Modeling of Thermal Properties of Persian Walnut Kernel as a Function of Moisture Content and Temperature Using Response Surface Methodology

Mamani, Imanali

doi:10.1111/jfpp.12527

Cited by 14 publications

(5 citation statements)

References 33 publications

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“…Regression, a statistical method, leverages the relationship between multiple variables within an observational database to anticipate outcomes based on other variables. Among various regression analyses, MLR is frequently utilized due to its simplicity (Mamani 2015;Nolan et al, 2015;Preacher et al, 2006). This technique assumes a linear relationship between quantitative variables (Piña-Monarrez & Ortiz-Yañez, 2015).…”

Section: Methodsmentioning

confidence: 99%

Enhancing rainfall estimation for water resource management through multiple linear regression approach in Khordha District, Odisha, India

Rath,

Verma,

Yadua

2024

Int. J. Res. Publ. Rev.

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Rainfall estimation holds paramount significance for optimizing water resource utilization and effective management, particularly in countries like India, characterized by an agro-based economy and limited irrigation infrastructure. This paper introduces a multiple linear regression (MLR) model tailored for estimating annual rainfall in Khordha district, Odisha, India. The model is designed to predict rainfall for a given year by leveraging data from the preceding three years.Through rigorous testing on a century-long dataset of annual rainfall, the model demonstrated exceptional performance. By setting the intercept of the MLR model to zero, the derived equation yielded highly accurate results. The predicted values exhibited a robust correspondence with observed data, resulting in a R² value of 0.963. This remarkable R² value underscores the model's suitability for application across the study area. The robustness and accuracy of this model offers valuable insights for enhancing hydro-meteorological assessments and informing strategic water resource management decisions in the region.

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Section: Methodsmentioning

confidence: 99%

Enhancing rainfall estimation for water resource management through multiple linear regression approach in Khordha District, Odisha, India

Rath,

Verma,

Yadua

2024

Int. J. Res. Publ. Rev.

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“…The water needed was calculated by the rewetting formula 12 : where Q —the weight of purified water that will be sprayed, W t —the initial weight of seeds sample, M f —the desired moisture content for seeds sample, and M i —the original moisture content for the seeds sample. Before testing, the seeds sample was allowed to equilibrate from 5 °C to room temperature in about 2 h’s time 13 .…”

Section: Methodsmentioning

confidence: 99%

Engineering properties of Cassia tora L. seeds and meal as a function of moisture content

Peng

Fang

Xiang

et al. 2022

Sci Rep

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Engineering properties are of great importance for Cassia tora L. seeds in aspects of harvesting, handling mechanical design and product processing. The effect of moisture content (7, 10, 13, 16 and 19%) (wet basis) on the properties: physical (length, width, bulk and true density, porosity, thousand seeds mass, coefficient of static friction and angle of repose), mechanical (hardness, fragmentation energy and failure deformations), and thermal (specific heat, thermal conductivity and thermal diffusivity), were systematically studied. As the moisture contents increase from 7 to 19%, the length (L) increased from 4.52 to 5.87 mm, the thickness (T) from 2.51 to 3.21 mm and the width (W) from 2.36 to 3.02 mm, respectively. The bulk and true density of Cassia tora L. seeds decreased from 775.83 to 654.17 kg/m3 and from 1295.21 to 1154.72 kg/m3, respectively, with the moisture content raised from 7 to 19%. The thermal conductivity of Cassia tora L. seeds meal was found to be 0.068–0.098 W m−1 K−1, 0.078–0.112 W m−1 K−1, 0.089–0.125 W m−1 K−1, 0.098–0.136 W m−1 K−1, 0.108–0.148 W m−1 K−1, 0.119–0.159 W m−1 K−1, respectively, at 25 °C, 45 °C, 65 °C, 85 °C, 105 °C and 125 °C in moisture ranges of 7–19%. The thermal diffusivity was found to decrease from 5.21 × 10–8 to 4.53 × 10–8 m2/s, from 5.75 × 10–8 to 4.91 × 10–8 m2/s, from 6.11 × 10–8 to 5.17 × 10–8 m2/s, from 6.52 × 10–8 to 5.36 × 10–8 m2/s, from 7.17 × 10–8 to 5.77 × 10–8 m2/s, from 7.36 × 10–8 to 5.84 × 10–8 m2/s, respectively, at 25 °C, 45 °C, 65 °C, 85 °C, 105 °C and 125 °C in moisture ranges of 7–19%. The results suggested that physical properties exhibited linear relationships with moisture content using the regression model, while mechanical properties showed a second-order polynomial relationship with moisture content. Furthermore, significant variation existed in thermal properties because of differentiate moisture content and temperature. These data and rules are also useful for high efficiency machines design and mechanisms development.

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“…As the fruits soften due to moisture uptake or loss upon soaking in hot water, the moisture content of the product is expected to change, as shown by the initial mass increase and possibly subsequent loss due to osmotic pressure. The moisture change during the process is given as follows (Mamani, 2015):

w_{t} goodbreak= \frac{m_{t} ()(, M_{t} goodbreak- M_{f})}{1 - M_{f}}

…”

Section: Methodsmentioning

confidence: 99%

Thermal softening kinetics of African black olive fruit: Influence of temperature and water absorption on the thermal maceration dynamics and thermophysical properties

Ndukwu

James

Mbanasor

et al. 2022

Food Processing Preservation

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Softening of the pulp of African black olive fruit (Canarium schweinfurthii) is one of the unit operations in the maceration and de‐pulping process of the pulp for consumption or to produce masticatories or oil. The softening process is temperature‐sensitive, and hot water treatments are applied arbitrarily by local processors that might result in the hardening instead of maceration or softening of the fruits. This study, therefore, investigates the effect of hot water treatment on the softening and maceration kinetics of the fruits at different temperatures. To achieve this, two varieties of the fruits were selected and immersed in a water bath at temperatures of 30–60°C. Some of the parameters determined were the moisture absorption rate, hardness ratio, dimensional changes, thermal properties, and softening kinetics. The results showed that the softening curves and kinetics were directly affected by the temperature of the hot water. Hardening of the pulp occurred at a hot water temperature of 60°C for the long variety. In contrast, softening did not take place at 30°C for both varieties. Maceration occurred at 40–50°C for the long variety and 40–60°C for the short variety. The maximum maceration rate was at 50°C with an average softening rate of 0.161 N/hr for long variety and the least rate was 0.0565 N/hr for 40°C short variety. The activation energy was 47.46 kJ/mol for the short variety and 48.06 kJ/mol for the long variety. All the properties were presented as a function of the temperature or moisture content with good results. The obtained data will be helpful in the scaling up of the de‐pulping process of the fruit by developing processing equipment for large‐scale industrial processing and also prevents hardening that can result in losses for small‐scale processors who soften and sell the fruits as snacks. Novelty impact statement Several studies abound on African black olive (Elemi) but none is available on the processing dynamics of softening the pulp for de‐pulping the fruits to produce masticatories or oil. A good number of these research focused on physical properties, biochemical contents, proximate composition, and other in vivo assessments. Therefore, the present study highlights the softening kinetics of the fruit during the maceration process. It showed that (1) hardening of the pulp occurs at 60°C while 30°C cannot cause maceration; (2) The maceration rate follows a three‐period pseudo first‐order kinetics; (3) Quicker maceration can be achieved at 50°C soaking water temperature.

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Modeling of Thermal Properties of Persian Walnut Kernel as a Function of Moisture Content and Temperature Using Response Surface Methodology

Cited by 14 publications

References 33 publications

Enhancing rainfall estimation for water resource management through multiple linear regression approach in Khordha District, Odisha, India

Enhancing rainfall estimation for water resource management through multiple linear regression approach in Khordha District, Odisha, India

Engineering properties of Cassia tora L. seeds and meal as a function of moisture content

Thermal softening kinetics of African black olive fruit: Influence of temperature and water absorption on the thermal maceration dynamics and thermophysical properties

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