Design and Development of Leaf Splitting Unit for Aloe Vera Gel Expulsion Machine

Chandegara, V. K.; Varshney, Ankur Nandan

doi:10.1111/jfpe.12098

Cited by 11 publications

(19 citation statements)

References 11 publications

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“…This is the summation of all the dissolved solids in the water such as salts, sugar, protein, acids, etc. More will be the total solids in the gel; poor will be the quality of gel (Chandegara, ). Percentage total soluble solid content was measured by placing two drops of the aloe vera gel on the scale of hand refractometer (0–32 °).…”

Section: Methodsmentioning

confidence: 99%

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Design, development, and evaluation of aloe vera leaf gel expulsion machine

Gajbhiye

Gupta²,

Alam

et al. 2017

J Food Process Engineering

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The aloe vera gel expulsion machine consists of auto adjustable grip rollers, mouth piece or front edge cutter, scrapping blades, and a driving unit. The grip rollers were provided with inclined trapezoidal teeth to increase the friction between aloe vera leaf and rollers. The design parameters of the machine were the speed along with the dimensions of grip rollers, spring tension for mouth piece, and clearance of scrapping blades. The jagged edges were cut as the leaf passed through mouth piece and grip roller pushed it against scrapping blades which removed the upper and lower rind. The machine was tested for its performance at different roller speed and leaf thickness. It was inferred that for getting maximum crude gel recovery, minimum residual gel percentage, and highest expulsion efficiency, the leaves should be fed at 75 rpm roller speed for leaf thickness more than 20 mm. Practical applications Aloe vera gel has been utilized for therapeutic properties including wound healing, constipation, thermal injury healing, ulcers, diabetes, anti‐inflammation, and immunomodulation. Nowadays it is used for commercial applications such as sun creams, soaps, shampoos, face wash, and lotions. It is also used for preparation of juices, yoghurt, flavored milk, health drinks, and beverages. In crushing method of gel expulsion the ingression of other chemical compounds deteriorates the gel quality. The machine was designed to avoid crushing and reduce manual contact for obtaining good quality gel from aloe vera leaves.

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Section: Methodsmentioning

confidence: 99%

“…The gel recovery was evaluated in terms of dependent parameters viz. crude gel recovery (%), residual gel percentage (%), and expulsion efficiency (%) (Chandegara & Varshney, ). Experiments were conducted by changing various machine and leaf parameters and readings were noted.…”

Section: Methodsmentioning

confidence: 99%

Design, development, and evaluation of aloe vera leaf gel expulsion machine

Gajbhiye

Gupta²,

Alam

et al. 2017

J Food Process Engineering

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“…It can be laborious when no information is available on the relationships between inputs and outputs. However, in this case, factor selection was easy since the relationships between variables were well known (Chandegara & Varshney, ). Hence, input variables were chosen based on their proven influence on process indices of the machine.…”

Section: Methodsmentioning

confidence: 99%

Modeling of process indices of Aloe vera gel extraction machine using artificial neural network

Dinesh

Kumar

Ramchandra

et al. 2017

J Food Process Engineering

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The performance evaluation of Aloe vera gel extraction machine in terms of extraction efficiency, gel recovery, and extraction loss were evaluated at three level of roller speeds (11.40, 15.10, and 18.80 rpm) and roller clearance (4, 5, and 6 mm). The data obtained were used for development of artificial neural network (ANN) model. The roller speed, roller clearance, extraction efficiency, gel recovery, and extraction loss were used as the inputs and the gel extraction efficiency, gel recovery, and extraction loss were the output from the model. New feed forward neural network was used for the model building and trained using Bayesian regularization training algorithm. Optimum ANN architecture was obtained by trial and error method. The results showed that the correlation coefficient for calibration and validation was .9751 and .9982, respectively, the root mean square error for calibration and validations was .4746 and .1258, respectively, and the ANN efficiency for calibration and validation was .9507 and .9964, respectively, were recorded for ANN model 5‐10‐3. Results indicated that ANN can be used efficiently for the modeling of the process indices of the Aloe vera gel extraction machine. Practical applications Using a set of experimental data from Aloe vera gel extraction machine artificial neural network (ANN) model was developed to evaluate and predict the performance of Aloe vera gel extraction machine in terms of extraction efficiency, gel recovery, and extraction loss. The evaluation of ANN model with test data proved that model has very good accuracy. Using this model one can search for optimum operation conditions of Aloe vera gel extraction machine to maximize the efficiency and gel recovery and minimize the extraction loss.

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“…The optimum treatment for the coating process is a gel with the lowest refractive index. Impurities in the extracted gel are indicated by a higher refractive index [ 36 ].…”

Section: Resultsmentioning

confidence: 99%

Physicochemical, Morphological, and Functional Characterization of Edible Anthocyanin-Enriched Aloevera Coatings on Fresh Figs (Ficus carica L.)

Al-Hilifi

Al-Ali

Al-Ibresam

et al. 2022

Gels

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In the present investigation, aloe vera gel (AVG)-based edible coatings enriched with anthocyanin were prepared. We investigated the effect of different formulations of aloe-vera-based edible coatings, such as neat AVG (T1), AVG with glycerol (T2), aloe vera with 0.2% anthocyanin + glycerol (T3), and AVG with 0.5% anthocyanin + glycerol (T4), on the postharvest quality of fig (Ficus carica L.) fruits under refrigerated conditions (4 °C) for up to 12 days of storage with 2-day examination intervals. The results of the present study revealed that the T4 treatment was the most effective for reducing the weight loss in fig fruits throughout the storage period (~4%), followed by T3, T2, and T1. The minimum weight loss after 12 days of storage (3.76%) was recorded for the T4 treatment, followed by T3 (4.34%), which was significantly higher than that of uncoated fruit (~11%). The best quality attributes, such as the total soluble solids (TSS), titratable acidity (TA), and pH, were also demonstrated by the T3 and T4 treatments. The T4 coating caused a marginal change of 0.16 in the fruit titratable acidity, compared to the change of 0.33 in the untreated fruit control after 12 days of storage at 4 °C. Similarly, the total soluble solids in the T4-coated fruits increased marginally (0.43 °Brix) compared to the uncoated control fruits (>2 °Brix) after 12 days of storage at 4 °C. The results revealed that the incorporation of anthocyanin content into AVG is a promising technology for the development of active edible coatings to extend the shelf life of fig fruits.

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Design and Development of Leaf Splitting Unit for Aloe Vera Gel Expulsion Machine

Cited by 11 publications

References 11 publications

Design, development, and evaluation of aloe vera leaf gel expulsion machine

Design, development, and evaluation of aloe vera leaf gel expulsion machine

Modeling of process indices of Aloe vera gel extraction machine using artificial neural network

Physicochemical, Morphological, and Functional Characterization of Edible Anthocyanin-Enriched Aloevera Coatings on Fresh Figs (Ficus carica L.)

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