首页> 外文期刊>Italian Journal of Agronomy >Morphological development, herbage yield and quality of Italian ryegrass during primary growth and regrowth: Regression models and yield optimisation
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Morphological development, herbage yield and quality of Italian ryegrass during primary growth and regrowth: Regression models and yield optimisation

机译:初级生长和再生期间意大利黑麦草的形态发育,牧草产量和品质:回归模型和产量优化

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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.
机译:这项研究的主要目的是建立简单的回归模型,以预测不间断生长期间的牧草生产参数,并有助于优化作为越冬捕获作物种植的意大利黑麦草(黑麦草)的饲草优化。在具有两个块重复的拆分图设计中,实地试验包括两个生长周期:作为整个图的一次生长(C1)和再生长(C2),以及以五天为间隔的十二个时间序列作为子图。对于每个时间点,测定了牧草干物质产量,平均体重阶段(MSW),粗蛋白含量(CP)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所研究参数差异的84.9%至94.0%。除了基于MSW的CP含量预测模型外,这些模型都优于整个67天的模型。两种预测因子的比较表明,在预测C1和C2期间测定的CP和NEL含量时,生长天数至少与MSW一样好。生长周期对所有研究参数模式的影响都很显着,表明生长条件起着重要作用。根据我们的研究结果,如果要尊重泌乳母牛所需的饲草质量,则不能在双捕获作物系统中完全利用意大利黑麦草的CP和NEL增产潜力。相反,它建议在五月初获得最大的单次收获,从营养和经济角度来看,这是合理的。

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