Airflow Resistance of Parchment Arabica Coffee

ARTICLE IN PRESS

doi:10.1016/j.biosystemseng.2005.02.008PH—Postharvest Technology

Biosystems Engineering (2005) 91 (2), 149–156

Airflow Resistance of Parchment Arabica Coffee

J.O. Agullo; M.O. Marenya

Department of Environmental and Biosystems Engineering, University of Nairobi, P.O. Box 30197, 00100, Nairobi;e-mail of corresponding author: [email protected]

(Received 23 March 2004; accepted in revised form 15 February 2005; published online 21 April 2005)

Resistance to airflow of clean bulk parchment coffee at moisture contents of 36�7, 30�7, 19�6 and 12�7% (w.b.)was studied for airflow range of 0�126–0�72m3 s�1m�2 using an experimental test column. Results indicatedthat resistance to airflow across a column of parchment coffee increased with increasing bed depth and airflowrate and decreasing moisture content for both dense and loose fill. Densely filled columns resulted in higherresistance to airflow. The resistance to airflow through a bed of parchment Arabica coffee has beencharacterised by Shedd’s model, Hukill and Ives model and a model giving an empirical relationship betweenairflow resistance and experimental variables. It also revealed that airflow rate had the highest effect onpressure drop followed by moisture content and bulk density.r 2005 Silsoe Research Institute. All rights reserved

Published by Elsevier Ltd

1. Introduction

Arabica coffee has the finest quality amongst othercoffee species such as Robusta, Liberica, etc. Owing to itshigh quality, Arabica coffee is used to blend other coffeesto realise the unique enjoyable taste that is associated withcoffee. To obtain this fine quality, Arabica coffee isprocessed using the wet method, which involves a numberof precise steps from the time the coffee cherry isharvested to the time it is roasted and liquored. Thesesteps include sorting, pulping, grading, fermentation,washing, soaking, drying and storage (Gumbe, 1995).Drying of parchment coffee involves the removal of

water between the parchment and the bean plus removalof internal moisture (Gumbe, 1995). The parchment canbe dried in the sun or by using mechanical and heatingmeans. An approach that is currently being used inKenya, to counter the problem of unreliable weather, isthe incorporation of parchment coffee conditioning binsin coffee factories. The bins are designed to allowmovement of air through a bed of parchment coffeefrom the bottom to the top. Although intended for theaeration of dry parchment coffee awaiting transporta-tion to the milling houses, conditioning bins are alsoused for the complete drying process of parchment thathas not reached the equilibrium moisture content.

1537-5110/$30.00 149

The important role the conditioning bins play inmaintaining the quality of bulk parchment Arabicacoffee calls for their proper design. Currently, thedesign of these structures is not scientific becausedata on airflow resistance of parchment Arabica coffeeare not available. Designers of drying and aerationsystems require data on airflow resistance of grainsfor the proper selection of fans, for the assessment offilling depths in storage bins and mathematical predic-tion of pressure drop and airflow patterns in thestored mass (Nalladurai et al., 2002). Factors that affectthe airflow resistance across beds of grains, seeds andother agricultural products are well documented(ASAE, 2000; Alagusundaram & Jayas, 1990). It isthe influence of these factors on airflow resistance ofclean parchment Arabica coffee that needs to beinvestigated in order to provide the data needed forthe engineering design of coffee conditioning bins andto develop a mathematical expression for predictingresistance to airflow across a bed of parchment Arabicacoffee.

The objectives of this study were to

(i)
determine the effect of moisture content, bed depth,method of filling and airflow rate on resistancecharacteristics of parchment coffee; and
r 2005 Silsoe Research Institute. All rights reserved

Published by Elsevier Ltd

ARTICLE IN PRESS

Notation

A,a,B,

b,c,d

model constants

Bd bulk density, kgm�3

F percentage of fines, %M moisture content, % (w.b.)Qa airflow rate, m3 s�1m�2

R2 coefficient of determinationrd average bulk density of dense-filled clean

parchment coffee, kgm�3

rl average bulk density of loose-filled cleanparchment coffee, kgm�3

DP pressure drop per unit depth, Pam�1

J.O. AGULLO; M.O. MARENYA150

(ii)
fit the data obtained to the selected models to predictthe airflow resistance through a bed of clean bulkparchment Arabica coffee.
2. Literature review

2.1. Factors affecting airflow resistance of grains in bulk

The prediction of airflow resistance is fundamental tothe design of efficient drying and aeration systems. Toselect an appropriate fan to adequately deliver theamount of air required in a drying and aeration system,it is necessary to know the magnitude of the resistance tobe overcome (Madamba et al., 1993). Resistance toairflow through a bed of grains and seeds is usuallyexpressed in terms of pressure drop. The pressure dropdepends on a number of product and environmentfactors such as airflow rate, bed depth, bulk density,presence of foreign material, moisture content andsurface and shape characteristics of the grain (Dairo &Ajibola, 1994).The moisture content of agricultural products has

been found to influence the size of product particles(Mohsenin, 1986). For the same product, particles withhigher moisture content have been observed to be biggerin size compared to those that are relatively dry. Highmoisture content of a product results in higher porosity,and hence an increase in moisture content of a productresults in decreased pressure drop across a given depth(Brooker et al., 1992). In a study of the effect ofmoisture content on laird lentils, an increase in moisturecontent from 10�4 to 19�9% resulted in a 22�5% decreasein resistance to airflow (Sokhansanj et al., 1990).Siebenmorgen and Jindal (1987) and Haque et al.(1982) observed a similar trend for rice and corn, andfor wheat and sorghum, respectively.Airflow rates and method of filling have a marked

effect on pressure drop of granular agricultural pro-ducts. Dairo and Ajibola (1994) found that pressuredrop along columns of sesame seeds increased withincrease in airflow rates. Farmer et al. (1981) and Haque

et al. (1982) made similar observations for blue stemgrass and maize, respectively. Kumar and Muir (1986)reported that the method of filling the bin had a markedeffect on airflow resistance primarily because of theeffect of the filling method on bulk density.

Airflow resistance across a column of agriculturalmaterials has been observed to increase linearly withincrease in depth of product column (Jayas et al., 1987;Sokhansanj et al., 1990; Dairo & Ajibola, 1994).However, the linearity in pressure drop can only beassumed for grain masses of depths ordinarily found infarm storage (Brooker et al., 1992). For deep beds, thisassumption may be incorrect because effects of othervariables such as method of filling, compression and sizeof foreign materials and the presence of fines are notonly unaccounted for, but are also difficult to assessaccurately (Brooker et al., 1992). Wood and Baolin(1987) found that for a bed of germinating barley, thepressure gradient due to airflow resistance increased bya factor of as much as six due to compression. Theeffect of compression made the total pressure dropincrease more rapidly with depth than the linearvariations observed on an uncompressed bed (Wood &Baolin, 1987).

2.2. Airflow–pressure drop relationships

Three empirical models are frequently cited in theliterature for predicting airflow resistance of granularagricultural products. One such empirical model isproposed by Shedd (1953). Shedd’s model is of the form

Qa ¼ ADPB, (1)

where: Qa is the airflow rate in m3 s�1m�2; DP is thepressure drop per unit depth in Pam�1; and A and B areconstants for a particular granular material.

As reported by Dairo and Ajibola (1994), Jayas et al.(1987) and Madamba et al. (1993), Shedd’s model,usually presented in logarithmic form, is only suitablefor predicting airflow resistance over a narrow range ofairflow rates. In several studies, the constants A and B inEqn (1) have been related to some product factors that

ARTICLE IN PRESS

(A)

T1

T6(D)

(C)

(B) Air Duct

To a Pitot tube

To a manometer

Plenum

Fig. 1. Schematic of airflow resistance apparatus used: (A) fan;(B) damper; (C) false floor; (D) test column; (T1)–(T6), air

taps

AIRFLOW RESISTANCE OF PARCHMENT COFFEE 151

influence airflow resistance across beds of granularagricultural materials. Dairo and Ajibola (1994) relatedthe model constants to moisture content and bulkdensity of canola seeds. Siebenmorgen and Jindal (1987)related these constants to moisture content, finesconcentration and bulk density.Hukill and Ives (1955) proposed an empirical

equation, which accounts for the non-linearity assumedin Shedd’s model. The empirical equation is of the form:

DP ¼CQ2

a

lnð1þ DQaÞ, (2)

where: C and D are empirical constants in Pa s2m�3 andm2 sm�3, respectively, for a particular grain.Equation (2) is also referred to as the airflow

resistance equation (ASAE, 2000). It is applicable overa wide range of airflow rates, i.e. airflow rate in therange of 0�002–2�0m3 s�1m2 (Dairo & Ajibola, 1994)and has been used extensively to fit experimental datafrom drying and aeration studies of several grainsand seeds to determine the constants C and D. Theexpression has also been used to fit experimental datafor alfalfa cubes to airflow rates of 3�15m3 s�1m�2

(Sokhansanj et al., 1993). Sokhansanj et al. (1990)reported a better fit of this model for their data onpressure drop across a bed of lentils than with Shedd’smodel. The constants are useful for designing dryingand aeration systems for agricultural produce.Standard stepwise non-linear regression techniques

have been used to develop statistical models showingthe empirical relationship between airflow resistance andthe experimental variables (Dairo & Ajibola, 1994). Theresultant relationship takes the following general form:

DP ¼ aQ2a þ bMQa þ cBdQa þ dFQa, (3)

where: M is moisture content, % (w.b.); Bd is bulkdensity, kgm�3; F is percentage of fines, %; and a, b, c

and d are model constants, dimensionless.Equation (3) has been used by Dairo and Ajibola

(1994) on sesame seeds and Siebenmorgen and Jindal(1987) on rough rice. Haque et al. (1982) used itfor maize, sorghum and wheat grains. Chung et al.(2001) have also used the equation to describe thestatic pressure drop of grain sorghum and rough rice.Equation (3) allows relative comparison to be madeof the various parameters (Dairo & Ajibola, 1994).Airflow rate, Qa is included as an overall multiplier toensure that a pressure drop is not predicted at zero airvelocity. This equation has been shown to adequatelypredict the effects of fines concentration, moisturecontent and airflow rate on airflow resistance (Haqueet al., 1978).

3. Materials and methods

3.1. Experimental apparatus

The apparatus used in this study is shown in Fig. 1. Itconsisted of a fan (A), damper (B), an air duct, a plenumchamber, a test column (C), a pressure drop measuringsystem (D) and an airflow measurement system. The testcolumn was a square tube of 250 and 1200mm high. Itwas constructed of 20mm thick chipboard and equippedwith a perforated floor made of 5mm square wirenetting. Six air taps (T1–T6) of 5mm diameter weredrilled at an interval of 200mm along the column. Ateach level, three pressure taps were extended 100mmusing an aluminium tube with a rubber stopper attachedto the tube to avoid leakages. The square tube testcolumn was used because it was readily available.Ideally, a circular test column should have been usedso as to eliminate the sharp corners that may be difficultto fill with parchment coffee.

The test column rested on the plenum chamber ofdimensions 650mm by 650mm by 420mm. The topof the chamber had a centrally located square openingof 250mm. The outer boundary of the opening was linedwith a 20mm thick rubber band on which the testcolumn rested. The inclusion of the rubber band madethe joint between the square opening on the plenum andtest column airtight. An airflow testing set (MKS, 1980Model, England) consisting of an inclined manometerconnected to a Pitot static tube was used to measure theairflow rates. The inclined manometer has an accuracyof 0�05mm of water.

Air was supplied into the test column by a six bladebackward-curved centrifugal fan driven by a 0�75 kWmotor (VEB Electro-Morton Worke Thukrm PDR/GDR, Denmark) with a rated speed of 2800min�1. Theadvantage of using this type of a fan is that firstly, it canbe throttled, with dampers, to zero air discharge withoutoverloading the motor. Secondly, due to rising pressure

ARTICLE IN PRESS


curve characteristics of a backward curved fan, in-stability of static pressure within the system is eliminated(Henderson et al., 1997), thus allowing for accuratedetermination of pressure drop. Different airflow rateswere obtained by throttling the fan using the damper.

Table 2

Influence of airflow rate, moisture content and bulk density on

pressure drop per unit depth

Variable Sum of squares F-value Probability (P)

Airflow rate, Qa 4 265 689 1527�80� 0�00Bulk density, r 21 301 7�63� 0�01Moisture content, M 88 664 31�75� 0�00Qa� r 4214 1�51 0�23Qa�M 24 600 8�81� 0�01r�M 2931 1�05 0�31

�Significant.

3.2. Bulk coffee sample

The parchment coffee used in this study was procuredfrom the University of Nairobi coffee factory, UpperKabete Campus. The choice of the initial moisturecontent of the sample was such that it coincided with themoisture content level at which monitored mechanicaldrying usually commences. Monitored mechanical dry-ing of parchment coffee commences at the white stage ofdrying parchment (Gumbe, 1995). At the onset of thisstage, the moisture content is about 37% (w.b.). Noforeign material or cracked parchment was permissibleas the study was to be done for clean bulk parchmentArabica coffee. For each experiment, the moisturecontent was determined by using the standard methodof drying a sample of about 25 g of parchment in anoven at 105 1C for 24 h. The in-bin bulk density for bothloose and dense filling parchment coffee in the testcolumn was determined as suggested by Dairo andAjibola (1994) and Jayas et al. (1987).Two methods, loose fill and dense fill as described by

Jayas et al. (1987), were used to fill the test column withthe parchment coffee. In the loose filling, a pipe of160mm diameter was centrally placed in the test columnand filled with parchment coffee. It was then withdrawngently to allow the parchment coffee to flow into the testcolumn with nearly a zero height of fall. For dense fill,samples were sprinkled into the chamber from a heightof 300mm into the test column in a rain-like manner

TablPressure drop per unit depth for loose- and dense-filling metho

Airflow rate (Qa)m�3 s�1 m�2

Pr

Mois

36�7 30�7

Loose fill,552 kg m�3

Dense fill,575 kg m�3


Den541

0�126 59�68 68�67 62�950�248 151�23 199�47 154�51 10�321 248�53 304�11 220�73 20�380 317�19 398�94 292�66 30�430 385�86 477�40 359�70 40�581 624�71 775�58 604�95 70�720 840�70 1090�00 784�80 9

and from corner to corner. The loose fill method hasbeen used extensively (ASAE, 2000) in many studies fordetermining the constants of Eqn (3) for a number ofagricultural grains, seeds and other agricultural pro-ducts. This choice is probably based on the assumptionthat the loose fill method results in product densitiesthat are close to those that would be realised under fieldconditions. The mean equivalent particle diameter of theparchment used in this study was 7�6570�056 for boththe loose- and dense-filled beds at moisture contentlevels shown in Tables 1 and 2. The respective mean bedporosities for the loose- and dense-filled parchment were0�419370�0172 and 0�396870�0083.

3.3. Determination of pressure drop

To determine pressure drops, the test column wasfilled with parchment coffee to a depth of 800mm at agiven level of moisture content and method of fill. Thefirst 200mm of the test column above the plenumchamber was used for straightening the air. Therefore,pressure drop measurements started from the air tap

e 1ds at different levels of moisture content of parchment coffee

essure drop, Pa m�1

ture content, % (w.b.)

19�6 12�7

se fill,kg m�3





73�58 45�78 77�66 49�87 78�8199�47 137�34 179�03 138�98 199�4794�30 202�74 216�60 209�28 299�2195�67 286�13 340�08 289�40 400�5890�50 351�33 413�65 364�61 480�6968�45 604�95 784�80 621�30 735�7581�00 833�85 997�35 817�50 997�35

ARTICLE IN PRESS


(T1) at a height of 200mm above the plenum. This tapwas also taken as the reference tap and the pressuredrops for subsequent taps were the differences in staticpressure between this tap and the subsequent taps at400, 600 and 800mm above the plenum.The experiments were done for four levels of moisture

content, two methods of filling and seven airflow rates.By throttling the fan, airflow rates of 0�126, 0�248, 0�321,0�380, 0�430, 0�581 and 0�720m3 s�1m�2 were obtained.The minimum airflow rate was determined by thecharacteristics of the fan, which could only be throttledto a minimum velocity of 0�126m3 s�1m�2. Bulkdensities for loose- and dense-filled test columns wereobtained as described by Jayas et al. (1987). For a givenset of experimental conditions, four replicates weredone. The mean temperature and relative humidityunder which the experiments were conducted were2472�5 1C and 60710%, respectively.

4. Results and discussion

4.1. Pressure drop through clean bulk parchment coffee

Table 1 presents the mean values of four replicates ofpressure drop per unit depth at various levels ofmoisture content and airflow rates for loose and densefilling of the test column. There was a general increase inpressure drop per unit length with increase in airflowrate. Similar observations are reported by Dairo andAjibola (1994) and Madamba et al. (1993) for sesameseeds and garlic slices, respectively. The increase inpressure drop with increased airflow can be attributed toincreased kinetic dissipation of the air as velocityincreases.

600

500

400

300

200

100

0

0.2 0.4

Bed depth, m

Pres

sure

dro

p, P

a

0.6

Fig. 2. A typical plot of the effect of depth versus pressure dropacross a bed of clean bulk parchment Arabica coffee at differentairflow rates and constant moisture content of 19�6%(w.b.):��J��, 0�126 m3 s�1 m�2; -�-�n-�-�, 0�381 m3 s�1 m�2;

– –&– –, 0�581 m3 s�1 m�2; - -}- -, 0�720 m3 s�1 m�2

The effect of bed depth on pressure drop for looselyfilled test column is shown in Fig. 2. For a givenmoisture content and filling method, airflow resistanceincreased linearly with increase in bed depth. Doublingthe bed depth, for instance from 0�2 to 0�4m,approximately doubles the pressure drop. This observa-tion is in agreement with the findings of Dario andAjibola (1994) and Jayas et al. (1987) for sesame andrapeseed, respectively. The observation, however, doesnot agree with the findings of Wood and Baolin (1987),who observed that static pressure drop increased morerapidly for a compressed bed depth of malt resulting in anonlinear relationship between the two parameters.

The effect of the method of filling on pressure dropper unit depth is illustrated in Fig. 3. The observedhigher pressure drops for dense fills is attributed toincreased bulk densities due to packing of grains, whichlead to increased kinetic energy dissipation. Similartrends in pressure drops for sprinkle-filled (dense fill)and spout-filled (loose fill) columns are reportedby Jayas et al. (1987). It is also reported that upto 50% increase in pressure drops between loose-and dense-filled grains and seeds have been observed(ASAE, 2000).

Table 2 summarises the analysis of variance of theeffects of airflow, moisture content and bulk density onpressure drop per unit depth of clean bulk parchmentArabica coffee. The three variables significantly (prob-ability, Po0�05) affected static pressure drop. Of thethree parameters that affect pressure drop (Dairo &Ajibola, 1994), airflow rate had the greatest effect. Onlythe interaction between airflow rate and moisturecontent was significant (Po0�05) on the observedpressure drop values.

4.2. Fitting the experimental data to the empirical models

4.2.1. Shedd’s model

The data obtained in this study were fitted to the twoempirical models, namely, Shedd’s model (1953) andHukill and Ives model (1955) that are commonly used inpredicting the pressure drop across beds of agriculturalgranular materials. The fitting of the experimental datato these two models was adopted in order to evaluatehow well the models fitted the experimental dataobtained in this study. The analysing and fitting of thedata to the empirical models was effected using S-Plus2000 (MathSoft, Inc., USA).

Past studies on airflow resistance of seeds and grains(Jayas et al., 1987; Madamba et al., 1993; Dairo &Ajibola, 1994; Sokhansanj et al., 1990) indicate thatfitting the same experimental data to each of the twoempirical models at times resulted in fits that are

ARTICLE IN PRESS

Air

flow

rat

e, m

3 s-1m

-2

Air

flow

rat

e, m

3 s-1m

-2A

irfl

ow r

ate,

m3 s-1

m-2

Air

flow

rat

e, m

3 s-1m

-2

0.8

0.5

0.2

0.1

0.8

0.5

0.2

0.1

0.8

0.5

0.2

0.1

0.8

0.5

0.2

0.1102

Pressure drop per unit depth, Pa/m

103

102

Pressure drop per unit depth

103

102


103

102


103

(a) (b)

(c) (d)

Fig. 3. Variation of pressure drop to the airflow for clean parchment coffee at various moisture contents and methods of filling,* loose and ~ dense fill: (a) loose density, rl ¼ 552 kg m�3, dense density, rd ¼ 575 kg m�3, moisture content ¼ 36�7%; (b)rl ¼ 510 kg m�3, rd ¼ 541 kg m�3, moisture content ¼ 30�7%; (c) rl ¼ 429 kg m�3, rd ¼ 458 kg m�3, moisture content ¼ 19�6%;

(d) rl ¼ 414 kg m�3, rd ¼ 436 kg m�3, moisture content ¼ 12�7%


significantly different. It was therefore necessary that theexperimental data obtained in this study be fitted to thetwo models. The constants associated with each modelwere thereafter determined and the degree of fit was alsoevaluated for each model. In addition, the experimentaldata were fitted to Eqn (3) with the object ofdetermining the effect of the various clean parchmentcoffee parameters on the resistance to airflow. Fittingof the experimental data to Eqn (3) had the object ofdetermining how the various product and environmentalfactors identified influenced the airflow resistance ofclean parchment Arabica coffee.In order to fit Shedd’s model to the experimental data,

Eqn (1) was transformed into its logarithmic form, Eqn (4).Linear regression analysis was then used to relate thepressure drop to airflow rate at various levels of thefactors studied and to determine the constants A and B.

log Qa ¼ log A þ B log DP. (4)

Figure 3 presents the plots of Eqn (4) at the four levels ofmoisture content levels and two categories of bulkdensity arising from the fill method used in theexperiments. The observed linear relationships depictedby the fits in these plots are in agreement with those ofseveral researchers including Shedd (1953), Haque et al.(1978), Kumar and Muir (1986) and Madamba et al.(1993), for relatively large-grains.

Table 3 presents the estimate of the coefficients forEqn (4) for pressure drops for different combinations ofmoisture content, bulk density and method of filling forthe range of airflow used in this study. From Table 3, itis apparent that significantly different values for theconstants A and B are obtained for different airflowranges for Shedd’s model. This observation has beenmade in other studies on airflow resistance of othergrains and seeds (Jayas & Muir, 1991; Shedd, 1953;Brooker et al., 1992). Owing to the different values forthe constants A and B, even transforming Shedd’s modelinto its logarithmic form [Eqn (4)] and fitting theexperimental data does not obtain a ‘perfect’ straightline as should be the case.

The foregoing observations not only make the use ofShedd’s model inaccurate in practical situations, for fanselection for drying and aeration systems, if applied forwider airflow rates, the selected fan may either be toolarge or grossly inadequate for a given system. Owing tothis shortcoming of Shedd’s model, other models havebeen developed that have been found to fit experimen-tally obtained data to wider airflow ranges with betterdegrees of fit (Hukill & Ives, 1955; Brooker et al., 1992).

4.2.2. Hukill and Ives model

Comparison of fits of experimental data coveringwide variations of factors that affect pressure drops

ARTICLE IN PRESS

Table 3

Coefficient of Shedd’s model on pressure drop (0.126–0.72m3 s�1m�2 airflow rates range)

Moisture content, % (w.b.) Bulk density, kg m�3 Coefficients Coefficient of determination (R2)

A� 10�3 B

Loose fill36�7 552 8�630 0�656 0�99830�7 510 9�311 0�651 0�99819�6 429 12�942 0�598 0�99812�7 414 14�060 0�582 0�998

Dense fill36�7 575 8�770 0�630 0�99930�7 541 8�279 0�640 0�99819�6 458 12�618 0�586 0�99812�7 436 6�353 0�684 0�994

Table 4

Coefficients and standard errors obtained for clean parchment

coffee using standard stepwise non-linear regression techniques[Eqn (3)]

Modelvariable

Modelcoefficient

Estimatedvalue

Standarderror

Q2a

a 1121�81 102�97

QaM b �7�35 2�78QaB c 1�36 0�22

B, bulk density in kgm�3; M, moisture content in % (w.b.); Qa, airflow

rate in m3 s�1m�2.


across beds of grains and seeds has shown that better fitsare obtained with Hukill and Ives model than withShedd’s model (Hukill & Ives, 1955). This observationhas been made for several studies on airflow resistanceof seeds and grains (Hukill & Ives, 1955; Jayas & Muir,1991; Dairo & Ajibola, 1994). The Hukill and Ive’smodel has been adopted by the ASAE (2000) forpredicting airflow resistance across beds of grains, seeds,other agricultural products and perforated metal sheets,and is referred to in the literature as the airflowresistance equation.To test the effect of average conditions of the factors

that affect pressure drop of clean parchment coffee(bulk density and moisture content), the experimentaldata obtained for the loose-fill columns in this studywas non-linearly fitted using the Hukill and Ives model[Eqn (2)]. The fit yielded empirical constants, C and D of4�340� 103 Pa s2m�3 and 14�04m2 sm�3, respectively,with coefficient of determination R2 value of 0�95. Thesevalues, like those for other crops tabulated by the ASAEStandards (2000) based on this model, can be used bydesigners of coffee conditioning bins for predicting theairflow resistance to overcome when designing aerationand drying systems for parchment Arabica coffee. Oncethe airflow resistance has been determined, a requisitefan for forcing the air through the column of parchmentArabica coffee can be selected. This will eliminate thecurrent improper design of coffee conditioning binsresulting in economical coffee conditioning bins that aretechnically superior.

4.2.3. Factors affecting airflow resistance across beds of

parchment Arabica coffee

The various levels of the factors that affect pressuredrop across a bed of parchment coffee were fitted tothe stepwise non-linear regression model, Eqn (3). This

approach allows for statistical investigation of theoverall and relative effects of the product and experi-mental factors in the models applied for predictingairflow resistance (Dairo & Ajibola, 1994; Chung et al.,2001). The values of the regression coefficients and thestandard error estimates obtained by fitting the experi-mental data to this model for clean bulk parchmentArabica coffee are presented in Table 4. The coefficientof determination was 0�988. The results of fitting theexperimental data to this model indicated that airflowrate had the greatest effect on pressure drop across bedsof parchment Arabica coffee followed by moisturecontent and bulk density.

5. Conclusions

(1)
Airflow resistance across a column of parchmentcoffee increased linearly with increasing depth.
(2)
Airflow resistance across a bed of parchment coffeedecreased with a decrease in moisture content forloose- and dense-filled test columns. However,

ARTICLE IN PRESS


increase in bulk density resulted in increased airflowresistance for all experimental conditions.

(3)
The static pressure drop was affected significantly byairflow rate, moisture content and bulk density, butairflow rate had the most significant effect.
(4)
The resistance to airflow across a bed of clean bulkparchment coffee can be characterized by bothShedd’s model and the Hukill and Ives model. Thesignificantly different constants returned for Shedd’smodel for different airflow ranges imply that the useof this model to accurately select the correct fan sizemay be limited to narrow ranges of airflow rates.
Acknowledgements

The authors are very grateful to the University ofNairobi, Department of Environmental and BiosystemsEngineering (DEBE), for sponsoring the research workand to the management of the Upper Kabete campusand the Kabete Coffee Factory for donating the cleanparchment Arabica coffee used in this study. Theassistance of Mr. Frederick Wanguhu, Senior Technol-ogist, DEBE, in setting up the experiment is highlyappreciated.

References

Alagusundaram K; Jayas D S (1990). Airflow resistance ofgrains and oil seeds. Postharvest News and Information,1(4), 279–283

ASAE (2000). Standards D272.3 MAR96. Resistance toairflow of grains, seeds, other agricultural products andperforated metal sheets. ASAE, St. Joseph, MI, USA

Brooker D B; Bakker-Arkama F N; Hall C W (1992). Dryingand Storage of Grains and Oilseeds. AVI Publication,New York

Chung D S; Maghirang R G; Kim Y S; Kim M S (2001). Effectsof moisture and fine material on static pressure drops in abed of grain sorghum and rough rice. Transactions of theASAE, 44(2), 331–336

Dairo O U; Ajibola O O (1994). Resistance to airflow of bulksesame seed. Journal of Agricultural Engineering Research,58(2), 99–105

Farmer G S; Busewitz G S; Whitney R W (1981). Resistance toairflow of blue stem grass. Transactions of the ASAE, 24(2),480–483

Gumbe LO (1995). Coffee processing notes. Second CoffeeImprovement Project (SCIP). Unpublished, Ministry ofAgriculture and Livestock Development, Nairobi, Kenya

Haque E G; Ahmed Y N; Deyoe C W (1982). Static pressuredrop in a fixed bed of grain as affected by grain moisturecontent. Transactions of the ASAE, 25, 1095–1098

Haque E G; Foster H; Chung D S; Lai F S (1978). Staticpressure drop across a bed of corn mixed with fines.Transactions of the ASAE, 21(5), 997–1000

Henderson S M; Perry R L; Young J H (1997). Principles ofProcess Engineering, 4th Edn. ASAE, ISBN 0-929355-8B-7

Hukill W V; Ives N C (1955). Radial airflow resistance ofgrains. Agricultural Engineering, 35(5), 332–335

Jayas D S; Muir W E (1991). Airflow-pressure drop data formodelling fluid in anisotropic bulks. Transactions of theASAE, 34(1), 251–254

Jayas D S; Sokhasanj S; Moysey E B; Barber E M (1987).Airflow resistance of canola (rapeseed). Transactions of theASAE, 30(5), 1484–1488

Kumar A; Muir W E (1986). Airflow resistance of wheatand barley as affected by airflow direction, fillingmethod and dockage. Transactions of the ASAE, 29(5),1423–1426

Madamba R; Driscoll H; Buckle K A (1993). Bulk density,porosity and resistance to airflow of garlic slices. DryingTechnology, 11(7), 1837–1854

Mohsenin N N (1986). Physical Properties of Plant and AnimalMaterials, 2nd Edn. Gordon and Breach Science Publishers,New York

Nalladurai K; Alugusundaram K; Gayathri P (2002). Airflowresistance of paddy and its byproducts. Biosystem Engineer-ing, 83(1), 67–75

Siebenmorgen T J; Jindal V K (1987). Airflow resistance ofrough rice as affected by moisture content, fines concentra-tion and bulk density. Transactions of the ASAE, 30(4),1138–1143

Shedd C K (1953). Resistance of grains and seeds to airflow.Agricultural Engineering, 4(9), 616–619

Sokhansanj S A; Falasncinki A; Sosoiki F W; Jayas D S

(1990). Resistance of bulk lentils to airflow. Transactions ofthe ASAE, 33(4), 1281–1285

Sokhansanj S; Li W; Fasina O O (1993). Resistance of alfalfacubes, pellets, and compressed herbage to airflow. CanadianAgricultural Engineering, 35(3), 207–213

Wood J L; Baolin C (1987). A thin layer method for theinvestigation of bulk density and airflow resistance distribu-tion during deep bed drying. Drying Technology, 5(3),383–408

Documents

Airflow Resistance of Parchment Arabica Coffee