1.
Occurrence Of Bacterial Contaminants In Poultry Meals And Their Antibiotic Resistance Pattern
by Nayyab Tariq (2009-VA-207) | Prof. Dr. Aftab Ahmad Anjum | Dr. Muhammad Nawaz | Dr. Muhammad Nasir.
Material type: ; Literary form:
not fiction
Publisher: 2015Dissertation note: Poultry is the second largest industry after textile industry in Pakistan. Its consumption
rate is very high as compared to other animal protein sources, as it is cheaper as compared to red
meat. To fulfill increasing demand of poultry, poultry production quality must be improved.
Many factors affect poultry production. One factor is feeding process. Efficiency of poultry
production depends mainly on feeding process which influences both the quality and quantity of
the poultry production (Grepay 2009). The rearing of poultry birds on commercial level requires
use of bulk quantities of poultry feed. Poultry feed costs 60-70% of total cost for production
(Sahraei et al. 2012). The main purpose to increase poultry production is to fulfill nutritional
requirements of human population that largely rely on poultry and poultry by products as a
source of protein(Obi and Ozugbo 2007).
Poultry feeds are food materials designed to contain all necessary feed ingredients for
proper growth, meat and egg production in birds (Obi and Ozugbo 2007). It is a mixture of
various components including plant proteins (cereals and by products, grains etc), animal byproducts,
fats, vitamins and minerals (Ravindran 2013). The major component of poultry feed is
protein which is the key component of eggs and meat. Protein sources in poultry feed are of
plant, marine and animal origin. Plant proteins may lack some of the essential amino acids, thus
are incomplete protein. Proteins of animal origin are better growth promoter than protein of plant
origin, but their safety is a concern. Among plant based proteins, soybean and canola meal are
produced in higher amounts worldwide (Alali et al. 2011). The animal protein sources include
poultry, fish, meat bone and poultry by products meal. Poultry meal is derived from clean tissues
Introduction
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of slaughtered poultry including bone after the moisture and fat have been extracted in the
rendering process. It may contain whole birds excluding feathers (Anonymus 2014). Among all
protein based meals, poultry meals and poultry by products meal are of superior quality and
provide higher protein content than plant, marine and meat based meals (Samli et al. 2006).
Quality of animal feed has gained importance worldwide. The feeds are found to be
associated with infectious or non-infectious hazards, thus influence human health (Sherazi et al.
2015). Poultry feed can act as carrier of animal and human pathogens (Aliyu et al. 2012). Poultry
feed can get contaminated at any point of harvesting, processing, storage or dispersal of feed.
Primary mode of poultry feed contamination is by dust, soil, water and insects. Poultry meals can
be another source of feed contamination. Poultry meals are added in feed as a source of protein.
Feeds of animal origin like poultry meals are richer in nutrients and water as compared to feed of
plant origin thus are found to have higher microbial load, facilitating the multiplication of
bacteria (Kukier and Kwiatek 2011). Inclusion of contaminated meals in feed increases microbial
load of poultry feed. The contamination of poultry feed not only influences appearance and
nutritional value of feed, but also affects animals and human who consumes it (Maciorowski et
al. 2007). The profitability of poultry production can be greatly affected due to the frequency of
feed contamination and the detrimental effects of the aflatoxins on performance of chickens
(Anjum et al. 2011). Poultry feeds have been implicated in several poultry diseases of viral
(Avian Influenza, Newcastle disease), bacterial (Salmonellosis, Infectious Coryza) and fungal
origin. Many human diseases like Traveler’s Diarrhea and Salmonella Paratyphoid fever have
been associated with consumption of poultry birds that contracted infections from poultry feed
(Obi and Ozugbo 2007).
Introduction
3
The poultry industry relies on ready to use poultry feed prepared by feed mills (Arotupin
et al. 2007). Both bacteria and fungi including mycotoxins usually contaminate feed at different
stages of pre or post processing, depending upon the conditions under which it is handled or
stored (D’Mello 2006). Poultry meals mostly get contaminated post rendering process. The
cooking step in rendering process inactivates bacteria, viruses, protozoa, and parasites(Meeker
and Hamilton 2006) . Still presence of contaminants in meals is attributed to post processing
contamination. Many bacterial pathogens reported in feed are Escherichia coli, Erwinia
herbicola, Salmonella spp., Listeria spp., Enterococcus fecalis, Cl. perferingens and Cl.
botulinum (Aliyu et al. 2012; Lateef and Gueguim-Kana 2014) . The contaminated feed results
in excessive activation of immune system and ultimately decreases poultry production and its
profitability (Kukier et al. 2012). In addition to bacterial contaminants, toxigenic fungi have
threatened quality and safety of feed and have caused severe losses to poultry industry in recent
times. Cereals and grains based poultry feed mostly get contaminated with fungi (Kwiatek and
Kukier 2008). Mycotoxin producing fungal genera that are reported in poultry feed are
Aspergillus, Penicillium and Fusarium (Greco et al. 2014).
As Poultry feed is the first step of the food safety chain in "farm-to-fork" model. Contaminated
feed can also serve as a source of antimicrobial resistant bacteria in poultry meat(da Costa et al.
2007). There are many evidences that pathogens in feed are transmitted to humans through
animals and food of animal origin. It can also become source of some human pathogens in
environment. Feed contamination by fungi is responsible for animal mycotoxicoses and through
consumption of contaminated animal food, results in human intoxications (Kukier et al. 2012).
Birds utilizing toxins containing feed are economical loss for farmers and also affects consumer
Introduction
4
health through its residues (Alam et al. 2012). Poultry feeds containing antibiotic resistant
bacteria results in loss of poultry productivity, making treatment of poultry diseases difficult.
Thus quality of animal food directly depends on usage of nutritionally balanced and safe feed.
Among many feed sources used, poultry meals are gaining importance for their higher nutritional
value, but very less work has been done in world particularly in Pakistan to determine
microbiological safety of poultry meals produced. There is the need to determine various quality
parameters which should be followed to ensure production of safe meal. Availability: Items available for loan: UVAS Library [Call number: 2252-T] (1).
2.
Evaluation Of White Sesame Seed Oil As A Functional Food Ingredient And Its Role To Mitigate Hyperglycemia
by Farhan Aslam (2011-VA-606) | Dr. Sanaullah Iqbal | Dr. Muhammad Nasir | Prof. Dr. Aftab Ahmad Anjum.
Material type: ; Literary form:
not fiction
Publisher: 2017Dissertation note: White sesame seed oil (WSSO) contains appreciable amount of various bioactive components including tocopherols, polyphenols, phytosterols and lignans (sesamin & sesamolin) known to have positive impact against certain diseases. Characterization of white sesame seed oil (PB Til-90) showed the presence of bioactive components make it suitable for human consumption. The comparison of WSSO based functional cookies and vegetable fat (VF) based cookies showed that energy and fat% were significantly higher (P < 0.05) in WSSO than VF cookies. At 60th day, mean moisture, peroxide value, and acidity were higher (P < 0.05) in VF cookies. Over time, protein and fiber% decreased significantly (p < 0.05) in both cookies but remained higher (P < 0.05) in WSSO at 60 days. By the end of the 60 days of storage time, moisture content in SO cookies increased approximately 34% (p < 0.05), while other components decreased significantly (p < 0.05) over time; (protein: -0.2%, fat: -3%, fiber: -5.5%, and ash: -7.9%). At 60 days there were significant (p < 0.05) differences between groups. Moisture was significantly higher in VF verses SO, whereas all other components were significantly (p < 0.05) lower in VF group compared to SO group; (protein: -7.6%, fat: -9%, fiber: -5% and ash: -11 %).
Over time, from baseline to 60 days, peroxide value increased approximately 252% in SO cookies. Additionally, in SO, acidity, nitrogen free extract, and thiobarbituric acid values increased (35%, 3%, 54% respectively), while bioactive components, sesamin and sesamol, decreased significantly (p <0.05) over time (i.e., -0.22% and -1.2% respectively). A similar trend was observed in VF cookies. Over the period from baseline to 60 days, the mean rating on each attribute decreased significantly (p < 0.05) for each cookie type. For SO cookies, colour decreased by about -5.5%, flavour -8%, taste -16%, texture -11.6%, crispness
SUMMARY
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-8% and overall acceptability by -14%. A similar trend was observed in VF cookies. In VF cookies, the mean rating for colour decreased -9%, flavour decreased by -11%, taste decreased by -11%, texture decreased by -12%, crispness decreased by -7% and overall acceptability decreased by -5.5%. By day 60, there were significant (p < 0.05) differences in the sensory rating between groups.
For efficacy study on rats, sixty-three male Sprague-Dawley rats were randomized into standard diet groups (normal control, NCON, n=21) and (diabetic control, DCON, n=21) and a diabetic sesame oil (DSO) (n=21) group which were fed a diet containing 12% WSSO. Blood samples were analyzed at 0, 30 and 60 days. Differences between groups and across days were assessed with two-way repeated measures ANOVA. At baseline, GLU and INS were similar in both diabetic groups (mean 248.4 + 2.8 mg/dl) and (mean 23.4 ± 0.4 μU/mL) respectively. At 60 days, GLU was significantly (p < 0.05) higher in DCON (298.0 ± 2.3 mg/dl) as compared to DSO (202.1 ± 1.0 mg/dl). Activities hepatic antioxidant enzymes increased significantly (p < 0.05) in each variable across time from baseline to 60 days; SOD: (9.7 ± 0.1 to 15.5 ± 0.6 IU/mg), CAT: (6.6 ± 0.1 to 12.5 ± 0.8 IU/mg), GPx (11.1 ± 0.3 to 35.9 ± 3.2 IU/mg), APx (48.7 ± 1.6 to 76.1 ± 1.9 IU/mg) in the DSO group as compared to the DCON and NCON groups. In the DSO group, CK decreased significantly (p < 0.05) from baseline (291.1 ± 0.9 U/L) to 60 days (245.5 ± 7.2 U/L) from both the control groups, while CK-Mb decreased significantly (p < 0.05) from baseline (550.5 ± 3.9 U/L) to 60 days (510.8 ± 6.8 U/L) from NCON group but was not significantly different from DCON group. Among liver function tests, ALP increased over time in both diabetic groups (i.e., in DSO group from baseline to 60 days it raised from 246.7 ± 3.3 U/L to 277.7 ± 2.8 U/L) and at 60 days was significantly higher (p < 0.05) than NCON in both groups but were not significantly different from each other. In contrast, ALT from baseline (81.5 ± 3.7 U/L) to 60 days (67.4 ± 2.7 U/L) and AST from baseline (148.7 ± 3.5 U/L) to 60 days (118.3 ± 1.2 U/L) significantly decreased
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(p < 0.05) in the DSO group as compared to DCON or NCON resulting in significantly lower values than both control groups by 60 days. At 60 days, urea in the DSO group decreased from baseline (38.5 ± 2.3 to 30.9 ± 1.1) such that it was significantly lower (p < 0.05) than both control groups. From baseline to 60 days, creatinine significantly increased (p < 0.05) in the two diabetic groups; in DSO group at baseline creatinine was (0.3 ± 0.0 mg/dl) and increased up to (0.4 ± 0.1) after 60 days whereas it remained fairly stable in the NCON group. At 60 days, creatinine was significantly higher in both the diabetic groups as compared to NCON. At 60th day; cholesterol, triglyceride, VLDL, and LDL was significantly lower (p < 0.05) and HDL significantly was significantly higher than DCON, and NCON. The results indicated that there were no significant differences between the DSO or DCON groups in electrolyte balance, minerals, and hematological values.
For efficacy study on humans, forty-six subjects with Type 2 diabetes were recruited and randomly divided into two equal groups (diabetic control, DCON) and diabetic sesame oil (DSO). At baseline, 30, 60, and 90 days, blood samples were drawn and analyzed. Two-way repeated measures ANOVA was used to evaluate the difference between groups and across time. In both groups GLU, INS, and HbA1c were not significantly different at baseline; (mean 187.07 + 5.63 mg/dl), (mean 12.12 ± 1.03 μU/mL), and (mean 7.55 + 0.37 %) respectively. At 90 days, GLU was significantly (p < 0.05) decreased in DSO (137.83 ± 3.16 mg/dl) when compared with DCON (218.13 ± 5.92 mg/dl) while insulin was significantly increased in DSO (23.13 ± 1.15 U/ml) as compared to DCON (7.93 ± 0.38 U/ml). At 90th day HbA1c was significantly lower (p < 0.05) in DSO as compared to DCON. TBARS was significantly lower (p < 0.05) in DSO (1.08 ± 0.05 [MDA] nmol/ml) as compared to DCON (2.26 ± 0.07 [MDA] nmol/ml). In DSO, activities of hepatic antioxidant enzymes (SOD, CAT, and GPx) increased while in DCON these activities decreased significantly (p < 0.05) across time period. Biomarkers of liver, cardiac and renal functions improved significantly in
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DSO as compared to DCON. At 90th day; cholesterol, triglyceride, VLDL, and LDL were significantly lower (p < 0.05) and HDL was significantly higher than DCON. There were no significant differences between the DSO or DCON groups in electrolyte balance, minerals, and hematological values.
Conclusion:
It was concluded that consumption of white sesame seed oil significantly improved blood glucose regulation, reduced oxidative stress, improved antioxidant activity and biomarkers hepatic, cardiac and liver enzymes in male sprague dawley rats and type 2 diabetic patients. Availability: Items available for loan: UVAS Library [Call number: 2950-T] (1).
