Department of Animal Sciences, University of Florida, Gainesville 32611.
Dairy Records Management Systems, Raleigh, NC 27603.
J Dairy Sci. 2020 Sep;103(9):8161-8173. doi: 10.3168/jds.2019-18138. Epub 2020 Jul 16.
Calving patterns and milk production are seasonal throughout the United States; however, the distribution of seasonality, and the extent to which this seasonality is due to direct effects of climate on milk production and reproductive performance or farm management, is not well quantified. Summer-to-winter (SW) ratios have been used as measures of seasonality, but other measures such as low-to-peak (LP) ratios have been proposed. Our objectives were (1) to describe the distribution of seasonality in calving pattern and milk production among herds in the United States, (2) to compare SW and LP ratios of calving pattern and milk production, (3) to quantify the effect of a seasonal calving pattern, parity, and percentage of dry cows on seasonality of milk production, and (4) to describe the association between seasonality in calving pattern and milk production, herd size, and daily milk production per cow. The final data set contained Dairy Herd Improvement Association lactation records from 2015 from 5,292 (calving pattern) and 5,200 (milk production) herds for 41 states in the United States. We used generalized linear regression models with 1 sinusoidal curve to model calving pattern and milk production per cow for each herd. For milk production, a model adjusting for days in milk (DIM) and the interaction of DIM and parity (ADJ) and a model that was not adjusted (NO) were run. Both models included the effect of the percentage of dry cows. We used SW and LP ratios calculated from the parameters of the sinusoidal component of the models as measures of seasonality. The variability within states for all seasonality measures was large. The median LP ratio of calving pattern was 0.61, and small herds were more seasonal (LP ratio 0.56) than large herds (LP ratio 0.75). For milk production, the median LP ratio-NO was 0.88, and the LP ratio-ADJ was 0.90. Small herds were more seasonal (0.89) than large herds (0.92) when their LP ratios-ADJ were compared. States in the south of the United States were the most seasonal for calving patterns and milk production. Adjusting for DIM and parity increased the LP ratio of milk production by 8.9% for 66% of the herds. Adjusting for the percentage of dry cows increased the LP ratio in 72.9% of the herds by a median value of 21.8%. The correlations between SW and LP ratios were weak. Herds that were more seasonal for milk production had a lower average daily milk per cow than less-seasonal herds. In conclusion, seasonality in calving patterns and milk production among herds varied greatly across the United States. Sinusoidal models with covariates allowed for quantification of the effects of calving pattern, DIM, and parity on the seasonality in milk production. The LP ratios captured the maximum seasonality better than SW ratios did.
产犊模式和牛奶产量在美国各地都具有季节性；然而，季节性的分布情况，以及这种季节性在多大程度上是由于气候直接影响牛奶产量和繁殖性能或农场管理，尚未得到很好的量化。夏季到冬季（SW）比率一直被用作季节性的衡量标准，但也提出了其他衡量标准，如低到高（LP）比率。我们的目标是：（1）描述美国牛群产犊模式和牛奶产量季节性的分布情况；（2）比较产犊模式和牛奶产量的 SW 和 LP 比率；（3）量化季节性产犊模式、胎次和干奶牛比例对牛奶产量季节性的影响；（4）描述产犊模式和牛奶产量季节性与牛群规模和每头牛日产奶量之间的关系。最终数据集包含了美国 41 个州的 5292 个（产犊模式）和 5200 个（牛奶产量）牛群的 2015 年奶牛改良协会泌乳记录。我们使用具有 1 个正弦曲线的广义线性回归模型来为每个牛群建模产犊模式和每头牛的牛奶产量。对于牛奶产量，运行了调整了泌乳天数（DIM）和 DIM 与胎次交互作用（ADJ）的模型和未调整的模型（NO）。两个模型都包括干奶牛比例的影响。我们使用从模型正弦分量参数计算的 SW 和 LP 比率作为季节性的衡量标准。所有季节性衡量标准的州内变异性都很大。产犊模式的中位数 LP 比率为 0.61，小奶牛群（LP 比率 0.56）比大奶牛群（LP 比率 0.75）更具季节性。对于牛奶产量，LP 比率-NO 的中位数为 0.88，LP 比率-ADJ 为 0.90。当比较 LP 比率-ADJ 时，小奶牛群（0.89）比大奶牛群（0.92）更具季节性。美国南部各州的产犊模式和牛奶产量最具季节性。对于 66%的牛群，调整 DIM 和胎次会使牛奶产量的 LP 比率增加 8.9%。对于 72.9%的牛群，调整干奶牛比例会使 LP 比率中位数增加 21.8%。SW 和 LP 比率之间的相关性较弱。在牛奶产量方面季节性更强的牛群，其平均日产奶量低于季节性较弱的牛群。总之，美国各地牛群在产犊模式和牛奶产量方面的季节性差异很大。带有协变量的正弦模型允许量化产犊模式、DIM 和胎次对牛奶产量季节性的影响。LP 比率比 SW 比率更好地捕捉最大季节性。
