The main aim of this research was to establish simple regression models for predicting herbage production parameters during uninterrupted growth and to contribute to forage optimisation of Italian ryegrass (Lolium multiflorum Lam.) cultivated as an overwinter catch crop. The field experiment in split-plot design with two block replicates consisted of two growth cycles: primary growth (C1) and regrowth (C2) as the whole plots, and twelve time series with five-day intervals as the sub-plots. For each time point, herbage dry matter yield, mean stage by weight (MSW) and contents of crude protein (CP) and net energy for lactation (NEL) were determined. Growth days for all production parameters and MSW for quality parameters were used as explanatory variables. Considering the practically relevant 47-day growth period, simple linear regression models explained from 84.9% to 94.0% of the variance of the investigated parameters. These models are better than those performed for the whole 67-day period, except for the model for MSW-based prediction of CP content. The comparison of the two predictors showed that growth days were at least as good as MSW in predicting CP and NEL contents determined during C1 and C2. The effect of growth cycle on the patterns of all investigated parameters was significant, indicating that growth conditions played an important role. Based on our results, CP and NEL yield potentials of Italian ryegrass cannot be completely exploited in a double catch crop system if the required forage quality for lactating cows is to be respected. It rather suggests getting the maximal single harvest in early May, which is justified from nutritional and economical standpoints.

中文翻译：

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意大利黑麦草在初级生长和再生长过程中的形态发育、牧草产量和质量：回归模型和产量优化

本研究的主要目的是建立简单的回归模型，用于预测不间断生长期间的牧草生产参数，并有助于作为越冬作物栽培的意大利黑麦草（Lolium multiflorum Lam.）的牧草优化。具有两个区组重复的裂区设计的田间试验由两个生长周期组成：初级生长（C1）和再生长（C2）作为整个地块，以及以五天为间隔的十二个时间序列作为子地块。对于每个时间点，测定了牧草干物质产量、平均重量阶段 (MSW) 和粗蛋白 (CP) 含量和泌乳净能量 (NEL)。所有生产参数的生长天数和质量参数的 MSW 用作解释变量。考虑到实际相关的 47 天生长期，简单的线性回归模型解释了调查参数方差的 84.9% 到 94.0%。除了基于 MSW 预测 CP 含量的模型外，这些模型优于在整个 67 天期间执行的模型。两个预测因子的比较表明，在预测 C1 和 C2 期间确定的 CP 和 NEL 含量方面，生长期至少与 MSW 一样好。生长周期对所有研究参数模式的影响是显着的，表明生长条件发挥了重要作用。根据我们的结果，如果要尊重泌乳奶牛所需的草料质量，意大利黑麦草的 CP 和 NEL 产量潜力无法在双收作物系统中完全开发。而是建议在 5 月初获得最大的单次收获，