Abstract

The accurate estimation of herbage intake is a key to adequately feed grazing ruminants. Ten dairy Sarda sheep fitted with a halter equipped with an accelerometer (BEHARUM device) were allowed to graze micro-swards of Italian ryegrass (Lolium multiflorum L.), alfalfa (Medicago sativa L.), oat (Avena sativa L.), chicory (Cichorium intibus L.) and a mixture (Italian ryegrass and alfalfa) for six minutes. Accelerometer data and video recordings of behaviour were collected simultaneously. The raw acceleration data were processed to calculate 15 variables: sum, mean, variance and inverse coefficient of variation (ICV, mean/standard deviation) for the X, Y and Z axes and the resultant. A database was created that included the acceleration variables and herbage intake (FMI, DMI, g), intake rate (FMIR, DMIR, g/minute), bite mass (FMBM, DMBM, g) either on fresh (FM) or dry matter basis (DM) and the logarithm of number of bites (LB) and bite rate (LBR) measured during the tests. Partial least square regression analysis (PLSR) was used to verify if acceleration variables could be used as predictors of behavioural traits. The precision and accuracy of PLSR were evaluated implementing the Model Evaluation System, in which predicted values were regressed against observed ones, based on r2 and Dent & Blackie test. The PLSR showed an overall good accuracy (Dent & Blackie test P = ns) and was proven precise for the estimation of LB (r2 = 0.87), LBR (r2 = 0.86), DMI and DMIR (r2 = 0.71). To conclude, BEHARUM can accurately estimate with high to moderate precision number of bites and herbage intake of sheep short term grazing Mediterranean forages.

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