Main Article Content
physicochemical properties, PLS regression, sensory acceptability
The quality of composite baked products, which varies due to complex interaction of flour components, needs to be predictable for product optimisation purposes. This paper reports the impact of cassava flour (CF) from five cassava genotypes grown with or without fertiliser application on the quality of composite cassava-wheat bread. Composite breads were made with 10% of wheat flour substituted with CF. Sensory acceptability of the bread samples were determined based on crumb attributes (softness, elasticity, structure and colour), crust appearance, flavour and overall acceptability. Factorial analysis showed cassava genotype and fertiliser application during field cultivation significantly affected the crust appearance and crumb elasticity while their interactions affected all the sensory properties (P<0.01). Crumb softness influenced the overall acceptability of the composite bread most significantly. The partial least square (PLS) regression models for predicting sensory acceptability scores from CF properties explained about 98-100% of the variability. Based on the PLS regression, the study concluded that pH, cyanogenic potential (CNP), and least gelation concentration (LGC) of CF were the most influential quality criteria affecting the sensory acceptability of composite bread. Generally, CF with lower CNP, acidity, amylose, and higher LGC values will give more acceptable freshly baked composite bread.
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