Optimum systems for harvesting with in-bin drying in Northern Britain

J. ugric. Engng Res. (1983) 28, 359-371

Optimum

Systems for Harvesting with In-Bin Northern Britain

Drying in

W. E. MUIR*; W. J. LAMOND~; G. W. INGRAMS; P. H. BAILEYI

Optimum systems to give minimum costs averaged over a 5 year period for the harvesting and in-bin drying of barley from 70 and 150 ha farms at Kinloss, Edinburgh and Leeming were determined using computer simulation. Because in practice a farm is unique, and in the present analysis both moisture content and maturity date of the crop are defined deterministically, some care should be exercised in applying the conclusions given to specific cases. Operating costs were similar at the three locations. Since harvesting costs accounted for the largest proportion of total costs, system costs were most sensitive to combine size and speed. Costs of fuel, electricity, labour and capital had little effect on the optimum systems. Crop conditions and some management factors such as when combining should start and how long it should take had considerable effect on the optimum systems and their costs. 1.

Introduction

In Scotland the main cultivated crop is barley used for malting and animal feed. It is grown on 436 000 ha or 71 o/0 of the farmland in crops and fallow other than grass.’ Because of the climatic conditions in the autumn, almost all barley is harvested by combine at moisture contents too high for safe storage. One of the many systems available for processing damp barley following combining is to dry and store it in individual bins. With such a system the farmer must make many decisions about such parameters as size and speed of the combine, number and size of grain bins, and size of fan and heater. To assist the farmer in making these decisions, the values of these parameters giving lowest cost for the system were determined using an optimization model which has been described previously.2 The drying model is of the equilibrium type, based by Muir and Ingram* on that described by Bloome and Shove.3 The optimization model was modified so that the moisture content of the crop was calculated from the weather data by the method described by Smith, Bailey and Ingram4 and the selected fan operated on a more realistic characteristic curve. A sensitivity analysis indicated the effect on costs of deviations from the optimum system. Further simulations determined the effect of possible changes in some of the economic, management and crop variables. 2.

Description of program and operating conditions

2.1. General description of program The computer program is a model of the grain flow from harvest through in-bin drying to storage. Because of inadequate information, variability of grain properties and climate, or complexity of the processes involved, many simplifications are necessarily made. Thus the results are regarded as being comparative and indicative of the sensitive parameters, since the simplifications are common to all configurations of the system. Each day is taken as a separate unit to be simulated before proceeding to the next day, and fields are assumed to be harvested in order of maturity. Harvesting can begin when the moisture content of the first field falls below a predetermined value. The number of hours that combine *Department of Agricultural Engineering, University of Manitoba, Winnipeg, Canada R3T 2N2 tScottish Institute of Agricultural Engineering, Bush Estate, Penicuik, Midlothian EH26 OPH, Scotland fformerly, Scottish Institute of Agricultural Engineering, Bush Estate, Penicuik, Midlothian EH26 OPH, Scotland Received 25 November

1982; accepted in revised form 31 March 1983

359 0021-8634/83/040359+13

$03.00/O

0 The British Society for Research in Agricultural

Engineering

360

OPTIMUM

HARVESTING

SYSTEMS

harvesting can occur on a day is determined as a function of rainfall and available working hours. All the grain harvested during the day is assumed to be added to the drying bins at midnight. Rate of air flow in each bin is calculated. The changes in temperature and moisture content of the grain in the ventilated bins are simulated for the next 24 h period using the weather data for that period. An indication of the deterioration of the grain during the 24 h period is calculated. The average costs over a period of 5 years, for a number of combinations of size and speed of combine, number and size of bins, and sizes of fan and heater are calculated. New combinations are determined according to a predetermined optimization procedure that attempts to find the combination giving the minimum cost averaged over the 5 year period. 2.2. Optimization subroutine The optimization subroutine was written according to the simplex method for function minimization described by Nelder and Mead .5 Optimum values are to be found for n variables (e.g. combine size and speed, number and size of bins, fan and heater size) which may be regarded as forming an n-dimensional space. Any linearly independent set of (n+l) points in this space is called a simplex, and each of the points is a vertex. A mean annual cost is associated with every point of the space and the objective of the method is to modify the initial, externally supplied simplex, by replacement of its vertices so as to move it to the minimum point of the annual cost surface. Four operations for calculating new vertices are used. A reflected vertex is located on a line extending from the highest cost vertex in the simplex through the centroid of the other vertices. The reflected vertex is on the opposite side of the centroid to the highest vertex. If the reflected vertex is below the lowest vertex, then an expanded vertex is calculated which is further along this line. If the reflected vertex is higher than the second highest vertex, a contracted vertex is located on the line between the centroid and the highest vertex. If the contracted vertex is higher than the highest vertex, then all the vertices of the simplex, except the lowest one, are contracted closer to the lowest one. New vertices are calculated until the standard deviation of the costs of the vertices in the simplex is reduced below a predetermined value. As a further check on whether the optimum has been reached 10 more vertices are calculated. If one of these 10 vertices has a cost that is more than 0.5% of the minimum cost below the previously found minimum, then 10 more vertices are calculated. In the last simplex the co-ordinates of the vertex with the lowest average cost are considered to define the optimum set of operating conditions for harvesting and drying. The program stops after 150 vertices have been calculated if an optimum has not been reached earlier. Typical input data for the model are shown in Table 1 with the values used for the basic system. Seven sets of values for number and area of bins, size of fan and heater and size and speed of combine are also read in and used as the initial simplex for the model. Output from the model consists of all the costs as listed in Table 2 for each system used by the model in the search for the optimum system. In addition, starting and finishing dates for combining, drying time, final moisture contents and weights of malting, feed and spoiled grain are available. 2.3. Basic operating conditions for the system Weather data for the 5 years 1968-1972 were obtained for Kinloss on the Moray Firth coast, Edinburgh and Leeming in North Yorkshire. Other weather stations may be more representative of the barley-growing regions of northern Britain, but the hourly data required were not available. The 5 years 196881972 were selected as they covered relatively good and poor harvesting conditions as well as typical harvesting weather. For the 100 days considered as the harvest period, average dry-bulb temperatures were 10.0, 9.8 and 10.5”C, average wet-bulb temperatures 8.9, 9.0 and 9.7”C and average total rainfall over the period was 168, 188 and 152 mm, all for Kinloss, Edinburgh and Leeming, respectively.

W.

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361

ET AL. TABLE 1

Typical input data Variable _-Crop Value sold for malt Value sold for feed Yield crop 1 Yield crop 2 Area crop 1 Area crop 2 Maturity date crop 1 Maturity date crop 2 Grain bulk density Final moisture content Starting moisture content Combine Resale value of combine after useable life as fraction of inital cost Field efficiency Useable life Bins Maximum number Useable life of bin structure Resale value of bin structure as proportion of initial cost Fan and heaters Index for type of heater control Useable life Resale value as proportion of initial cost Control value of relative humidity to switch on heater

Units

--

96 93 4.1 4.1 35 35 9 16 599 16 22

f/t

w

t/ha t/ha ha ha day of August day of August kg/m3 % (wet basis) o/0(wet basis)

0.5 0.75 3

years

10 20 0.0

years

3 20 0.0 0.68

years

TABLE 2

Detailed costs of optimum system at Edinburgh 70 ha farm

150 ha farm

Item

Fixed costs Combine Fan Heater Bins Sub-total Operating costs Combine Fan Heater Sub-total Grain losses Shedding Header Threshing Uncut * Quality Sub-total Total

Valuefor basic system

f/ha

%

f/ha

%

41.4 1.3 0.3 17.0 60.0

33.1 1.1 0.3 13.5 48.0

24.1 1.2 0.3 15.9 41.5

23.0 1.6 0.2 15.1 39.9

30.1 7.5 2.7 40.3

24.0 6.0 2.2 32.2

17.3 10.1 1.6 29.0

16.5 9.6 1.5 27.6

2.9 10.2 8.1 0.0 3.6 24.8 125.1

2.3 8.2 6.4 0.0 2.9 19.8 100

3.3 10.8 8.1 0.0 11.9 34.2 104.7

3.1 10.3 7.7 0.0 11.4 32.5 100

??Although some non-optimum systems included charges for grain left uncut at the end of harvest, no grain was left uncut in any of the optimum systems

362

OPTIMUM

HARVESTING

SYSTEMS

In 1977, in Scotland’s main growing regions, 6 32% of the farm area in barley was on farms growing between 50 and 100 ha of barley with an average area per farm of 70 ha. Farms with areas of barley greater than 100 ha and with an average area of 147 ha contained 28% of the total barley area. Therefore, we studied farms with grain areas of 70 and 150 ha. A number of assumptions about crop and management variables were made. Costs do not include the costs of producing the crop, which were considered to be constant for all harvesting systems. The mean yield of the barley was assumed to be 4.1 t/ha, which was the mean yield for barley in 1976 in Scotland.6 The farm area in barley was considered to be divided into two equally-sized fields of malting barley with maturity dates 9 and 16 August. Combining, with one combine having a field efficiency’ of 75%, could start when the moisture content of the crop fell to 22% (wet basis). Costs which could be incurred included loss of crop if the grain were not cut and dried by 100 days after the maturity date and loss in value of any grain for which the drying and storage regime was unable to maintain at malting quality. The storage units were assumed to be separate outside steel-bins with perforated floors. The bin capacity was set equal to lO5o/o of the possible grain yield per unit area, multiplied by the farm area in barley. One fan and heater could ventilate simultaneously any combination of the bins. The fan characteristic curve was given by P = 2

100 In (3.47-0.0247

V)

[

1 1

for V331,

. ..(l)

. ..(2) 100 In (3.47-00247 V)-31+V for V<31, [ where P is the fan static pressure, Pm is the maximum fan static pressure and V is the volume flow as a percentage of the free inlet and outlet volume flow. Maximum fan static pressure and free air volume were selected by assuming that, with all the grain harvested and all bins being ventilated, the fan would use 97% of its maximum available power and deliver 60% of the free air volume at 66% of the maximum static pressure. Ventilation was stopped at a mean moisture content of 16% (wet basis). The electric heater in the air duct came on when the air leaving the fan was above 68 o/orelative humidity. Fixed costs of the combines were determined using an initial capital cost P = go

C = 7030+1425

. ..(3)

S,

where C is the initial capital cost of the combine (in E) and Sis the capacity of the combine (in t/h). Initial capital costs of the bins were calculated using the following equations, derived from analysis of catalogue prices (including delivery to site but not erection) for 1981 supplied by a leading British manufacturer: H,

. ..(4)

A
m2, B = 85.89-11.31

AG16.4

m2, B = 68.89 -9.63

H,

. . .(5)

AG23.7

m2, B = 50.90 -5.58

H,

. ..(6)

AG50.0

m2, B = 38.20 -3.30

H,

. ..(7)

where A is the area of bins (in m2), B is the initial capital cost of a bin (in E/m3) and H is the wall height (in m) (minimum 2.5 m, maximum 5.5 m). Linear interpolation was used for bins with areas intermediate to those listed above. The cost was set at &19.19/m3 for bins with wall height greater than 5.5 m. Initial capital costs of the fan and motor were calculated by the equations given by Muir and Ingram,* updated for the increase in prices 1975 to 1981: P<2.5,

F = 412 -112P,

2.5cPcl2.5, Pal2.5,

F = 153 -8P F = 50,

. ..(8) . ..(9) . ..(lO)

W.

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MUIR

363

ET AL.

where P is the size of fan (in kW) and F is the initial capital cost of fan and motor (in g/kW). Initial capital costs of the heater and the on-off heater control were ;E16/kW and 582, respectively. Annual fixed costs were calculated according to the procedure used by Audsley and Boyce.” The resale value of the combine after 3 years of use was assumed to be 50% of the capital cost.* The bins, fan and heater were assumed to have no resale value after 20 years of use. The interest rate was set at 10%. Labour, repairs and fuel for the combines were calculated according to the procedure of Audsley and BoycelO with the wage rate set at &1.83/h and the cost of fuel at &O.155/l. Repairs and labour needed for operating the in-bin drier were assumed to be negligible. Cost of electricity for the fan and electric heater was set at EO.O3/kWh. The prices assumed were those current early in 1981; ;E96/t for malting barley and E93/t for feed barley. The penalty charge for underdrying was set at &2.00/t for each per cent excess moisture. Shedding, header and threshing losses were calculated from equations developed by Muir and Ingram2 based on the harvesting model described by Audsley and Boyce.’ Assessment of grain deterioration was based on the equation given by Roberts9 for the effect of time, temperature and moisture content on the storage life of the seeds. The annual cost of the harvesting and preservation system was averaged over the 5-year simulation period for Kinloss, Edinburgh and Leeming. Costs included were fixed costs of the storage structures; fixed and operating costs of the harvesting and drying equipment; and losses in income due to uncut grain, shedding, header and threshing losses, reduction in grain quality from malting to feed caused by deterioration or underdrying and reduction in grain weight by overdrying. 3. 3.1.

Results and discussion

Optimum

systems for the basic conditions

The combination of number, height and area of bins, size of fan and heater and size and speed of combine which give the minimum average cost over the 5-year period is selected by the model as the optimum system (Table 3). TABLE 3 Optimum systems for basic conditions

Grain bins ___--___ Location

Farm size, ho

Number

Area, m2

Height,

m

Combine

Fan size, k W

Heater size, k W

Size, t/h

15.0 10.6 12.6

10.1 5.9 6.0 8.3 11.1 9.5

2.8 2.1 2.7 3.6 3.7 3.9

__----___-_

--Kinloss Edinburgh Leeming Kinloss Edinburgh Leeming

I

_ -____

70 70 70 150 150 150

2 2 2 3 3 3

87.7 85.7 87.7 149.3 149.5 149.6

5.5 5.7 5.5 6.5 6.5 6.5

-- --

Speed, km/h 3.0 3.0 2.7 3.7 3.6 3.6

-

Differences in the parameters and operating costs for the optimum systems among the three locations are small. If the optimum systems for Edinburgh are used at the other two locations operating costs over the 5-year simulation period increase overall by an average of 3.5% with a maximum of 8 y0 (Table 4). For the 5 years of weather data used the minimum and maximum costs in different years deviate from the mean cost by an average difference of only 12% and a maximum absolute difference of 35%. The year-to-year differences are about one-third as much again when the optimum systems for Edinburgh are used at the other two locations. It may be noted that the year-to-year differences in costs in this work are much smaller than those found in simulations of

364

OPTIMUM

HARVESTING

SYSTEMS

TABLE 4

Costs of basicsystems System Location

Kinloss Edinburgh Leeming Kinloss Edinburgh Leeming

Farm size, ha

70 70 70 150 150 150

cost,b/ha

Optimum system

I

I Edinburgh system

Mean

Maximum

Minimum

126.6 125.2

137.8 128.3

121.8 121.3

1367 125.2

167.9 125.3

121.6 94.4

106.4 138.1

106.2 133.6

I

conditions in Manitoba.‘O Changing weather conditions are less important than in Canada and penalties due to rain on the swathed crop are not applicable in Great Britain. The largest cost item is the annual fixed cost of the combine which makes up one-quarter to one-third of the total cost (Table 2). Fixed and operating costs of the combine and grain losses during harvesting make up about three-quarters of the total costs. Thus, when attempting to reduce costs most benefit will probably be gained from effort applied to improve the harvesting operation. Increasing farm size from 70 ha to 150 ha decreases the cost per hectare by 16% mainly by reducing the fixed and operating costs of the combines. Kabernick and MuirlO found that in Manitoba costs were not decreased above an area of 240 ha. 3.2. Sensitivity of costs to changes in system parameters The sensitivity of the total systems costs to changes in the parameters (for instance bin dimensions, fan and heater size) of the optimum systems for 70 ha and 150 ha farms located near Edinburgh were determined (Figs 1-7). Figs 2-7 refer to the effect of changing the relevant parameter while the remaining parameters are held at the original optimum system level. The effects of changes in the parameters are the same for both sizes of farms with the curves for the 150 ha below and in most cases to the right of the 70 ha curves. Although fixed costs represent about 40% of the total cost a simultaneous decrease in size of all the parameters being optimized causes a greater increase in total cost than a similar increase in size (Fig, 2). This is because a general increase in parameters increases costs and losses in grain value while decreases cause increased losses due to uncut grain and inadequate drying. A small number of large diameter bins is indicated as the optimum system (Table 3). However, increasing the number of bins will give greater flexibility for only a small increase in simulated costs (Fig. 2). Increases in cost as bin height is reduced are due to increasing cost of bins per unit volume (Fig. 3). Increasing cost as height is increased is due to the loss of grain quality as the fan (held at a constant size) is unable to maintain adequate airflow to achieve optimum drying in deeper bins (Fig. 3). It may be noted that as site costs are liable to increase with bin height, in practice the minimum costs would probably be achieved with rather shallower bins than predicted by the model. Decreasing fan power causes a rapid increase in total cost due to increased grain deterioration, but an over-capacity fan has only marginal effect on the total cost (Fig. 4). Heater size has little effect on the total cost because the extra heat is used for only a short period of time and its operating and fixed costs are less than 2.5% of the total cost (Fig. 5 and Table 2). Installation of a large fan and heater could be of considerable benefit in years when wet weather means that the grain has to be harvested at a higher moisture content and dried with air of high ambient humidity.

W.

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MUIR

365

ETAL. 200

120

IOC -50

-25

0

Simultaneous

change

25 in all parameters

50

75

being optimized,%

Fig. 1. Sensitivity of system cost to simultaneous changes in all system parameters: ?? . 70 ha farm; ?? , 150 ha f arm I00

1

I

r

I

I

I

I I

I 2

I 3

I 4

I 5

I 6

160_z zi f s 140E 0) b ;; 120 -

100

0

Number

Fig. 2.

7

of bins

Sensitivity of system cost to number of bins: W, 70 ha farm; ?? , 150 ha farm

16015

lZO, y-y-y , 100

0

2

4

6

Bin height,

8

IO

I2

m

, 70 ha farm: 0, 150 ha farm Fig. 3. Sensitivity of system cost to bin height: ??

366

OPTIMUM

HARVESTING

SYSTEMS

18C l-

2 c-i_

160

f s : E m

140

i IO

I

1

20

I

I

I

30

40

50

60

Fan power, kW

Fig. 4. Sensitivity of system cost to fan power: ?? , 70 ha farm; 0, I50 ha farm

0 <

w

140 c

;

120p---4 * .

1001 0

J

I

I

I

I

5

IO

15

Heoter

power,

20

I

25

kW

Fig. 5. Sensitivity of system cost to heater power: H, 70 ha farm: 0, 15’0ha farm

Of the individual parameters, combine size and speed appear to be the most critical (Figs 6 and 7). Decreases in combine size and speed from the optimum cause an increase in cost because of the uncut grain, whereas increase in combine size above the optimum results in increased fixed costs and likelihood of grain deterioration (since the drier is now overloaded). An increase in combine speed gives higher threshing and deterioration losses. The increased deterioration is due to loading the drier more rapidly and at a higher moisture content than the drying system can accommodate and still maintain the barley at malting quality. However, a farmer with a larger combine could combine at lower moisture contents and operate at slower speed to reduce the extra cost. 3.3. Sensitivity of optimum systems to changes in operating conditions The model was run with specific changes to the input data to give a comparison between: (i) optimum system chosen when operating conditions were changed and (ii) optimum system for the original input conditions. Table 5 shows the results of the simulations for a 70 ha farm at Edinburgh and, similarly, Table 6 gives a few results for a 150 ha farm. The tables give the cost of operating the basic system with the modified input data and show whether major changes in

W.

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MUIR

367

ET AL. 200

I

I

I

,

I 2

I 4

1 6

I 8

180-

IZO-

100. 0

Combine

Fig. 6.

IO

t/h

, 70 ha farm; 0, 150 ha farm Sensitivity of system cost to combine size: ??

loo-‘0

2

’

6

4 Combine

Fig. 7.

capacity,

speed,

I

8

km/h

Sensitivity of system cost to combine speed: W, 70 .hafarm; 0, 150 ha farm

the basic system are needed when the operating conditions change. The costs will naturally be the same when the basic system is again selected, by the model, as the optimum system for the particular operating conditions. 3.3.1. Economic factors Changes in the economic factors, i.e. all costs (electricity, fuel, wages and capital) up SO%, energy (electricity and fuel) costs up 5074, capital costs for combine, bins, fan and heater up SO%, malting and feed barley prices down 33% and up 50% had very little effect on the parameters of the optimum system (Tables 5 and 6). It should be noted that where the grain price is not changed

Basic conditions All costs up 50% Energy cost up 50% Capital costs up 50% Grain prices down 33% Grain prices up 50% Grain yield up 50% Maturity 7 d earlier Maturity 7 d later Maturity same both fields Grain sold for feed Starting moisture content = 17.5% Starting moisture content = 25% Heater on-off, r.h. = 58% Heater on-off, r.h. = 78% Proportional heater, r.h. = 58% Proportional heater, r.h. = 68% Heater on all time No heater

Change in basic condition

-

I Height m 5.7 5.7 5.7 5.7 5.6 5.7 7.0 5.6 4.9 5.6 5.4 5.5 5.6 5-7 5-7 5-l 5.7 5.3 5.9

Area m2 85.6 85.6 85.6 85.6 86.5 85.6 100.0 86.5 99.0 85.7 90-2 87.4 869 85.6 85.4 85-6 85.6 90.9 82.2

Number 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

Grain bins Heater size, kW 5.9 5.9 5.9 5.9 5.4 5,9 6.6 5.4 6.9 6.0 4.1 9.0 7.5 5.9 7.5 5.9 5.9 4.3 0

Fan size, kW 10.5 10.5 10.5 IO.5 12.0 10.5 198 12.0 12.1 10.6 9.7 8.4 14.5 10.5 13.2 10.5 10.5 9.7 17.7

;:: 2.1 2.1 2.3 2.3

2.1 2.1 2.1 2.1 2.3 2.1 2.7 2.3 2,9 2.1 2.3 2.3 2.1

;:; 2.9

3.0 3.0 3.0 3.0 3.0 3.0 2.4 3.0 3.2 3.0 2.9 3.4 3.0 3.0 2.9 3.0

Speed, km/h

Combine Size, t/h

Effect of changes in operating conditions on a 70 ha farm at Edinburgh

TABLE 5

I

-

125.2 177.2 130.3 134.5 116.9 137.6 165.6 126.6 123.6 126.5 122.0 130.3 126.4 126.6 124.7 126.9 125.4 127.1 126.4

Optimum

125.2 177.2 130.3 134.5 116.9 137.6 223.9 137.9 135.1 126.5 125.1 142.7 127.5 126.6 125.2 126.9 125.4 127.3 129.3

Basic

System cost, E/ha

0

2

m

2

2 z >

: 2

W.

E.

MUIR

369

ET AL.

TABLE 6 Effect of changes in operating conditions on a 150 ha farm at Edinburgh

Grain bins Change in basic condition

____~-Number

Area, m2

Height, m

Fan size, kW

Heater size, kW

System cost, E/ha --_-__-_

Combine -

-

---

Size, t/h

Speed, km/h

3.1 3.1

3.9 3.7 3.6

Optimum

Basic

3.6 3.6

104.5

104.5

145.4

145.5

3.6 3.6 3.8

102.7 109.3 160.7

110.2 109.3 233.8

----~__--~____---~~

Basic conditions All costs up 500,:, Grain sold for feed Energy costs up SOY/, Grain yield up 5006

3

149.5

6.5

26.6

3

149.5

6.5

26.6

3 3 5

150 149.5 244.0

6.5 6.5 6.0

23.2 26.6 63.1

11.1 11.1 10.2 11.1 20.0

the costs due to grain losses will remain constant. The optimum system for the farm need not be changed with changes in the economic factors. It is notable that increases in energy costs have little effect on the total cost because direct energy costs make up only 8-l 1 oh of the total costs. 3.3.2. Crop conditions A 50% increase in crop yield causes large changes in the parameters for the optimum system (Tables 5 and 6). Although the overall cost is increased by nearly one-third and the difference in cost between the optimum and basic systems is 35%, by adding one bin to the basic system and reducing the combine speed the increase in cost is reduced to 13%. Even the basic system would, of course, give an improved margin as although the harvesting costs per hectare are increased by increase in yield, the costs per tonne are reduced. Although costs increased only slightly, the parameters for the optimum system changed considerably with changes in crop maturity dates through both fields maturing 7 days earlier and 7 days later. However, when both fields mature on 9 August the basic system is again selected as the optimum. For both the earlier and later maturity dates the basic system costs 9% more than the optimum. With the late-maturing crops a much larger combine capacity is required to complete the combining by the end of the harvest season. The relatively large effects of crop yield and maturity dates on the optimum systems highlight one of the major weaknesses of the model. Under practical conditions both factors vary from year to year while in the model they are constant, independent of weather throughout the year. 3.3.3. Management practices For both 70 ha and 150 ha farms, if a farmer decides to grow barley for feed, the optimum system is considerably different from the basic system which values all the grain that meets the criterion for malting quality at malting grain price and only the remainder as feed grain (Tables 5 and 6). But using the optimum system for the basic conditions gives less than 3% increase in cost above that for the optimum system for the new conditions. Although there is a slight reduction in annual fixed costs total income is reduced in proportion to the price difference between malting and feed barley. Cost of drying is also sensitive to the final moisture content of the grain. Using the basic system for a 70 ha farm the overall cost can increase 11 y. if the drying is continued until the top layer in the bin is 15:/, instead of 16% moisture content. If the drier is switched off when the moisture content is only down to 17% the cost can increase by 11 o/o due to deterioration in the grain quality. Starting to combine at a later date, when the moisture content is 17.5% has a similar effect to crops maturing later in that they both require much greater combine capacity (Table 5). If the

370

OPTIMUM

HARVESTING

SYSTEMS

indicated changes in the optimum system are made the cost for starting at 25% moisture content is I o/o higher than that for starting at 22%. If the basic system is used there is an increase of only 2% in the costs (Table 5). This contrasts with the conclusion that when using a high temperature continuous drier combining should be started as early as possible.* Changes in the heater control seem to have little effect on the costs even though the proportional control was given an initial capital cost of &600 as compared with &82 for the on-off control. In general farm practice the farmer will want to harvest his grain within a much shorter time than the loo-day period allowed in the model. Consequently, he may use a larger and/or faster combine and also use shallower bins to avoid the problems that can arise when attempting to dry deep beds of wet grain safely. 4.

Conclusions

The model requires further improvement to simulate the effect of weather, geographical location and agricultural factors on the maturity date and yield of the crop, so that these parameters can be calculated instead of being assumed. Thus some care should be exercised in applying the following conclusions to specific cases and management practices. 1. System costs are similar at the three locations, Kinloss, Edinburgh and Leeming. 2. Increasing farm size decreases costs per hectare mainly by decreasing the fixed costs of the combine. 3. Fixed and operating costs of the combine and grain losses are the largest cost factors. 4. In developing a system a farmer should tend towards over capacity instead of under capacity for the combine and fan. 5. Changes in the economic factors will not require changes in the system parameters. 6. Late maturing crops require a larger combine than earlier maturing crops. 7. Increases in crop yield require much larger fans and larger combines operated more slowly to reduce crop losses. This can be partially offset by adding a bin to the basic system and operating at a slower combine speed. 8. The drying operation should be watched closely so that the grain is neither underdried or overdried. 9. Operating the system at 78% relative humidity instead of 68% as used in the model does not affect the cost of the basic system but the optimum system for the higher humidity would give a marginal improvement. Acknowledgements The first author thanks the Department of Agriculture and Fisheries for Scotland for providing facilities and the Agricultural Research Council of the United Kingdom for financial assistance, the National Research Council of Canada for providing financial assistance and the University of Manitoba for granting sabbatical leave to study drying and storage in the U.K. REFERENCES

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