Over the last 5½ years, the Swine Management Services (SMS) database has grown to 770 farms with 1.3 million females and still growing. The database profile continues to change as it grows and more very productive farms are added. For example, the number of farms in the Top 10% has increased from 15 to 77, during this period, and average herd size has grown from 800 to 1,140 sows.
Chart 1 shows female death loss data broken down as Top 10%, Top 25%, Top 50%, and All Farms. The trend lines, from September 2006 to July 2010, shows the red trend line indicating average female death loss for all farms has dropped from 9.4% to 7.2%.
In the Top 10% farms, female death loss increased from 5.7% in September 2006 to 7.8% in May 2008, and then dropped to 7.1% in August 2010. A closer look at the trend lines left us wondering why female death loss has dropped over the last three years. The improvement could be attributed to improved animal husbandry skills of farm staff. We feel the PQA Plus and TQA certification of employees and PQA Site assessments have had a positive effect. The emphasis placed on these programs over the last 3-4 years has reinforced the importance of making timely culling and euthanizing decisions for animals with body condition issues or injuries.
Also during this timeframe, packers that harvest cull animals stopped taking sows with body condition problems, lameness, abscesses, etc. This may have contributed to the increase in sow mortality in the top farms. Farms that wanted to sell cull sows had to do a better job of reducing these problem sows.
Breaking Down Death Loss
Digging a little deeper, we looked at a subset of 109 farms with 605,000 sows in the SMS Swine Smart in-depth analysis database. This data was used to create Charts 2-5.
In Chart 2 – Percentage Death Loss, by Parity – you will see there is wide variation in sow death loss by farm and parity. The breakdown by parity shows that, on average, 14.1% were Parity 0, 17.6% were Parity 1, 13.3% were Parity 2, 13.5% were Parity 3, 12.7% were Parity 4, 11.4% were Parity 5, 8.2% were Parity 6 and 5.6% Parity 7 or higher.
Additional analysis identified some causes of this variation, such as when new gilts enter the unit, gilt development programs, size and age of gilts at first breeding, season of the year, type of sow housing, lactation feeding methods, and training of employees to observe and treat heath-challenged animals.
Chart 3 shows the cumulative death loss by parity. It is noteworthy that 14.7% of the death loss was gilts that never had a litter, higher than the 14.3% death loss of Parity 6 and Parity 7+ sows. Also, nearly half of the death loss (46.7%) was in Parity 2 and lower. Everyone remembers the 600-lb. female they carried out, but there are 2-3 lightweight females carried out for every heavy one. Again, gilt development and employee training are key to reducing female death loss.
Chart 4, Death Loss Percentage, by Parity, again shows lots of variation by farm. The annual female death loss for the 109 farm subset is 7.32%. Broken down, the percentages by parity were: 1.04% Parity 0 females, 1.29% Parity 1, 0.97% Parity 2, 0.99% Parity 3, 0.93% Parity 4, 0.83% Parity 5, 0.60% Parity 6 and 0.41% Parity 7+ females.
The variation in Parity 0 death loss ranged from 0% to 3.5%. Some farms enter gilts in their sow records program upon arrival and others wait until first breeding to enter gilts; this can be up to a 120-day difference in how long gilts are in the sow records program. Consequently, those farms that wait and enter gilts at first breeding are understating female death loss by leaving out the gilts that died during gilt development. We feel it is important to enter gilts as soon as they are purchased or selected for the gilt development unit in closed herds. This is a key number in helping to improve gilt development management.
In Chart 5, death loss percent is broking down in a scatter graph for the 109 farms in the subset. This shows there was tremendous variation amongst farms during the 52-week period of the dataset. There were farms with female death loss under 2% but as high as 14% (7.32% average). Of course, sow death loss increases during an outbreak of porcine reproductive and respiratory syndrome (PRRS) or swine influenza virus (SIV) or during periods of extreme heat in the summer.
There are many reasons for female death loss that are specific to each farm. Staff training and written standard operating procedures (SOP) can help lower female death losses. Staff must be able to identify health-challenged sows early, provide proper treatment, and develop a method for tracking the treated animals for at least 12 months. Often, it is helpful to identify one person who is responsible for treating and tracking the animals.
Key Performance Indicators
Tables 1 and 2 (below) provide 52-week and 13-week rolling averages for key performance indicators (KPI) of breeding herd performance. These tables reflect the most current quarterly data available and are presented with each column. The KPI’s can be used as general guidelines to measure the productivity of your herd compared to the top 10% and top 25% of farms, the average performance for all farms, and the bottom 25% of farms in the SMS database.
If you have questions or comments about these columns, or if you have a specific performance measurement that you would like to see benchmarked in our database, please address them to: firstname.lastname@example.org or email@example.com.
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Mark Rix and Ron Ketchem
Swine Management Services, LLC