It has been shown that milk infrared (IR) spectroscopy can be used to predict detailed milk fat composition. In addition, polymorphisms with substantial effects on milk fat composition have been identified. In this study, we investigated the combined use of milk IR spectroscopy and genotypes of dairy cows on the accuracy of predicting milk fat composition. Milk fat composition data based on gas chromatography and milk IR spectra were available for 1,456 Dutch Holstein Friesian cows. In addition, genotypes for the diacylglycerol acyltransferase 1 (DGAT1) K232A and stearoyl-CoA desaturase 1 (SCD1) A293V polymorphisms and a SNP located in an intron of the fatty acid synthase (FASN) gene were available. Adding SCD1 genotypes to the milk IR spectra resulted in a considerable improvement of the prediction accuracy for the unsaturated fatty acids C10:1, C12:1, C14:1 cis-9, and C16:1 cis-9 and their corresponding unsaturation indices. Adding DGAT1 genotypes to the milk IR spectra resulted in an improvement of the prediction accuracy for C16:1 cis-9 and C16 index. Adding genotypes of the FASN SNP to the IR spectra did not improve prediction of milk fat composition. This study demonstrated the potential of combining milk IR spectra with genotypic information from 3 polymorphisms to predict milk fat composition. We hypothesize that prediction accuracy of milk fat composition can be further improved by combining milk IR spectra with genomic breeding values.

中文翻译：

---

结合使用牛奶红外光谱和基因型可以改善对牛奶脂肪成分的预测。

业已表明，牛奶红外（IR）光谱可用于预测详细的牛奶脂肪成分。另外，已经鉴定出对乳脂组成具有实质性影响的多态性。在这项研究中，我们调查了牛奶红外光谱法和奶牛基因型的组合使用，以预测牛奶脂肪成分的准确性。基于气相色谱和牛奶红外光谱的牛奶脂肪成分数据可用于1,456头荷兰荷斯坦黑白花奶牛。此外，二脂肪酸甘油酰基转移酶1（DGAT1）K232A和硬脂酰辅酶A去饱和酶1（SCD1）A293V多态性的基因型和位于脂肪酸合酶（FASN）内含子中的SNP都是可用的。将SCD1基因型添加到牛奶IR光谱中，可显着提高对不饱和脂肪酸C10：1的预测准确性，C12：1，C14：1顺式9和C16：1顺式9及其相应的不饱和指数。将DGAT1基因型添加到牛奶IR光谱中可提高C16：1 cis-9和C16指数的预测准确性。将FASN SNP的基因型添加到红外光谱中并不能改善对乳脂成分的预测。这项研究证明了将牛奶IR光谱与来自3个多态性的基因型信息相结合来预测牛奶脂肪成分的潜力。我们假设通过将牛奶IR光谱与基因组育种值相结合，可以进一步提高牛奶脂肪成分的预测准确性。将FASN SNP的基因型添加到红外光谱中并不能改善对乳脂成分的预测。这项研究证明了将牛奶IR光谱与来自3个多态性的基因型信息相结合来预测牛奶脂肪成分的潜力。我们假设通过将牛奶IR光谱与基因组育种值相结合，可以进一步提高牛奶脂肪成分的预测准确性。将FASN SNP的基因型添加到红外光谱中并不能改善对乳脂成分的预测。这项研究证明了将牛奶IR光谱与来自3个多态性的基因型信息相结合来预测牛奶脂肪成分的潜力。我们假设通过将牛奶IR光谱与基因组育种值相结合，可以进一步提高牛奶脂肪成分的预测准确性。