Finding best exotic breed proportion in crossbred lactating sheep kept under farmers’ conditions in Ethiopia determined by use of nested Legendre polynomials with limited data

ABSTRACT

The present study was conducted to estimate milk production performance and fit lactation curves for groups of ewes of Local and of Awassi crosses, with a variable blood level, reared under farmer’s environment. The Weigh-Suckle-Weigh method plus hand milking was used to estimate milk yield for ewes. A total of 466 observations from 115 ewes were used. Estimated least-squares adjusted means for the milk production over 120 days were 0.56?kg day^?1 (Local), 0.67 (<30% Awassi), 0.86 (30–50% Awassi), and 0.96 (>50% Awassi). Groups with 30–50% Awassi and >50% Awassi ewes produced significantly (p?<?0.05) more milk than Local ewes. Significant differences were observed between <30% Awassi and >50% Awassi crossbred groups. The best crosses (>50% Awassi) produced over 70% more milk than the local ewes which demonstrates the potential that exists in increasing milk production through the initiated crossbreeding programme with sheep in Ethiopia.     

Effects of Moringa oleifera silage on milk yield,nutrient digestibility and serum biochemical indexes of lactating dairy cows

This study investigated the effects of Moringa oleifera (MO) as a partial substitute of alfalfa hay on milk yield, nutrient apparent digestibility and serum biochemical indexes of dairy cows. MO was harvested at 120 days post‐seeding. Fresh MO was cut, mixed with chopped oat hay (425:575 on a DM basis), ensiled and stored for 60 days. Sixty healthy Holstein dairy cows were allocated to one of three groups: NM (no MO or control), LM (low MO; 25% alfalfa hay and 50% maize silage were replaced by MO silage) or HM (high MO; 50% alfalfa hay and 100% maize silage were replaced by MO silage). The feeding trial lasted 35 days. The LM and HM diets did not affect dry matter (DM) intake, milk yield or milk composition (lactose, milk fat, milk protein and somatic cell count). The apparent digestibility of DM and NDF was lower for HM group than NM group. Additionally, there were no significant differences in serum biochemical indexes between the LM and NM groups. The HM group had lower serum concentrations of total cholesterol, high‐density lipoprotein cholesterol, and low‐density lipoprotein cholesterol and higher serum concentrations of urea than the NM group. The partial replacement of alfalfa hay (≤50%) and maize silage with MO silage had no negative effects on milk yield, in vivo nutrient apparent digestibility or serum biochemical indexes of lactating cows.     

Prediction of chemical composition and peroxide value in unground pet foods by near‐infrared spectroscopy

The massive development of the pet food industry in recent years has lead to the formulation of hundreds of canine and feline complete extruded foods with the objective of meeting both the needs of the animals and numerous demands from pet owners. In the meantime, highly variable raw material compositions and the industry's new production techniques oblige manufacturers to monitor all phases of the extrusion process closely in order to ensure the targeted composition and quality of the products. This study aimed at evaluating the potential of infrared technology (visible and near‐infrared spectrophotometer; 570–1842 nm) in predicting the chemical composition and peroxide value (PV) of unground commercial extruded dog foods. Six hundred and forty‐nine commercial extruded dog foods were collected. For each product, an unground aliquot was analysed by infrared instrument while a second aliquot was sent to a laboratory for proximate analysis and PV quantification. The wide range of extruded dog food typologies included in the study was responsible for the wide variability observed within each nutritional trait, especially crude fibre and ash. The mean value of the 208 pet foods sampled for PV quantification was 17.49 mEq O₂/kg fat (min 2.2 and max 94.10 mEq O₂/kg fat). The coefficients of determination in cross‐validation of NIRS prediction models were 0.77, 0.97, 0.83, 0.86, 0.78 and 0.94 for moisture, crude protein, crude fat, crude fibre, ash and nitrogen‐free extract (NFE) respectively. PV prediction was less precise, as demonstrated by the coefficient of determination in cross‐validation (0.66). The results demonstrated the potential of NIRS in predicting chemical composition in unground samples, with lower accuracy for moisture and ash, while PV prediction models suggest use for screening purposes only.     

Ranking cows’ methane emissions under commercial conditions with sniffers versus respiration chambers

This study assessed the ranking of dairy cows using individual-level correlations for methane (CH₄) emission on-farm using sniffers and in respiration chambers. In total 20 lactating dairy cows, ten Holstein and ten Jerseys were recorded using sniffers installed in milking robots for three weeks of lactation and subsequently in respiration chambers (RC) where they were each recorded on three occasions within the RC. Bivariate linear mixed models were used to determine the individual-level correlations (r_I) between sniffer and RC phenotypes as proxies for genetic correlations. Despite differences in feeding and management, the predicted CH₄ production from sniffers correlated highly with RC CH₄ production r_I?=?0.77?±?0.18 and CH₄ breath concentration correlated nearly as well with RC CH₄ production r_I?=?0.75?±?0.20. These correlations between sniffers on-farm and RC demonstrate the potential of sniffers measurements as large-scale indicator traits for CH₄ emissions in dairy cattle.