In the rolling hills of Italy, where the Italian Mediterranean Buffalo (IMB) has long been a staple of dairy production, a significant leap forward in genetic evaluation is unfolding. Stefano Biffani, a researcher at the Institute of Agricultural Biology and Biotechnology (CNR IBBA) in Italy, has pioneered the implementation of a groundbreaking method called single-step genomic best linear unbiased predictor (ssGBLUP). This innovative approach is poised to revolutionize the way breeding values are estimated for both genotyped and non-genotyped animals, promising to enhance accuracy and genetic progress for key traits in the IMB breed.
The study, recently published in ‘Revista Científica’ (Scientific Journal), delves into the potential of ssGBLUP to integrate genomic information into the genetic evaluation system of the IMB. By leveraging phenotypic data from over 740,000 lactations and morphological data from nearly 92,000 buffalo cows, along with genotypes from over 2,150 animals, the research provides compelling evidence of the method’s efficacy.
Biffani explains, “The inclusion of genomic data in our evaluation system allows us to achieve a more precise estimation of breeding values, which can lead to faster genetic progress for important traits such as milk production, mozzarella yield, and morphological characteristics.”
The study compared the traditional best linear unbiased prediction (BLUP) method with the ssGBLUP approach, revealing significant improvements in accuracy and genetic gain. For production traits, the correlation between estimated breeding values (EBVs) from partial and whole datasets increased by up to 49% when using ssGBLUP, with some traits showing an accuracy boost of over 20%. Even for non-genotyped females, the benefits were substantial, indicating a broader impact across the herd.
The implications of this research extend beyond the immediate benefits to the dairy industry. As Biffani notes, “This technology can enhance the efficiency of dairy production, potentially leading to more sustainable and economically viable practices. By improving the accuracy of breeding values, we can select animals that are not only more productive but also better suited to the environmental and economic demands of modern agriculture.”
Looking ahead, the successful implementation of ssGBLUP in the IMB breeding program sets a precedent for other livestock species. The methodology’s ability to integrate genomic data seamlessly into existing evaluation systems could inspire similar advancements in other agricultural sectors. This research, published in ‘Revista Científica’, marks a significant milestone in the field of genomics and animal breeding, paving the way for future innovations that could reshape the landscape of dairy production and beyond.