(An ISO 9001:2008 Certified Online Journal) ISSN:2455-9660

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Volume 02 Issue 10 (October-2017) | IJERAS

Title: Fabrication and Reinforcement of Composite Plate Using Natural Fiber (Coir)

Authors: Mr RAVI SHANKAR, JEEVA P , SATHYA NARAYANAN K, NIVEDHA

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Due to increase in global warming the scientist are focusing more on the use of natural fibres like coir, jute, bagasse, etc. This has created awareness among the people to use natural fibre as much as possible to decrease global warming. In past years there has been an effort to develop composites and to replace the global warming producing products by using composite materials. Since there is variety of natural fibre available in India it gives attention to develop the composite materials. Reinforcement in natural fibre has gained attention due to low cost, easy availability and low density of the products. Agriculture waste can also be used to create the natural fibres reinforced composite for daily use. Although glass and other products have high specific strength their field of applications are very less. In such a time a investigation has been used to use coir instead of other composite materials.

Page 1-2

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Title: Chemometric classification of broad beans (Vicia faba) using ATRFTIR spectra of pod

Authors: W. TEROUZI, A. GORFTI, A. OUSSAMA

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In this work, we were interested to use Fourier transform mid-infrared (FT-MIR) spectroscopy with chemometrics, for discrimination of broad beans from several producing regions of Morocco. Broad beans samples picked three zones named Barkan, Oled Youssef and Sidi Jaber. The spectral data, obtened by direct analysis on pods without any preliminary treatment, were subjected to a preliminary derivative elaboration based on the Gap algorithm to reduce the noise and extract a largest number of analytical information from spectra. Linear discriminant analysis (LDA) was adopted as classification method, and Principle component analysis (PCA) was employed to compress the original data set into a reduced new set of variables before LDA. On the basis of principal component analysis (PCA), three distinctive clusters were recognized. Then, PCA-LDA was performed to assess the discrimination capacity of the measurement data between the three cultivars. Application of PCA-LDA on an external test set of thirty four samples allowed to classify them into three clusters with a correct classification of 100%.

Page 3-7

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Title: Application of multivariate analysis to predict adulteration of Moroccan traditional butter by mashed potatoes

Authors: W. TEROUZI, F. KZAIBER, A. GORFTI, A. OUSSAMA

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In this paper, Attenuated Total Reflectance-Fourier Transform Mid Infrared Spectroscopy (ATR-FTMIR), combined with multivariate analysis, has been used to quantify the mashed potatoes content in a binary mixture with traditional cow’s butter. Blends of traditional cow’s butter with different percentages (0–35%) of mashed potatoes were measured using ATR-FTMIR spectroscopy. Spectral and reference data were firstly analyzed by principal component analysis (PCA) to check outliers samples. Partial least square regression (PLSR) was used to establish calibration model. Excellent correlation between ATR-FTMIR analysis and studied blend samples was obtained R2 = 0.99; with Root Mean Square Errors of Prediction 2.36, Limit of Detection 7.08%, and Relative Prediction Errors as low as 0.67. These results indicate that actually developed technique can be used for rapid prediction of mashed potatoes content in traditional cow’s butter.

Page 8-12

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