Bleeding Efficiency and Meat Oxidative Stability and Microbiological Quality of New Zealand White Rabbits Subjected to Halal Slaughter without Stunning and Gas Stun-killing

Abstract

A study was conducted to compare the effect of halal slaughter without stunning and gas stun killing followed by bleeding on residual blood content and storage stability of rabbit meat. Eighty male New Zealand white rabbits were divided into two groups of 40 animals each and subjected to either halal slaughter without stunning (HS) or gas stun-kill (GK). The volume of blood lost during exsanguination was measured. Residual blood was further quantified by determination of haemoglobin content in Longissimus lumborum (LL) muscle. Storage stability of the meat was evaluated by microbiological analysis and measuring lipid oxidation in terms of thiobarbituric acid reactive substances (TBARS). HS resulted in significantly higher blood loss than GK. HS had significantly lower residual haemoglobin in LL muscle compared to GK. Slaughter method had no effect on rabbit meat lipid oxidation at 0, 1, and 3 d postmortem. However, at 5 and 8 days of storage at 4°C, significant differences (p<0.05) were found, with meat from the GK group exhibiting significantly higher levels of MDA than that from HS. At day 3, greater growth of Pseudomonas aeroginosa and E. coli were observed in the GK group (p<0.05) with B. thermosphacta and total aerobic counts remained unaffected by slaughter method. At days 5 and 7 postmortem, bacterial counts for all tested microbes were affected by slaughter method, with GK exhibiting significantly higher growth than HS. It can be concluded that slaughter method can affect keeping quality of rabbit meat, and HS may be a favourable option compared to GK due to high bleed out.

A comparison of bleeding efficiency, microbiological quality and lipid oxidation in goats subjected to conscious halal slaughter and slaughter following minimal anesthesia

“…However, no group (HS or AS) had TBARS value that reached detectable concentration for humans as established by Insausti et al (2001). The similarity in lipid oxidation observed in the present study corroborates the report of Nakyinsige et al (2014) in rabbits, which showed that slaughter…”

“…For instance, glucose which is the substrate preferentially used by many microorganisms such as Pseudomonas (Warriss, 2000) when growing in meat is readily available in blood. Nakyinsige et al (2014) observed that lower amount of residual blood in the carcass of rabbits subjected to halal slaughter caused lower bacteria count. In chicken, Ali, Abdalla, and Mahgoub (2011) also reported that higher blood loss in halal slaughter was associated with lower bacteria count in minced meat at 48 h postmortem.…”

“…The non-significant difference in microbiological quality between the treatments is expected given the similarity in the blood loss from the treatments. According to Nakyinsige et al (2014), the amount of blood left within the carcass after bleeding is one of the most significant factors affecting the level of contamination and thus increase the degree of the deterioration. The high nutritive value of blood in conjunction with favorable temperature, pH, water activity and relative humidity influence the degree of deterioration in meat (Lerner, 2009).…”

“…This could be due to the orientation of the animal at slaughter which affects bleed-out or differences in techniques used for measurement of blood loss. Nakyinsige et al (2014) found higher blood loss in rabbits subjected to halal slaughter without stunning as compared to gas stunned animals followed by bleeding. Poor bleeding efficiency is a major quality defect which can even lead to undesirable discoloration and short shelf life (Griffiths & Purcell, 1984).…”

Development of microbial spoilage and lipid and protein oxidation in rabbit meat

“…After subtracting the OD of blank (standard 4) from all standard and sample values, a standard curve was obtained by plotting the ∆OD 535 against standard concentrations. TBARS (µM MDA equivalent) concentration of the samples was calculated according to the equation: [TBARS] = [(R sample -R blank ) ÷ Slope (µM -1 )] × n(Nakyinsige et al, 2014).…”