Producer question: Can growth curves based on my pigs' actual performance help me fine-tune diets to fit their needs more accurately?
Tokach's answer: Growth curves can do two things.
- They help you determine nutrient requirements in a commercial setting.
- They let you examine the economics of various feed regimens and establish optimal slaughter weights.
The National Research Council's new "Nutrient Requirements of Swine" contains a CD-ROM nutrition modeling program. The three programs let you look at nutrient needs of grow/finish, lactating or gestating sows. (See page 74 for more details.)
To use NRC's grow/finish model – or any modeling program – to its best effect, you need to employ growth curves that match your pigs' growth rates.
You can use closeout data and work backward to establish such curves. Still another way may give a more accurate picture of the pig's changing nutrient requirements through various finishing stages.
Kansas State University and Purdue University researchers have developed a protocol using real-time ultrasound scans to evaluate protein and lipid accretion levels as the pig grows.
Critical inputs include pig age and weight as well as ultrasound backfat and loineye measurements.
Here are the steps to follow to ensure you collect the right growth-curve data:
1. Randomly select and put double ear tags on 39 or 40 pigs per group per gender. For example, if the group has 10 or fewer pens, pick 13 pigs from each of three pens. If the group has more than 10 pens, pick 10 pigs from each of four pens.
You need at least 32 pigs of each sex to get accurate data. By starting with 39 or 40, you have room for error if a pig dies, loses its ear tag or otherwise drops out of the analysis.
Make sure the pigs you pick are healthy but average for the group.
2. Select pens randomly from across the length of the building, excluding sick pens. Make sure you get a variation of pens within the building. For instance, don't use all pens on a north wall or at one end of the barn.
3. At the initial weighing, record the date, the pig's identification, gender, weight, backfat, loineye area and age. Collect weights and ultrasound readings of backfat and loineye measures every three weeks. For the last measurement, take the pigs as heavy as feasible to get a good closing weight.
Purdue researchers note the early and late data lead to more accurate lean growth predictions, lean and lipid accretion rates, and amino acid requirements. That's why you need to take pigs to higher weights (about 270 pounds).
4. During each ultrasound session, record the same information that you collected at the initial weigh-in. Input the data on a spreadsheet for easy interpretation.
5. If you usually top out pens, keep the tagged pigs until the end of the test. Get an average weight of pigs on test that's heavier than your average marketing weight. This allows better interpretation of the curves.
You'll need a certified ultrasound technician to perform scans to get accurate data. (See sidebar.)
6. Record the date and nature of any clinical disease outbreak and any diagnosis made. Also keep a list of the diets fed, including the dates and amounts fed.
7. Collect average daily gain, average daily feed intake and feed-to-gain ratios for the closeout on the groups.
8. After the experiment, send a computer disk of the spreadsheet, a hard copy of the spreadsheet, the disease records, the diet data and closeout information to whatever entity will be helping you formulate growth curves and subsequent diet recommendations. (For example, Kansas State and Purdue do this.)
Those personnel will analyze the data and provide lysine requirement estimates for pigs in that group.
There's also a shortcut if you can't get ultrasound measurements every three weeks. You can do a mass scanning of several different size pigs on your operation in a single day.
You would scan 32 pigs of each gender. Use pigs that entered the finishing unit at three-week intervals to get the best results. This mimics the every-three-week scanning in the previous example. Though mass scanning is not as accurate, it provides a snapshot of the herd's needs.
Collect all the information as outlined. One warning: Make sure the heaviest hogs you measure don't come from pens that you've topped out. Those pigs will not produce average or representative growth rates as they will be the slower-growing pigs left in the pen.
With information from the scans and weighings, you can start to understand nutrient requirements. Animal scientist Allan Schinckel and his staff at Purdue helped us use the on-farm data collection to estimate protein and lipid accretion curves for the genders on a given farm.
Kansas State swine nutritionists use estimates of lipid and protein accretion to determine how to calculate farm-specific lysine needs. We calculate an energy requirement, then a daily lysine requirement. From these, we can figure the lysine-to-calorie ratio. We use that ratio to formulate the final diets for each finishing phase.
This method is more accurate than using a model based on pigs measured in a controlled research setting. Customizing the curves to your pigs in your buildings on your farm should make the estimates more accurate. That should lead to more-optimal growth rates and better returns on the feed costs for your operation.
Mike Tokach is a swine nutritionist at Kansas State University, Manhattan, Kan. Swine researchers Steve Dritz and Jim Smith of Kansas State also contributed to this column.
Pro Center Talk is part of the PORK'98 producer education program presented at World Pork Expo: The Pork Pro Center.
Stop by the air-conditioned tent and visit with more than 100 industry experts at this year's WPX, June 6-8.
Where to Get a Trained Technician
To get the most accurate backfat and loineye measurements to establish growth, lean and lipid curves, you need to hire a trained real-time ultrasound technician.
You can get a list of certified technicians from the National Swine Improvement Federation at 203 Polk Hall, P.O. Box 7621, North Carolina State University, Raleigh, NC 27695-7621, or contact NSIF's Web site at http://mark.asci.ncsu.edu/nsif/certif.htm.