The livestock development planner is commonly faced with a series of demands for meat and milk and must answer the following questions:
LDPS2 is designed to help the livestock planner to:
LDPS2 consists of eight interrelated sheets (including two hidden sheets), each one assuming a particular function. There are 19 animal systems modeled in LDPS2, as shown in Table 2 below. The seven broad animal categories (dairy cattle, beef cattle, sheep, goats, buffalo, pigs and poultry) are subdivided into animal systems. These subsystems may reflect geographic differences (i.e. savanna vs. forest), social and economic differences (i.e. nomadic vs. sedentary), etc.
When using LDPS2, there is no compulsory sequence of action. Since LDPS2 is a spreadsheet, all calculations are simultaneous. Furthermore, LDPS2 comes with a complete set of default data included, so you can start working with it right out of the box.
However, the preloaded data sets may not fit. Furthermore, you may have your own data sets at hand. It is therefore recommended that you edit the default parameters to ensure that they are error free and consistent with your own data.
Index |
Name |
Inputs |
Outputs |
| 1 2 3 4 |
Dairy cattle, system 1 Dairy cattle, system 2 Dairy cattle, system 3 Dairy cattle, system 4 |
Productivity values and Milk production | Milk, meat, hides and
manure; Herd structure Energy needs Protein requirements |
| 5 6 7 8 |
Beef cattle, system 1 Beef cattle, system 2 Beef cattle, system 3 Beef cattle, system 4 |
Productivity values and Milk production | Milk, meat, hides and
manure Herd structure Energy needs Protein requirements |
| 9 10 11 |
Sheep, system 1 Sheep, system 2 Sheep, system 3 |
Productivity values and Milk production | Milk, meat, wool and
manure Herd structure Energy needs Protein requirements |
| 12 13 14 |
Goats, system 1 Goats, system 2 Goats, system 3 |
Productivity values and Milk production | Milk, meat, wool and
manure Herd structure Energy needs Protein requirements |
| 15 16 17 |
Buffalo, system 1 Buffalo, system 2 Buffalo, system 3 |
Productivity values and Milk production | Milk, meat, hides and
manure Herd structure Energy needs Protein requirements |
| 18 | Pigs, combined | Productivity values and Milk production | Meat Herd structure Energy needs Protein requirements |
| 19 | Poultry, combined | Productivity values and Milk production | Eggs and meat Herd structure Energy needs Protein requirements |
Models used by LDPS2
Three models are used within LDPS2:
1) The Demand-driven routine allows the calculation of a herd's size and composition, given a specified demand for domestic meat or milk. After you set the production target and the productivity parameters (fertility rate, mortality rates, etc.), LDPS2 calculates the required herd size and composition based on a demographic model contained in sheet "Calculations". Some animal systems share the same demographic model (and thus the same equation set):
Results are shown in sheet "Results". These animal systems are explained in more detail in the next section.
2) The Resource-driven routine is like using the Demand-driven routine backwards: instead of asking the question "What herd size and composition is needed, given my production target?", you would rather ask yourself "What production is attainable, given total resources available and within the limits of resources allocated to the various systems?". Because demand-driven routine doesn't take resource availability into account, the resource-driven routine is a way of checking back on the targets to ensure that the calculated herds are sustainable. Resource-driven works for all 19 animal systems. Results are shown in sheet "Results".
3) The Herd growth routine calculates, on a yearly basis, the size and composition of the specified system, given a base year structure of the herd. After the user has edited the base year figures and set the number of years, LDPS2 calculates, for every year, the herd size and composition, the quantity of every product generated and the energy needs and balance, given the allocated resources. You can select a projection period ranging from 2 to 20 years. The base year is Year 0. Results are shown in sheet "Results".
TIP |
Recalculation of LDPS2 is set to "Manual" by default. This is to prevent LDPS2 from constantly recalculating the whole 8 sheets, which can be quite annoying on a slow computer. Since calculations are manually performed, changes made to the sheets (new parameters or new labels) may not be taken into account immediately by LDPS2. To update all calculations at once, simply press the F9 key on your keyboard (You can also set recalculation to "Automatic" from the menu "TOOLS_OPTIONS_CALCULATION"). |
The first step in using LDPS2 is to edit the default parameter sets included in the spreadsheet. These parameters can be found in sheet "Parameters". The upper-left part of the sheet contains the parameters for Demand-driven routine, as shown in figure 9.
Parameter names are shown in columns B for Dairy Cattle, G for Beef Cattle, and so on. To see the full name of a parameter, you can change the column's width. This operation has no effect on the calculations.
The columns refer to specific animal systems while the lines refer to individual parameters. For example, cell C7 in sheet "Parameters" refers to the parameter "Fertility rate" of the animal system called "Dairy Cattle, System 1".
To edit values, simply select the desired cell using the mouse (or the arrows on your keyboard) and type in the new value. Remember that ONLY BLUE CELLS CAN BE EDITED. Other cells contain equations and are normally protected. If you try to change the content of a protected cell, LDPS2 will display message telling you that protected cells cannot be edited. In order to change the content of these cells, you have to first remove the protection from the current sheet.
CAUTION |
Removing protection from a sheet enables you to change whatsoever is contained in that sheet. Before removing the protection, make sure you have an unmodified copy of LDPS2 somewhere. |
CAUTION |
When editing parameters, typing characters instead of numbers will cause calculation errors. Be very careful when typing new values in sheet "Parameters" since these values are used throughout the application. Labels can be made of characters and numbers, or they can be left blank. They have no effect on calculations. |
Sheet "Labels" is used to change the default names used by LDPS2 throughout the spreadsheet. For example, you can model up to four animal sub-systems for Dairy Cattle. By default, these sub-systems are named "System 1", "System 2" and so on. To change these defaults, simply type in a new name. For example, in the Dairy Cattle animal system, change "System 1" to "Nomadic". This change is instantly updated throughout the spreadsheet, so every cell using "System 1" before will now show "Nomadic" instead. If not, press the F9 key on your keyboard to update all labels.
The Demand-driven section of LDPS2 calculates the composition, size and feed requirements of the livestock systems needed to meet specific production targets. "Demand-driven" means that it is the user-defined demand target for domestic livestock products (in terms of tons of meat, eggs or milk) that drives all the calculations. LDPS2 answers this simple question: "What herd size and composition do I need to product X tons of meat (milk) per year?".
The following pages explain how Demand-driven routine works, and how to use it. Section 2.4 explores the Herd Growth routine in full detail. Figure 10 shows a graphical representation of the way LDPS2 works for all Dairy Cattle systems.
The demands are set within the "Parameters" sheet, line 5. This is either a milk, meat or eggs target, expressed in metric tons per year. The way these demands are used within the system's equation set is explained 2.3.1.1 below. Section 2.3.1.2 explains how the energy requirements are calculated after herd size and composition has been determined by LDPS2.
TIP FOR EXCEL 7 USERS |
Some cells contain a small red square in the upper right corner. This mark indicates that a label is attached to the cell. To see the label, select "INSERT_NOTE" from the main Excel menubar. With Excel 7, just leave the cursor over the cell for 1 second. The label is then displayed. A label gives information on the units used for that particular cell. |
Dairy cattle and Buffalo (systems 1 to 4 and 15 to 17)
For dairy cattle and buffalo systems, the milk target drives all the calculations. The system calculates the number of cows required to produce the desired amount of milk and then builds the total herd that results from the computed number of lactating cows. While milk is the actual production target2, all dairy and buffalo herds produce meat, hides and manure as by-products from culls and slaughter stock.
Heads and energy requirements for draught animals are also computed. Draught power is considered an output of adult dairy cattle, beef cattle and buffaloes only. Draught animals are regarded as a "by-product" of dairy and buffalo production systems, where surplus calves (i.e. those calves not kept for herd growth) are partly diverted into draught use, and partly diverted into slaughter stock. The number of surplus calves diverted into draught use depends on the power output expected from draught animals. These power requirements are specified by the user. LDPS2 then allocates surplus calves to draught use until needs are met, the extra calves (if any) being diverted into slaughter stock. The flow chart on the previous page illustrates this method for dairy cattle.
Draught animals are not put to work all year. During the days where they are idle, they assume the same productivity and needs as the males from their group of origin (dairy cattle or buffalo). During the days where they are put to work, they need more energy. The set of parameters applied to these animals is adjusted accordingly. Draught animals typically have two system LSUs applied to them: one for idle days (same as male replacement), and one for working days.
Draught animals have their own parameter set. These parameters can be edited in the "Parameters" sheet.
The same model is used for all dairy and buffalo systems. The differences in the various types are accounted for by different values in the productivity data used for the calculations.
Beef cattle, Sheep and Goats (systems 5 to 14)
For beef cattle, sheep and goats, the meat target drives the calculations, all other products being calculated as residual values. The user sets the desired amount of beef as a production target, and sets the level of each parameter. The spreadsheet then calculates the herd size and composition required to meet that demand value. The results can be seen in the "Results" sheet.
All those meat-oriented systems also produce milk as a by-product (in the same manner that meat is viewed as a by-product by milk-oriented systems, i.e. Dairy cattle and Buffalo). Table 3 shows products computed by LDPS2 for each animal type.
As for Dairy Cattle and Buffalo, number and energy requirements for draught animals are also computed.
Pigs (system 18)
As for beef cattle, sheep and goats, the pig system is also meat-driven. Meat is the only product calculated for this system. There are two sub-systems modeled: intensive (modern) production and traditional production. Unlike the previous livestock systems, these two sub-systems are analyzed and computed together. Total production demand is split between the two sub-systems by the user who must supply, as one of the parameter values (see sheet «Parameters», cell Y6), the fraction of production to be met by the intensive system. A zero value means that the traditional sub-system supplies 100 percent of the required meat, while a value of 1 means that all of the production demand will be met by the intensive sub-system. Therefore, the value provided should be somewhere between zero and 1.
| Type | Products |
| Dairy cattle | Milk, meat, hides, manure |
| Beef cattle | Meat, milk, hides, manure |
| Sheep | Meat, milk, wool, manure |
| Goats | Meat, milk, fleece, manure |
| Buffalo | Milk, meat, hides, manure |
| Pigs | Meat |
| Poultry | Meat, eggs |
CAUTION |
Some parameters are expressed as percentage values. Typing "2" therefore means 200%, not 2%. If you mean 2%, you should type ".02" and let LDPS2 convert the displayed value into "2%". Check all the percentage values you changed before consulting the results. |
Poultry (system 19)
The poultry system is in fact composed of three sub-systems: village production of meat and eggs , commercial egg production and commercial meat production. These three sub-systems are combined by LDPS2 to meet the global production targets for meat and eggs.
For the poultry system, two targets are set: meat and eggs (See Sheet "Parameters", cells AA5 and AA6). But unlike other systems, the main drive comes from human population (see sheet "Parameters", cells AA7 and AA8). The village poultry population being set as a proportion of the human population, the village poultry produce eggs and meat not in response to the production targets, but rather as a function of human population and the productivity values of the flock.
After calculation, the village eggs production is subtracted from total egg target. The remaining egg target becomes the production target for the commercial egg production sub-system. Village meat production and meat from culls from the commercial egg sub-system are subtracted from global meat production target. The remaining meat becomes the meat production target for the commercial meat production sub-system. Figure 11 shows how the poultry system works.
Commercial egg production is driven by the unsatisfied egg target after the village egg production has been subtracted out. LDPS2 calculates the size and composition of the laying flock required to meet the remaining egg production target. This laying flock also produces meat through the normal culling of the laying flock. That meat is subtracted from the unsatisfied meat production target.
Commercial meat production is driven by the unsatisfied meat target after both the village meat production and the commercial egg system's meat from culling have been subtracted out. LDPS2 calculates the size and composition of the poultry meat flock required to satisfy the remaining meat production target.
In some cases, this approach will lead to overproduction. In the case of village production, the production targets may be smaller than the production of meat and eggs resulting from the projected increase in village poultry population. When the egg and meat production targets are out of balance there can be over production of meat resulting from the incidental culls of the commercial egg laying flock. The user is encouraged to use several iterations of the programme to ensure that the production targets are consistent.
The easiest way to set the rural population figures is first use 1 as both the current and future population for the base year LDPS session. Then, the future population can be increased by the expected percentage. For example, if the population is expected to increase by 20% by the horizon year, set the base year to 1 and the horizon year population to 1.2.
Draught power calculation
Parameters No. 47-57 are used for draught calculation (Parameters sheet, rows 51-61). As mentioned above, number and energy requirements for draught animals are computed for cattle and buffaloes. They are calculated as a by-product in order to avoid over-estimation of the herd size.
| 47 | Peek animal draught power demand / month | 6000000 |
| 48 | Are there Draught specific oxen?(Y=1 / N=0) | 1 |
| 49 | Are Male Breeders used for draught?(Y=1 / N=0) | 1 |
| 50 | Are Female Breeders used for draught?(Y=1 / N=0) | 0 |
| 51 | Are Male replacements used for draught?(Y=1 / N=0) | 1 |
| 52 | Number of days worked, Draught specific animals | 100 |
| 53 | Number of days worked, Breeders | 100 |
| 54 | Number of days worked, Replacements | 100 |
| 55 | Average productivity /animal /day, draught specific oxen | 1 |
| 56 | Average productivity /animal /day, Breeders | 1 |
| 57 | Average productivity /animal /day, Replacements | 1 |
In LDPS2, four kinds of animals are available for draught use, breeders (males and females), male replacements and draught specific oxen. The user can select animals used for draught with parameters No. 48-51. LDPS2 distributes total power demand to draught specific oxen, which come from other (slaughter) stock, at first. When the demand is not satisfied by the stock, the remaining demand is distributed to male breeders, male replacements and female breeders, in turn.
It is difficult to estimate total requirements for draught (or animal) power with a set of generalized coefficients because different types of work, techniques and other factors affect the requirements. Then, LDPS2 does not estimate the requirements, but the user determines it empirically. LDPS2 calculates number of draught animals with the following formula:
| No. of draught animals = (Peek power requirement per month) / 30 days / (Average productivity per animal per day) |
A unit for the requirement and productivity is also defined by the user. Hectares/day, Man-day or Animal-day, for example, will be available. The following is an example in Nepal.
|
Cultivation with hill Zebu and swamp buffalo in Nepal (Oli, 1985) (1) hill Zebu
| ||||
| Nature of work | Maize | Wheat | Rice | |
| First ploughing | 8 | 10 | 11 | |
| Second ploughing | 7 | 7 | 10 | |
| Seeding | 7 | 6 | 6.6 | |
(2) swamp buffalo
| ||||
Once the size and composition is calculated, the feed requirements are determined. The feed requirements are calculated first as SYSTEM SPECIFIC LSUs and then converted into REFERENCE LSUs.
LSU stands for Livestock Standard Unit. It is a standard measure of the energy needs of livestock systems. In LDPS2, System Specific LSUs are measures of the annual energy needs of each member of the herd relative to the needs of the breeder female, which are assumed to be the greatest. The breeder female in all livestock systems (except Poultry) is assigned a System Specific LSU of 1. The other members of the herd are assigned LSU ratings that are proportional to the breeder female LSU of 1. The default System Specific LSUs of the various members of the livestock systems are listed in table 5 below.
System |
System LSU |
Dairy Cattle Female breeder |
1.0 1.0 0.7 0.7 0.7 1.2 0.4 0.4 |
Beef Cattle Female breeder |
1.0 1.0 0.7 0.7 0.7 1.2 0.4 0.4 |
Sheep Female breeder |
1.0 1.0 0.8 0.8 0.8 0.6 0.6 |
Goats Female breeder |
1.0 1.0 0.7 0.7 0.8 0.5 0.5 |
Buffalo Female breeder |
1.0 1.0 0.7 0.7 0.7 1.2 0.4 0.4 |
Pigs Female breeder |
1.0 1.0 0.4 0.4 0.4 0.3 0.3 |
This means that, for example, the annual energy needs of the pig male replacement is 40% that of the female breeder.
The SYSTEM SPECIFIC LSUs can be found in range [A59 : K68] of sheet "Parameters". Figure 12 below shows that portion of the sheet. The user can change the values manually.
The REFERENCE LSU is a measure used to arrive at a consistent value of the energy required by animals. The REFERENCE LSU is defined as:
"a 500 kg mature cow, with a calving interval of 13 months, producing 3,500 kg of milk per lactation (butterfat 40 gr/kg, non-fat solids 80 gr/kg). It is also equivalent to the annual metabolisable energy (ME) requirement of the LSU for maintenance, growth, pregnancy, lactation and activity. This is defined as 35,600 MJ" 3.
The SYSTEM SPECIFIC LSUs are converted into REFERENCE LSUs using the following formulas:
Dairy Cattle, Beef Cattle and Buffalo
REFERENCE LSU = (CME/35600) * SYSTEM SPECIFIC LSU
Where:
CME is the Metabolic Energy required for maintaining the breeding female of the livestock system for one year.
CME is calculated as:
CME = (365*(8.3 + (0.091 * (Female breeder Carcass Weight in kg * 2)))) + (MEP * Milk Yield per Lactation in kg * Fertility Rate)
where MEP is defined as the metabolisable energy required for milk production.
By default, MEP is set to:
5.0 for Dairy Cattle
5.0 for Beef Cattle
8.3 for Buffalo
These MEP values can be edited in range [L72 : L76] of sheet "Parameters".
Sheep and Goats
REFERENCE LSU = (CME/35600) * SYSTEM SPECIFIC LSU
where CME is the Metabolic Energy required for maintaining the breeding female of the livestock system for one year. CME is calculated as:
CME = (365 * (1.8 + (0.1 * (Female breeder Carcass Weight in kg * 2)))) + (MEP * Milk Yield per Lactation in kg * Fertility Rate)
where MEP is defined as the metabolisable energy required for milk production.
By default, MEP is set to:
4.6 for Sheep
4.6 for Goats
Pigs
REFERENCE LSU = 0.3 * SYSTEM SPECIFIC LSU
Poultry
REFERENCE LSUs for Poultry are calculated by multiplying the number of birds by specific factors, one for each type of bird:
| Village flock: | .007 |
| Commercial egg culls: | .007 |
| Commercial layers: | .014 |
| Commercial egg breeders: | .014 |
| Commercial meat breeders: | .014 |
| Commercial broilers: | .001 * Carcass weight in kg |
Calculated LSUs are aggregated to a total herd SYSTEM SPECIFIC LSU. The total is then converted into REFERENCE LSUs using the formulas above. The resulting aggregated value is shown in the Demand-driven results as "Total LSU" in sheet "Results" of LDPS2. Poultry system is calculated directly in REFERENCE LSUs so no conversion is needed.
Conversion of REFERENCE LSUs into MJ or Mcal can be made using the following equations:
MJ = REFERENCE LSUs × 35,600
Mcal = REFERENCE LSUs × 35,600 / 4.184
Range [B82 : O87] of sheet "Parameters" contains constants used by LDPS2 . These constants cannot be changed. They represent standard conversion coefficients needed in the equations.
Inventory of feed resources is performed using the "Resources" sheet. Figure 13 shows a screenshot of the upper left corner of the "Resources" sheet. In figure 13, the visible part of the sheet allows the user to manually set the amount of grazing land available to the different animal systems. Grazing land is subdivided into 11 land classes, based on the length of the growing season. All these classes need not be completed. Just fill in the classes you need. All quantities (except hectares) are in tons of dry matter.
The sheet "Resources" contains input screens for 5 types of feed resources:
|
NOTE |
|
As for animal systems, the names of the feed resources are provided for information only since they can be modified, with the exception of grazing land. You can change the names of the feed types within the sheet "Labels". |
1) Grazing land: The grazing land resources are classified according to the duration of the growing season, defined as those days when the environmental conditions (moisture and temperature) are suitable for the growth of grass land vegetation.
The amount of land in each class ( in hundreds of hectares) is multiplied by a specific factor to reflect the higher carrying capacity of land with longer growing seasons. These factors are:
| From | To | Factor |
| 0 days | 75 days | 23.5 |
| 76 days | 89 days | 13.0 |
| 90 days | 119 days | 10.4 |
| 120 days | 149 days | 6.9 |
| 150 days | 179 days | 4.5 |
| 180 days | 209 days | 3.1 |
| 210 days | 239 days | 2.0 |
| 240 days | 269 days | 1.4 |
| 270 days | 299 days | 0.9 |
| 300 days | 329 days | 0.6 |
| 330 days | 365 days | 0.4 |
The carrying capacity of the grazing land is assumed to depend upon the length of the growing period. The best pastures, with a growing period of 365 days, are assumed to be able to support (1÷0.4 =) 2.5 REFERENCE LSUs per hectare ( i.e. 2.5 * 35,600 MJ). Multiplying this reference carrying capacity by the corresponding factor listed in the table gives the energy equivalent of that specific class of pasture in terms of REFERENCE LSUs. The user may modify the carrying capacity by changing the factors in the sheet "Resources", range [G7:G17].
To calculate the available grazing land in terms of REFERENCE LSUs, LDPS2 divides the number of 100 hectares entered in sheet "Resources", range [C7 : C17] by the corresponding factor. Resulting values are shown in range [H7 : H17]. Grazing land classes are then grouped into two broad classes for further calculations:
1) 0 to 89 days
2) 90 to 365 days
Other user-defined parameters are:
1) Energy content of grazing land, in millions of Joules per kilogram of dry matter;
2) Protein content, in grams per kilogram of dry matter;
3) Crude fiber content, in grams per kilogram of dry matter.
2) Crop residues: Crop residues are organic matter left behind after harvest. Typically, these consist mainly of straws and stubble from crop production. You can define up to 10 different types of crop residues. Only crop residues actually available for animal consumption should be considered. Amounts are in tons of dry matter.
Other user-defined parameters are:
1) imports, in tons of dry matter per year;
2) Exports, in tons of dry matter per year;
3) Energy content of crop residues, in millions of Joules per kilogram of dry matter;
4) Protein content, in grams per kilogram of dry matter;
5) Crude fiber content, in grams per kilogram of dry matter.
Calculation for crop residues is performed as follows:
Total LSUs = 
NOTE |
Calculations are the same for all feed types except grazing land. |
Table 6 shows some representative energy content for common crop residues.
| Crop residues | Energy content (in MJ/kg DM) |
| Wheat straw | 5.6 |
| Rice straw | 5.6 |
| Maize stover | 7.3 |
| Sorghum stover | 8.4 |
| Sugar cane tops | 9.0 |
Source: Tropical feeds
TIP |
You may find information on feed values in "Tropical feeds" published by FAO . |
3) Primary products
Primary products are chiefly cereals that are intended for use as animal feed. Commercial poultry operations, for instance, almost always use primary products as feed (cracked corn, laying mash, etc.). Ten types can be defined in LDPS2.
Table 7 shows some representative energy content for common primary products.
| Primary products | Energy content (in MJ/kg DM) |
| Maize | 14.2 |
| Wheat | 14.0 |
| Sorghum | 13.4 |
| Millet | 11.3 |
| Cassava | 12.2 |
| Soybean | 14.9 |
Source: Tropical feeds
4) Crop by-products
The most important crop by-products are cereal brans and oilcakes. These are the by-products of milling and crushing cereals and oil seeds. Table 8 shows some representative energy content for common crop by-products.
| Crop by-products | Energy content (in MJ/kg DM) |
Cereal brans
WheatOil cakes Shelled groundnuts |
10.1 12.5 12.5 11.4 9.5 8.7 13.3 11.0 |
Source: Tropical feeds
5) Fodder
The last type of feed resources considered by LDPS2 is fodders. Ten types can be defined. As with the other feed resources, it is extremely important to include only those fodders that will actually be available to the livestock.
For every individual feed resource, there are 6 different values that you can set:
You can also set the relative prices of each one of the 6 feed types. These prices need not be actual real prices. The only important aspect is their importance relative to that of others. For example, if crop residues are twice as expensive as fodder, you could simply set the price of crop residues to 2 and that of fodder to 1. Keeping these relative values small (between 0 and 10) will assure a faster performance of the optimization routine.
Using the reference LSU (35600 MJ), these values are converted into total Livestock Standard Units, or LSU ( column H or I) and into total digestible protein content (column I or J) given in millions of tons per year. For grazing land, conversion of hectares into total LSU is performed using a standard conversion factor (column G).
After you have set the amount of feed resources available and their associated technical parameters (energy and protein content), you are ready to allocate these resources to the various animal systems.
The feed utilization matrix (FUM) can be found in sheet "Resources", column N. Figure 14 shows the FUM of LDPS2, as found in sheet "Resources". There are two ways to do so: 1) manually allocate feed resources, or 2) optimize allocation between systems using linear programming. These two methods are explained below.
For the animal systems you do not want to analyze, enter zero values in the cells of the corresponding line.
Manual allocation is a quite straightforward method: Go to column N of sheet "Resources" and manually allocate available feed resources to the systems of your choice. Available feed resources per type of feed is shown in row 6. The more feed you allocate, the more values in row 7 and column W ("Total allocated") increase, and the more values in row 8 ("Total remaining") and column X ("Total missing") decrease.
Allocation of feed resources in LSU is automatically converted in tons of digestible proteins in range [N30 : X54] of sheet "Resources" (just below the FUM). The values contained in this range cannot be edited.
CAUTION |
Since LDPS2 does not provide any mechanism to prevent allocation of more feed then there actually is, you should constantly check row 8 (« Total remaining ») and column X (« Total missing »). Be Also careful not to enter negative values; even if negative allocation does not make any sense, LDPS2 won't reject these values. |
Automatically optimized feed allocation is one of the new features added to LDPS2. It calculates optimal feed quantities based on feed requirements and relative prices (or values)4. Optimization of feed allocation is performed using the integrated linear programming capabilities of Excel 5 and 7. There are 139 preset constraints on the systems:
1) Constraints forcing the remaining energy per feed type (line 8 of the FUM) to be greater than or equal to zero (6 constraints);
2) Constraints forcing the total missing energy per animal system (column X of the FUM) to be equal to or smaller than zero (19 constraints);
3) Constraints forcing every allocated amount of LSU (blue cells of the FUM) to be greater than or equal to a minimal energy allocation. These minimum values are user-defined. The matrix used to enter the minima is located in sheet "Resources", range [N57 : U80].
Once you have edited the minimum values in range [N57 : U80], you are ready to start the optimization procedure. This is done by clicking on the "Optimize allocation" button over cell N3. Once pressed, you have two choices: you can run the allocation procedure with or without taking relative prices into account. A wait screen then informs you that LDPS2 is calculating. The optimization routine can take up to 30 minutes to find a solution. You can stop the procedure any time by pressing the CONTROL and BREAK keys simultaneously.
Solution may be impossible for a particular set of values: LDPS2 will then stop the procedure and inform you that no feasible solution could be found.
CAUTION |
Optimization is a resource intensive process within Excel. It is recommended to use this procedure only if you have a Pentium 90 MHz (or better) with at least 16 megabytes of memory. |
Once you have set the production demand targets and the productivity parameters, you can display results for the system of your choice using the "Results" sheet. Once you select the desired settings and press the «CALCULATE» button, calculations are performed for all systems at once but only the selected one is displayed. The sheet "Results" is simply a more convenient way of showing some of the results. The detailed set of results, along with all the calculations, can be found in the hidden sheet "Calculations".
CAUTION |
You may display the sheet "Calculations". This sheet is hidden by default to prevent any accidental changes to it. Beware not to change any equation contained in this sheet, since it will change the way LDPS2 behaves and may impede completely the calculations. |
Animal systems are selected using the top pull-down list near cell G1. Make sure that demand-driven is selected in the second pull-down list (cell G2). The third pull-down list is used to set the number of years in the herd growth routine. It is not used within the demand-driven routine.
The following figure shows the results screen using the default data set for "Dairy cattle, System 1" system.
The upper range of values shows detailed results for every class of animal within the selected system. Note that classes (and products) may be changing from one system to the other (try selecting Poultry instead of Cattle).
Row 45 to 49 shows some calculated ratios and variables for the selected system. Table 9 shows the results associated with the different animal systems.
| Dairy and Buffalo | Beef, Sheep and Goats | Pigs | Poultry | |
| Number of breeders | X | X | X | |
| Number of producers | X | |||
| Number of replacements | X | X | X | |
| Number of other stock | X | X | ||
| Number of draught animals | X | |||
| Number of youngs | X | X | ||
| Village animals | X | |||
| Commercial animals | X | |||
| Total heads | X | X | X | X |
| Birthing rate | X | X | ||
| Offtake rate | X | X | ||
| Females in milk | X | |||
| Average milk yield | X | X | ||
| Meat from fallen animals | X | X | ||
| Manure production | X | X | ||
| Resources needed | X | X | X | X |
| Resources allocated | X | X | X | X |
| Resources shortage | X | X | X | X |
In the Demand-driven routine, LDPS2 performs six more types of calculations. Each one is explained below.
1) Meat production, in tons per year:
Meat production is calculated by multiplying the number of culls per class by the average carcass weight of the corresponding class:
where:
Meati = Meat production for class i, in tons
Cullsi = Number of culls from class i
CWi = Average carcass weight for class in tons
TotalMeati = Total meat production for system n
2) Milk production, in tons per year:
Milk production only concerns the breeder females of Dairy Cattle, Beef Cattle and Buffalo systems. Milk production is calculated as follows:
where:
Milk prodn = Milk production for system n in tons
Breedersn = Number of female breeders in system n
Fertn = Fertility rate
MYIELDn = Milk yield per lactation, in tons
MILKEDn = Fraction of female breeders that are milked
3) Hides production, in tons per year:
LDPS2 also calculates usable hides and skins produced by dairy and beef cattle, sheep, goats and buffalo systems. Six parameters are needed:
1° proportion of female breeders producing usable hide ;
2° proportion of male producing usable hide ;
3° proportion of other males producing usable hide ;
4° proportion of for male breeders ;
5° proportion of for female breeders ;
6° proportion of for other stock .
Total yield per class of animal and per system is then calculated as follows:
where:
Hidesi = Hides production from class i, in tons per year
Cullsi = Number of culls from class i
WEIGHTi = Average weight of skin (green weight), in tons
USABLEi = Proportion of usable skins from culls
Hidesn = Total hides production for system n
Total production is calculated as the sum of all yields per class. The same procedure is employed for sheep and goats systems, using an average weight per head per class.
4) Wool production, in tons per year:
Three specific parameters are used to calculate wool production:
1° Number of shearings per year per class ;
2° Standard fleece weight (SFW);
3° percentage of yield that is sold or used, for all classes (default value: 0).
Classes being:
1° Breeding females2° Breeding males
3° Replacement females
4° Replacement males
Parameters necessary for wool/hair calculations are:
Standard fleece weight (kg)
Shearings per year, breeder female
Shearings per year, breeder male
Shearings per year, replacement female
Shearings per year, replacement male
Wool used or sold, breeder female
Wool used or sold, breeder male
Wool used or sold, replacement female
Wool used or sold, replacement male
Total yield in tons/year is then calculated in the following way:
YIELDi = HEADSi * SHEARINGSi * USEDi *SFWn
totYIELD = 
where
YIELDi = Yield of wool/hair for class i
HEADSi = Number of heads in class i
SHEARINGSi = Number of shearings per year for class i
USEDi = Percentage of product that is used or sold in class i
SFWn = Standard fleece weight of shearings for production system n
and :
totYIELDn = Total production of wool/hair for production system n
This product is then presented onscreen along with meat, milk and hides. These calculations are meant for sheep and goats systems only. It is also assumed that only adult animals are shorn.
5) Manure output
Calculations needed to estimate manure output are complex. Data needed to perform these calculations will rarely be available, especially for countries with little data on the livestock sector. Therefore, only gross estimates can be produced.
One of the major problems arising when one tries to estimate manure output is the fact that only metabolisable energy is taken into account throughout LDPS2. Non-digestible fibers constitute an important part of the dry matter content of manure. Estimating production (in tons per year) of manure without taking into account the non-metabolisable part of ingested feed can only lead to systematic under-estimation of dry matter production.
Keeping these observations in mind, there is a simple way of approximating the maximum theoretical manure output for a given class of land or feed resource. Maximum manure output (MMO) from a given feed resource can be calculated as follows:
where:
MMOi = Tons of manure from feed resource i (maximum value)
totLSUi = Total LSUs available from feed resource i
rLSU = Reference LSU (35600 MJ/kg d.m.)
MEi = Metabolisable energy per kilo of feed resource i
cFAC = Conversion factor (kilos into tons). This is a constant equal to .001
The previous equation can be applied to every single feed resource and every class of grazing land. In the latter case, MMOi cannot be calculated directly since MEi is not available (in the actual version of LDPS2). The user will be requested to input the energy content per kilo for each class of grazing land. Breaking down of the conversion factor used in LDPS2 yields two unknown parameters that are used to calculate manure output from grazing land. The user could then choose the one parameter he finds more reliable and/or available, the other one being calculated automatically by LDPS2. Calculations are explained below.
LDPS2 converts hectares of grazing land into total LSUs by means of a simple conversion factor, which can be written as follows:
CONV multiplied by the number of hectares gives the number of LSUs per year for that particular class of grazing land. Since CONV can be broken down into two unknown parts:
and 
the user could be asked to input either one or the other part, depending on which one is available. If "Tons/ha/year" is supplied, "Energy/ton" can be calculated automatically, using the actual conversion factor CONV.
The previous equation holds for all feed resources since "Energy/ton" is already available for "Crop residues", "Primary products", "Crop by-products" and "Fodders".
Converting the maximum manure output from individual feed resources into manure production by class of animal is more complex and requires information on animal diets. The breakdown of the various feeds consumed by a particular class of animal is not known. On the other side, the amount of each individual feed resource entering a particular system is known, along with the global amount of energy consumed by each class of animal inside a particular system. Unfortunately, there is no way of connecting these two sets of data directly.
One possible solution is to calculate feed resource proportions used by each production system. First, the total energy consumed by class of animal needs to be computed. The following table shows these calculations for an imaginary dairy cattle herd .
| Energy consumption per class, dairy cattle | ||||
| sLSUs | Energy consumed (MJ/head) | Total heads /class | Total energy (MJ/class) | |
| breeding females | 1 | 30401.5 | 104166.7 | 3166823.3 |
| breeding males | 1 | 30401.5 | 104166.7 | 3166823.3 |
| Replac females | 0.7 | 21281.1 | 52873.8 | 1125210.0 |
| Replac males | 0.7 | 21281.1 | 52873.8 | 1125210.0 |
| Other stock | 0.7 | 21281.1 | 0.0 | 0.0 |
| Young females | 0.4 | 12160.6 | 10416.7 | 126672.9 |
| Young males | 0.4 | 12160.6 | 10416.7 | 126672.9 |
| Total | 334914.3 | 8837412.4 | ||
Where: Total energy/class = Energy/head * total heads/class
Feed resource energy availability is then computed for every production system. A percentage is also calculated reflecting the weight (in terms of LSUs) of every single feed in the total available for that system, as shown below:
| Feed resources available for dairy cattle | |||
| (1000 LSUs) | % | MJ / kg | |
| Grazing land <90 | 10000 | 16.95 | 4.16 |
| Grazing land >90 | 20000 | 33.90 | 5.96 |
| Crop residues | 6000 | 10.17 | 15.4 |
| Primary products | 15000 | 25.42 | 10.00 |
| By-products | 5000 | 8.47 | 10.00 |
| Fodders | 3000 | 5.08 | 10.00 |
| Total | 59000 | 100.00 | |
Ex: 16.95% = 10000 * 100 / 59000
Feed energy availability per type of feed is actually a weighted average of every single feed resource specified by the user. In the case of grazing land, it is a weighted average of the different land types in each of the two groups ("under 90 days" and "over 90 days"). Feed resources consumed by type of feed and by class of animal is then computed using total energy consumed per class (first table) and feed proportions (second table), along with the energy content per feed type, producing the following figure:
Column totals represent total manure production per class of animal, while line totals represent total manure production by feed type for a given production system (in the previous example, dairy cattle).
Manure production per type of animal and per feed resource is thus calculated as:
where
i = feed resources
j = type of animalFeed consumed may differ from feed available, since availability may be higher then needs. In the case where availability is lower than needs, the number of heads in each class is adjusted accordingly by LDPS2, thus lowering the "Total heads" column in the first table.
The main postulate underlying these calculations is that all types of animal in a given system consume feed resources in the same proportions. The release of this postulate requires a detailed diet scheme for every type of animal. Such a procedure has not been implemented yet.
6) Protein needs
Along with energy content, feed requirements and availability can be expressed in terms of Digestible Protein content. If the user wants to take into account protein content, he needs to input all the necessary data, i.e. protein content (grams per kilogram of dry matter) of every feed resource and protein requirements (in kilograms per year) for every class of animal.
The Feed Utilization Matrix then displays both energy content and protein content. Allocating feeds in one of these two forms implies automatic calculation of the other one, for consistency. Protein content is calculated as a residual.
In LDPS2, protein requirement and supply are calculated only for ruminants. When amino acids are provided as intact proteins there is never an overall deficiency of nitrogen in poultry diets (Farrell 1987) and it is recommended to provide 18 grams/day CP for poultry laying 50 grams eggs mass/day. However, the user should take care to specify those feeds for use by poultry which have an analysis adequate for use by them. Because of the same reason, protein use by pig is not modeled in LDPS2 at this stage (Anderson, 1993).
6.1) Protein availability
Calculation of total protein content of feeds is performed as follows:
For grazing land:
where Proteini = Total protein content of feed i
totLSUi = Total LSUs available from feed i
PROTi = Protein content of feed i in grams per kilogram of dry matter
ENERGYi = Energy content of feed i in MJ per kilograms of dry matter
For other feed resources:
where TONSi = Tons of feed i available
PROTi = Protein content of feed i in grams per kilogram of dry matter
The user should be aware that the available amount of protein is a somewhat crude estimate based on aggregation of individual protein content. Whenever possible, calculations made by LDPS2 regarding protein availability should be cross-checked with field data in order to validate and/or adjust the parameters used.
6.2) Fiber content
For ruminants, protein content (as calculated above) is adjusted to account for fiber content of feedstuff. Since the value of a feedstuff to ruminants is a function of crude fiber content (among other factors), crude protein content is converted into degradable protein by use of a conversion factor. Following Anderson5, degradable protein is computed as follows:
and
where: D factor = Degradability factor (fraction)
CP = Crude protein content, in grams per kg of dry matter
CF = Crude fiber content, in grams per kg of dry matter
Crude protein is calculated by LDPS2, based on feed availability, whereas Crude fiber are user-specified parameters. With fiber-rich feedstuff, D factor can be negative. Negative values are thus set to zero by LDPS2.
6.3) Protein requirements
Feed requirements can also be expressed in terms of tons of digestible protein per year and per class. The equations needed to calculate protein requirements are presented in the following pages. Classes and systems of interest are cattle and sheep. Buffalo calculations would be the same as cattle, and goats calculations would be the same as sheep.
6.3.1) Cattle
According to "The Nutrient Requirements of Ruminant Livestock (Agricultural Research Council Working Party, 1980, CAB)", the protein requirements (gr/head/day) can be calculated with following formula :
DCP = Rumen Degradable Protein (RDP) + Undegradable Protein (UDP)
where RDP = 7.8 × ME
UDP = if (1.91 × TP - 6.25 × ME <0, 0, 1.91 × TP - 6.25 × ME)
ME (Metabolisable Energy in MJ/head/day)
TP (Tissue Protein Retention)
TP = EUP + DLP + PIG (for young, replacement and other stocks)
= EUP + DLP + MP (for breeders, MP for male = 0)
EUP (Endogenous urinary requirements) = 37 × log10LW -42.2
DLP (Dermal loss requirements) = 0.11 × LW0.75
PIG (Protein in gain) = DG×(168.07-0.16869×LW+0.0001633×LW2)×(1.12-0.1223×DG)
MP (Milk protein) = C × 6.25 × totLact/365
C = constant (Friesian = 4.8, Ayrshire = 5, Jersey = 5.7)
totLact = milk yields per head per year
LW = average liveweight in kilogram
DG = daily gain calculated with LW and years in each class
And protein requirement for pregnancy has to be added to CP for female breeders. Additional protein requirement for pregnancy (during last two months of pregnant period) is 270 grams per day (Animal nutrition, McDonald et al., 1973, p447).
Then, additional protein requirement for pregnant female cattle breeder (PFP) is;
PFP = 270 × Fertility rate × 60 / 365 (g/day)
6.3.2) Sheep:
The protein requirements (gr/head/day) for sheep is also calculated with following formula :
DCP = Rumen Degradable Protein (RDP) + Non-degradable Protein (UDP)
where : RDP = 7.8 × ME
UDP = if (1.91 × TP - 6.25 × ME <0, 0, 1.91 × TP - 6.25 × ME)
ME (Metabolisable Energy in MJ/head/day)
TP (Tissue Protein Retention) = EUP + WP + PIG (for young, replacement and other stocks)
= EUP + WP + MP (for breeders, MP for male = 0)
EUP (Endogenous urinary requirements) = 0.147 × LW +3.375
WP (Wool protein) = 6.25 × 0.85
PIG (Protein in gain) = DG×(160.4-1.22×LW+0.0105×LW2 (for male)
= DG×(156.1-1.94×LW+0.0173×LW2 (for female)
MP (Milk protein) = 6.25 × 7.66 × totLact/365
totLact = milk yields per head per year
LW = average liveweight
DG = daily gain calculated with LW and years in each class
And protein requirement for pregnancy has to be added to CP for female breeders. Additional protein requirement for pregnancy (during last six weeks of pregnant period) is :
-0.5 × LW + 50 grams per day (Animal nutrition, McDonald et al., 1973, p449).
Then, additional protein requirement for pregnant female sheep breeder (PFP) is;
PFP = (-0.5 × LW + 50) × Fertility rate × 42 / 365 (g/day)
2.4 Herd Growth routine
The herd growth routine is used to calculate the yearly expansion of the herds given a specified herd size and composition in the base year. The base year data is input by the user. All other parameters are transferred from Demand-driven routine (to ensure consistency).
The Herd growth routine is designed to model any of the five major livestock systems considered by LDPS2: Dairy cattle, Beef cattle, Sheep, Goats and Buffalo. The systems are, however, analyzed using exactly the same model. The differences in results only pertain to differing productivity parameters as specified by the user. Pigs and Poultry herd/flock are not modeled. The high growth rates and ease of import of these livestock usually allow these systems to expand very quickly. Constraints to their expansion are not biological growth constraints, but rather they are such things as available feed or capital.
Figure 17 : Flows of animals in the Herd Growth Routine
flow \ class YOUNG REPLACEMENT BREEDER OTHER Increase flow +YA +RA +BA +OSA Decrease flow -RA-OSA -BA -BC -OSS Death - Death - Death - Death - Death Trade +Imp.-Exp. +Imp.-Exp. +Imp.-Exp. +Imp.-Exp 2.4.1 Setting up Base year data
Parameters are passed from Demand-driven to herd growth, except the base year data, which specifies the herd size and composition for LDPS2 to start with. In some of the systems with long gestation periods and single offspring, the size of the breeding herd is one of the major constraint to increasing herd size. Occasionally, when such constraints are important, importing of livestock has been used to speed up herd growth.
Base year data can be edited within the "Parameters" sheet, starting at cell A96. The first 7 parameters (blue cells in rows 100 to 106) refer to the base year herd structure. The remaining parameters (8 through 26, rows 107 to 125) are copied from Demand-driven parameters. To change these values, go back to the Demand-driven parameters (sheet "Parameters", starting at cell A1).
The user needs to edit parameter No. 27 and 28 (rows 126 and 127). All parameters in the Herd Growth routine are equivalent to those in the Demand Driven routine with the exception of the Fraction of female young retained (No.28). The Herd Growth routine, unlike the Demand Driven routine, does not assume a stable herd. The number of young retained for use as future replacements and growth of the breeding herd is a policy variable that the user sets. The number of female young retained for herd maintenance and augmentation in the Herd Growth routine is: The total number of female young minus the fraction of young that are sterile times the fraction of female young retained. The reminder of young are placed in the Other stock class for eventual slaughter. Thus, the parameter `Fraction of female young retained' operates on a much larger number in the Herd Growth routine than in the Demand Driven routine.
If the Herd growth models are to have any value then the base year data should be as accurate as possible. This is particularly true for the female classes of animals (female breeders, female young and female replacements) since they are the prime constraint to herd growth.
TIP
The best way to test and adjust the productivity parameters is to run LDPS2 using real historical data series, when available. By comparing the results with the actual herd size and composition, you will be able to fine tune your parameter set to reflect more closely the observed evolution of the herds.
2.4.2 Setting up yearly imports and exports
Herd Growth routine lets you specify yearly imports and exports of live animals. The yearly values are supposed constant throughout the projection period. Figure 18 shows the upper left corner of the input table for imports and exports of live animals. This input table can be found in sheet "Parameters", range [A139 : J174].
Figure 18: Input table for imports and exports of live animals
Within the Herd Growth routine, net imports (imports minus exports) are added to the herd's classes at the end of each projection year. The resulting figures are then used base herd size and composition at the beginning of the next year.
2.4.3 Calculating results
Within the Herd Growth routine, calculations are not simultaneous (as is the case with Demand-driven routine). Herd Growth routine is started when "Herd growth routine" is selected from the pull-down menu at the top of sheet "Results" (on top of cell G2).
Figure 19 shows a 6-year period results for Dairy cattle, System 2. Note that figure 19 shows only the upper left part of the results sheet (first 6 years). LDPS2 allows a total projection period of 20 years.
The same results are shown for all growth systems. Pigs herds and poultry flocks are not projected with the Herd Growth routine.
If you change the selected animal system or the number of years, LDPS2 recalculates all the results. While recalculating, LDPS2 halts all screen activity, so you won't be able to move around or do some other tasks.
Figure 19: Herd Growth results sheet
2.5 Sensitivity analysis
The sensitivity analysis is a feature of LDPS2 that allows you to test how results are affected by changes in the parameter values. Some parameters affect greatly the results, while others have almost no effect. Sensitivity analysis allows you to test which parameters have the most influence on the resulting values.
Sensitivity analysis is performed using the sheet "Sensitivity". Figure 20 shows the content sheet "Sensitivity" where a sensitivity analysis is performed using the milk production target of Dairy cattle and Buffalo systems as the varying parameter. Results show a 5% increase in total milk production (target result to analyze) from a 5% increase in the parameter value, which suggests a linear relationship between the parameter and the result.
To perform a sensitivity analysis, just select the desired animal system, parameter, result and percentage increase or decrease), and press "CALCULATE". Result is shown in cell F15.
You can change the percentage increase in the parameter used by LDPS2. Just type a new value in cell D15.
Figure 20 : Sensitivity analysis
2.6 Saving your work
Since LDPS2 is an Excel workbook, saving the file saves the results altogether. If you want to save multiple result sets, you may use any of the following methods:
save the ldps2.xls workbook under a different name (for example, ldps2a.xls or result1.xls) with the "File_Save As" menu ;
copy the results and paste the values in a different workbook;
copy the calculations sheet and paste the values in a different workbook. This method saves all results from Demand-driven AND Herd Growth, but in a much less orderly fashion than in sheets "Results" and "Growth".
2.7 Printing results
The simplest way to print results is by pressing the "Print results" button in sheet "Results". This prints the visible results in range [B1 : J19]. To print other results, first select the appropriate ones using the pull-down menus, press "Calculate" and then press "Print results".
If you want to print another part of the sheet, or any range in another sheet, first select a range of cells in the sheet of your choice. For example, select range [A1 : J18] in sheet "Results" to print results from Demand-driven routine. Then, using the standard Excel "Print" command (FILE_PRINT), select your printer, turn it on, et voilà!.
You can print whatever part of LDPS2 you want: Results, parameters, equations, labels, etc. Choose "File_Print preview" from the main Excel menubar to make sure the selected area fits in one page.
NOTE
You can print whatever part of LDPS2 you want: Results, parameters, equations, labels, etc. Choose "File_Print preview" from the main Excel menubar to make sure the selected area fits in one page.
2 The target can be seen either as a demand or a production target, since within LDPS2, production is assumed to meet demand, without any economic modeling of demand and production.
3 LDPS Technical Reference, 1987, page 51
4 Relative prices (values) are defined by the user on the basis of farm prices or protein contents, for example. The most economic (low valued) feed is allocated first in the automaticcally optimized allocation.
5 See Anderson (1993) in the reference section.
