MANAGEMENT ▶▶▶


No historical data but fresh info from the barn


Improving pig performance requires proper management and proactive response. Online decision support can help with that, as can support based on data from the pigs currently in the barn.


BY DR KATARINA NIELSEN DOMINIAK, SEGES, DENMARK F


or many producers of finisher pigs, the traditional way to evaluate productivity is to compare historic data of carcass weight for a batch of pigs with an average amount of feed fed to those pigs during their growth


period. Those data are then benchmarked with similar data from the previous batches of pigs, or perhaps with a defined target value for herd-specific productivity in order to evaluate whether the last batch of pigs performed satisfactorily or not. In other words, each new batch of pigs is managed based on historic data from previous batches, and the degree of success for the current batch is evaluated when that batch itself is history too.


Using cameras on-farm So, could real-time data instead of historic data be used for management? That question was key in a trial that formed part of the project PigSys, an international ERA-NET research pro- ject. To answer the question, camera-based, automatic weight- ing systems were chosen – they are an example of a data source which can be used actively in data-driven management. Such systems provide daily information on the weight of pigs in the current batch, which makes it possible for the farmer to evaluate productivity during the present growth period and implement interventions for the current batch or optimise managerial parameters like climate control and feeding strate- gy for upcoming batches before new pigs are inserted. Data from camera-based weightings of the pigs as well as cli- mate data automatically monitored in two Danish farms (A and B) laid the groundwork for optimised productivity and management in both farms.


Farm A: Group daily gain estimates As part of the trial, farm A was given estimates of the daily gain of a group of pigs. The farm had ad libitum dry feed au- tomates in each pen with weighting cameras placed above those automates in 24 selected pens in the herd. Whenever a pig in the pen was eating, the camera took a picture, and the weight of the pig was estimated based on those pictures. The


10 ▶ PIG PROGRESS | Volume 37, No. 1, 2021


daily output from the weighting system was the average of all weightings from four pens per 24 hours. The pig producer actively used graphs from the weekly re- ports to benchmark the productivity of each batch against previous batches. During the project period he optimised his feeding strategy as well as his strategy for room temperature at insertion of a new batch of pigs (see Figure 1). If the growth in a section diverged from what was expected, the farmer used the information from water data, feed data and temperature data to optimise his management routines.


Farm B: Individual daily gain estimates As part of the same trial, farm B was given estimates of the daily gain of the individual pigs. That farm applied a restrictive liquid feeding strategy. Until the experimental setup used in this project was developed, no camera-based weighting sys- tem could be used in farms with restrictive liquid feeding. This is because the camera is traditionally placed above the feed- ing trough, but with restrictive liquid feeding the pigs stand shoulder-to-shoulder and eat at the same time two to three times a day when the feed is rationed. That makes it impossi- ble for the weighting algorithm to distinguish the pigs from each other and generate a weight estimate. For the PigSys project, a prototype setup was developed that made it possible to generate camera-based weightings of


Figure 1 - Growth curves (group daily gain estimates). Curves from previous batches (reference), the current batch, and the production goal are shown.


Weight Section 3 from 2019–09–17 – 2019–10–30 120 100 80 60 40 20 0 0 20 40 Days after insertion Initial weight 28 kg


Reference Current Goal = 1.1 kg/day


60 80


Weight (kg)


PHOTO: DR KATARINA NIELSEN DOMINIAK


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