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Showing papers by "Antonello Cannas published in 2008"


Journal ArticleDOI
TL;DR: The appearance of terpenes in sheep and goat milk is enhanced by grazing on some novel pasture species, such as Galium verum, Cichorium intybus and Chrisantemum coronarium, which modify milk and cheese sensorial profile, compared to grazing on conventional forages.

247 citations


Journal ArticleDOI
TL;DR: Challenging tasks for future research on dairy sheep grazing management and nutrition are on-farm application of recent technological advances, such as image-based estimation of pasture biomass and quality, evaluation of sheep dietary quality by faecal Near Infrared Reflectance Spectrometry, and establishment of remote control systems.

68 citations


Journal ArticleDOI
TL;DR: A model of two ruminoreticular sequential NDF pools, based on lignin turnover and the turnover associated to the descending phase of the elimination of Yb-labelled forage particles in the faeces of sheep, is proposed and evaluated.

48 citations


Journal ArticleDOI
TL;DR: A generalized compartmental model of digestion (GCMD) based on implicit theoretical concepts and the gamma probability density function to estimate fibre digestion parameters is proposed and is consistent to a broader compartmental models presented in a companion paper that integrates aspects of fibre digestion and passage.

41 citations


Journal ArticleDOI
TL;DR: The Small Ruminant Nutrition System for sheep can accurately predict dietary organic matter digestibility, ADG of growing lambs and changes in SBW of mature sheep and the SRNS for goats is suitable for predicting ME intake and the energy balance of lactating and non-lactating adult goats.
Abstract: A mechanistic model that predicts nutrient requirements and biological values of feeds for sheep (Cornell Net Carbohydrate and Protein System; CNCPS-S) was expanded to include goats and the name was changed to the Small Ruminant Nutrition System (SRNS). The SRNS uses animal and environmental factors to predict metabolizable energy (ME) and protein, and Ca and P requirements. Requirements for goats in the SRNS are predicted based on the equations developed for CNCPS-S, modified to account for specific requirements of goats, including maintenance, lactation, and pregnancy requirements, and body reserves. Feed biological values are predicted based on carbohydrate and protein fractions and their ruminal fermentation rates, forage, concentrate and liquid passage rates, and microbial growth. The evaluation of the SRNS for sheep using published papers (19 treatment means) indicated no mean bias (MB; 1.1 g/100 g) and low root mean square prediction error (RMSPE; 3.6 g/100g) when predicting dietary organic matter digestibility for diets not deficient in ruminal nitrogen. The SRNS accurately predicted gains and losses of shrunk body weight (SBW) of adult sheep (15 treatment means; MB = 5.8 g/d and RMSPE = 30 g/d) when diets were not deficient in ruminal nitrogen. The SRNS for sheep had MB varying from -34 to 1 g/d and RSME varying from 37 to 56 g/d when predicting average daily gain (ADG) of growing lambs (42 treatment means). The evaluation of the SRNS for goats based on literature data showed accurate predictions for ADG of kids (31 treatment means; RMSEP = 32.5 g/d; r2= 0.85; concordance correlation coefficient, CCC, = 0.91), daily ME intake (21 treatment means; RMSEP = 0.24 Mcal/d g/d; r2 = 0.99; CCC = 0.99), and energy balance (21 treatment means; RMSEP = 0.20 Mcal/d g/d; r2 = 0.87; CCC = 0.90) of goats. In conclusion, the SRNS for sheep can accurately predict dietary organic matter digestibility, ADG of growing lambs and changes in SBW of mature sheep. The SRNS for goats is suitable for predicting ME intake and the energy balance of lactating and non-lactating adult goats and the ADG of kids of dairy, meat, and indigenous breeds. The SRNS model is available at http://nutritionmodels.tamu.edu.

24 citations