Physical property and resistance to airflow through bulk and thin-layer lemon fruit
Version of Record online: 21 DEC 2012
© 2012 Blackwell Publishing Ltd
Quality Assurance and Safety of Crops & Foods
Volume 4, Issue 5, pages e12–e19, December 2012
How to Cite
2012) Physical property and resistance to airflow through bulk and thin layer lemon fruit. Quality Assurance and Safety of Crops & Foods, 4, e12–e19, 4:5, 12–19., (
A, B = constants; A1, A2, A3, B1, B2, B3 = product-dependent coefficients; L = length, mm; W = width, mm; H = height, mm; GMD = geometric mean diameter, mm; ε = porosity; R2 = coefficient of determination; RMSE = root mean square error; P % = mean relative percentage deviation modulus; Q = airflow rate, m3 s−1 m−2; ΔP = pressure drop, Pa m−1; ρ = air density, kg m−3; ρt = kernel density, kg m−3; ρb = bulk density, kg m−3; μ = air viscosity, m2 s−1; ϕ = sphericity(%).
- Issue online: 21 DEC 2012
- Version of Record online: 21 DEC 2012
- Manuscript Accepted: 25 MAY 2012
- Manuscript Revised: 19 MAY 2012
- Manuscript Received: 7 MAR 2012
- lemon fruit;
- pressure drop;
- resistance to airflow;
Physical properties of lemon fruit are important for drying system and Kept in stock.
The prediction of airflow resistance is fundamental to the design of efficient drying and aeration systems for lemon fruit.
Using a laboratory unit, two sets of experiments were carried out, namely thick and thin layers. In the thick-layer experiments, four bed depths, 11 flow rates and four temperatures 25, 35, 45 and 55 C. In the thin layer (two kernels depth, 3 cm), the kernels were put together in three arrangements: A, B and random; five moisture contents and 11 flow rates were studied.
Results indicated that resistance to airflow through a column of lemon fruit increased with increasing bed depth and airflow rate. In the latter experiment, pressure drop decreased with a decrease in moisture content. Airflow rate was the most significant factor affecting the pressure drop of lemon fruit in both experiments.
Three applicable models (Shedd, Hukill and Ives, and Ergun) were used to evaluate the pressure drop data. The Ergun model, with higher values for coefficient of determination and lower values for sum of square error and mean relative deviation modulus, is the best model for predicting pressure drop across lemon fruit bed for the conditions studied.