Most seed oils are edible while some are used generally as raw material for soap production, chocolate, margarine, and recently in biodiesel formulations as potential candidates capable of replacing fossil fuels which are costly and destructive to the environment. Oilseeds are a green and major reservoir which when properly exploited can be used sustainably for the production of chemicals at both the laboratory and industrial scales. Oil extraction is one of the most critical steps in seed oil processing because it determines the quality and quantity of oil extracted. Optimization of the extraction conditions for each extraction method enhances yield and quality meanwhile a carefully chosen optimization process equally has the potential of saving time and heat requirements with an associated consequence on cost reduction of the entire process. In this review, the techniques used to optimize oil extraction from plant materials which can be consulted by stakeholders in the field are brought to focus and the merits and demerits of these methods highlighted. Additionally, different types of optimization techniques used for various processes including modeling and the software employed in the optimization processes are discussed. Finally, the quality of the oil as affected by the methods of extraction and the optimization process used are also presented.

The effect of particle size and drying temperature on drying rate and oil extracted yields of Buccholzia coriacea (MVAN) and Butyrospermum parkii (ENGL) was investigated. Air drying studies carried out on B. coriacea and B. parkii, tropical food sources subject to high post-harvest losses, have resulted in the establishment of a significant difference between oil yields extracted from samples of various particle size pretreatments (paste, 4 mm, 8 mm and whole kernels) dried at 45 and 60°C with the highest oil yield given by the 4 mm thick slices dried at 45°C. The influence of temperature and particle thickness on the drying rate has been evaluated. The drying constants were found to depend on both temperature and particle thickness. Analysis of the oil extracted from the 4 mm thick slices dried at 45°C showed that apart from the acid value (52.4%), the saponification (181.2 mg g )1 KOH), peroxide (8.6 meq kg )1 ) and the unsaponifiable (7.43%) matter values of the extracted shea butter remain within the limits cited in the literature while a close analysis of the cake suggests that it could be a good mineral source.

Considering drying as a key farm-based, quality determining unit operation in the cocoa processing chain, this paper reviews recent studies in the drying methods and quality parameters of cocoa beans. Open sun, solar, oven, microwave, and freeze drying methods have been investigated at various levels in the drying of cocoa beans with objectives to improve the drying properties and final quality of cocoa beans. While an open sun dryer employs natural passive mechanisms, the solar drying methods can employ a combination of passive and active mechanisms. The oven, microwave, and freeze drying methods are fully active requiring electrical energy inputs. To improve drying rates in the open sun method, dryer materials and location of drying trays are the parameters optimized since the drying temperature depends on solar intensity. For solar dryers, materials, angles of elevation, heaters, and fans are manipulated to optimize energy absorption and drying parameters. For the oven and microwave methods, drying air properties are directly controlled by electronic systems. Moisture content, mouldiness, bean colour, pH, titratable acidity, fat content, and acetic acid concentration are the most widely evaluated bean quality parameters.

The response surface method employing Doehlert's experimental design was used to optimise the cooking of sheanuts to strike a balance between the advantages and disadvantages usually offered by the process. The independent factors investigated were cooking time, cooking temperature and nut size while the responses were moisture content of the kernels, amount of oil extracted, acid and peroxide values of the butter. Second order polynomial models were generated to describe the process for the responses studied. The validity of the models was tested and it was found that they could be used to explain respectively 83%, 99% and 95% of the variation of moisture content, acid value and peroxide value. The cooking process greatly reduced the free fatty acid values of the butter (<6%) but increased its peroxide value (up to 20 meq/kg). The cooking process was significantly influenced by all three independent factors investigated. The optimum conditions defined for the cooking process were: cooking time (95-120 min), cooking temperature (75-90°C) and nut size (40-45 mm). These optimal conditions gave the following responses: moisture content 51.97% w.b., amount of oil extracted 47.47%, acid value (as FFA) 2.76% and peroxide value 3.87 meq/kg. The parameters of the cooking conditions could be set to appropriate values to give butter of either category 1, 2 or 3 in terms of acid and peroxide values.number of experiments r 2 regression coefficient RSEE relative standard error of the estimate Δu increment V titre volume (ml) V 0 volume of blank (ml) x i coded value of variable i x 1 coded value of cooking time (dimensionless) x 2 coded value of cooking temperature (dimensionless) x 3 coded value of nut size (dimensionless) X i real value of variable i X 0 i central value of the real variable i X 1 real value of cooking time (min) X 2 real value of cooking temperature (°C) X 3 real value of nut size (mm) Y 1 moisture content (% w.b.)