The study was carried out with the interest of investigate the beef cattle production system. A baseline survey was conducted on beef cattle production in Bangladesh from two districts of each division. The study was conducted to up-date knowledge on the state of beef fatteners in their own environment. The findings of the baseline survey revealed that major beef fatteners (90%) in Rajshahi division started their cattle fattening using own money, followed by 50%, 40%, 50%, 40%, 50% and 55% in Dhaka, Khulna, Barishal, Chattogram, Sylhet and Rangpur, respectively. The average size (4.93) of livestock holding per farm in Barishal division was considerably higher than that of Dhaka (4.35), Khulna (4.71), Rajshahi (3.83), Chattogram (3.35), Sylhet (4.29) and Rangpur (3.69), respectively. In the study area, the average size (2.14, 2.63 and 2.77) of indigenous cattle per farm in the division of Khulna, Barishal and Rangpur, respectively was considerably lower than those (3.47, 3.27, 3.40 and 3.93) of Dhaka, Rajshahi, Chattogram and Sylhet division, respectively. The average duration (18.6 month) of the fattening program was considerably higher in Dhaka division than that (11.6 month) of Rangpur division. Majority of the farmers followed semi-intensive feeding system. The amount of rice straw/h/d supplied to the beef cattle is remarkably lower (3.57 and 3.72 kg) in Rajshahi and Rangpur division than those (4.38, 4.57, 4.82, 4.32 and 4.32) in the division of Dhaka, Khulna, Barishal, Chattogram and Sylhet, respectively. The amount of concentrates supplied (817.86, 814.71 and 887.50 g) to their beef cattle in Barishal, Sylhet and Rangpur, respectively was considerably higher than those (758.82, 721.43, 772.22 and 739.71 g) of Dhaka, Khulna, Rajshahi and Chattogram division, respectively. In conclusion, there were differences in demographic information, source of capitals for fattening, herd size, duration of fattening, production system and feeding system among the divisions of Bangladesh.

Near Infrared (NIR) Spectroscopy leads a great opportunity to replace the expensive and time-consuming chemical conventional analysis for determination of the quality of meat products. This study was conducted aiming to evaluate the feasibility of NIRS and to establish a rapid assessment method to easily predict the quality of chicken meatball. Samples of meatball (n=123) were collected from Golden Harvest Company of Bangladesh. After collecting sample, spectra were obtained prior to analysis and a total of 369 NIRs were collected and stored in computer by DLP NIR scan Nano Software. To generate reference data 123 meatball samples were analyzed for proximate components, instrumental color CIE L*, a*, b*, and pH of meatball. After that a partial least square regression model for calibration and cross validation were developed for data analysis using The Unscrambler X software. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), coefficient of calibration (R²C) and coefficient of cross validation (R2 CV). Calibration equations were developed from reference data using partial least squares regressions. The standard deviation is 2.41, 0.14, 2.1, 0.41, 1.31, 0.31, 1.26, 0.38, and 0.38 for L*, a*, b*, pH, DM, moisture, CP, EE and ash respectively which indicates that all values are adequate for analytical purposes. Predictive ability of the models was assessed by coefficient of determination of cross-validation (R2 CV) and root mean square error of cross-validation. Predictions were good (R2 CV=0.84) for lightness (L*), (R2 CV=0.72) for redness (a*), (R2 CV=0.77) for yellowness (b*), (R2 CV=0.78) for pH, (R2 CV=0.73) for CP, (R2 CV=0.83) for EE (R2 CV=0.72) for moisture, (R2 CV=0.72) for DM and (R2 CV=0.74) for ash. From the results, it can be concluded that NIRS can be used for the rapid assessment of physico-chemical traits of chicken meatball.

The aim of this study was to test the ability of image technology to predict quality and safety of chicken sausage. Chicken sausages were chosen for image capture. Traits evaluated were color indexes (L*, a*, b*), pH, drip loss, cooking loss, dry matter, moisture, crude protein, ether extract, ash, thiobarbituric acid reactive substances (TBARS), peroxide value (POV), free fatty acid (FFA), total coliform count (TCC), total yeast and mold count (TYMC) and total viable count (TVC). Images were analyzed using the software Matlab (R2015a). Conventional analytical technology i.e., proximate, bio-chemical and microbiological analyses were followed for reference value. Calibration and prediction model were fitted using The Unscrambler X software. Results of this work show that image technology may be a useful tool for prediction of meat quality traits in the laboratory and meat processing industries. The L* value from imaging analysis had medium correlation with a* (r=0.28), b* (r=0.29), pH (r=0.31). A medium correlation found in CP (0.29) with „a*‟ value obtained from imaging analysis. In this experiment we found lower calibration and prediction accuracy in a*, crude protein and ether extract value. From this study it may be recapitulated that image technology has a potentiality to replace analytical technology for meat laboratory and processing units.

The objective of this study was to examine the effect of age on the grading of carcass of indigenous cattle. This experiment was conducted with five (5) treatments (T1 , T2 , T3 , T4 and T5 ) where T1 = 0 Permanent incisor, T2 = 2 Permanent incisors, T3 = 4 Permanent incisors, T4 = 6 Permanent incisors, T5 = 8 Permanent incisors having ten (10) replications. From this study, the mean rib eye muscle area (REA) and the mean rib fat thickness was 43.26, 49.93, 61.38, 70.43, 69.24 cm2 and 0.61, 0.68, 0.66, 1.07 and 0.97 cm with T1 , T2 , T3, T4 and T5 , respectively. The mean retail cut percentage of our indigenous beef cattle was 52.36, 52.27, 53.32, 52.69 and 52.58 with T1 , T2 , T3, T4 and T5 dental age groups, respectively. It also reveals that the overall maturity (on the basis of skeletal maturity and lean maturity) of indigenous beef cattle was A80 , B 90 , C 90, D80 and E 80 withT1 , T2 , T3, T4 and T5 dental age groups, respectively. Indigenous cattle population was fallen in the marbling sub groups of Slight91 , Small90, Small59, Modest57 and Moderate40 with T1 , T2 , T3, T4 and T5 dental age groups, respectively. With the combination of overall maturity and marbling score, indigenous cattle for beef production possess in the quality grade of Select, Choice, Commercial, Utility and Utility with respect to T1 , T2 , T3, T4 and T5 dental age groups. Indigenous cattle did not satisfy the criteria for the highest quality grade e.g., Prime to Standard and the lowest quality grade e.g. Cutter to Canner. In conclusion, dental age maturity had a highly significant (p<0.001) effect on average skeletal maturity, marbling score of the carcass and also had a significant (p<0.01) effect on rib fat thickness as well as on rib eye muscle area (REA) irrespective of all age group of indigenous beef carcass in Bangladesh. This research will play a vital role in the path toward the development of Bangladeshi beef standards and will be helpful to grade indigenous beef cattle at butcher or commercial beef industries level.

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