Predictive Modeling of Textural Quality of Almonds During Commercial Storage and Distribution

Taitano, Li Zuo; Singh, Rajesh

doi:10.1007/978-1-4614-7906-2_26

Cited by 3 publications

(3 citation statements)

References 36 publications

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“…The GAB model was used to calculate the equilibrium moisture content (EMC) as the best model (Taitano & Singh, ):

M = \frac{m_{0} {CKa}_{w}}{((), 1 - {Ka}_{w}) ((), 1 - {Ka}_{w} + {CKa}_{w})}

where, M is the equilibrium moisture content (kg H 2 O/kg solids), m 0 is the monolayer moisture content (kg H 2 O/kg solids), and a w is the water activity of almonds. C and K are the constants related to the heat of sorption of the first layer and multilayer, respectively.…”

Section: Methodsmentioning

confidence: 99%

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The effect of ultrasound pre‐treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network

Kaveh

Jahanbakhshi

Abbaspour‐Gilandeh

et al. 2018

J Food Process Engineering

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In this study, different drying conditions were investigated on quality and thermodynamic properties of almond kernel. Experiments were performed using a convection dryer with ultrasound pretreatment in 40, 50, 60, and 70 °C air temperature, 1 m/s air velocity, and duration of ultrasonic pre‐treatment of 0 min (for control sample), 10, 20, and 40 min. The drying kinetic of the almond kernel was estimated by 15 mathematical models. Furthermore, Artificial Neural Networks (ANNs) and Adaptive Neuro‐Fuzzy Inference Systems (ANFIS) were applied to fit the experimental data on the thin layer drying. The lowest and highest values of the effective moisture diffusivity (Deff) was 1.81 × 10−9 and 9.70 × 10−9 m2/s, respectively. Activation energy (Ea) of the samples was obtained between 26.35 and 36.44 kJ/mol. The highest and lowest values of specific energy consumption (SEC) were calculated 561.72 and 169.88 kW hr/kg, respectively. Maximum (13.14%) and the minimum (7.1%) values of shrinkage were achieved at air temperatures of 70 and 40 °C, respectively. The color changing of dried samples was obtained between 9.14 and 17.96. Furthermore, results revealed that the ANFIS model had the high ability to predict the moisture ratio (R2 = 0.9998 and MSE = 0.0003) during drying. As a result, ANFIS model has the highest ability to evaluate all output as compared with other models and ANNs method. Practical applications Algorithms are modern methods that have been successfully applied to solve the various problems and modeling in engineering and science. Drying is one of the oldest procedures to preserve the food quality. Reduction of moisture content to a certain value can be caused to decay and minimize the microbiological activity and deteriorating chemical reactions in agricultural products, respectively. Determination of almond drying process under convective with ultrasound pre‐treatment dryer in terms of desirable thermal properties (effective moisture diffusivity and energy consumption) provides the high‐quality products. Furthermore, this research can be able to provide a technical basis for almond drying and the related equipment designing.

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“…The GAB model was used to calculate the equilibrium moisture content (EMC) as the best model (Taitano & Singh, ):

M = \frac{m_{0} {CKa}_{w}}{((), 1 - {Ka}_{w}) ((), 1 - {Ka}_{w} + {CKa}_{w})}

Section: Methodsmentioning

confidence: 99%

“…The moisture ratio (MR) of almonds during drying was calculated through Equation 1 (Ricce, Rojas, Miano, Siche, & Augusto, 2016): The GAB model was used to calculate the equilibrium moisture content (EMC) as the best model (Taitano & Singh, 2013):…”

Section: Drying Fitting Curvesmentioning

confidence: 99%

The effect of ultrasound pre‐treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network

Kaveh

Jahanbakhshi

Abbaspour‐Gilandeh

et al. 2018

J Food Process Engineering

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show abstract

“…Temperature conditions were chosen to be high enough to accelerate the development of lipid peroxidation and rancidity over the typical shelf life of roasted almonds 7,27 but not so high as to alter the typical progress of rancidity. 10 Humidity levels were chosen to avoid increasing the moisture content of almonds 28 and thereby altering the texture, as this might produce an unintended negative bias in consumer perception. 29 Rancidity development was evaluated by measuring PV, FFAs, CDs, total tocopherols, and volatile organic compounds by HS-SPME-GC/MS at 1-month intervals over the 12-month storage period.…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

Chemical and Sensory Characterization of Oxidative Changes in Roasted Almonds Undergoing Accelerated Shelf Life

Franklin

Chapman

King

et al. 2017

J. Agric. Food Chem.

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In almonds, there is no standard method for detecting oxidative changes and little data correlating consumer perception with chemical markers of rancidity. To address this, we measured peroxide values (PV), free fatty acid values (FFAs), conjugated dienes, tocopherols, headspace volatiles, and consumer hedonic response in light roasted (LR) and dark roasted (DR) almonds stored under conditions that promote rancidity development over 12 months. Results demonstrate that, although rancidity develops at different rates in LR and DR almonds, consumer liking was not significantly different between LR and DR almonds. Average hedonic ratings of almonds were found to fall below a designated acceptable score of 5 ("neither like nor dislike") by 6 months of storage. This did not correspond with recommended industry rejection standard of PV < 5 mequiv peroxide/kg oil and FFA < 1.5% oleic. FFAs remain well below <1.5% oleic during storage, indicating that FFAs are not a good marker of rancidity in roasted almonds stored in low humidity environments. Regression of consumer liking to concentration of rancidity indicators revealed that selected headspace volatiles, including heptanal, octanal, nonanal, 2-octenal, 2-heptanone, 2-pentylfuran, hexanal, and pentanal, had a better correlation with liking than did nonvolatile indicators.

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Period of susceptibility of almonds to aflatoxin contamination during development in the orchard

et al. 2016

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Predictive Modeling of Textural Quality of Almonds During Commercial Storage and Distribution

Cited by 3 publications

References 36 publications

The effect of ultrasound pre‐treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network

The effect of ultrasound pre‐treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network

Chemical and Sensory Characterization of Oxidative Changes in Roasted Almonds Undergoing Accelerated Shelf Life

Period of susceptibility of almonds to aflatoxin contamination during development in the orchard

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