Development of Ternary Concrete Utilizing Agricultural Waste Material

The present project proposes to utilize rice husk and maize cob husk ash in the cement to mitigate the adverse impact of cement on environment and to enhance the disposal of waste in a sustainable manner. Ternary concrete / MR concrete was prepared by using rise husk and maize cob ash with cement. For the present project, five concrete mixes MR-0 (Control mix), MR-1 (Rice husk ash 10% and MR-2.5%), MR-2 (Rice husk ash 10% and MR-5%), MR-3 (Rice husk ash 10% and MR-2.5%), MR-4 (Rice husk ash 10% and MR-2.5%) were prepared. M35 concrete mix was designed as per IS 10262:2009 for low slump values 0-25mm. The purpose is to find the optimum replacement level of cement in M35 grade ternary concrete for I – Shaped paver blocks.In order to study the effects of these additions, micro-structural and structural properties test of concretes have been conducted. The crystalline properties of control mix and modified concrete are analyzed by Fourier Transform Infrared Spectroscope (FTIR), Scanning Electron Microscopy (SEM), and X-Ray Diffraction (XRD). The results indicated that 10% Rice husk ash and 5% maize cob ash replaced with cement produce a desirable quality of ternary concrete mix having good compressive strength. The results of SEM analysis indicated that the morphology of both concrete were different, showing porous structure at 7 days age and become unsymmetrical with the addition of ashes. After 28 day age, the control mix contained more quantity of ettringite and became denser than ternary concrete. XRD analysis revealed the presence of portlandite in large quantity in controlled mix concrete while MR concrete had the partially hydrated particle of alite.

Mechanism and isotherm modeling of effective adsorption of malachite green as endocrine disruptive dye using Acid Functionalized Maize Cob (AFMC)

Cationic Malachite green has been identified as a candidate for the endocrine disruptive compound found in the environment. In this study, the mechanism and isotherm modeling of effective adsorption of cationic malachite green dye onto acid-functionalized maize cob (AFMC) was investigated by batch technique. The operational parameters such as initial concentration (100–600 mg/L); contact time (10–120 min) and pH (3–10) influenced the removal efficiency and quantity adsorbed. A maximum of 99.3% removal efficiency was obtained at optimum conditions. AFMC physicochemical properties (surface area 1329 m2/g and particle size 300 μm < Ф < 250 μm) enhanced its efficiency. Based on R2 > 0.97 and consistently low values of adsorption statistical error functions (ASEF), equilibrium data were best fitted to Freundlich isotherm. Kinetic data were best described by a pseudo-second-order model with consistent R2 > 0.98 and validated by ASEF. The mechanism of the process was better described by intraparticle diffusion. Evidence of the adsorption process was confirmed by the change in morphology via Scanning Electron Microscopy (SEM) and surface chemistry by Fourier Transform infrared (FTIR). The performance of AFMC enlisted it as a sustainable and promising low-cost adsorbent from agro-residue for treatment of endocrine disruptive dye polluted water.

DeepCob: precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics

Background Maize cobs are an important component of crop yield that exhibit a high diversity in size, shape and color in native landraces and modern varieties. Various phenotyping approaches were developed to measure maize cob parameters in a high throughput fashion. More recently, deep learning methods like convolutional neural networks (CNNs) became available and were shown to be highly useful for high-throughput plant phenotyping. We aimed at comparing classical image segmentation with deep learning methods for maize cob image segmentation and phenotyping using a large image dataset of native maize landrace diversity from Peru. Results Comparison of three image analysis methods showed that a Mask R-CNN trained on a diverse set of maize cob images was highly superior to classical image analysis using the Felzenszwalb-Huttenlocher algorithm and a Window-based CNN due to its robustness to image quality and object segmentation accuracy ($$r=0.99$$ r = 0.99 ). We integrated Mask R-CNN into a high-throughput pipeline to segment both maize cobs and rulers in images and perform an automated quantitative analysis of eight phenotypic traits, including diameter, length, ellipticity, asymmetry, aspect ratio and average values of red, green and blue color channels for cob color. Statistical analysis identified key training parameters for efficient iterative model updating. We also show that a small number of 10–20 images is sufficient to update the initial Mask R-CNN model to process new types of cob images. To demonstrate an application of the pipeline we analyzed phenotypic variation in 19,867 maize cobs extracted from 3449 images of 2484 accessions from the maize genebank of Peru to identify phenotypically homogeneous and heterogeneous genebank accessions using multivariate clustering. Conclusions Single Mask R-CNN model and associated analysis pipeline are widely applicable tools for maize cob phenotyping in contexts like genebank phenomics or plant breeding.

Design of locally sourced activated charcoal filter from maize cob for wastewater decontamination: an approach to fight waste with waste

This research studied decontamination of laboratory wastewater with an activated carbon derived from maize cob, an agricultural waste to ascertaining its adsorption effectiveness for water treatment. The preparation conditions such as the concentration of the activating agent, impregnation ratio, impregnation temperature, impregnation time, activation temperature and activation time were optimized. The adsorbent’s porous properties revealed its adsorption potency was correlated with the iodine value. The test adsorbent showed significant contaminants adsorption in the laboratory wastewater; the results obtained were within the standards for drinking water set by the regulatory agencies. This agricultural waste could be considered for the preparation of activated carbon which would ultimately serve as an alternative method of decontaminating laboratory wastewater.

OPTIMIZATION OF LACCASE PRODUCTION BY CURVULARIA LUNATA USING MAIZE COB AS SUBSTRATE

Researchers are showing interest in laccase because it is able to degrade several lignocellulosic biomass. It is important to optimize laccase production to achieve higher yield at a lower cost using agricultural wastes. This study was aimed at optimizing the culture conditions for laccase production. Previously isolated and characterized laccase producing Curvularia lunata was collected from the laboratory of Microbiology department, ABU, Zaria. Maize cobs which were used as substrate were collected from Seed Processing Unit of Institute for Agricultural Research, Zaria and the proximate composition of the substrate was determined according to AOAC guideline. The optimum fermentation type for laccase production was determined after which the culture conditions for laccase production were optimized. Laccase activity was determination by guaiacol assay. The proximate compositions of the maize cob were found to be Moisture content (3.18%), Crude protein (2.50%), Crude fat (32.20%), Crude fibre (3.15), Ash content (1.88%) and Carbohydrate content (57.09%). Higher laccase activity was recorded under solid state fermentation compared to submerged fermentation. The optimum culture conditions were found to be inoculum size 3 x 5 mm, pH 5, incubation temperature 30 oC and incubation period of 6 days. The culture conditions for laccase production by Curvularia lunata using maize cob as substrate were optimized

Engineering Properties of Concrete with a Ternary Blend of Fly Ash, Wheat Straw Ash, and Maize Cob Ash

In recent years, recycled materials mostly available in abundant quantities in local agricultural fields are considered as potential constituent material for concrete production. Also, cement production emits many toxic gases in the atmosphere, which causes environmental pollution and greenhouse gases. Thus, recyc;ed materials, such as fly ash (FA), wheat straw ash (WSA), and maize corn ash (MCA) are condered as cementitious binders in concrete for sustainable development. This study aims to determine the engineering properties of concrete with a ternary blend of fly ash, wheat straw ash, and maize cob ash. A total of 73 concrete cubes, 42 reinforced concrete prisms and 42 concrete cylinders were cast to examine mechanical properties of concrete at 7, 28, and 56 curing days. At 28 days (maturity period), the experimental results showed an increase in compressive, tensile, and flexural strength by 12.28%, 9.33%, and 9.93%, respectively, at 9% substitution of ternary cementitious materials (TCM). However, the density of concrete was reduced by 9.92%, with an increase in the TCM content after 28 days. Moreover, the modulus of elasticity was improved by 14.23% with an increase in the content of TCM up to 18% after 28 days, and drying shrinkage of concrete was reduced with the introduction of TCM content after 50 days. However, the workability of fresh concrete decreased as the percentage of TCM increased. Results of this study proved that agricultural materials investgated could be good fit as binder in cementitious composites.