Antonello Cannas

Feeding strategies to design the fatty acid profile of sheep milk and cheese

The majority of sheep milk produced in the world is transformed into cheese. Feeding is a major factor affecting the quality of sheep milk and, therefore, of sheep cheese. Because fat is the main compound of cheese, this review gives an update on the effects of feeding and nutrition on milk fat content and deeply discusses feeding strategies aimed at increasing the levels of healthy fatty acids (FA), such as conjugated linoleic acid and omega-3 FA, in milk and cheese in the human diet. In addition, the use of alternative feed resources such as by-products, aromatic plants, and phenolic compounds in the sheep diet and their effects on milk and cheese FA composition are also discussed. Among feeding strategies, grazing and the use of supplements rich in oils seem to be the best and the cheapest strategies to improve the nutritional value of the fatty acid profile in sheep cheese.

A generalized compartmental model to estimate the fibre mass in the ruminoreticulum: 2. Integrating digestion and passage.

Models used to predict digestibility and fill of the dietary insoluble fibre (NDF) treat the ruminoreticular particulate mass as a single pool. The underlying assumption is that escape of particles follows first-order kinetics. In this paper, we proposed and evaluated a model of two ruminoreticular sequential NDF pools. The first pool is formed by buoyant particles (raft pool) and the second one by fluid dispersed particles (escapable pool) ventrally to the raft. The transference of particles between these two pools results from several processes that reduce particles buoyancy, assuming the gamma distribution. The exit of escapable pool particles from the ruminoreticulum is exponentially distributed. These concepts were evaluated by comparing ruminoreticular NDF masses as 43 and 27 means from cattle and sheep, respectively, to the same predicted variable using single- and two-pools models. Predictions of the single-pool model were 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. Predictions of the two-pool model were obtained by estimating fractional passage rates associated to the ascending and descending phases of the same Yb excretion profiles in sheep faeces. All turnovers were scaled to the power 0.25 of body mass for interspecies comparisons. Predictions based on lignin turnover (single pool) and the two-pool model presented similar trends, accuracies and precisions. The single-pool approach based solely on the descending phase of the marker yielded biased estimates of the ruminoreticular NDF mass.

A Generalized compartmental model to estimate the fibre mass in the ruminoreticulum: 1. Estimating parameters of digestion

Parameters related to the microbial digestion of nutrients in the ruminoreticulum have been estimated by fitting mathematical models to degradation profiles generated from kinetic studies. In the present paper, we propose a generalized compartmental model of digestion (GCMD) based on implicit theoretical concepts and the gamma probability density function to estimate fibre digestion parameters. The proposed model is consistent to a broader compartmental model presented in a companion paper that integrates aspects of fibre digestion and passage. Different versions of the GCMD were generated by increasing the integer order of time dependency of the gamma function. These versions were fitted to 192 published fibre degradation profiles that were obtained using an in vitro fermentation technique. The quality of fit was evaluated based on the frequency of minimum sum of squares of errors (SSE), the number of runs of signs of residuals, and its likelihood probability calculated according to the Akaikes Information Criterion. The likelihood of the proposed model was also compared to a discrete lag time model (DLT), which is commonly used to interpret fibre degradation profiles. The GCMD had superior quality of fit compared to the DLT and was considered more likely in describing 68.75% of the profiles evaluated. Only 9.38% of the degradation profiles that were fitted to the DLT model had a lower SSE. Even though the degradation profiles studied were generated by incubating feed samples up to 96h, the true asymptotic limit of fibre degradation can only be achieved by long-term fermentations. This fact leads to questioning the uniformity of the potentially digestible fibre fraction and a further approach based on GCMD-type model was used to account for its heterogeneous nature.

Use of animal and dietary information to predict rumen turnover

A database was developed from 16 scientific publications to explore mechanisms controlling rumen turnover. The database included 70 treatment means (43 cattle and 27 sheep) from experiments in which rumen contents were measured by complete manual evacuation or by slaughter. Rumen turnover was estimated as the ratio between rumen contents (kg of DM) and feed intake (kg of DM/h). Predictors were intake, body weight (BW), metabolic BW (BW0.75), and the dietary components crude protein (CP), neutral detergent fiber (NDF), neutral detergent solubles (NDS), acid detergent lignin and ash. The best linear models obtained to predict rumen turnover (T) for NDF, NDS, dry matter (DM) and acid detergent lignin (LIGN), respectively, were: T NDF = 23.84 - 10.26 ln(D-NDFI); r 2 : 0.28, P T NDS = 17.08 - 13.39 ln(D-NDSI); r 2 : 0.76, P T DM = 20.16 - 10.14 ln(D-NDSI); r 2 : 0.65, P T LIGN = 37.69 - 30.77 ln(D-NDFI); r 2 : 0.70, P These curvilinear relationships were likely due, at least for NDF and lignin, to the increase in rumen NDF content (% of BW) that occurred when intake of dietary, or forage, NDF (% of BW) increased. In the database, turnover of NDF and NDS showed additive behavior. No differences were found between cattle and sheep in rumen NDF, NDS and DM turnovers. When fed at the same level of intake of forage NDF (% of BW), sheep had significantly lower rumen NDF contents (% of BW) than cattle. The rumen evacuation technique is a valuable tool to explore interspecies relationships. The use of this large dataset derived from the scientific literature improved the understanding of the relationships existing among feed intake, body size and the components of rumen turnover, and allowed their quantification.

Effects of heat stress and diet on milk production and feed and energy intake of Sarda ewes

Abstract Ten Sarda dairy ewes (5th-6th month of lactation; 1995 ± 353 g/d of milk yield) were divided into two isoproductive groups and fed two different diets (high and low fiber) from May 20th to June 18th 2003, to evaluate diet effects on milk yield and intake. In addition, the relationships between meteorological conditions, measured during that unusually hot period, and milk yield and quality, dry matter intake, NDF or NDL were determined, to study animal responses to heat stress. Diet did not have any significant effect on the evaluated parameters. Milk yield was reduced by 20% (0.39 kg/d per head) as minimum temperatures changed from 9-12 °C to 18-21 °C. Similar milk yield reduction was observed as mean temperature-humidity index (THI) went from 60-65 to 72-75. As wind speed increased from 1.5-2.5 m/s to 2.5-4 m/s, milk yield increased by 10%. Milk composition was not affected by heat stress throughout the experiment except for milk somatic cell count, which was increased by high temperatures. Dry matter, fibre and net energy intake varied significantly during the trial, with consistent and marked decreases as heat load increased.

A nutrition mathematical model to account for dietary supply and requirements of energy and other nutrients for domesticated small ruminants: The development and evaluation of the Small Ruminant Nutrition System

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.

Models for estimating feed intake in small ruminants

This review deals with the most relevant limits and developments of the modeling of intake of sheep and goats reared intensively and extensively. Because small ruminants are normally fed ad libitum, voluntary feed intake is crucial in feeding tactics and strategies aimed at optimal animal production. The effects of genetic, neuroendocrine, hormonal, feed and environmental factors on voluntary feed intake were discussed. Then, several mathematical models to estimate dry matter intake (DMI) were examined, with emphasis on empirical models for sheep and goats in intensive farm systems or in extensive areas under pasture or rangeland conditions. A sensitivity analysis of four models of prediction of DMI in housed lactating dairy sheep and meat sheep breeds was also presented. This work evidenced a large variability in the approaches used and in the variables considered for housed sheep and goats. Regarding the estimation of feed intake for grazing sheep and browsing goats, the accuracy of estimates based on empirical models developed so far is very low when applied out of the boundaries of the studied system. Feeding experiments indoors and outdoors remain fundamental for a better modeling and understanding of the interactions between feeds and small ruminants. However, there is a need for biological and theoretical frameworks in which these experiments should be carried out, so that appropriate empirical or mechanistic equations to predict DMI could be developed.

Non-nutritional factors affecting lactation persistency in dairy ewes: a review

Abstract Milk production is largely related to the shape of the lactation curve. Key elements of the lactation pattern are peak yield, which is the maximum daily yield reached during lactation, and lactation persistency, which is the medium rate of milk yield decrease after the lactation peak. The ideal lactation curve should have a reasonably high peak and a flat trend afterwards. A more persistent lactation is desirable because it is related to better animal health and reduction of feeding costs. Effective strategies to improve lactation persistency require a deep understanding of the main factors that affect this trait, including genetics, hormonal status and administration, udder morphology, seasonal changes, management, animal health (e.g. mastitis), stress and nutrition. This review covers the effects of non-nutritional factors on lactation persistency in dairy sheep.

The Small Ruminant Nutrition System: development and evaluation of a goat submodel

Abstract The Small Ruminant Nutrition System (SRNS) is a computer model based on the structure of the Cornell Net Carbohydrate and Protein System for Sheep. A version of the SRNS for goats is under development and evaluation. In the SRNS for goats, energy and protein requirements are predicted based on the equations developed for the SRNS for sheep, modified to account for specific requirements of goats. Feed biological values are predicted based on carbohydrate and protein fractions and their ruminal degradation rates, on forage, concentrate and liquid passage rates, on microbial growth, and on physically effective fiber. The evaluation of the SRNS for goats based on literature data showed that the SRNS accurately predicted the ADG of kids (RMSEP = 32.5 g/d; r2 = 0.85; CCC = 0.91), and the daily MEI (RMSEP = 0.24 Mcal/d g/d; r2 = 0.99; CCC = 0.99) and the energy balance (RMSEP = 0.20 Mcal/d g/d; r2 = 0.87; CCC = 0.90) of goats.

Effects of different fat-enriched concentrates on fatty acid profile of cheese from grazing dairy sheep

References A trial on different fatty acid supplementation was run in grazing dairy sheep. Forty-eight lactating Sarda ewes were randomly allocated to four homogeneous groups: PAS, control group grazing for 22h/d without supplementation; NOF, group supplemented with a cereal based non-fat enriched concentrate; C182, group supplemented with a concentrate rich in sunflower seeds; and C183, group supplemented with a concentrate rich in linseeds. The results showed that the concentrates, based on oilseeds from both sunflower and linseed sources determined high C18:1 t11 and CLA c9 t11 cheese fat content. Moreover linseeds supplementation improved the concentration in the cheese of other beneficial fatty acids such as LN and PUFAω3.