The Effect of Variety and Drying On the Engineering Properties of Fermented Ground Cassava Chukwuneke J.L1*, Achebe C.H1, Okolie P.C1 and Okafor E.A2 1 Department of Mechanical Engineering, Nnamdi Azikiwe University, P.M.B 5025 Awka, Nigeria 2 School of Engineering, Energy Centre, Robert Gordon University, Aberdeen. AB10 1FR *Corresponding Author E-mail: [email protected] Abstract: - Many food processing industries use cassava as their basic raw material. The existence of improved varieties of cassava demands that the effect of variety on the engineering properties of fermented ground cassava is studied in order to generate data for design and optimum performance of various driers used in cassava processing. This paper attempts to provide data on the engineering properties such as moisture content, specific heat capacity, thermal conductivity, thermal diffusivity, bulk density and mass transfer coefficient of some cultivars as well as determine the effect of variety on the drying and engineering properties of fermented ground cassava using two high yield improved cultivars (Tms 30572 and NR 8082) and one native cultivar (Akpu Bonny). General models were also obtained, which could be used to predict the specific heat and thermal conductivity at different moisture content of the cultivars. The specific heat capacity obtained ranged from 1.53kJ/kgK to 3.49kJ/kgK while the thermal conductivity ranged from 0.24W/moC to 0.51W/moC for dried fermented ground cassava of these cultivars. The highest moisture content of 48.66% was obtained after fermentation with the NR 8082 variety. At same moisture content, the specific heat capacity and thermal conductivity were found to be different for cultivars with different proximate compositions but similar for cultivars with close proximate compositions. The drying rate, thermal diffusivity and mass transfer coefficient of each cultivar varied with proximate composition, hygroscopy, product surface area and change in density after drying. Therefore, the same drying conditions cannot be used for drying the different cultivars except if they have close engineering properties. Keywords: Fermented ground cassava, Specific heat capacity, Thermal conductivity, Thermal diffusivity, Bulk density, Effect of variety, Cultivars, Drying rate, Moisture Content, proximate compositions . 1. INTRODUCTION 1.1. Background of the Study The design, simulation, optimization, operation and control of food processing operations require basic engineering properties of foods. Food technologists require data on engineering properties for various purposes such as process design, quality assessment and evaluation. Cassava is widely grown in Africa and some other parts of the world. It plays a central role in the diets of most Nigerians. This is why  attributed garri (a staple food from drying of fermented cassava flour) as the commonest food amongst the teeming poor West African people. Fermented cassava flour is, therefore, one of the most important cassava products and the methods of processing depend on local customs. However, the industrial utilization of cassava roots into various food and non-food uses is expanding by the day. Consequently, food industries need to understand the various engineering or physical properties of ground cassava in other to use it as a raw material. These properties include; 1. Specific heat capacity which is the amount of heat (kJ) needed to raise the temperature of a unit mass (kg) by a unit change in temperature (k). 2. The thermal conductivity which is the amount of energy, in form of heat, "conducted through a body of unit area and unit thickness in unit time when the difference in temperature between the faces causing heat flow is unit temperature difference . 3. The thermal diffusivity determines how fast heat propagates or diffuses through a material. Knowledge of these engineering properties is necessary not only because they are important on their own but they are the commonest indicators of other properties and qualities . These engineering properties are known to be affected by density, moisture content and temperature, and will help the engineer to generate data for the design and operation of driers for cassava processing. Drying is an inevitable unit operation in the food processing industries since dehydrated foods normally last longer due to the absence of microbial activities. 1.2. Aims and Objectives A review of pertinent literature revealed that such data on engineering properties of foods were lacking ; Hence the objectives of this study are to determine; at various stages of drying fermented ground cassava into garri: 1. The moisture content. 2. The specific heat capacity. 3. The thermal conductivity. 4. The thermal diffusivity. 5. The bulk density. 6. The mass transfer coefficient. 7. To determine the effect of variety on the drying and engineering properties of fermented ground cassava. 1.3. Significance of Study The significance of this work cannot be overlooked just as cassava itself. Knowledge of the engineering properties is necessary because they are the commonest indicators of other food qualities. Engineering properties are important data needed for quality assessment and evaluation, design, operation and control of driers since drying is an inevitable stage in the production of both food and agricultural products. Also, knowledge of these properties and how they are affected by drying will enhance better understanding of the heat and mass transfer phenomena for drying of agricultural products. Moreover, it provides an opportunity to apply the principles of chemical and Mechanical engineering processes which will help as a guide to any interested industrialist for future applications taking into account the engineering properties of ground cassava. 1.4. Scope / Limitations The study attempts to determine the various engineering properties such as moisture content, specific heat, thermal conductivity and thermal diffusivity of fermented ground cassava only. The study is also restricted to three varieties of cassava; two improved ones (Tms 30572 and NR 8082) and a native variety. 2. METHODOLOGY 2.1. Sample Preparation This involved the preparation of cassava cultivars, one native cultivar (Akpu Bonny) and two high yield improved cultivars (Tms 30572 and NR 8082) all obtained from Root-crops Development Centre, Agricultural Research Institute, Igbariam, Anambra State, Nigeia. The cultivars were harvested in the month of April, peeled, washed, grated and packed in three different sacks for pressing. They were then allowed to ferment for 72 hours. The mashed cassava was sieved with a mesh of 2.4mm. A hot circulating air oven was used to determine the drying rates. 2.2. Determination of Engineering Properties I. Moisture Content The moisture content was determined before and after fermentation. Three different crucibles were washed and dried in an air oven for about 40mins; 5.0g of each sample were carefully weighed into each of the identified crucibles, it is then dried in a hot circulating air oven at 105°C for 24hours. Further drying was continued until the final weight of dry sample became stable. The initial moisture content of the samples was calculated as the total moisture loss divided by total sample weight and presented in W W2 percent wet basis. (1) X 1 100 w W1 Where: Xw = moisture content on wet basis, W1 = Initial weight of sample, W2 = Final weight of sample after drying. The moisture content on dry basis was calculated using; Xd W1 W2 100 W1 1 (2) The moisture content on dry basis at any time‘t’ was also calculated using the equation; Xt (dry basis) = 1 −2 2 × 100 (3) Where; W2 is the weight of dried sample and W1 is the weight of sample at any time t. II. Proximate Compositions The Association of Analytical chemists method was used to determine the carbohydrate, moisture, protein, fat, fibre and ash (dry ashing method in a furnace) content of the samples . The proximate composition was determined after drying in an air oven at 70oC for 24hours. III. Ash Content Determination A silica dish was heated at 600oC, cooled and weighed; 2.0g of the sample was carefully transferred into the dish. The dish was then placed into a muffle furnace and ashed at 600 oC for 3hours. It was then allowed to cool in desiccators before taking the final weight. This procedure was carried out for all the ℎ ℎ samples and the ash content was calculated thus; % Ash = ℎ ℎ × 100 (4) IV. Fat Content Determination Soxhlet extractor was used. An extraction flask was thoroughly washed and dried in hot oven for 30mins. It was placed in desiccators to cool. 2.0g· of sample was accurately weighed and transferred into a rolled ashless filter paper and placed inside the extractor thimble. The thimble was placed into soxhlet extractor. Some reasonable quantities of petroleum ether, about three-quarter of the volume of the flask were placed inside the extraction flask. The heater was switched on and the set up was heated for about 3hours at low temperature so that the temperature of the petroleum ether is not exceeded. Finally, the extracted oil was dried at 1000C and weighed. The difference in the weight of empty flask and the flask with oil gives the oil content of the sample. The percentage fat is thus calculated as; % fat = − × 100 (5) Where; A = weight of empty flask, B = weight of sample, C = weight of flask + oil after drying. V. Moisture Content Determination The sample for proximate analysis was heated at 600C in a hot air circulating oven for 24hours. The moisture content was determined using 2.0g of sample on dry weight basis. VI. Fibre Content Determination 2.0g of the sample was collected (W1) 150ml of preheated H2S04 was added and heated to boiling for 30mins. It was then filtered and the residue washed three times with hot water. 150ml preheated KOH was added and heated to boiling for another 30mins, filtered, washed three time with hot water and three times with acetone before drying at 1300C for 1 hour. The sample was then weighed (W2), ashed at 500oC and the ash also weighed (W3). The fibre content is thus calculated; % Fibre W2 W3 100 (6) W1 Where; W1 = weight of sample, W2 = weight after pretreatment & drying, W3 = weight after ashing. VII. Protein Content Determination 2.0g of the dried sample was weighed into 30ml kjeldahl flask and 15m1 cone H2S04 and 1.0g of the catalyst mixture (kjeldahl catalyst mixture, a mixture of 20g potassium sulphate, 1.0gram copper sulphate and a pinch of selenium powder) were added. The mixture was heated until a greenish clear solution appeared (about 30mins), it was heated for more 30mins before allowing to cool. 10ml of distilled water was added to avoid caking. The digested solution was then transferred to the kjeldahl distillation apparatus. A 50ml receiver flask containing 5ml boric acid indicator solution was placed under the condenser of the distillation apparatus so that the tip is about 2cm inside the solution. The digested sample in the apparatus had10ml of 40% NaOH solution added through the funnel stop-cork. The distillation commenced immediately the steam by-pass was closed and the inlet stop-cork on the steam jet arm of the distillation apparatus opened. When distillation reached about 35ml mark on the receiver flask, the process was stopped by closing the inlet stop-cork first, then opening steam by-pass. The resulting solution was then titrated to the first pink colour with 0.1M HCl. Calculation follows thus; Vol.HCl 14.01 0.1 6.25 50 100 1000 weight of sample 100 (7) Where; 14.01 = Nitrogen standard, 50 = dilution factor, 6.25 = crude protein factor, 0.1 = concentration of HCI, 1000 - ppm, 100ml distilled. VIII. Carbohydrate Content Determination The carbohydrate content was determined by difference (i.e. by subtracting other constituents in each sample from 100%). IX. Determination of Specific Heat Capacity Specific heat capacities were determined using the various proximate compositions of the samples. These were obtained by applying . Cp = 4.180xw + 1.711xp + 1.929xf + 1.547xc + 0.908xa (8) Where; Cp is the specific heat capacity in kJ/kgK and x are respective mass fractions of water, protein, fat, carbohydrate and ash, present in each cultivar. X. Determination of Thermal Conductivity The thermal conductivities of the samples were obtained by substituting the various proximate composition of the sample in the expression developed by . K = 0.24Xc + 0.155Xp + 0.16Xf + 0.135Xa + 0.54Xw (9) 0 Where; K is the thermal conductivity W/m C of sample. XI. Determination of Thermal Diffusivity Thermal diffusivity () determines how fast heat propagates or diffuses through a material. This was determined from the thermal conductivity K, density ρ, and specific heat Capacity Cp using the dimensionally correct equation developed by . = k/ ρCp (m2/s) (10) XII. Determination of Bulk Density The bulk density was determined using a centrifuge tube, at intervals of drying until the density becomes constant. The weight of the centrifuge tube and its content (sample) was noted, it was later tapped until there was no longer change in volume, and the centrifuge tube and its content were reweighed. The weight was later obtained. The bulk density was calculated using the expression. Weight of sample (kg/m3) Volume of sample (11) XIII. Determination of Mass Transfer Coefficient This is a function of drying rate. The drying rate per unit area is proportional to the bulk density difference or concentration difference . dm f p Adt (12) dm Kc f p Adt Kc 1 dm f p Adt (13) Where; f and p are the bulk density of feed and products respectively, dm = change in mass after each interval of drying, dt = time difference, A = surface area of the particles given as 2 A N pM p Dp (14) Where; Np = Number of particles per unit mass, Mp = Mass of products, D p = Mean particle diameter = Dpd, d = Mass fraction retained on the sieve. A small quantity of about 0.5g of the dried product was counted as accurate as possible to obtain the number of particles per unit mass. The samples were then sieved in sieves of 0.8mm, 1.6mm and 2.0mm respectively to obtain the mean particle size diameter. 3. PRESENTATION OF DATA 3.1. Moisture content at Harvest: Weight of sample used =5.0g in each case Cultivar NR8082 Tms30575 Native Table 1: Weight of sample at harvest Weight of crucible (g) Weight of crucible + wet sample (g) 29.04 34.04 29.17 34.17 28.54 33.54 Crucible + sample (dried)(g) 30.64 31.045 30.368 Table 2: Weight of sample at intervals of drying and Weight of dried sample after 48hours 2.1. Weight of sample at intervals of drying Cultivar Weight of Weight of Weight Weight Weight Weight Weight Weight empty petridish + after 10 after 20 after 30 after 40 after 50 after 60 petridish(g) sample (g) mins (g) mins (g) mins (g) mins (g) mins (g) mins (g) NR8082 12.137 26.137 25.367 24.347 23.949 23.782 23.711 23.704 Tms30575 17.577 22.577 22.464 Native 19.845 24.845 23.648 2.2. Weight of dried sample after 48hours 20.737 22.905 20.395 22.633 20.321 22.590 20.281 22.586 Cultiver NR 8082 Tms 30572 Native Weight (g) 1.5385 2.3578 2.9597 20.261 22.586 Weight after 70 mins (g) 23.704 20.261 - 3.2. Proximate Analysis: Weight of sample used = 2.0g in each case Table 3: Table for Fat, Protein, Ash and Moisture content calculations 3.1. Table for Fat content calculations Cultivar NR 8082 Weight of empty flask (g) 32.664 Empty flask + extracted oil (g) 32.664 Weight of oil Nil Tms 30572 Native 33.930 33.724 33.930 33.724 Nil Nil 3.2. Table for Protein content calculations Cultivar Initial burette reading (cm3) Final burette reading (cm3) Volume of HCl used (cm3) NR 8082 20.60 20.70 0.1 Tms 30572 20.40 20.60 0.20 Native 20.70 20.90 0.20 3.3. Table for Ash content calculations Cultivar Weight of empty Silica dish + sample after Weight of sample Sample + silica Weight silica dish (g) treatment (g) after pretreatment (g) dish after ash(g) of ash (g) NR8082 26.210 26.284 Tms30572 29.062 29.121 Native 28.380 28.483 3.4. Table for Moisture content calculations Cultivar Weight of crucible + sample (g) 0.074 0.059 0.103 26.22 29.07 28.39 0.01 0.008 0.01 NR 8082 22.492 Weight of crucible + sample after Weight of moisture (g) drying (g) 22.456 0.036 Tms 30572 Native 16.749 22.098 16.699 22.059 NR 8082 0.043 0.039 Table 4: Table for calculation of bulk density during drying Tms 30572 Native Cultivar Time (min) Mass of Volume of Time Sample Centrifuge (min) (g) Tube (cm3) Mass of Volume of Time Sample Centrifuge (min) (g) Tube (cm3) Mass of Volume of Sample Centrifuge (g) Tube (cm3) 10 3.930 0.006 10 4.887 0.009 10 3.803 0.0060 20 3.210 0.006 20 3.160 0.007 20 3.060 0.0065 30 2.812 0.006 30 2.818 0.0075 30 2.788 0.009 40 2.645 0.007 40 2.744 0.012 40 2.745 0.0095 50 2.574 0.012 50 2.704 0.017 50 2.741 0.017 60 2.567 0.016 60 2.684 0.045 60 2.738 0.025 3.3 Tabulated Results and Simple Calculations: (Mass of sample used = 5.0g in each case) Cultivars Table 5: Moisture content of cultivars before fermentation Mass of dried crucible Mass of crucible + sample Weight of % moisture + wet sample (g) after drying for 24hours moisture (g) content (wet basis) NR 8082 Tms 30572 34.040 34.170 30.640 31.045 3.40 3.125 68 62.5 Native 33.640 30.368 3.172 63.44 Table 6: Moisture content of cultivars after dewatering and fermentation for 72 hours (wet basis) Cultivar Mass of petridish Mass of petridish + sample after Weight of moisture % moisture + wet sample (g) drying to stable weight (g) (g) expelled content (wet basis) NR8082 26.137 23.704 2.433 48 Tms30572 22.577 20.261 2.316 46.32 Native Cultivar NR 8082 Tms 30572 Native 24.845 22.586 2.559 45.18 Table 7: Moisture content at intervals of drying (wet basis) 10mins 20mins 30mins 40mins 50mins 53.09 25.05 9.54 3.04 0.27 82.08 17.73 4.99 2.24 0.75 33.74 11.64 1.71 0.15 - 60mins - Table 8: Hygroscopic properties of cultivars Cultivar MC (g) MD (g) 2.892 % water % reabsorbed Ash 12.66 1.05 % Fat Nil % % Protein Fibre 0.22 3.20 % % Moisture Carbohydrate 1.80 93.73 NR8082 2.567 Tms30572 2.684 3.039 13.23 1.50 Nil 0.44 2.55 2.15 93.36 Native 3.081 12.40 0.15 Nil 0.44 4.60 1.95 92.86 2.741 MC = Mass of cassava after drying to final moisture (g), MD = Mass of dried sample 48 hours later after drying (g) Table 9: Effect of Variety on the surface Area and Mass Transfer Coefficient of the Cultivars Cultivar Surface Area (m2) Density before Density after Mass transfer drying (kg/m3) drying (kg/m3) Coefficient Kc m/s(x10-6) NR 8082 Tms 30572 0.897 0.415 655 543 160.44 59.64 1.632 x 10-6 3.25 x 10-6 Native 0.850 551.2 171.3 2.332 x 10-6 Table 10: Effect of variety on the drying rate of the cultivars Total drying time Drying rate after Drying rate after Drying rate of stable (mins) 20 mins (kg/hr) 40 mins (kg/hr) weight (kg/hr) NR 8082 50 5.37 3.53 2.61 Tms 30572 60 5.52 3.38 2.32 Native 50 5.82 3.38 3.07 % Moisture Content (dry basis) Cultivar 90 80 70 60 50 40 30 20 10 0 NR 8082 Tms 30572 Native 0 10 20 30 40 50 60 Time (mins) Specific Heat capacity (kJ/kgK) Fig. 1: Drying curve for the cultivars 4 3.5 3 2.5 2 1.5 1 0.5 0 NR 8082 Tms 30572 Native 0 10 20 30 40 50 % Moisture Content (wet basis) Fig. 2: Specific Heat of Cultivars at Various Moisture Contents 60 Thermal Conductivity (W/m0C) 0.6 NR 8082 Tms 30572 Native 0.5 0.4 0.3 0.2 0.1 0 0 10 20 30 40 % Moisture Content (wet basis) 50 60 Fig. 3: Thermal Conductivity of Cultivars at Various Moisture Contents Bulk density (kg/m2) 700 NR 8082 Tms 30572 Native 600 500 400 300 200 100 0 0 20 40 60 % Moisture Content (dry basis) 80 100 Fig. 4: Bulk density variations with Moisture Contents Thermal diffusivity (m2/s) 1.00E-03 NR 8082 Tms 30572 Native 8.00E-04 6.00E-04 4.00E-04 2.00E-04 0.00E+00 0 20 40 60 % Moisture Content (dry basis) 80 Fig. 5: Thermal Diffusivity Variations with Moisture Contents 100 4. DISCUSSION 4.1. Moisture Content The moisture contents obtained before and after fermentation by drying the cultivars with a circulating air oven is shown in Tables 6 and 7 respectively. The initial moisture content of cassava at harvest was not stable and may be dependent on season. The cultivars used here were harvested in the month of April. NR 8082 had the highest moisture content of 68% at harvest, but Native cassava had the highest moisture expelled after drying. This suggests that the native cassava was more porous than the improved cassava in agreement with the studies in . 4.2. Drying Rate The moisture content (dry basis) decreases as drying time increases for all the cultivars during the drying process as shown in fig.1. The total drying time differed at approximately the same moisture content for all the cultivars, Tms 30572 with almost the same moisture content (wet basis) with the Native cassava after fermentation, had the longest total drying time of 60mins while native cassava had the shortest total drying time of 50mins. Fig.1 suggests that two cultivars with same initial moisture content did not have same drying characteristics. Other properties like the differences in chemical composition of the cultivars may have contributed to this. The drying rate decreased as the drying time increased for all the cultivars as show in table 2.1. This implies that the drying rate decreased with increase in moisture content (wet basis) as against that reported by . The drying rate of NR8082 and Tms 30572 at stable weight was low compared with native cassava. The native cassava had the highest drying rate of 3.07kg/hr at stable weight with shortest drying time which also confirms its highly porous property, as show in table 2.1. 4.3. Proximate Composition Table 8 shows the proximate composition of the cultivars. The improved cultivars had a slightly higher percentage of carbohydrate (93.36 - 93.73%) than the native cultivar (92.86%). All the cultivars do not contain fat since there was no oil extract from them. The geographical location of these cultivars as well as time of planting and harvest may have been responsible for this. Tms 30572 and the native cultivar have the same protein content higher than that of NR8082. The native cultivar ranked highest in fibre content but contains the least percentage of ash. These might have contributed to its shortest drying time. The type of drier used might have equally affected the total drying time as well as the drying rate. Also the differences in the drying rate can be attributed to the difference in their chemical compositions. The same drying condition cannot therefore be used for drying different cultivars. 4.4. Specific Heat Capacity and Thermal Conductivity In order to determine the effect of moisture content on specific heat capacity and thermal conductivity, the data in table 2.2 and the model equations of (8) were used to calculate the specific heat capacity and (9) was used to calculate the thermal conductivity at various range of moisture contents. The specific heat capacity increased with moisture content (wet basis) for all the cultivars. The native cultivar (fig. 2) had a different specific heat capacity than the other cultivars. The native cultivar seems to have a lower ash and carbohydrate content from other cultivars (Table 8) which might have contributed to this difference. The two improved cultivars exhibited close specific heat capacities probably due to the fact that they had approximately the same carbohydrate content. Tms 30572 and NR 8082 had very close specific heat at different moisture contents showing that cultivars with similar chemical composition (ash and carbohydrate) might have the same specific heat capacity. The specific heat capacities of Tms 30572 and NR 8082 were high compared with the native cultivars, probably because of their high carbohydrate and ash contents. More heat energy will therefore be required in other to dry cultivars with high ash and carbohydrate content. The specific heat obtained from this work ranged from 1.53kJ/kgK-3.49kJ/kgK which compare favorably with that of ; who obtained up to 3.5kJ/kgk. The thermal conductivity of each of the cultivars also increased with moisture content (wet basis). The native cultivar from (fig. 3) still exhibited a different thermal conductivity relative to other cultivars. The two improved cultivars had almost the same thermal conductivity at different moisture contents. Tms 30572 and NR 8082 still exhibited higher thermal conductivity than the native cultivar. 4.5. Bulk Density The bulk density of each cultivar decreased as the moisture content (dry basis) decreased during drying as shown in fig.4, but it was almost stable with moisture content below 13% dry basis. This goes to suggest the hygroscopic property of cassava as shown by  during the drying of a native cassava cultivar. At particular moisture content under the same drying conditions the bulk density differed for each cultivar which meant that the mass transfer rate would also differ for all the cultivars, since mass transfer rate is a function of the density of the sample dried. 4.6. Thermal Diffusivity The thermal diffusivity increased as moisture decreased, but was almost constant below the hygroscopic moisture of about 13%. The thermal diffusivity also differed slightly for each cultivar when determined at the same moisture as shown in fig.5. Thermal diffusivity determines how fast heat propagates or diffuses through a material. From the results, the native cultivar and NR8082 with higher density had low thermal diffusivity while the diffusion of heat is fastest in Tms 30572. NR8082 was the least porous (least thermal diffusivity from fig.5) and also has high carbohydrate and least protein content; this should have contributed to the low thermal diffusivity. 4.7. Hygroscopic Property and Porosity The dried ground cassava from each cultivar was reweighed after 48 hours of drying and the results show that 12.4% - 13.23% moisture was reabsorbed after the drying by the various cultivars. All the cultivars exhibited hygroscopic property. Tms 30572 reabsorbed the highest moisture, indicating that it is more porous and hygroscopic than the other cultivars. Its highest thermal diffusivity also goes to confirm this. This must have also led to the increase in the rate of mass transfer of moisture from Tms 30572. This is in contradiction with the results of the native cultivar’s porosity, which expelled the highest moisture with the shortest drying time. It can therefore be said that the diffusion of heat and mass through the pores of a cultivar does not depend on porosity alone but can also be affected by the chemical compositions of the cultivar, as reported by . 4.8. Surface Area and Mass Transfer Coefficient The surface area was obtained when the fermented ground cassava cultivars were dried to stable weight. Tms 30572, with the least surface area of 0.415m2 has the longest drying time. The Native Cultivar with surface are of 0.85m2 dried faster than Tms 30572 suggesting that the drying time does not entirely depend on the surface are. The proximate composition of the cultivars has a great effect on the drying rate even when the cultivars surface area is small. Tms 30572 has the highest mass transfer coefficient which was due to its low product surface area and relatively lower density difference. 5. CONCLUSION AND RECOMMENDATION The proximate composition of the cultivars had a very great impact on their engineering properties. The difference in the drying rate could therefore be attributed to the difference in their chemical composition. It can be said that the moisture content, specific heat capacity, and porosity also affected the rate of diffusion of heat and mass through the cultivars. The specific heat capacity and thermal conductivity of each cultivar varied with the proximate composition, water content and density, indicating that cultivars with similar chemical composition had same specific heat capacities as could be seen in the improved cultivars. 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