ABSTRACT
Cowpea is widely grown and consumed in sub-Saharan Africa because of its low cost and high mineral, protein, and other nutritional content. Nonetheless, cooking it takes considerable time, and there have been attempts on techniques for speeding up the cooking process without compromising its nutritious value. Infrared heating has recently been proposed as a viable way of preparing instantized cowpea grains that take a short amount of time to cook while maintaining desired sensory characteristics. Despite this, only a few studies have shown the impact of moisture, temperature, and cooking time on cooking characteristics such as bulk density, water absorption (WABS), and the pectin solubility of infrared heated cowpea precooked using this technology. Artificial neural network was used as a machine learning tool to study the effect of a prediction model on the infrared heating performance and cooking characteristics of precooked cowpea seeds. With R values of 0.987, 0.991, and 0.938 for the bulk density, WABS, and pectin solubility, respectively, the prediction model created in this study utilizing an artificial neural network (a type of machine learning) outperformed the traditional linear, 2-factor interaction, and quadratic models.
Subject(s)
Vigna , Cooking , Hot Temperature , Machine Learning , Pectins , WaterABSTRACT
Dika kernels are known for their mucilaginous consistency, but limited work has been reported about it. This study investigated the flowing characteristics (share stress and viscosity) of the dika kernel and its soup; and this was assessed at specific temperatures (30, 50, 70 and 90) °C by the use of a viscometer. All samples behaved as non-Newtonian fluids. The bulk, tapped and loose densities of the powdered samples were obtained to evaluate the Carr index, Hausner ratio and porosity. The viscosity and shear stress of the reconstituted powder and soup samples as a function of the shear rate were investigated (30-90 °C). Dika kernel at its natural moisture content has excellent flowing property (1.118 Hausner ratio, 10.566 Carr index and 20.300% porosity), but increase in moisture content decreased this ability. The viscosity of the soup (165.789-14,546.341 mPa s) was higher than the reconstituted dika (69.831-206.240 mPa s) at all temperature studied. Shear stress was temperature-dependent, and Bingham and Power-law models gave the best predictions of flow.
ABSTRACT
The main objective of the research is to develop a recipe of instant dry soup mix for easy preparation of ogbono soup. Instant ogbono mix powder was processed using common locally ingredients. Dika kernel powder, dried ugwu leaf, crayfish, stock fish, and a mixture of locust bean, onion, seasoning and Cameroon powder were formulated at different ratios to find the best acceptable ogbono mix powder. The samples were subjected to proximate, functional, vitamin, mineral, and sensory analyses. The formulated sample D with the highest ratio of crayfish and stock fish had the highest value of protein and carbohydrate (24.13 and 35.61%, respectively). The control sample (100% dika kernel powder) was low in moisture content (6.20%) but high in crude fat, other samples followed in this order (control > A > B > C > D) for crude fat. Ash, crude fiber, and carbohydrate showed a significant difference (P < 0.05) in all the samples. The functional properties of the sample showed a significant difference (P < 0.05) in all the samples with the control having the highest value for the water absorption, swelling capacity, and bulk density which may be due to the high crude fiber and low moisture content recorded for the control sample in the proximate analysis. The mineral content of all the samples were higher than the control with phosphorous having the highest value and iron the least value. Vitamin C was the main dominating vitamin in the sample followed by vitamin B2, vitamin A, and vitamin B3. The sensory evaluation revealed that 100% dika kernel powder gave a good attribute of the soup but with less nutritional composition, while some formulated samples showed a similar attribute with higher nutritional value. Sample A with the highest overall acceptability had the best attribute of ogbono soup. Instant ogbono mix powder has higher nutritional value and easy to cook.
