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Growing Degree Day: Noninvasive Remotely Sensed Method to Monitor Diet Crude Protein in Free-Ranging Cattle
Rangeland Ecology & Management ( IF 2.3 ) Pub Date : 2020-01-14 , DOI: 10.1016/j.rama.2019.12.001
Douglas R. Tolleson , Jay P. Angerer , Urs P. Kreuter , Jason E. Sawyer

The daily nutritional balance of free-ranging cattle is the net result of intake from available forage biomass and nutritive value weighed against the nutritional requirements of the animal. Plant phenology influences nutritive value. Plant phenology is dictated by time of year and an accumulation of photosynthetically active days. Growing degree day (GDD) is a concept that quantifies this relationship and has been used to predict nutritive value in perennial range grasses. GDD could be substituted for chemical analysis to inform grazing animal nutritional monitoring efforts. We hypothesized that in C4 grass-dominated rangelands, a cumulative GDD calculation would correlate with diet crude protein (CP) predictions obtained by fecal near infrared spectroscopy (FNIRS) from free-ranging cattle. Therefore, the objectives of our research were to evaluate the effectiveness of GDD to predict FNIRS-derived determinations of grazing cattle diet CP in 1) two groups of three individual animals grazing a small native pasture and 2) large commercial-scale herds grazing expansive rangelands. For the first objective, cumulative GDD and FNIRS-predicted diet CP were strongly correlated (r2 = 0.76; P < 0.01). Relationships between cumulative GDD and FNIRS-predicted diet CP for the second objective varied considerably among ranches, ranging from a low r2 of 0.05 (P = 0.871) to a high r2 of 0.78 (P < 0.049). Similar values for individual ranch/year combinations were stronger; ranging from a minimum r2 of 0.44 (P = 0.556) to a maximum of 0.95 (P = 0.051). The aggregate relationship between GDD and FNIRS-predicted CP for all ranch/year combinations was highly significant (r2 = 0.37; P < 0.001), but the standard error was 1.86% CP. The noninvasive remotely sensed grazing animal nutritional monitoring method described here was accurate enough to inform tactical rangeland diet quality assessments but was not accurate enough to inform operational-scale grazing management decisions.



中文翻译:

生长度日:监测散养牛饮食粗蛋白的无创遥感方法

自由放养的牛的每日营养平衡是从可利用的牧草生物量摄入的净结果和营养价值与动物的营养需求相称的结果。植物物候影响营养价值。植物物候由一年中的时间和光合作用天数的累积决定。生长度日(GDD)是一种量化这种关系的概念,已被用于预测多年生草丛中的营养价值。GDD可以代替化学分析,从而为放牧动物的营养监测工作提供信息。我们假设在C4草为主的牧场中,累积GDD计算将与粪便近红外光谱(FNIRS)从放养牛身上获得的日粮粗蛋白(CP)预测相关。因此,我们研究的目的是评估GDD的有效性,以预测FNIRS得出的确定放牧牛日粮CP的确定:1)两组,每只三只动物在一个小型天然牧场上放牧,2)大型商业规模的牛群,在广阔的牧场上放牧。对于第一个目标,累积的GDD和FNIRS预测的饮食CP高度相关(r 2  = 0.76;P <0.01)。牧场中第二目标的累积GDD与FNIRS预测的饮食CP之间的关系差异很大,范围从低r 2为0.05(P  = 0.871)到高r 2为0.78(P <0.049)。单个牧场/年份组合的相似值更强;r 2的最小值为0.44(P  = 0.556),最大值为0.95(P  = 0.051)。对于所有牧场/年份组合,GDD与FNIRS预测的CP之间的总体关系非常显着(r 2  = 0.37;P<0.001),但标准误为1.86%CP。此处介绍的非侵入式遥感放牧动物营养监测方法足够准确,可以为战术牧场饮食质量评估提供依据,但不够准确,不能为行动规模的放牧管理决策提供依据。

更新日期:2020-04-21
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