To view PDF files, you must have a copy of the Adobe Acrobat Reader which is available as a free download:
Gary D. Dial and Chris Rademacher - College of Veterinary Medicine, University of Minnesota, St. Paul, MN Brad Freking - New Fashion Pork, Inc., Jackson, MN Mark Weaver - Swine Graphics Enterprises, Webster City, IA
It has been said all-to-often, but it remains true, that the grow-finish phase of production is, by far, the financially most important phase of a commercial swine operation. It is the stage where most production costs are incurred. Relative to other production phases, grow-finish contributes the largest portion of total feed cost/market pig, the greatest single cost of production. And, since the growing pig spends more time in this phase than in any other phase of production, grow-finish also incurs the highest facility cost/pig, the second greatest production cost. Relative to weaned pig and feeder pig enterprises, the grow-finish enterprise has the greatest pig-to-pig variation in revenues. Inherent with this variation, is a greater opportunity for revenue enhancement than occurs with the sale of either weaned pigs or feeder pigs .
Both production costs and market revenues for the grow-finish phase are driven by biological performance. If pigs grow slowly, facility utilization drops, resulting in higher facility costs/pig. Throughput of the operation, called capacity utilization, is also reduced with slow growing pigs, since either fewer pigs can be grown in the facility or pigs have to be sold at lighter weights. When pigs inefficiently convert feed to gain, feed costs, on both a per pig and per kg basis, are increased. On the revenue side, variation in the growth performance of pigs results in increased market sort loss and variable carcass quality, causing premiums to suffer. Thus, for both cost and revenue reasons, it is essential that the factors influencing the biological performance of the growing pig be understood.
In contrast to the breeding herd, there are relatively few biological endpoints monitored during the grow-finish phase; the most common ones being average daily feed intake (ADFI), average daily gain (ADG), the efficiency of conversion of feed to gain (FE), percent mortality (%M), and number of turns per pig space/year (turnover ratio). One might, therefore, expect grow-finish diagnostics to be simple. But, the opposite is true: troubleshooting problems in grow-finish phase of production are typically difficult and frequently frustrating. Norms and targets of production are less well understood than those for the breeding herd. The interrelationships between production endpoints have been less clearly defined. The identities and relative impact of influencing factors, called risk factors in medical terminology, on endpoint measures of grow-finish production have not been well elucidated. Traditional management practices have thwarted the collection of data that would have allowed a better understanding of grow-finish production measures and their risk factors.
Traditionally, most producers have used continuous flow management of their grow-finish facilities making it difficult to track feed disappearance and determine the weights of pigs as they pass through the grow-finish phase. Thus, computations of standard measures of growth performance have, at best, been estimates and have had little diagnostic value. Because the majority of production costs are incurred during the grow-finish phase, financial endpoints of production have been added to biological endpoints as measures to be monitored in the assessment of grow-finish performance. The inherent difficulties of interfacing financial information systems with production management systems has retarded the merger of financial with biological data into a single information system. Until recently, producers have not only been unable to capture and report biological information, but it has been rare for them to have access to accurate financial information. This lack of access to integrated biological and financial data has retarded the development of diagnostic tools for use on the grow- finish enterprise.
Times, however, are changing. Fully integrated information systems are now becoming available. The swine industry has moved to all-in/all-out production. Swine production is becoming a business with a clear focus on both enterprise profit and return on investment. This business atmosphere has created a demand for diagnostic tools for use in troubleshooting grow-finish production problems. While it is tempting to jump right in to grow-finish troubleshooting, there are several fundamental steps that must be accomplished before the biological problems of the grow-finish phase can be efficiently and effectively diagnosed. It is essential that producers with farms having grow-finish production problems:
Only then, can a strategy for reducing the detrimental influences of limiting factors be successfully developed and implemented. A good record system is absolutely essential for the diagnosis and management of a production problem, whether it be a nutritional, disease, health, environmental, or management related.
This review describes the fundamentals of diagnosing biological problems of the grow-finish phase of production. It begins with an overview of the whys and hows of keeping grow-finish records, continues on with a discussion of standards of production, and concludes with procedures for the identification of the risk factors associated with various types of suboptimal growth performance.
In the past, swine producers have relied on visual observations, empirical impressions, and a crudely kept records when managing their grow-finish enterprises. Swine businesses typically grew out of diversified agri-businesses, where pig production was seen as a way of adding value to crops being produced. There was limited business orientation, and producers were primarily concerned with making enough money to support their lifestyles. Most were not worried about financial endpoints routinely monitored in other business fields, such as return on invested capital. Efficiency was not a concern; product quality was never discussed.
In recent years, a business approach has emerged in the swine industry, fueled, in part, by the influences of business people entering the pork production from either outside the agriculture sector or from more progressive agricultural commodities, such as poultry. These new entrants have not only been interested in biological efficiency, but they have brought a keen focus on financial efficiency. Increasingly, they are also turning their attention to product quality. Consequently, there is a growing realization in the swine industry that the process of producing pork is like a manufacturing process, and this process must be controlled if it is to be profitable. As has occurred in the manufacturing businesses, information systems will be the hub of swine production control systems.
What does the future hold for production information systems? We believe that: Grow-finish records will become the feedback, monitoring, and control system regulating the speed and efficiency of the pork manufacturing process and the quality of the pork product being produced.
Increasingly, the swine industry is coming to realize that pork production is like a manufacturing businesses, in which inputs are converted into products valued by consumers. As with any other business, the swine production process in the future will be based upon conclusions drawn from data analysis. Data will be captured and used by producers to monitor ongoing processes and, thereby, determine when a process is either out of control, in the manufacturing sense, or not reaching a production optimum. It will be used to identify those factors that are causing the process to be aberrant and then to prioritize them according to their relative importance. Data will be used to determine when and how to intervene at appropriate points during the growth phase to correct the cause of the problem. In addition, similar to manufacturing businesses, information systems will allow capacity utilization to be optimized while, at the same time, improving product quality. Those producers having access to accurate and comprehensive databases and the ability to use them will have a competitive advantage in both cost reduction and revenue maximization.
What kind of information will be captured? Production information systems will become the central data collection tool used to synthesize data coming from multiple sources. Data will flow into them from the feed mill, the processing plant, accounting packages, environmental management software, and health management systems. Information systems also will be used to capture data pertaining to either an individual pig or a group of pigs, called pig-level information. Examples include gender, diet, the application of a management practice, and diagnostic test results. Farm-level information also will be captured, including such things as building or equipment design, genetics, production system, and health status of the herd.
How will data be captured? Some data will continue to be manually entered into the swine production software. Thus, efficiency, flexibility, and built-in data integrity checks will remain a priority. Traditionally, data capture of grow-finish information has been at pen side or in the feed mill followed by subsequent manual data entry into the software. This has been fraught with clerical errors, as more than one person dealt with the data before it made its way into the database. To expedite efficiency and accuracy of data capture, hand-held devices will commonly be used in the future to capture data and upload it directly into a processing computer. Some data, such as carcass, feed, and environmental data, will be captured electronically and transferred by modem or direct linkup to the production software. As the cost of this new technology becomes more reasonable, data will be transferred in the future among computers via the airwaves.
Will the swine production information system meet all of the needs of a producer? Analyses unforeseen by authors of software systems will always require that a suite of software products be used together to address the applications of users. It is likely that the principle software used by producers to manage their farm operations will remain the production software. But, data will flow out of it into other data management systems. Financial packages will receive kilograms, pigs, and days captured by the production information system and use it to generate reports to be used for internal management applications and for external reporting (i.e. credit, taxes). Raw and compiled data will be exported to decision aids and simulation models, which will use it to assist producers in choosing a course of action to follow. And, as users look toward more flexible ways of handling their data, it will become a routine task to export data into database systems, spreadsheets, and graphic programs.
How will swine production information systems be used? Software will become specialized toward specific applications. For example, accounting software will be used to capture information to be used for both external and internal reporting of financial summaries. Production software will not only be used to monitor a production process, allowing the identification of the need for intervention, but it will increasingly be used to manage the production process. Producers will use their production software to determine when to administer a treatment, a management procedure, or to change a diet or the environment. In addition, production software will become vital tools for both solving production problems and for optimizing production efficiency. As producers learn to use their databases and to share their databases with others, swine information systems will become industry research tools for identifying new production and business technologies.
In order to have useable records, information systems must be set up right. When beginning to design a grow-finish record keeping system, the first thing that needs to be done is to lay out a detailed floorplan of all the buildings. This plan must be accompanied by indications of how and at what ages pig are moved among rooms. Rooms must be clearly identified by numeric or alphanumeric codes. The feed bin serving each location needs to be identified, along with its capacity and the type of feed it will hold. By allowing a pictorial depiction of the grow-finish enterprise, floor plans allow a determination of what data can be collected where.
Pig flow through a barn also determine the type of data that can be collected. All-in/all-out production allows a producer to track a group of animals individually, whereas combining groups together in a continuous-flow barn do not. In a continuous-flow system, data is kept at a location level, and each group of pigs loses its identity upon entry. Continuous flow operations make it difficult to calculate time and growth variables, since there is no set endpoint for a group and the population is continuously changing. We feel that if data integrity is imperative, as is usually the case, locations must be managed all-in/all-out, either by room, barn, or site. All-in/all-out allows data for specific groups of pigs to be captured as they progress through the grow-finish enterprise. Thus, accurate feed, financial, marketing as well as biological information can be collected for each group. Group close-out reports and profit:loss statements can subsequently be generated for each group. Fortunately, propelled by the inherent production advantages of all-in/ all-out and the desire for group-level data, the swine industry is moving rapidly toward the broad scale implementation of all-in/all-out production.
A critical element of keeping records that will be useful for troubleshooting problems of the growing pig is giving each group its own unique identification. To facilitate diagnostic efforts, the identification number should, in itself, give specific information about that group. Data such as the year placed, stage of production, grower identity, barn identification, number of turns of the barn during that year, and gender can be coded into a group ID. For example, with the group ID 9564323, 95 refers to the year pigs were placed, 6 is the code for the finishing stage, 4 refers to grower who owns the barn, 3 represents the barn number, 2 represents the turn number for the barn, and 3 is the code for gender, in this case mixed sex pigs. The use of group codes not only facilitates diagnostic efforts when problems occur, but they also allow individual farms to conduct database analyses directed toward improving production. The standardization of codes across farms allows multiple farm files to be merged into larger databases. By virtue of their size and because constituent farms have different production systems, multifarm databases have considerable value in addressing the production issues of a group of farms. They also are essential for establishing production targets for farms having similar production systems and those in a similar geographic region.
The movement of pigs to a new location provides an opportunity to capture beginning and ending weights for that group. Individual pig weights allow the computation of weight variation, a key determinate of facility utilization and ADG. Since it is not feasible to collect individual weights on all but a few farms, only group weights are usually collected. Group weights can help you estimate facility utilization, but they are only a crude estimate. They do not consider the time from when the average pig is removed from a room until the slowest growing pig is moved out. The compilation of group weights at entry and exit allows the calculation of group-to-group variation, which is essential for diagnostic efforts, as discussed below. To be optimally useful, weights should be taken at ages consistent with industry practices. For example, pigs typically enter the nursery at 14 to 25 days, weighing 4 to 7 kg (9 to 15 lbs); they typically leave the nursery phase at 9 to 11 weeks weighing 18 to 25 kg (40 to 55 lb); and they usually are sold in U.S. markets at 24 to 28 weeks weighing 230 to 260 lb. By weighing pigs at these times, reference standards will be more readily available.
By taking weights at several times during the growth phase of a subset of pigs, growth curves can be established for use in subsequent performance monitoring. As subsets of different subpopulations are tracked over time, multiple growth curves can be established for different sexes of pigs, dietary regimens, health statuses, different ambient conditions and seasons, and different facility types. The establishment of growth curves allows the performance of a current group to be related to a reference standard at any point in time during the growth phase. When adjusted to standard weights using a growth curve, the performance of groups having different beginning and ending weights can be more accurately compared than when unadjusted parameters are used. Thereby, growth curves are useful to evaluate current performance as well as to identify opportunities to improve performance.
When pigs are moved in or out of a group, dates need to be recorded as well as the number and weights of pigs. Recording pig movement information is essential for production measures to be accurate. In particular, any time animals are removed from a group, the date, number of pigs, weight and type of removal should be recorded. Types of removals include sales of weaned, feeder, cull, pre-market or market pigs, deaths, and transfers to other groups. If pig movements are not tracked, data becomes inaccurate and less useful in troubleshooting. Groups of pigs should be assigned to a location. Each location should be served by a separate feed bin and feed management system. Because feed is the largest cost of production for any phase of production, the amounts and types of each diet must be recorded for each group. This not only allows the computation of the total feed cost, on a per pig and per kg of gain basis, but it also allows the determination of the amount and cost of each diet used per pig. Accurate feed records allow feed budgeting, a powerful tool for controlling feed costs.
Nursery diets are the most expensive diets fed to the growing pig. The time of entry into the nursery is also the most critical stage in the weaned pigs life. The monitoring of feed intake during the initial 7 to 14 days after pigs are weaned allows troubleshooting of performance problems and ensures that nursery diets are changed as appropriate. The amount of feed delivered to a pen of pigs should be recorded onto feed intake cards, preferably on a pen basis. With small groups of pigs or when the weights of pigs in a group are relatively uniform, recording feed disappearance on a room basis is sufficient. When pen feed intake cards are used, they should include targets for the amount of feed to be given to each pen by average weight of the pigs in the pen. Only the feed that is hand-delivered into the room, typically the prestarter and starter diets, is recorded; feed that is automatically delivered into the room is tracked at the bin level.
Feed intake monitoring during the finishing phase is at least as critical as it is during the nursery phase. With larger groups of grow-finish pigs in which feed bins are filled relatively frequently, feed intakes are typically determined at the bin level. When daily estimates of feed intake are required, the amount of feed delivered to a representative feeder in a room can be captured using individual weigh-hoppers or weigh-meters located above the feeder. As with the nursery phase, the routine monitoring of feed intake allows problems in a room to be identified as they occur, instead of after a group has been closed out. In addition, feed intake monitoring allows diets to be changed as nutrient intake needs change with age.
As an adjunct to feed intake monitoring, water intake can be monitored. Water meters can be placed in the water line serving each individual room. After standard water intake curves have been created, the daily or twice daily recording of water intakes allows the identification of problems in consumption as they emerge. Tracking water consumption is easier than feed intake monitoring. However, in our experience, feed intake falls for a room before water intake does; thus, water monitoring is an adjunct rather than a replacement for feed intake monitoring.
Ambient environmental effects on pig performance and health have long been established. Traditionally, high:low thermometers have been used to capture daily temperature extremes for both nursery and grow-finish pigs. While these thermometers are simple to use, they fail to provide the producer a mean temperature and with a permanent record of the fluctuations that occur between the times that the thermometer is reset. Typically, they are read only once or twice daily and, thus, do not give a very accurate depiction of the ever-changing environment in which the pig is living. They also do not give any indication of other measures of ambient conditions, such as humidity, wet-bulb temperature, air velocity, or gas levels. To fill this need, manufacturers of ventilation equipment are developing computer systems that both drive ventilation systems and, through remote sensing, capture data on the ambient environment. As this data is merged with biological data in production software, the producer can determine temporal relationships between performance and ambient conditions.
Traditionally, treatments and pig mortalities are recorded on room logs. While mortality events are routinely recorded into production record systems, morbidity events, such as treatments and the occurrence of clinically ill pigs, are not captured. As production information systems improve in their ability to present data in formats more useful to producers in their decision-making, morbidity as well as mortality events will be captured. Then, it will be necessary to capture dates, number and identities of pigs treated, drug dosage, duration of treatment, and response to treatments at the room, pen, or individual pig levels. In addition to morbidity and mortality information, results of disease diagnostics will be captured, including results of blood tests, necropsies, and tests done on collected specimens. Capturing this information will not only assist the producer in understanding more fully how to manage a disease process, but it also will allow them, for the first time, to fully understand the impact of disease on production. Producers and their veterinarians will be able to gauge the efficacy of treatments. Retrospective databases will be used to better understand the epidemiology of those diseases that cause reduced performance but little mortality.
When a pig dies, several key bits of data must be collected. The date, weight, number of deaths and the primary reason or clinical sign is valuable in diagnosing a problem. In addition, recording clinical signs, such as diarrhea, lameness, or pneumonia, will assist the user of the database in diagnosing the disease. Because of difficulties in establishing a diagnosis without laboratory confirmation, observed symptoms, not a specific disease or etiology, should be recorded.
Traditionally, most farm accounting has been done for external reporting, either for credit or tax applications. Increasingly, producers want access to information for managerial reasons, called internal reporting. In the future, it is likely that accounting software packages will be used to capture financial information and, perhaps, some biological data, such as unit sales. This will allow the producer to generate enterprise financial statements and to use the other capabilities of the software, including such things as payroll, accounts payable, and inventory management. Financial data will be integrated with biological data in the production software. In this fashion, costs and revenues can be allocated to location or group, and profit:loss statements generated by location, stage of production, group, or enterprise. As financial data becomes available, grow-finish diagnostics will include biological as well as financial endpoints.
Historically, producers have only captured unit sales and revenue information in their production software when marketing their swine. Because this information was summary data, it generally was captured by manual data entry. As processing technologies emerge to better differentiate carcasses of different quality, producers will be paid according to the quality of the pigs that they sell. Presently, U.S. producers are now paid on the basis of backfat, the only measure of quality currently used. In the future, it will become commonplace for them to be paid on an individual carcass basis for an assortment of quality parameters, perhaps, including such things as meat color, water holding capacity, and pH. As the amount of data collected increases, producers will want this data to be captured by their production software. The integration of carcass parameters with production information will allow producers to troubleshoot pork quality problems, just as they now use their production records to diagnose biological problems.
The recording of marketing data is perhaps the most challenging of all grow-finish data collection. The difficulty lies in the inconsistencies between packers in how measurements are made and how data is reported to producers. Different processing plants have different ways of determining backfat and differences in how they calculate lean premiums; sort loss is calculated differently from plant to plant. These differences make comparison of many carcass parameters across packers meaningless. As the industry moves toward standardized techniques for assessing and reporting quality scores, plant-to-plant comparisons will become more valuable. But, for the time being, individual carcass data can be usefully merged with biological, feed, and financial data as long as it comes from the same processing plant. Because it is time consuming to manually enter individual carcass data into the production software, electronic capture of the data directly from the processing plant will become a standard procedure. Individual carcass data will not only allow averages to be calculated for carcass traits, but it will also allow the variation in traits to be determined.
Carcass data that can be captured at the present time on an individual animal basis at most processing plants includes: carcass weight, backfat, loin eye depth, % lean, carcass base price value, % yield, grade, lean premiums or deductions, sort loss, net carcass value, and condemnations. Lot-level information not currently available on an individual pig basis includes: the amount of trimming and the standard yield used by the processing plant. Once the data is stored in the production database, it can be exported to marketing decisions aids, for further analysis.
In order for production parameters to be meaningfully interpreted, the formulas used in their calculation must be understood.
Average Daily Gain (ADG). ADG mediates its influence on the profitability of a commercial operation through its effects on facility utilization and farm output. While there is considerable variation on its importance as a biological variable, there can be little doubt that on farms in which grow-finish space is limiting, ADG contributes significantly to the farms profitability. ADG can be crudely estimated from days to market. Either days on feed or days to market can be used to estimate the age of pigs, which together with pounds of liveweight marketed allows ADG to be calculated. Potentially useful formulae to be used in the absence of computerized records include:
|Days in Facility =||
Average Pig Inventory ______________________ # Pigs Sold or Moved
|X Days in Period|
|Days on Feed =||
Ending Inventory ______________________
Pigs Added per Month
|X 30.5 Days (average # of days per month)|
|Days to Market =||
Current Pig Inventory ______________________
# of Pigs Weaned per Year X Postweaning Survival Rate
|Days to Market =||
Current Pig Inventory ______________________
# of Pigs Sold per Marketing
|X Marketing Interval (days)|
|Days to Market =||
7 X Average Nursery Inventory ______________________
# of Pigs Weaned per Week
+ 7 X Average Grow-Finish Inventory ______________________________________
+ # of Pigs Moved Into G/F Each Week
Computerized record systems compute days to market or days per stage of production according to the following formula:
Days to Market =
Total # of Live Pig Days _________________________________________________________________________
# Market Pigs Sold + # Others Sold + # Transfers + # Removals + # Pigs Moved Out
Average daily gains computed from hand-held records commonly overestimate growth rates because they do not account for the weight gains of dead pigs or the gains of poor-performing pigs moved back in production. Systems that use ear-notching or group identification records to determine the age of marketed pigs often give erroneous ADG for the same reason. Computerized record systems estimate ADG based upon pig-days and, thus, depend upon entry and exit weights and dates for live and, sometimes, dead pigs. Computerized record systems differ in how pig-days are counted for dead pigs. Some include dead-pig days; others do not. IN systems that consider dead pigs, calculations of ADG include pig-days prior to mortality in the denominator. Depending upon how death weights are handled, a high death rate may or may not have a significant effect on ADG computations. The formula that PigCHAMP uses for calculating ADG is:
Total Liveweight Out - Total Liveweight In _____________________________________
Total # Live Pig Days
|Total Liveweight Out =||Total Lb Sold + Lb Removed + Lb Transferred + Lb Moved Out|
|Total Liveweight In =||Total Lb Moved In + Lb Purchased|
ADG is simple to calculate in theory, but ADG calculations often prove quite difficult in practice since they require scales to record initial and final weights. More rigorous systems record pig weights at strategic movement points in order to correctly allocate gain to specific rooms or phases of production. Less intensive systems relate weaning weights to sales weights in the computation of ADG, and therefore do not allow the delineation of ADG for the various production stages of the growth phase. All record systems require a reconciliation of pig inventory with pigs entering, sold, dying, and moved. Because of inherent inaccuracies in determining pig weights and numbers, the use of rolling averages with monthly increments to 3-to-6-month averages will decrease ADG fluctuations.
Feed Efficiency (FE). While feed is the largest single expense in pork production, whether grow-finish, nursery, or weaned pig, it is the least stable of all inputs.Nutrient costs vary daily, and the amount of ingredients used in a diets change dramatically as the pig ages. Also, the ability of the pig to efficiently utilize nutrients varies throughout the year with changes in ambient conditions. The health status and gender of the pig are also known to effect its nutrient needs and, thus, diet costs. Thus, FE is one of the most important predictors of feed cost/unit gain and, thereby, is often one of the most important measures of overall productivity, margin over all costs (i.e. profit).
Comparisons of FE among producers are not reasonable without first considering diet costs, since the use of expensive ingredients in a diet may allow a competitive FE that is negated by high feed costs per unit gain. Similarly, special feed manufacturing procedures may increase the efficiency of feed conversion, while the marginal feed cost/unit gain falls. Since both pigs and pits consume grain, FE calculations are often confounded by feed wastage. Further, as discussed with ADG, some FE calculations do not consider the weight gain of pigs that die or are destroyed; thus, these calculations will overestimate FE relative to those systems that consider dead pig weights. FE for a given phase of production can be estimated without using computerized records with the following formula:
LB Feed Delivered for a Given Time _______________________________________________
# Pigs Marketed during a Given Time X Average LB Gain
|PigCHAMP calculates FE using the formula:|
Total Feed In - Total Feed Out ____________________________________
Total Liveweight Out - Total Liveweight In
Average Daily Feed Intake (ADFI). As with FE, calculations of ADFI are confounded by feed wastage; therefore, ADFI is really an estimate feed disappearance, not feed intake. ADFI does not take into account nutrient density of the ration. Pigs fed diets high in fibrous ingredients, such as barley, or relatively low in energy, such as sorghum-milo, typically will have a higher ADFI than pigs fed rations high in energy, such as a corn:soy diet supplemented with fat. Pigs typically eat to meet their energy needs. Thus, ADFI is less meaningful than average daily nutrient intake. Monthly records of ADFI together with a knowledge of nutrient density of the diet allows diets to be regularly reformulated to assure the provision of the minimal daily nutrients for optimal performance. Records of ADFI also allow for more dynamic responses to changes in piglet performance, such as seasonal changes in ADFI or changes in ADFI occurring with environmental or health stresses. In the absence of computerized record systems, ADFI can be estimated by the formulae:
|ADFI =||LB Feed Delivered _____________________________________________|
Average # Pigs in Inventory X Average # Days per Pig
|ADFI =||LB Feed Delivered per Month ____________________________________________________|
Ending Pig Inventory X 30.5 Days (average # days per month)
|PigCHAMP calculates ADFI using the formula:|
|ADFI =||Total LB Feed Delivered - Total Feed Left Unused ___________________________________________|
Total # Live Pig Days
Mortality. High mortality rates cause the following: lower ADG by reducing the total LB liveweight marketed (numerator) and by increasing the total number of live pig days (denominator); higher FE by reducing the total live weight marketed (denominator); and reduced estimates of ADFI by reducing total live pig days (denominator). Mortality can be reported in terms of annualized or standardized mortality. They can be estimated without the use of computerized records using the formulae:
|% Annualized Mortality =||# Pigs Dying in a Given Time Period X 365 days ____________________________________________
Total # Pigs in Group X # Days in Time Period
|% Standardized Mortality =||# Pigs in a Group Dying ________________________
Total # Pigs in the Group
|% Standardized Mortality =||# Pigs Dying per Unit Time ______________________________
# Pigs Entering during that Time
Annualized mortality allows comparisons between farms and between groups having different lengths of production. While initially more difficult to use, annualized mortality adjusts for the days at a given production stage that a pig is at risk of dying. Standardized mortality is more commonly used, but by not being adjusted for inventory days, does not allow comparisons between stages of production on the same farm or comparisons across groups having different inventory lengths. It also does not allow contrasts among multiple farms. In production systems using standardized mortality, 2% mortality in a prenursery having a 3-week pig-inventory period cannot be equated directly to a 2% mortality in a grower having an 8-week pig-inventory period. High mortality rates not only are typically associated with high medication costs, but also require that feed, non-feed variable costs, and fixed costs (including feeder pig costs) be spread over survivors, resulting in higher production costs for each marketed pig.PigCHAMP calculates mortality according to the formula:
|% Standardized Mortality =||# Deaths + # Destroyed __________________________________|
# Entered + # Purchased + # Moved In
Turnover Ratio. Facility costs together with other fixed costs, such as taxes and depreciation, are the second leading cost of production for the grow-finish phase, thus, justifying turnover ratio as a measure of grow-finish efficiency. Facility utilization is commonly estimated by measuring facility turns per given time unit (e.g. turns/animal space/year). It reflects the capacity utilization of facilities used for the growing pig. Turnover ratio can be estimated from the formula:
|Facility Turns per Year =||365 Days per Year __________________________________
Interval (Days) Between Consecutive Groups of Pigs in a Given Location
|PigCHAMP calculates turnover ratio using the formula:|
|Turnover Ratio =||# Marketed + # Sold as Breeders + # Moved Out __________________________________________
# Pig Days
The numerator utilizes pigs. Producers do not sell pigs, they sell kilograms (pounds) of pork. A more accurate method of estimating efficiency of facility utilization is, therefore, based upon a calculation of pounds pork produced per unit floor space.
|Lb per FT2 =||Lb Live Weight Marketed _________________________|
Floor Space Available for Pigs
The computer calculates this measure of facility utilization using the formula:
|Lb per FT2 =||(Lb Marketed + Lb Sold as Breeders + Lb Moved Out) X 365 Days __________________________________________________________|
Total Ft2 Space Available for the Group X # Days in Time Period
(including pens, aisles, partitions, and feeder spaces; inside barn dimensions)
Other Calculations and Definitions. Several additional terms used by PigCHAMP are also useful in troubleshooting grow-finish problems.
|Total Pig Days =||The sum of the days that all of the pigs were in a location during the reporting period.|
|Pig Days in a Group Space =||Total Pig Days Average ____________________________________________________________________|
# Market Pigs Sold + # Other Sales + # Transfers + # Removal + # Moved Out
|Average # of Days to Market =||Total Pig Days _________________________________________|
# Market Pigs Sold + # Sold/Moved for Breeding
|Average Inventory =||Total # Pig Days ____________________|
Total # Days in Period
|Feed Cost per Unit Gain =||Total Feed Cost ______________________________________________________|
(Wt. Sold + Wt. Moved Out) - (Wt. Purchased + Wt. Moved In)
|Feed Cost per Pig =||Total Feed Cost ______________________________________|
# Pigs Sold + # Other Sales + # Moved Out
Special Considerations. Before generating the reports to be used in diagnostic investigations, there are several things that should be considered.
The next step in troubleshooting growth performance is to establish norms and targets for the measures to be assessed. Targets vary with the starting and ending weights of the pigs being evaluated. For example, pigs entering the grow-finish phase of production at an average of 45 lb (9 weeks of age) and leaving at 240 lb (23 weeks) might be expected to have a ADG of approximately 1.65 lb/day, a FE of 2.95, and a standardized mortality rate of 2.5% during that growth period. Pigs entering the grow- finish phase at lighter weights generally would be expected to have lower ADG, better FE, and higher %M. In contrast, pigs entering the grow-finish phase at heavier weights would likely have a higher ADG, poorer FE, and lower %M. At the other extreme, pigs completing the grow-finish stage at heavier weights would be expected to have a higher ADG, higher FE, and, perhaps, higher mortality than pigs completing this phase at lighter weights. Thus, reference standards are most meaningful when they encompass the weight ranges of the pigs being assessed. Growth performance reference standards for nursery and grow-finish pigs are given according to beginning and ending weights in Tables 1 and 2. As mentioned earlier, growth curves can be used to adjust growth parameters to standard beginning and ending weights so that more accurate comparisons can be made to reference standards and more meaningful contrasts made across groups and farms.
Factors recognized as influencing growth performance can be categorized as ambient environment and season; building and equipment design; health status; management; nutrition, feeding management practices, and delivery systems; individual pig and group factors; and production system. Some of these are farm or barn-level factors, such as facility design, nutrition program, and production system, and affect all groups produced by the farm or pass through a particular barn. Others are group-level factors, such as gender and health status, and affect only a specific group or a subset of groups. Each factor affects the various measures of growth performance in a different way. Many of the factors are common to several of the endpoints. One explanation for the commonality of risk factors comes from the fact that FE, ADG, and ADFI are related to each other, as shown below.
ADFI = ADG X FE
lb feed consumed/day = lb bodyweight gain/day X lb feed consumed/lb bodyweight gain
Throughout the ranges in ADFI seen on commercial farms, there is a positive relationship between ADFI and both ADG and FE (Figures 1). As ADFI increases, FE becomes higher (poorer) and ADG increases. The relationship between ADFI and ADG is linear. ADFI accounts for approximately 80% of the variation in ADG, indicating that the two are very highly related. Because of their strong relationship, ADFI and ADG are considered together in the following discussion of risk factors. The relationship between ADFI and FE is curvilinear; the rate of increase in FE declines at higher ADFI. ADFI accounts for only about 10% of the variation in FE; thus, the two are not highly related. Similarly, ADG and FE have a negative, linear relationship. That is, FE tends to improve as ADG increases. ADG accounts for less than 10% of the variation in FE; thus, the two are not highly related.
Average Daily Gain (ADG) and Average Daily Feed Intake (ADFI). ADG is the consequence of a complex interaction between feed intake and efficiency of ingested nutrient utilization. As FE is held constant, pigs that eat more tend to have higher ADG. Thus, the measurement of ADFI is paramount in troubleshooting problems of ADG. Because of the high correlation between ADG and ADFI, the two measures change in parallel. When attempting to diagnose problems involving either ADFI or ADG, one would expect that increases or decreases in either one would be accompanied by corresponding changes in the other.
ADFI and ADG are often calculated incorrectly because of mistakes in data collection. Erroneous estimates can result from inaccurate estimates of the amount of feed remaining in bins when groups are closed out, which causes the numerator in the ADFI calculation to be off. There can be a failure to account for the inventory days associated with dead pigs or pigs moved out of a group, a denominator error in the ADFI calculation. Errors in the calculation of ADG are often due to feed disappearance estimates being inaccurate, mistakes in estimates of live pig weights, or the weights of dead pigs or pigs moved out of a group not being considered.
Several factors have been observed to effect the voluntary feed intakes of ad- libitum-fed pigs (Figure 2). Management practices such as mixing multiple pens or groups of pigs, multiple pen-to-pen moves postweaning, and frequent sorting and regrouping of pigs disrupt social hierarchy and transiently depress ADFI. In general, any management practice that disrupts the social hierarchy of a pen can depress feed intake by 50% or more for at least a week. Since not all pigs are affected equally, a common sequelae to mixing, sorting, and moving is reduced gains and increased variation in weights.
Suboptimal ventilation rates and air distribution, and ineffective evaporative cooling, especially during the summer, cause increased expenditures of energy for thermoregulation while depressing feed intake. ADFI changes with season, partly in response to circannual changes in ambient temperature and partly because of photoperiodic influences. When pigs are exposed to temperatures above their thermoneutral zones, as often occurs in confinement, ADFI is depressed; thus, the nutrient density of the diet must be increased in order for a pigs daily needs to be met. In contrast, pigs exposed to temperatures below their thermoneutral zone, such as pigs housed outside or in lots during the winter, must consume more energy to meet their metabolic needs. The thermoneutral zone is 18-28 oC (65-82 oF) for pigs weighing 20-50 kg (45-110 lb) and 10-20 oC (50-68 oF) for pigs up to market weights. Feed intake will decrease at approximately 1 g/kg liveweight per degree celsius above the upper critical temperature. As ambient temperature falls below the lower critical temperature, 5 g of feed/kg liveweight is required to compensate for each degree celsius drop in temperature. Because of seasonal changes in ADFI, nutrient insufficiencies may occur unless diets are changed with season.
Being difficult to measure, temperature fluctuations are commonly ignored on commercial farms. Changes in temperature, especially those greater than 2-3 oC (5 oF), require several days before pigs fully acclimate to reach physiological steady state. Temperature fluctuations are associated with reduced ADFI and poorer growth performance. They also increase susceptibility to diseases, which adversely affect appetite.
Humidity extremes also affect pig performance. Pigs have difficulty in cooling themselves at high humidities and, therefore, eat less. At low humidities, pigs are increasingly predisposed to pneumonia, as a result of bacterial pathogens impinging deeper in the lungs and lung clearing mechanisms being compromised.
Dietary factors, feed management, and feed delivery system comprise, perhaps, the largest set of factors influencing ADFI. Pigs fed pelleted diets consume less than those fed meal diets. Presumably the reduction in ADFI that comes with pelleted diets is due to reduced feed wastage. Diets ground finely to improve FE may be less palatable. ADFI varies with grain type, with feed intake typically falling as the corn in a diet is replaced by certain cereal grains. While yet to be proven, producers have long thought that pigs fed freshly harvested grains, especially corn, have higher ADFI than those that fed grains harvested during the previous seasons. Feed contaminated with mycotoxin, especially vomitoxin or aflatoxin, is consumed at a lower rate than uncontaminated feed.
With conventional multispace ad libitum feeders that are in good condition and adjusted regularly, feed wastage varies from less than 2% to almost 8% of feed offered, with the average being from 3.0 to 3.5%. For poorly designed feeders in poor condition or feeders not regularly adjusted, feed wastage can be as high as 20%. Feeder design may influence ADFI and feed wastage both through the pigs spatial requirements at feeder-space level and feed delivery mechanisms. Inadequacies in trough depth or head clearance, trough lip height, depth and contour of trough, and length of trough per nominal feeding space can effectively limit the number of pigs/feeder space. Poor feeder design can result in pigs having to adopt unnatural postures while eating, resulting in pigs needing a longer time to eat; thereby, dominant pigs keep subordinate pigs from accessing feed. If a feeder is improperly designed, feed may bridge in its reservoir, restricting access to feed. Some feeders are particularly susceptible to wicking, which not only predisposes the feed to bridging but also to spoilage. Ease of adjustment of a feeders nose baffle and agitator responsiveness affect the speed at which feed flows from the reservoir into the trough.
Stocking density and number of pigs per pen can influence feed intake by restricting access to feeders. The feed intakes of finishing pigs become compromised somewhere between 0.5 and 0.65 m2/pig (5.5 and 7.0 ft2/pig). ADFI improves 3 to 5% for each 0.1 m2 (1 ft2) increase in space allowance above 0.3 m2 (3 ft2)/pig for grower pigs (20-50 kg; 45-110 lb). Similar modest increases in feed intake are observed for pigs up to market weight when stocking densities increase above 0.65 m2 (7 ft2). When the number of pigs/pen exceeds 35 pigs or so, the amount of activity and aggression in the pen increases, resulting in reduced ADFI. Pen configuration, location of feeders in pens, and number of feeder spaces per pig are associated with reduced ADFI, especially if access to feed is restricted, as when stocking densities are high. Pigs grown in high stocking densities often establish strict social hierarchies with negative effects on the feeding of subordinate pigs.
Access to water affects feed intake. ADFI is reduced if access to water is limited, as when there are too many pigs per waterer. Water intake may be limited when the water flow rate is either insufficient or the flow rate is too high from nipple waterers for a pig to drink comfortably. The effects of inadequate water delivery systems is compounded during periods when water intake increases, as during the summer months.
Genetic programs that select for FE without corresponding emphasis on ADFI can result in terminal hogs with reduced appetites, and subsequently low ADG. Gender affects feed intake. Gilts have lower appetites than males. It remains controversial whether barrows or boars have the highest feed intakes.
Both chronic and acute diseases, whether respiratory, enteric, or systemic, can depress ADFI. Acute diseases typically cause transient and profound effects on feed intake, whereas chronic disease have subtle, more persistent effects on feed consumption. Practices that allow diseases to be spread among pigs having different health statuses, such as commingling pigs from different farms, are frequently associated with lower ADFI. There is growing evidence that several high health technologies being broadly implemented across the swine industry today are associated with improved feed intakes. These technologies include single-sourcing of pigs, all-in/all-out by building or site, segregated early weaning, multiple-site production, and single-age groups/site. Presumably, these technologies influence feed intake by improving the health status of the pigs. Segregated early weaning appears to also influence feed intake by altering the pigs immune system, which has indirect effects on the pigs appetite.
Feed Efficiency. As with ADFI, unrecorded feed deliveries and errors in estimating the amount of feed remaining in a bin cause FE to be inaccurate. Thus, FE should always be viewed in light of ADFI. If ADFI appears to be abnormally low, then FE will be found to be better than it actually is. In this case, the numerator in the FE calculation is lower, causing FE to be improved. Similarly, overestimating pig weights can cause FE to appear artificially low. In this instance, the denominator is too large, resulting in a low FE. As previously mentioned, failure to record weight gains of dead pigs causes FE to be inordinately high, especially on herds with high mortality rates. Also, errors in recording the transfer weights of pigs moved out of a group will cause FE to be poorer than it actually is.
The factors causing suboptimal FE are similar in some respects to those influencing ADFI, but different in other respects (Figure 3). Similar to ADFI, number of pigs per pen and stocking density affect FE; presumably FE improves as reduced feed intake allows improved digestibility. FE tends to be better when there are less than 300-400 pigs/air space. Pigs fed on perforated floors, such as total slatted floors, tend to have lower FE than those fed on solid-concrete floors or partially slatted floors, presumably because feed wastage is reduced. Being exposed to broader temperature extremes, pigs housed in open-front buildings and those reared in lots, whether dirt or concrete, tend to have lower feed efficiencies than those housed in conventional confinement buildings. Feed efficiencies are lower during the cooler months, especially in hogs exposed to the inclement weather, as an increasing proportion of consumed calories are used to meet increased metabolic needs. Daily temperature fluctuations and daily temperatures exceeding the thermoneutral zone are associated with poorer FE.
Several types of feed-related inadequacies detrimentally affect FE. When associated with feed wastage, feeder design or feeder adjustment commonly cause reduced FE. Wet feeders have been observed in some studies to have better FE than dry feeders; however, this has not always been borne out in trials on commercial farms. Suboptimal FE occurs with improper feed milling, especially inadequate mixing of nutrients and suboptimal fineness of grind. Pelleted feeds generally have greater FE than meal rations. Deficiencies in nutrient intake, whether caused by elevated temperatures or improperly formulated rations, are associated with reduced FE. Protein, especially lysine, is a nutrient commonly deficient in finishing rations. Protein insufficiencies occur with improper lysine:calorie ratios, which allow pigs to eat until their energy needs are met while not consuming sufficient protein. Insufficiencies in energy are especially common in nursery and grower pigs, which often cannot consume enough energy to meet their growth needs before they are satiated. While the financial advantage varies with the cost of grain, the failure to add fat to summer diets may result in suboptimal FE. Some mycotoxins, such as aflatoxin, cause reduced FE through pathological effects on internal organs and tissues. Diets that do not contain growth promotants, such copper sulfate or antibiotics, and those containing antibiotics that are less effective as growth promotants, especially during the early stages of growth, are associated with reduced ADFI.
Pigs fed liquid diets or fed on the floor are typically limit fed, even though on some farms they are fed so as to consume nearly the same as pigs having unrestricted access to feeders. Limit feeding is often associated with reduced feed wastage and increased digestibility associated with slower gut motility, resulting in reduced nutrient requirements/unit of gain.
Deviation from a sound genetic program remains widespread on the commercial swine farms of North America. It is not uncommon for producers to use backcross animals having reduced growth heterosis or to use genetic lines not aggressively selected for growth performance. FE is subsequently compromised. In addition, the failure to feed nutrient dense rations to genetically improved pigs having high lean accretion rates also may be associated with suboptimal FE.
Both acute and chronic diseases have detrimental effects on FE as the immune responses of the pig divert energy from growth to combatting infection. Because they reduce both the prevalence and severity of select diseases, high health technologies, such as all-in/all-out by site and segregated early weaning, are associated with improved FE.
Mortality Rate. Mortality rates are typically calculated as the sum of deaths and pigs destroyed by the producer. Because of the tendency for producers to under-report deaths, mortality rates need to be reconciled by taking a physical inventory of the group. That is, producer-recorded mortality should equal the difference between the groups current inventory and the number of pigs sold or transferred to another group. As indicated earlier, the correction of standardized mortality for days in the period to create an annualized mortality parameter allows groups and farms having different period lengths to be compared. Mortality rates may be inflated when the total number of pigs in the group is understated. The denominator in the mortality rate calculation should not only include the number of pigs entering from an earlier stage of production and the number purchased, but it should also be adjusted for pigs transferred into the group from other groups.
Mortality rates on commercial farms typically show a biphasic pattern in the nursery and a multiphasic pattern in finishing. Mortality usually peaks within the first two weeks after pigs are placed in the nursery. Similarly, an initial peak of mortality is commonly observed during the initial 2 to 3 weeks after pigs are placed in the finishing phase. However, a second peak of mortality is also observed in many multi-site production systems approximately 8 to 12 weeks after placement of finishing pigs.
Mortality rates are influenced by a set of factors that somewhat overlap those of ADFI and FE (Figure 4). Mortality rates are influenced by building design, health, production system, management, and nutrition. Greater numbers of pigs per pen and pigs per room, higher stocking densities, and frequent mixing and sorting detrimentally affect mortality, as they do for ADG and FE. Mortality is usually higher when pigs are commingled from multiple sources than when they are single-sourced. Similarly, facilities used continuously have higher mortality rates than those managed in an all- in/all-out fashion. Multiple-site production and single-age groups/site reduce transmission of diseases among pigs of different ages, thereby reducing mortality rates.
In some farms, pigs placed during the winter have higher mortality rates than those placed during warmer seasons; in other farms, mortality rates are highest during the summer. Pigs exposed to extremes of temperature and to daily temperature fluctuations are more susceptible to diseases. Clearly, numerous diseases acutely affecting the pig cause increased mortality, a notable example being Actinobacillus pleuropneumonia. In addition, chronically infected pigs (Porcine Reproduction and Respiratory Syndrome), those having resolved infections but persistent lesions (e.g. salmonella), and those complicated by secondary pathogens (e.g. Mycoplasma hyopneumoniae) also have higher mortality rates. Growing swine reared in closed herds or in high-health herds typically have reduced mortality rates relative to herds receiving breeding stock from multiple sources or herds that obtain stock endemically infected with pathogens. Flooring, ventilation, waste management, and gating around a pen of pigs affect its exposure to pathogens and, thus, its mortality rates.
Access to diets that are highly palatable allows pigs to rapidly initiate their growth phases. In contrast, pigs feed diets that are not consumed readily will not only grow more slowly but will often have higher mortality rates. While increasingly rare, nutrient deficiencies (e.g. selenium/vitamin E) occasionally occur on commercial farms causing increased mortality.
Turnover Ratio. Turnover ratio refers to the number of times a group would pass annually through a facililty at its current ADG. Higher turnover ratios are achieved with higher ADG and with shorter inventory durations. Downtime for a facility refers to the time that the space is unoccupied by pigs. It typically includes the time taken to clean the facilities and the time from cleaning until the next group arrives. When down time is considered in estimates of facility utilization, the term facility turns is commonly used.
ADG mediates its affects on the profitability of a farrow-to-finish enterprise through its effect on turnover ratio, similar in manufacturing businesses to a term called capacity utilization (Figure 5). As shown, ADG has two effects. (1) When space is limiting, ADG effects the weight at which pigs can be sold. The most profitable weight is typically that added during the late stages of growth. Pigs that grow slowly often do not have time to achieve target market weights, so they are discounted. (2) ADG also affects the number of groups that can be grown in the system. When entire groups grow slowly, there may not be sufficient facilities to hold them, requiring that groups be sold at light weights or that they be sold before entering the next phase of production. Whether affecting market weight or group capacity, ADG has a substantial effect on the profitability of a swine enterprise. As demonstrated in Figure 6, ADG exerts its effect on profitability through fixed costs. As ADG slows down, the total weight marketed through a facility falls. Consequently, there are fewer pounds across which to spread fixed costs.
Feed Cost per Pound of Gain. Feed constitutes the greatest portion of total cost of production, regardless of production phase. It, therefore, is one of the most useful diagnostic measures of grow-finish performance. Feed cost/lb gain is comprised of feed efficiency and feed cost (Figure 7). In order for comparisons to be meaningfully made, the composition of feed costs must be determined. By definition, the calculation of feed costs should include the cost of feed delivered to the bin from which it will be fed. Thus, the cost of growth promotants; grind, mix, and delivery charges; and shrink occurring during manufacturing and delivery should be included. Because it comprises feed costs, inaccuracies in the calculation of FE will make estimates of feed cost/lb of gain erroneous.
The inter-relationships between the factors affecting the profitability of a farrow-to- finish farm are shown in Figure 8. As just discussed, FE exerts its effects through feed cost/lb gain and, thus, through variable costs. ADG affects profit by influencing the number of pigs marketed and the average liveweight of marketed pigs. It, thus, impacts the total pounds marketed from a farm. In turn, total weight marketed combines with both revenues and variable costs. It joins with revenues received/lb to create the total revenues of a farm. Similarly, it combines with total cost/lb to generate the total variable costs for a time period. When total variable costs are subtracted from total revenues, margin over variable costs (MOVC) results. The adjustment of MOVC for total fixed costs gives the total profit for a farm. We feel that an understanding of these inter- relationships is an essential prelude to the effective troubleshooting of the grow-finish phase of production.
Figure Legends <figures not yet online>
Figure 1 - Two-way relationships between ADFI, ADG, and FE, with the third variable held constant at its mean value.
Figure 2 - Inter-relationship among the factors influencing average daily feed intake
Figure 3 - Inter-relationship among the factors influencing feed conversion efficiency
Figure 4 - Inter-relationship among the factors influencing growing pig mortality rates
Figure 5 - Inter-relationship among the factors influencing the capacity utilization for a farrow-to-finish operation
Figure 6 - Inter-relationship among the factors influencing fixed costs of production
Figure 7 - Inter-relationship among the factors influencing feed costs
Figure 8 - Inter-relationship among the factors influencing the profitability of a farrow-to-finish operation