Analysis of Energy

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Journal of Food Engineering 82 (2007) 217–226

Analysis of energy usage in the production of three selectedcassava-based foods in Nigeria

S.O. Jekayinfa a,*, J.O. Olajide b

a Department of Agricultural Engineering, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Oyo State, Nigeriab Department of Food Science and Engineering, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Oyo State, Nigeria

Received 28 April 2006; received in revised form 31 January 2007; accepted 1 February 2007Available online 16 February 2007

Abstract

A study was conducted in 18 cassava processing mills situated in the southwestern part of Nigeria to investigate the energy utilizationpattern in the production of three different cassava products, viz: ‘gari’, cassava flour and cassava starch. Six mills specializing in theproduction of each of the products were randomly selected for investigation. The computation of energy use was done using the spread-sheet program on Microsoft Excel. Optimization models were developed to minimize the total energy input into each production line.The results of the study showed that the observed energy requirements per tonne of fresh cassava tuber for production of gari, starch andflour were 327.17, 357.35 and 345 MJ, respectively. The study identified the most energy-intensive operations in each production line andconcluded from optimization results that the total minimum energy inputs required for the production of gari, cassava starch and cassavaflour per tonne of fresh cassava tuber were 290.53, 305.20 and 315.60 MJ, respectively.� 2007 Elsevier Ltd. All rights reserved.

Keywords: Cassava products; Energy requirement; Unit operation; Optimization models

1. Introduction

1.1. Energy use and analysis in food processing

Energy and food are major concerns of most of thedeveloping countries such as Nigeria. About 70% of Nige-rian population depends on agriculture which contributesmore than 40% to the gross national product of the coun-try. With the introduction of high-yielding varieties, inten-sive cropping systems, increased usage of fertilizers andchemicals, and high level of farm mechanization, the mod-ern agriculture has become energy intensive. As in otherindustries, rising fuel cost and supply limitations plagueevery sector of Nigerian agricultural industry and theseindustries are now, more than ever before sensing the needfor energy related research to reduce costs through energy

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doi:10.1016/j.jfoodeng.2007.02.003

* Corresponding author. Tel.: +234 8033942248.E-mail address: [email protected] (S.O. Jekayinfa).

conservation and prevent possible shut downs consequentto reduced availability of energy resources.

Few processing factories have any precise idea of theenergy consumption of different production areas and inthe absence of detailed internal monitoring, the energy effi-ciencies of different operations is also usually unknown.Knowledge of energy consumption for each product in afactory is useful for several purposes such as budgeting,evaluation of energy consumption for a given product,forecasting energy requirement in a plant, and for planningplant expansion. A limited number of studies have beenreported in literature on the determination of energy con-tents of field operations. These include a study reportedby Chang, Chang, and Kim (1996) involving the develop-ment of an energy model and a computer simulation modelto assess the requirements of electricity, fuel and labour forrice handling, drying, storage and milling processes in RiceProcessing Complex (RPC) in Korea.

Harper and Tribelhorn (1995) compared the relativeenergy costs of village – prepared and country processed

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Nomenclature

Pl peelingW washingG gratingD dewateringGD grindingC chippingS sievingF fryingFG filteringR re-sievingP post-grindingM mixing

SW starch washingML millingDR dryingCB cake breakingZ production output of a particular cassava prod-

uct

Subscript

g garis cassava starchf cassava flour

218 S.O. Jekayinfa, J.O. Olajide / Journal of Food Engineering 82 (2007) 217–226

weaning foods, both made from the same ingredients, butprocessed differently before being used. Palaniappan andSubramanian (1998) analysed the 5-year energy consump-tion data for 25 tea factories in South India. The variationin energy consumption in killowatt hour per kg of tea madein both CTC and orthodox factories-based on factors suchas type of tea produced, production capacity of factoriesclimate, etc., were analysed. They also studied the specificenergy consumption for the different processes. The con-sumption of direct energy from major sources in tea indus-try in Assam India was studied by Baruah andBhattacharya (1996). They submitted that a tea gardenrequired an estimated 18,408 MJ/ha of human energy inthe first year. Other similar works reported in literaturerelating to evaluation of energy efficiency in processingindustries include cashew-nut processing in Nigeria (Jekay-infa & Bamgboye, 2003, 2006); palm-kernel oil processingin Nigeria (Jekayinfa & Bamgboye, 2004, 2007) rice pro-duction in Bangladesh (Islam, Rahman, Saker, Ahduzz-aman, & Baqui, 2001) sugar-beet production in Morocco(Mrini, Senhaji, & Pimentel, 2002) and, energy and labouruse in Italian agriculture (Pellizzi, 1992). This study wasundertaken to investigate the energy use pattern in theselected cassava processing mills in southwestern Nigeriaand to develop predictive models that could estimate andoptimize the energy demand of each unit operation for dif-ferent selected cassava products.

1.2. Cassava

Cassava (Manihot esculenta Crantz) is a perennial vege-tatively propagated shrub commonly cultivated within thelowland tropics. The world production of cassava rootincreased from 70 million tonnes in 1960 to 154 million ton-nes in 1991 (CIAT, 1993). Subsequently, the estimatedannual global production of cassava between 1998 and2001 was 168 million tonnes fresh weight out of whichabout 70% was produced in Nigeria, Brazil, Thailand, Indo-nesia and Democratic Republic of Congo (FAO, 2001).

Cassava is the second most important staple, after maizein terms of calories consumed and a major source of calo-ries for about 40% of the African population (Nweke,1992). It thus alleviates food crisis in Africa because ofits agricultural advantages. The main advantages arehigher yield per unit area of land as well as per unit oflabour compared to other cereals under similar conditions.It is tolerant to drought and produces on poor soils whereother staples fail. Cassava roots are rich in carbohydrates,but other nutrients are in low levels (Cock, 1985).

Nigeria still remains the largest cassava producer in theWorld producing about 35 metric tonnes/annum. Nigeria’sprimum inter pares position is mainly due to the distribu-tion of the high yielding, disease resistant varieties. Thesecassava varieties were developed by the International Insti-tute of Tropical Agriculture (IITA), and other nationalresearch institutes like the National Root Crop ResearchInstitute (NRCRI), as well as the Federal Government’seffort in increasing food crops through their various pro-grammes like the National Accelerated Food ProductionProgramme, Operation Feed the Nation, the AgriculturalDevelopment Project assisted by IFAD Cassava Multipli-cation Programme, which according to Oke (2005) couldgive as high a yield as 80–90 tonnes/ha.

One of the major problems associated with cassava isthe rapid post harvest deterioration, which renders itunpalatable as food. Initially, deterioration is due to phys-iological processes, which occur within 2–3 days of harvest,and are subsequently followed by microbial deteriorationwithin 5–7 days (Beeching, Dodge, Moore, & Wenham,1994). Deterioration necessitates the prompt consumptionor processing of cassava soon after harvest.

Processing of cassava is necessary for several reasons: itis a means of removing or reducing the potentially toxiccyanogenic glucosides present in the fresh cassava. Process-ing as a means of preservation yields products that havedifferent characteristics and thus create variety in cassavadiets. Numerous methods of processing have been devel-oped for cassava in different parts of the world and these

S.O. Jekayinfa, J.O. Olajide / Journal of Food Engineering 82 (2007) 217–226 219

methods result in the production of a wide variety of foodproducts (Lancaster, Ingram, Lim, & Coursey, 1982).

1.3. Some traditional staple foods from cassava

Flour or starch from roots and tubers, especially cassavaare utilized in the preparation of various food gels, snacksand baked goods. Such traditional products from cassavainclude gari, industrial starch, flour, etc.

1.3.1. Gari

Gari is widely known in Nigeria and other West Africancountries. It is called ‘‘atoukpou” in Bokinafaso (Nweke,1992). The processing operations involved are shown inFig. 1. Some of the processing steps such as grating, millingand water expression are mechanized (Igbeka, Griffon, &Jory, 1992; Lancaster et al., 1982). In the Eastern part ofNigeria, palm oil is often added during frying (toasting)operation. Addition of palm oil prevents burning duringgarifying and it has additional desirable effect of changingthe colour of the product to yellow. The average urbanconsumer prefers gari because it is a pre-cooked food prod-

Grate

Dewater

Cake breaking

Dry

Mill finely

Ferm

Cassavaflour

Material

Unit Operation

Key

Fig. 1. Processing steps for the sel

uct. Production of one tonne of cassava costs $19.50. Themarket price of gari is between $54.63 and $78.04 per tonne(Oke, 2005).

1.3.2. Cassava starch

Cassava starch is the starting point for so many impor-tant industrial products such as dextrin, glucose syrup, etc.Cassava starch is preferred amongst other types because ofits good gelling property. Traditionally, cassava starch isproduced by first washing the peeled root manually andthen grating to produce starch milk from which the fiberis separated through special strainers or sieved throughmuslin cloth and washed thoroughly and the starch willthen collect and settle down (Fig. 1).

The indicative price of cassava starch in Nigeria is about$456/tonne, with market value of about $22.6million/annum, leading to the creation of about 150,000 jobs(Oke, 2005).

1.3.3. Cassava flour

The utilization of cassava in the production of fast foodswould make the urban population attracted to such noo-

Peel/Wash

Mill

Bagged Mash

ent 2, 4 and 6 days

Dewater

Pulverise/sift

Roast

Chip and grind

Mix with water 4, 6, 10 day

Filter

Wash

Dewater

Dry

Mill

Cassavaroots

Gari

Starch

ected cassava-based products.


dles, breakfast cereals, pies, etc. Presently in Nigeria, thereis a regulation that all wheat flour should contain 10% cas-sava flour and this presently requires 200,000 tonnes of cas-sava flour in which only about 10,000 tonnes have beensupplied. One of the important reasons responsible for thisis the standard required to the cassava flour which is highand cannot be compromised (Oke, 2005).

The estimated market value of cassava flour in Nigeriais $25million/annum with an employment potential ofabout 800,000 jobs at two people/tonne. To be able to sat-isfy this demand, about 400 small scale factories produc-ing 2 tonnes of cassava flour per day are needed (Oke,2005).

2. Materials and methods

Processing data for the three products were gathered bydirect measurement during the normal operation period ofsix randomly selected mills specializing in the production ofeach selected cassava-based food. The random selectionwas done from the pool of mills that were not only up todate in their data management practice but also less than10 years old to ensure that they were within their usefulyears. The areas of study covered Osun and Oyo Statesof Nigeria. Osun and Oyo States cover an area of 17,600sq. km and have a total population of about 5 million peo-ple (1991 census), with a population density of about 284people per sq. km.

The energy analysis was based on process analysis inwhich the direct energy consumption in every successiveproduction step was estimated and the materials input toeach operation also indicated. The principal operationsinvolved in the production of each selected cassava-basedfood are highlighted in Fig. 1. The estimation of thermalenergy (obtained from the use of fuel), electrical energy(obtained from electricity use from the national grid) andmanual energy (from human labour) was done as follows(Jekayinfa & Bamgboye, 2004, 2006, 2007).

2.1. Evaluation of electrical energy

The rated horsepower of each motor was multiplied bythe corresponding hours of operation and summed to findthe electrical energy usage by equipment. A motor effi-ciency of 80% was assumed to compute the electrical inputs(Johnson, 1999; Rajput, 2001).

2.2. Evaluation of thermal energy

Energy from fossil fuel was assigned to each unit opera-tion according to their level of consumption. The totalquantity of energy consumed from fossil fuel was convertedto common energy unit (Joule) by multiplying the quantityof fuel consumed by the corresponding calorific value(lower heating value) of the fuel used (Ezeike, 1981; John-son, 1999; Rajput, 2001).

2.3. Evaluation of manual energy

Manual energy was estimated based on the value recom-mended by Odigboh (1997). According to Odigboh (1997),at the maximum continuous energy consumption rate of0.30 kW and conversion efficiency of 25%, the physicalpower output of a normal human labour in tropical cli-mates is approximately 0.075 kW sustained for an 8–10 hwork day. All other factors affecting manual energy expen-diture were found insignificant and therefore neglected. Todetermine the manual energy input for a given operation,the time spent by the worker on each operation wasrecorded. This included the intermittent resting periods.For any unit operation, the manual energy expenditure,Em, was determined by

Em ¼ 0:075 � N � T a ðkWhÞ ð1Þwhere

0.075 = the average power of a normal human labour inkWN = number of persons involved in an operationTa = useful time spent to accomplish a given task (oper-ation), h

To access the energy demands (electrical, fuel or man-ual) in all the eight unit operations of cassava-based foodproduction, quantitative data on operating conditions weremeasured. The energy consumed in all the unit operationsinvolved in the production of each of the selected cassava-based products was measured and a series of equationswere developed for each of the unit operations.

2.4. Experimental procedure

Before the commencement of the experiments, knownquantity of fuel was measured into the empty tank of thecaptive electricity generator in each mill. The initial readingof the electric power-reading meter installed in each sectionof the mill was taken at this time. After the completion ofthe processing of 1000 kg of raw cassava into any of theselected three products, the quantity of the fuel left in thegenerator’s tank and the reading of the electric meter,installed for this purpose, were taken. The differences inthese readings represented the quantity of fuel used (inlitres) and the electric power consumed in (kW), respec-tively. For each of the operations, the number of personsinvolved was counted and the time taken was also recordedusing a stopwatch with all intermittent resting and idle per-iod deducted. From this procedure it was possible to assignthermal, electrical, both thermal and electrical, or manualenergy, as the case may be, to each unit operation. Conver-sion of these raw data to energy equivalent was done usingthe developed energy equations.

The processing facilities of all the selected mills are verysimilar. All the mills selected were evaluated over the sameperiod and seasons, and as a result, the error of seasonal


changes was eliminated. No prior experimental conditionswere used as data collection in each locality was done as themills were in operation. The apparatus used for the studyinclude:

(i) A stop watch for measuring production time.(ii) A measuring cylinder for quantifying the amount of

fuel consumed during each unit operation.

For consistency, the energy components were calculatedon the basis of 1000 kg of raw cassava. This approach issimilar to that used in previous studies by Ezeike (1981)and Jekayinfa and Bamgboye (2003, 2004, 2007). Usingenergy accounting symbols presented by Singh (1978) with

Mass flow (kg)

Electrical energy (MJ)

Thermal energy (MJ)

Manual energy (MJ)

Unit operation 485

14.60

0.94

28.13

9.0

223.38

0.59

7.50

10.50

22.38

1.22

0.30

8.25

Fig. 2. Energy flow diagram in a

slight modifications, energy and mass flow diagrams (Figs.2–4) were constructed for a typical gari, starch and flourmills, respectively.

Various models (linear, semi-log, log-linear and polyno-mial) were tried to develop the functional relationshipbetween energy input and food productivity to optimizethe food production system. The selection of appropriatemodel for a particular situation was made on the basis ofR2 value. The general equation fitted for different cas-sava-based foods was of the following nature (Sidhu,Singh, Singh, & Ahuja, 2001):

y ¼ A0 þXm

i¼1

Xn

j¼1

AijðxjÞii

ð2Þ

Peeling

Washing

Grating

Dewatering

Sieving

Frying

Re-sieving

Cassava1000

Post-grinding

FinetexturedGari 250

15Fibres

600Water

120peels

15Garilumps

typical gari processing mill.

Mass flow (kg)


Thermal energy (MJ)

Manual energy (MJ)

Unit operation

Peeling

Washing

Chipping

Grinding

Mixing

Filtering

Starch Washing

2.920.21

28.13

Cassava1000

9.0

223.75

0.59

1.20

1.20

80.55

0.60

Dewatering

0.94

Starch500

380Water

120Peels

8.25

Fig. 3. Energy flow diagram in a typical starch producing mill.


where m is equal to 1 for linear relationship and 2 for qua-dratic relationship; y, yield, kg/tonne of cassava; A0, inter-cept; n, number of independent variables; Aij, regressioncoefficients; and xj is the independent variable. The sensi-tivities of the apparatus used in the course of this studyand the error analysis were calculated .

3. Results and discussion

3.1. Energy requirement for gari processing operations

Average energy inputs at different stages of productionof gari are presented in Table 1 and Fig. 2. From Table 1and Fig. 2, it was observed that in all the gari processing

mills investigated; thermal energy is mostly used, followedby manual energy and electrical energy. This shows thatmajority of the mills depend on fuel for operations.75.2% of the average total energy in all the gari millswas obtained from thermal source, followed by 17.8%and 7.0% obtained from manual and electrical energysources, respectively. This evidently shows that most ofthe tedious operations involved in gari processing areactually carried out mechanically with over 80% of energyconsumption attributed to either the use of internal com-bustion engine or electric motors for operating processingmachines.

Considering the unit operations during gari production(Fig. 2), it was observed that all the unit operations

Mass flow (kg)


Thermal energy (MJ)

Manual energy (MJ)

Unit operation

Peeling

Washing

Grating

Dewatering

Cake Breaking

Milling

7.30

0.90

28.13

Cassava1000

9.0

223.75

0.59

0.60

0.15

67.13

Cassavaflour 200

120Peeks

8.25

Drying

0.60

600Water

80Water

Fig. 4. Energy flow diagram in a typical cassava flour producing mill.


required manual energy in different quantity. Only gratingutilized all the available energy sources. The average energyuse for grating (232.22 MJ) was the highest accounting for

Table 1Estimates of energy input by unit operations for production of ‘‘gari”from 1000 kg of cassava tubers

Unitoperation

Time(h)

Energy (MJ) Percentof totalElectrical Thermal Manual Total

Peeling 25.00 – – 28.13 28.13 8.60Washing 8.00 – – 9.00 9.00 2.75Grating 1.13 8.25 223.38 0.59 232.22 71.10Dewatering 2.50 – – 0.94 0.94 0.29Sieving 2.00 – – 7.50 7.50 2.30Frying 2.00 – 22.38 10.50 32.88 10.06Re-sieving 3.25 – – 1.22 1.22 0.37Post

grinding2.00 14.60 – 0.30 14.90 4.60

Total 45.88 22.85 245.76 58.18 326.79 100.00Percent of

total7.00 75.20 17.80 100.00

71.1% of the total energy consumption. This was followedby frying (32.88 MJ, 10.06%), peeling (28.13 MJ, 8.6%) andpost grinding (4.9 MJ, 4.6%). Other results include washing(9.0 MJ, 2.75%), sieving (7.5 MJ, 2.3%), re-sieving(1.22 MJ, 0.37%) and dewatering (0.94 MJ, 0.29%). In all,the total energy requirement for processing 1000 kg of cas-sava tuber into ‘gari’ is 326.79 MJ. The mean value oferrors between the measured value and the true value was0.152. The standard deviation of the differences in the 6mills was 0.174 with a worst-case error of 0.03.

3.2. Energy requirement for production of cassava starch

Table 2 and Fig. 3 show the average energy consump-tion on the basis of all unit operations involved in cassavastarch production in the study area. Eight readily definedunit operations common to all starch mills visited are: cas-sava peeling, washing, chipping, grinding, mixing, filtering,starch washing and dewatering. From Table 2, it can be

Table 2Estimates of energy input by unit operations for the production of cassavastarch from 1000 kg of cassava tubers

Unitoperation

Time(h)


Peeling 25.00 – – 28.13 28.13 7.87Washing 8.00 – – 9.00 9.00 2.52Chipping 1.13 8.25 223.75 0.59 232.59 65.09Grinding 0.40 2.92 80.55 0.21 83.68 23.42Mixing 4.00 – – 1.20 1.20 0.34Filtering 4.00 – – 1.20 1.20 0.34Starch

washing2.00 – – 0.60 0.60 0.17

Dewatering 2.50 – – 0.94 0.94 0.26Total 47.03 11.17 304.30 41.87 357.34 100.00Percent of

total3.13 85.15 11.72 100.00

Table 3Estimates of energy input by unit operations for the production of cassavaflour from 1000 kg of cassava tubers

Unitoperation

Time(h)


Peeling 25.00 – – 28.13 28.13 8.12Washing 8.00 – – 9.00 9.00 2.60Grating 1.13 8.25 223.75 0.59 232.59 67.15Dewatering 0.40 – – 0.90 0.90 0.26Cake

breaking2.00 – – 0.60 0.60 0.17

Drying 4.00 – – 0.60 0.60 0.17Milling 1.00 7.30 67.13 0.15 74.58 21.53Total 41.53 15.55 290.88 39.97 346.40 100.00Percent of

total4.49 83.97 11.54 100.00


observed that thermal energy accounted for more than 85%of the total energy consumption in all the mills. 11.72% and3.13% of the total energy used could be attributed to man-ual and electrical energy sources, respectively. This againshows that the most tedious and energy consuming opera-tions (chipping and grinding) were performed mechanicallyby the use of machines powered by either an electric motoror internal combustion engine.

As depicted by Table 2 and Fig. 3, only two operations(chipping and grinding) combined the use of all availableenergy sources. Other operations that were performedentirely manually are peeling, washing, mixing, filtering,starch washing and dewatering with average energy require-ments of 28.13, 9.0, 1.20, 1.20, 0.60, and 0.94 MJ, respec-tively. Conclusively, the average total energy requirementfor producing cassava starch in all the mills investigated is357.34 MJ per 1000 kg of cassava tubers, with the meanvalue of errors of 0.158 and standard deviation of 0.185.

3.3. Energy requirement for production of cassava flour

Energy consumption pattern in the production of cas-sava flour from selected typical mills in the study area ispresented in Table 3 and Fig. 4. Production of flour com-prises 7 readily defined unit operations viz: Peeling, wash-ing, grating, dewatering, cake breaking, drying, andmilling. The average total energy consumption per1000 kg of raw cassava tubers for all these 7 unit opera-tions in the selected cassava flour mills was 346.40 MJ.The mean value of errors between the measured valuesand true value was 0.165. The standard deviation of the dif-ferences in the 6 mills was 0.158 with a worst-case error of0.03. The two prominent energy intensive operations aregrating and milling, accounting for 67.15% and 21.53%of the total energy, respectively. Other operations withtheir percent energy contributions in parenthesis are peel-ing (8.12%), washing (2.60%) and cake breaking (0.17%).As with other 2 cassava products, thermal energy was themostly used energy source with average total contributionof 83.97% of the total energy consumed. This was followed

by manual energy and electrical energy with percent contri-butions of 11.54% and 4.49%, respectively.

As indicated in Fig. 4, cassava conversion rate in a typ-ical flour-producing mill is 20%. It could be observed in allthe processing mills visited that thermal energy, from theuse of fuel, was prominent. This is due to incessant failurein power supply from the national grid during the periodthis study lasted.

3.4. Optimization equations

Eqs. (3)–(5) are the optimization equations developedfor the selected cassava-based foods from the raw energydata collected on the basis of different unit operations.The production output of different products under studywas optimized by multi-variable technique with no con-straints with respect to various energy inputs. The tech-nique enables the maximum production output achievedand the optimum value of each unit operation to be calcu-lated for each product. Table 4 is the summary of data col-lected on observed and optimum values for product outputand energy inputs from different unit operations.

3.4.1. Gari

Both linear and quadratic relationships gave significantcorrelation for gari production. On the basis of R2 valueof 0.85, which is the higher value, linear model was selectedas given in Eq. (3)

Y g ¼ 25Plg þ 8W g þ 1:3Gg þ 2:5Dg þ 20Sg þ 20F g

þ 3:2Rg þ 2P g ð3Þ

Variation explained by this relationship was 85% andthe remaining 15% variation might be due to unforeseenand sometimes, unexplainable parameters, such as opera-tors’ ages and experiences, equipment types and age, man-agement practices, maturity and cultivars of cassava tuberbeing processed, etc. All unit operations involved in gariproduction contributed significantly to energy consump-tion. The most significant unit-operation in the developedmodel was grating.

Table 4Comparison of observed and optimum values for product output and energy inputs from different unit operations for gari, cassava starch and cassavaflour

Unit operation Gari Cassava starch Cassava flour

Obs. V.(MJ)a

Opt. V.(MJ)b

Change(%)

Obs. V.(MJ)

Opt. V.(MJ)

Change(%)

Obs. V.(MJ)

Opt. V.(MJ)

Change(%)

Peeling 28.13 20.15 �28.37 28.13 18.15 �35.48 28.13 20.13 �28.44Washing 9.00 7.00 �22.22 9.00 7.10 �21.11 9.00 7.10 �21.11Grating 232.22 217.92 �6.16 – – – 232.59 216.90 �6.75Chipping – – – 232.59 205.00 �11.87 – – –Grinding – – – 83.68 71.81 �14.09 – – –Dewatering 0.94 0.74 �21.28 0.94 0.74 �21.28 0.90 0.90 –Mixing – – – 1.20 1.00 �16.62 – – –Sieving 7.50 7.00 �6.67 – – – – – –Cake breaking – – – – – – 0.60 0.45 �25.00Filtering – – – 1.20 1.00 �16.67 – – –Frying 32.88 28.50 �13.32 – – – – – –Drying – – – – – – 0.60 0.60 –Milling – – – – – – 74.58 70.38 �5.63Re-sieving 1.22 1.02 -16.40 – – – – – –Starch washing – – – 0.60 0.40 �33.33 – – –Post grinding 14.90 11.50 �22.82 – – – – – –Total energy

(MJ)326.79 293.83 �10.09 357.34 305.20 �14.59 346.40 315 �8.85

Yield (kg) 250.00 325.00 30.00 500 585.00 +17.00 200 230 +15.00

a Obs. V. – Observed valueb Opt. V. – Optimized value


Gari yield was maximized for the optimum level of dif-ferent energy inputs. The maximized yield value was esti-mated to be 325 kg of gari/tonne of cassava tuber for thetotal energy inputs level of 293.83 MJ. The input energyas can be seen in Table 1 and Figs. 1 and 2 consisted ofpeeling, washing, grating, dewatering, sieving, frying, re-seiving and post grinding. The optimum level in peelingoperation can be achieved by using more energy per tonneof raw cassava tuber to be peeled. This can be achieved byincreasing the number of persons involved in peeling. Also,optimal levels can be achieved for washing, dewatering andfrying operations by the same method of increasing theenergy per materials to be processed. Grating, seiving, re-seiving and post grinding are also very critical operationsin gari production in respect to timeliness. Therefore toachieve optimal levels of energy input, one could makeuse of more efficient and tested equipment for each of theoperations.

3.4.2. Cassava starch

The yield of cassava starch was best explained by linearequation having tested all other models based on the R2

value. The relationship between cassava starch yield andvarious energy inputs is given by Eq. (4). The R2 valuefor the equation was 0.88

Y s ¼ 25Pls þ 8W s þ 1:3Cs þ 2:5GDs þ 20M s þ 20F s

þ 3:25Ss þ 2Ds ð4Þ

As observed in the case of gari, the remaining 12% varia-tion not explained by the relationship in Eq. (4) could be

connected to unforeseen parameters such as mentioned inthe preceeding subsection. All the energy inputs have sig-nificant contributions to the model.

Cassava starch yield was also maximized for optimumlevel of various energy inputs. The maximized cassavastarch output was estimated to be 585 kg/tonne of raw cas-sava tuber for the total energy inputs level of 305.20 MJ.The energy inputs for cassava starch production were frompeeling, washing, chipping, grinding, mixing, filtering,starch washing and dewatering as presented in Table 2and Figs. 1 and 3. The comparison of observed and opti-mum value for various energy inputs was also presentedin Table 4.

3.4.3. Cassava flourThe 84% variation in yield of cassava flour was signifi-

cantly explained by a linear equation (Eq. (5)) with R2

value equal to 0.84

Y f ¼ 25Plf þ 8W f þ 1:13Gf þ 0:4Df þ 2CBf þMLf ð5Þ

Yield of cassava flour was also maximized with multi-variable technique with no constraints. The estimated yieldof cassava flour from the developed equation was 230 kg/tonne of raw cassava tuber for 315.6 MJ of total energyinput from unit operations consisting of peeling, washing,grating, dewatering, cake breaking, drying and milling.Similar to the observation in the two previously discussedproducts, energy consumption in manual operations suchas peeling, washing, dewatering, cake breaking and dryingcould be optimized by carefully deciding on the number of


persons that could be involved in these operations on thebasis of available work place thereby reducing time ofoperation, increasing production output and reducing unitcost of production. The energy inputs for grating and mill-ing can be optimized by using high-capacity motorizedgrater and attrition mill, respectively.

4. Conclusions

The following conclusions can be drawn from the resultsof this study:

� The observed energy requirements per 1000 kg of freshcassava tuber for production of gari, starch and flourare 327.17 MJ, 357.35 MJ and 345 MJ, respectively.� The study identified the most energy-intensive opera-

tions in each production line and concluded from opti-mization results that the total minimum energy inputsrequired for the production of gari, cassava starch andcassava flour per tonne of fresh cassava tuber were290.53, 305.20 and 315.60 MJ, respectively.� The energy consumption for all manual operations in all

selected production lines could be optimized by carefullydeciding on the number of persons that could beinvolved in these operations on the basis of availablework place thereby reducing time of operation, increas-ing production output and reducing unit cost of produc-tion. The energy use in mechanized operations could beoptimized by using efficient and high-capacity process-ing machines, for example, IITA (International Instituteof Tropical Agriculture) developed cassava processingequipment.

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