IDENTIFICATION OF RISK FACTORS AND ESTABLISHMENT OF BIOINDICATORS FOR PIGLET MORTALITY UNDER ORGANIC HUSBANDRY CONDITIONS IN DIFFERENT PIG GENOTYPES (BioFeSt)

In BioFeSt, approaches for reducing piglet losses in organic farms are being developed by analyzing relationships between biomarkers for allostatic load, i.e. the cumulative effects of chronic stress on piglet mortality, and identifying risk factors. To this end, biomarkers (cortisol, cholesterol, low-density lipoprotein, high-density lipoprotein, triglycerides, creatinine and glucose) are obtained from saliva and blood samples from pregnant and lactating sows over several parities on days of varying stress levels. This will initially be carried out in an ongoing model trial at the Research Institute of Farm Animal Biology (FBN) on the German Landrace and the German Saddleback pig in order to clarify, among other things, which markers are particularly meaningful in which sample material and measured at which times. Based on this, the proposed biomarkers will then be analyzed on organic farms (PIC, German Landrace, German Saddleback, crossbreeds) to test their suitability for practical use. Based on this, the proposed biomarkers will then be analyzed on organic farms (PIC, German Landrace, German Saddleback, crossbreeds) to test their suitability for practical use. Video data will be used to assess sow maternal behavior, frequency of suckling and sow reactions to piglets in distress, as well as data on the health, body weight and body condition of sows and piglets, lactation, feeding, bedding characteristics and suckling condition of sows and piglet mortality. The aim is to identify sows with a high allostatic load and a potentially increased risk of piglet mortality at an early stage so that supportive measures can be introduced. The work is being carried out in close cooperation with practice partners, breeding organizations and agricultural consultants with the common goal of reducing piglet losses. Together with the BÖL projects ProFerkel and OHFOES, field data is collected according to a comparable scheme, thus achieving better transferability into practice.