The cassava flours and starches have elicited great use in the food and non-food industry. The diversity in cassava genotypes accounts for differences in end-product properties, and would require characterization of cassava varieties for suitability of culinary and processing. This review showed that screening criteria of cassava cultivars end-user properties include proximate contents, amylose content, structural, swelling, gelatinization and pasting characteristics, including freeze-thaw stability properties of cassava-derived flours and starches. Literature shows that the physiochemical properties vary with genetic factors (i.e. genotype). In this review, the amylose content was found to be the main genetic trait for discriminating the cassava varieties for gelatinization and pasting processes including resistant starches. Moreover, cassava derived raw materials (flours and starches) were found to have various application in baking, edible film, syrup, glucose, alcohol, and soups production.

The environment and food safety are major areas of concern influencing the development of biodegradable packaging for partial replacement of petrochemical-based polymers. This review is aimed at updating the recent advances in biodegradable packaging material and the role of virtual technology and nanotechnology in the tomato supply chain. Some of the common biodegradable materials are gelatin, starch, chitosan, cellulose, and polylactic acid. The tensile strength, tear resistance, permeability, degradability, and solubility are some of the properties defining the selection and utilization of food packaging materials. Biodegradable films can be degraded in soil by microbial enzymatic actions and bioassimilation. Nanoparticles are incorporated into blended films to improve the performance of packaging materials. The prospects of the fourth industrial revolution can be realized with the use of virtual platforms such as sensor systems in authentification and traceability of food and packaging products. There is a research gap on the development of a hybrid sensor system unit that can integrate sampling headspace (SHS), detection unit, and data processing of big data for heterogeneous tomato-derived volatiles. Principal component analysis (PCA), linear discriminant analysis (LDA), and artificial neutral network (ANN) are some of the common mathematical models for data interpretation of sensor systems.

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Fresh cassava roots are transformed into shelf stable raw materials (flours and extracted starches). Chemical composition (moisture, protein, lipid, fibre and amylose content, cyanide contents), dry matter, starch extraction yields, particle size distribution and whiteness index are some of the quality characteristic requirements for selection of varieties in breeding programs, and raw materials for industrial processes. Starch yields ranges 20–35%, and vary with genotype. The crude protein (1–2%) and crude fat (∼1%) are considered minor components of cassava and are indicative of the poor nutritional quality. The cumulative of particles passing finer than sieve (D90) is commonly selected for industrial applications because it yields a large proportion of flour in the range 90–96% finer particle than sieve size. The amylose is the main genetic trait for categorising starches into waxy, semi-waxy, normal/regular and high amylose types when amylose content is 0–2, 3–15, 16–35, and > 35% of the total starch, respectively. Additionally, amylose is basic criteria for blending flours of different botanical sources. Cassava varieties are classified as sweet and bitter varieties when cyanide values are in the range 15–50 and 50–400 ppm, respectively. The a* (redness-greenness) and b* (yellowish) are considered as impurities in white fleshed cassava.