The desires for the establishment of national energy self-reliance and development of alternative fuels to fossil fuels have given birth to bioenergy which is based on the use of renewable agricultural-based (low-cost) materials as feedstock (Haas et al. 2006). Over the last decades, a tremendous amount of studies/researches have been carried out by using low-costs feedstock to produce alternative fuels to petroleum/natural gas whose prices are soaring in the world market coupled with their rapid depletion (Sai et al. 2018). Furthermore, the challenges of global warming and emission of carbon monoxide (CO) and carbon dioxide (CO2) are driving immense growth in the global production of bioenergy (Oyelade et al. 2017). It is important to note that the emissions of CO and CO2 are partly or majorly due to the type of fuel used, quality of fuel used, incomplete combustion of the fuel and the state of the engine (Oniya, 2012). Therefore, biodiesel is an optimistic substitute to fossil diesel fuel due to similarity in their properties (Adewuyi et al., 2014). According to Sai et al. (2018) and Oyelade et al. (2017), biodiesel is non-toxic, eco-friendly, renewable, biodegradable and comparatively a clean fuel used in internal combustion engines.
Biodiesel, a mixture of mono-alkyl esters of both saturated and unsaturated long chain-fatty acids, is produced by transesterification of waste frying oil, oilseeds, algae or animal fats with either ethanol or methanol in the presence of an alkaline catalyst (Kassem et al. 2018). The transesterification process for biodiesel production can be carried out using both homogenous (acid or base) and heterogeneous (acid, base or enzymatic) catalysts. In the last decades, homogenous catalysts especially sodium hydroxide (NaOH) or potassium hydroxide (KOH) have attracted attention in alkaline-based biodiesel production (Phan and Phan, 2008). However, they are costly, and their removal is very difficult because of large amount of waste water produced (Omotoso and Akinsanya, 2015).
Daily increase in human population brings about food-fuel crisis due to the use of edible oils such as canola oil, soyabean oil, cotton oil, palm kernel oil and rapeseed oil for biodiesel production. Adewuyi et al. (2014) reported that over 95% of biodiesel produced globally is from edible oils which consequently leads to food shortage, and as a result, attention has been shifted to the use of non-edible oils for biodiesel production. They stated further that, non-edible oils contain higher free fatty acid (FFA) than edible oils. Therefore, pretreatment is needed so as to lower the FFA content present in non-edible oil to a workable/normal level. The major cost incurred in biodiesel production is feedstock cost which contributes about 70-85% to the total production cost (Oraegbunam et al. 2022; Adewuyi et al. 2014). One of the best way to reduce biodiesel production cost is the use of non-edible oils as feedstock for biodiesel production (Samuel et al. 2021; Adewuyi et al. 2014). Therefore, it has become imperative to search for underutilized non-edible oils as feedstock for biodiesel production.
Among the non-edible oils that seems appealing for biodiesel production is Huran crepitans (also known as sandbox, possum wood or jabillo) seed oil due to its oil content range (36.4-72.2%) and presence of unsaturated fatty acid, linoleic (˃50%) (Oraegbunam et al. 2022). Hura crepitans is a dicotyledon plant which belongs to the family of Euphorbiaceae. It is usually grown in tropical region of North and South America in Amazon Rainforest, and its tree can be as tall as 100ft (about 30m) with its leaves about 2ft (Oniya et al. 2014). It has dark mark, pointed spines and smooth brown bark. Nigerians (most especially rural dwellers) underutilize Hura crepitans plant as it is being planted purposely for shelter. Some researchers (Adewuyi et al. 2014; Oniya et al. 2014) have reported transesterification of Hura crepitans seed oil for biodiesel production while optimal conditions for biodiesel production from Hura crepitans L. seed oil using RSM were determined by Oyelade et al. (2017). However, in an open literature, few researchers have worked on using artificial intelligence (AI) modelling techniques to predict biodiesel yield from Hura crepitans seed oil. Among the artificial intelligence modelling techniques, both artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) which gives hybrid algorithm are preferred in this study due to their ability to handle non-linear and complex stochastic dataset.