efficiency of 98.7%.
Common bean is considered a recalcitrant crop for in vitro regeneration and needs a repeatable and efficient in vitro regeneration protocol for its improvement through biotechnological approaches. In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. Plumular apice explants pretreated with 20 mg/L BAP exerted a negative impact and resulted in minimum shoot regeneration frequency and shoot count, but produced longer shoots. All output variables (shoot regeneration frequency, shoot counts, and shoot length) increased significantly with the enhancement of BAP concentration in the post-treatment medium. Interaction of the pretreatment × post-treatment medium revealed the need for a specific combination for inducing a high shoot regeneration frequency. Higher shoot count and shoot length were achieved from the interaction of 5 mg/L BAP × 1.00 mg/L BAP followed by 10 mg/L BAP × 1.50 mg/L BAP and 20 mg/L BAP × 1.50 mg/L BAP. The evaluation of data through ML models revealed that R2 values ranged from 0.32 to 0.58 (regeneration), 0.01 to 0.22 (shoot counts), and 0.18 to 0.48 (shoot length). On the other hand, the mean squared error values ranged from 0.0596 to 0.0965 for shoot regeneration, 0.0327 to 0.0412 for shoot count, and 0.0258 to 0.0404 for shoot length from all ML models. Among the utilized models, the multilayer perceptron model provided a better prediction and optimization for all output variables, compared to other models. The achieved results can be employed for the prediction and optimization of plant tissue culture protocols used for biotechnological approaches in a breeding program of common beans.
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