Thermal Properties of Foods

Şahin, Serpil; Şümnü, Servet Gülüm

doi:10.1007/0-387-30808-3_3

Cited by 104 publications

(108 citation statements)

References 34 publications

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“…Thermal conductivity and thermal diffusivity have to be determined to estimate the rate of heat transfer (Ikegwu, Ezeh, 2012). Thermal conductivity determines the ability of a material to conduct heat (Sahin, Sumnu, 2006). Thermal diffusivity data can be used to determine the duration of thermal processes (Mahapatra et al, 2013).…”

Section: Resultsmentioning

confidence: 99%

“…Thermal diffusivity data can be used to determine the duration of thermal processes (Mahapatra et al, 2013). The thermal properties of food products can be measured directly, with the use of different devices and techniques such as an analyser KD2 Pro and thermal analysis (Lever et al, 2014;Barnwal et al, 2015;Perussello et al, 2015), and indirectly using mathematical calculations based on the chemical composition (water, protein, fat, carbohydrates, fibre and ash), temperature and structure of the analysed material (Choi, Okos, 1986;Sahin, Sumnu, 2006;Wang et al, 2008;Carson, 2015). Therefore, some of our findings can be used for mathematical modelling.…”

Section: Resultsmentioning

confidence: 99%

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Thermophysical and chemical properties of seeds of traditional and double low cultivars of white mustard

Ropelewska

Jankowski

Zapotoczny

et al. 2018

Zemdirbyste-Agriculture

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The aim of this study was to compare the thermal, physical, mechanical and chemical properties of white mustard (Sinapis alba L.) seeds of the traditional cultivar 'Radena' and the double low cultivar 'Warta'. The selected thermal properties were determined with an analyser KD2 Pro. Cultivar 'Warta' was characterised by higher thermal conductivity (0. ). Cultivars 'Warta' and 'Radena' had identical thermal diffusivity (0.087 mm 2 s -1 ). The values of the highest initial endothermic peaks and the last endothermic peak were determined from differential scanning calorimetry curves. The mean values of common peaks for both cultivars were determined at −17.5, 86.0 and 402.3 °C for 'Warta', and −16.5, 69.9 and 400

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Thermophysical and chemical properties of seeds of traditional and double low cultivars of white mustard

Ropelewska

Jankowski

Zapotoczny

et al. 2018

Zemdirbyste-Agriculture

View full text Add to dashboard Cite

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“…The fruit heat variation due to the environment was calculated, knowing the fruit volume, its density and estimating the specific heat capacity, as proposed by Sahin & Sumnu (). Fruit and air temperature displayed similar profiles but fruit temperatures were higher than air temperature under control and even more under water‐stressed conditions.…”

Section: Resultsmentioning

confidence: 99%

Respiration climacteric in tomato fruits elucidated by constraint‐based modelling

et al. 2016

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Summary Tomato is a model organism to study the development of fleshy fruit including ripening initiation. Unfortunately, few studies deal with the brief phase of accelerated ripening associated with the respiration climacteric because of practical problems involved in measuring fruit respiration.Because constraint‐based modelling allows predicting accurate metabolic fluxes, we investigated the respiration and energy dissipation of fruit pericarp at the breaker stage using a detailed stoichiometric model of the respiratory pathway, including alternative oxidase and uncoupling proteins. Assuming steady‐state, a metabolic dataset was transformed into constraints to solve the model on a daily basis throughout tomato fruit development.We detected a peak of CO 2 released and an excess of energy dissipated at 40 d post anthesis (DPA) just before the onset of ripening coinciding with the respiration climacteric. We demonstrated the unbalanced carbon allocation with the sharp slowdown of accumulation (for syntheses and storage) and the beginning of the degradation of starch and cell wall polysaccharides. Experiments with fruits harvested from plants cultivated under stress conditions confirmed the concept.We conclude that modelling with an accurate metabolic dataset is an efficient tool to bypass the difficulty of measuring fruit respiration and to elucidate the underlying mechanisms of ripening.

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“…Maximum reflectance at the longer wavelengths of 640–740 nm indicates red objects. Hue is defined on the Munsell colour tree in the circumferential direction by five principals (R, red; Y, yellow; G, green; B, blue; P, purple) and five intermediates .…”

Section: Resultsmentioning

confidence: 99%

Chemometric and phenolic attributes of blended wines assessed by multivariate techniques

2015

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The aim of the study was to investigate the quality of blended wines produced from Vitis vinifera L. Cabernet Sauvignon, Merlot and Sauvignon blanc grapes. Wines were processed according to accepted conventional methods for white and red wines. Blended wines were produced with different ranges (25, 50, 75 and 100%) of Cabernet Sauvignon, Merlot and Sauvignon blanc wines. Produced wines were evaluated for total phenols (mg/L), total tartaric esters (mg/L caffeic acid), total flavonols (mg/L quercetin), chemometric parameters such as D280%, D420%, D520%, D620%, dA%, CD%, T, CI%, R%, Y% and B%, CIELAB parameters, protein, total and volatile acidity. Analyses on an n-dimensional scale demonstrated the relationships among the wines of different grape origins and different blending ratios. On the basis of these differences, two main groups were plotted using principal component analysis and cluster analysis. The results demonstrate the possibilities of optimizing wines on the basis of defined parameters.

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Thermal Properties of Foods

Cited by 104 publications

References 34 publications

Thermophysical and chemical properties of seeds of traditional and double low cultivars of white mustard

Thermophysical and chemical properties of seeds of traditional and double low cultivars of white mustard

Respiration climacteric in tomato fruits elucidated by constraint‐based modelling

Chemometric and phenolic attributes of blended wines assessed by multivariate techniques

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