Modeling of Ethiopian Beef Meat Marbling Score Using Image Processing for Rapid Meat Grading.

Meat characterized by a high marbling value is typically anticipated to display enhanced sensory attributes. This study aimed to predict the marbling scores of rib-eye, steaks sourced from the Longissimus dorsi muscle of different cattle types, namely Boran, Senga, and Sheko, by employing digital image processing and machine-learning algorithms. Marbling was analyzed using digital image processing coupled with an extreme gradient boosting (GBoost) machine learning algorithm. Meat texture was assessed using a universal texture analyzer. Sensory characteristics of beef were evaluated through quantitative descriptive analysis with a trained panel of twenty. Using selected image features from digital image processing, the marbling score was predicted with R2 (prediction) = 0.83. Boran cattle had the highest fat content in sirloin and chuck cuts (12.68% and 12.40%, respectively), followed by Senga (11.59% and 11.56%) and Sheko (11.40% and 11.17%). Tenderness scores for sirloin and chuck cuts differed among the three breeds: Boran (7.06 ± 2.75 and 3.81 ± 2.24, respectively), Senga (5.54 ± 1.90 and 5.25 ± 2.47), and Sheko (5.43 ± 2.76 and 6.33 ± 2.28 Nmm). Sheko and Senga had similar sensory attributes. Marbling scores were higher in Boran (4.28 ± 1.43 and 3.68 ± 1.21) and Senga (2.88 ± 0.69 and 2.83 ± 0.98) compared to Sheko (2.73 ± 1.28 and 2.90 ± 1.52). The study achieved a remarkable milestone in developing a digital tool for predicting marbling scores of Ethiopian beef breeds. Furthermore, the relationship between quality attributes and beef marbling score has been verified. After further validation, the output of this research can be utilized in the meat industry and quality control authorities.

Design, construction, and testing of passive type solar tunnel for maize grain disinfestations.

In this study, a solar tunnel of passive-type designed, constructed and tested for storage insect pest disinfestation. The designed solar tunnel was 1.9 m wide and 3 m long with the maize grain holding capacity of 150 kg, 300 kg, and 450 kg with 5 cm, 10 cm, and 15 cm layer thickness respectively. To evaluate the performance of the solar tunnel, maize grain infested with storage pests was kept in the solar tunnel with 5 cm, 10 cm, and 15 cm layer thickness for 4 consecutive days. During the study, the temperature and relative humidity profile of the air in the tunnel and the temperature in maize grain was recorded. Germination percentage and number of live insects were evaluated after each day of disinfestations. The highest temperature recorded in the solar tunnel was in the range of 64.6-67.6 °C during the study period. Complete disinfestations of the grain were obtained on the first day for 5 cm layer thickness and the second day for 10 and 15 cm layer thickness. The higher germination percentage was recorded for 15 cm layer thickness in all experimental days. Of all the treatments the combination of the layer thickness of 15 cm and two day disinfestations time were found to be the best combination for using the tunnel for maize grain disinfestations in terms of achieving complete disinfestations; maintaining germination capacity of the grain and time required to disinfect a large amount of grain.

Melissopalynology and antioxidant properties used to differentiate Schefflera abyssinica and polyfloral honey.

Honey can be categorized as monofloral and polyfloral honey. There is a strong interest in science and commerce, to further differentiate honey. In the present study, Schefflera abyssinica and polyfloral honey from Sheka Forest, Ethiopia was investigated. Botanical origin was determined based on Melissopalynology. Refractive index, moisture, sugars, ash, pH, free acidity, hydroxymethylfurfural, optical density, diastase activity, protein, and color were determined based on the standard method of the international honey commission (IHC) and AOAC. Antioxidant activity and Antioxidant content were determined using UV- visible spectroscopy. The level of pollen dominancy for monofloral honey (Schefflera abyssinica) ranged from 76.2 to 85.8%. The polyfloral honey stuffed with a variety of pollen grain ranged from 2.2% (Coffea arabica) to 23.2% (Schefflera abyssinica). Schefflera abyssinica honey contained more total phenolic compounds (75.08 ± 2.40 mg GAE/100g), and total flavonoids (42.03 ± 1.49 mg QE/100 g), as well as had stronger DPPH (44.43 ± 0.97%) and hydrogen peroxide (78.00 ± 4.82%) scavenging activity. The principal component analysis revealed that Schefflera abyssinica honey associated with the antioxidant properties of total phenolic, total flavonoids, DPPH, and H2O2., which revealed that floral honey sources can essentially differentiated by antioxidant patterns. The higher electrical conductivity (0.42 ± 0.02 mS/cm), ash (0.41 ± 0.05 g/100g), pH (4.01 ± 0.08), optical density (0.26 ± 0.03) and diastase activity (5.21 ± 0.17 Schade units) were recorded in polyfloral honey. Schefflera abyssinica and polyfloral honey satisfy the requirement of national and international standards. The pollen analysis in combination with antioxidant properties distinguishes Schefflera abyssinica from polyfloral honeys.