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Predicting Daily Dry Matter Intake Using Feed Intake of First Two Hours after Feeding in Mid and Late Lactation Dairy Cows with Fed Ration Three Times Per Day

机译:在中期和晚期哺乳酸奶牛喂养后,使用前两小时的前两小时的食用摄入量预测每日干物质摄入量,每天服用3次喂食奶牛

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摘要

The objective of this study was to evaluate the feasibility of using the dry matter intake of first 2 h after feeding (DMI-2h), body weight (BW), and milk yield to estimate daily DMI in mid and late lactating dairy cows with fed ration three times per day. Our dataset included 2840 individual observations from 76 cows enrolled in two studies, of which 2259 observations served as development dataset (DDS) from 54 cows and 581 observations acted as the validation dataset (VDS) from 22 cows. The descriptive statistics of these variables were 26.0 ± 2.77 kg/day (mean ± standard deviation) of DMI, 14.9 ± 3.68 kg/day of DMI-2h, 35.0 ± 5.48 kg/day of milk yield, and 636 ± 82.6 kg/day of BW in DDS and 23.2 ± 4.72 kg/day of DMI, 12.6 ± 4.08 kg/day of DMI-2h, 30.4 ± 5.85 kg/day of milk yield, and 597 ± 63.7 kg/day of BW in VDS, respectively. A multiple regression analysis was conducted using the REG procedure of SAS to develop the forecasting models for DMI. The proposed prediction equation was: DMI (kg/day) = 8.499 + 0.2725 × DMI-2h (kg/day) + 0.2132 × Milk yield (kg/day) + 0.0095 × BW (kg/day) (R2 = 0.46, mean bias = 0 kg/day, RMSPE = 1.26 kg/day). Moreover, when compared with the prediction equation for DMI in Nutrient Requirements of Dairy Cattle (2001) using the independent dataset (VDS), our proposed model shows higher R2 (0.22 vs. 0.07) and smaller mean bias (−0.10 vs. 1.52 kg/day) and RMSPE (1.77 vs. 2.34 kg/day). Overall, we constructed a feasible forecasting model with better precision and accuracy in predicting daily DMI of dairy cows in mid and late lactation when fed ration three times per day.
机译:本研究的目的是喂食后评价使用的第一2小时干物质采食量的可行性(DMI-2H),体重(BW),和牛奶产量来估计每日DMI在中期和后期奶牛带馈送比每天三次。我们的数据包括来自76头奶牛2840条个人意见的两项研究,其中2259点的观测曾担任54头奶牛和581点的观测担任从22种牛验证数据集(VDS)开发数据集(DDS)就读。这些变量的描述性统计26.0±2.77公斤/天(平均值±标准偏差)的DMI,14.9±3.68公斤/ DMI-2H中的天,35.0±5.48公斤/牛奶产量的天,和636±82.6公斤/天的BW在DDS和23.2±4.72公斤/ DMI的天,12.6±4.08公斤/ DMI-2H中的天,分别30.4±5.85公斤/产奶量的天,和597±63.7公斤/在VDS BW中的一天,。多元回归分析采用SAS的REG程序开发DMI预测模型中进行。所提出的预测方程为:DMI(kg /天)= 8.499 + 0.2725×DMI-2H(kg /天)(kg /天)+ 0.0095×BW(kg /天)(R2 = 0.46,平均值±0.2132×奶产量偏置= 0 kg /天,RMSPE = 1.26Hz kg /天)。此外,当与DMI奶牛的营养需要使用独立的数据集(VDS),我们提出的模型显示出较高的R2(0.22对0.07)和较小的平均偏差(-0.10对1.52千克预测方程(2001)进行比较/天)和RMSPE(1.77对比2.34公斤/天)。总体上,我们构建了更好的精度和准确度可行的预测模型中,当日粮饲喂,每天三次,每天预测中期和后期泌乳奶牛的DMI。

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