Animal Production Systems Group, Wageningen University & Research Center, 6700 AH Wageningen, the Netherlands.
Wageningen Livestock Research, Wageningen University & Research Center, 6700 AH Wageningen, the Netherlands.
J Dairy Sci. 2019 Nov;102(11):10439-10450. doi: 10.3168/jds.2018-16118. Epub 2019 Sep 5.
The rising plate meter (RPM) is used to measure grass height, which subsequently is used in a calibration equation to estimate herbage mass (HM), an important parameter for optimization of feed management in grazing systems. The RPM is placed on the sward and measures the resistance of the sward toward the plate, which depends not only on grass length, but also on sward structure. The accuracy of the calibration equation for the RPM to estimate HM across grazing systems, however, has not yet been evaluated. Therefore, our aim was to analyze the effect of intensive grazing systems on RPM calibration for perennial ryegrass pastures. To do so, we studied 2 grazing systems: compartmented continuous grazing (CCG) and strip grazing (SG), which differ in key grazing characteristics, such as pre- and post-grazing heights and period of regrowth, that may influence tiller density and vertical flexibility of the sward. The experiment was performed from April until October in 2016 and 2017 with 60 dairy cows, at a fixed stocking rate of 7.5 cows per hectare. To calibrate the RPM, 256 direct measurements of HM >4 cm (i.e., above stubble) were collected by cutting and weighing plots of grass for CCG and SG. Our main interest was in the HM above stubble because this is consumed by cows. Herbage mass <4 cm represents the stubble left after grazing. Differences in HM <4 cm may (partially) explain differences in HM >4 cm between the grazing systems. Therefore, HM <4 cm was additionally measured on 4 out of every 8 plots per grazing system by cutting out quadrats to 0 cm with an electric grass trimmer. Our results showed an average error margin in our calibration equations of 25 to 31%, expressed as the root mean square error of prediction (RMSEP) as a percentage of the observed HM >4 cm. Differences between grazing systems were relatively small, and including grazing system as a factor in the regression model to explain the increase in HM per centimeter of grass did not reduce the RMSEP of the model to any relevant extent. On the other hand, HM <4 cm was significantly greater on CCG compared with SG, with 2,042 kg of DM per hectare for CCG and 1,676 kg of DM per hectare for SG. The HM <4 cm, however, is not used for grazing, and this difference was not reflected in the HM >4 cm. Our results indicate that we can use one region-specific calibration equation for perennial ryegrass pastures across intensive grazing systems, despite relatively large differences in pre- and post-grazing heights and period of regrowth.
升片仪（RPM）用于测量草高，随后将其用于校准方程中以估计牧草量（HM），这是放牧系统中优化饲料管理的重要参数。RPM 放置在草丛上，测量草丛对平板的阻力，阻力不仅取决于草的长度，还取决于草丛的结构。然而，尚未评估 RPM 用于估算放牧系统中 HM 的校准方程的准确性。因此，我们的目的是分析密集放牧系统对黑麦草牧场 RPM 校准的影响。为此，我们研究了 2 种放牧系统：分区连续放牧（CCG）和条带放牧（SG），它们在关键放牧特征上有所不同，例如放牧前后的高度和再生期，这些特征可能会影响分蘖密度和草丛的垂直弹性。该实验于 2016 年和 2017 年 4 月至 10 月进行，共有 60 头奶牛，每公顷的固定载畜率为 7.5 头。为了校准 RPM，通过切割和称重 CCG 和 SG 的草样来收集 256 个 HM>4cm（即高于茬口）的直接测量值。我们的主要兴趣是茬口以上的 HM，因为这是奶牛消耗的部分。HM<4cm 代表放牧后的茬口。HM<4cm 的差异可能（部分）解释了放牧系统之间 HM>4cm 的差异。因此，在每个放牧系统的 8 个草样中，有 4 个草样用电动割草机切成 0cm 来测量 HM<4cm。我们的结果表明，我们的校准方程的平均误差幅度在 25%到 31%之间，以预测均方根误差（RMSEP）表示为观察到的 HM>4cm 的百分比。放牧系统之间的差异相对较小，将放牧系统作为解释每厘米草增加的回归模型中的一个因素并不能在任何相关程度上降低模型的 RMSEP。另一方面，CCG 的 HM<4cm 明显高于 SG，CCG 为每公顷 2042 千克 DM，SG 为每公顷 1676 千克 DM。然而，HM<4cm 不用于放牧，并且这种差异没有反映在 HM>4cm 中。我们的结果表明，尽管放牧前后的高度和再生期有较大差异，但我们可以在密集放牧系统中使用一个特定于特定地区的校准方程来估算黑麦草牧场。
