1. INTRODUCTION
Microalgal biodiesel promises to be a zero CO2-emitting
and renewable energy source. The biodiesel production from microalgae
includes various steps beginning from cultivation of the desired strain
followed by harvesting, drying of microalgal slurry, oil extraction from
the biomass, and transesterification of lipid to biodiesel (O’Connell,
Savelski, & Slater, 2013). However, the downstream processing of the
harvested microalgal slurry faces several technical challenges for
cost-effective biodiesel production. Drying of microalgal biomass is one
of those important steps. Dewatering of the harvested microalgal slurry
is essential to enhance the viability of biomass for lipid extraction,
and also to reduce the costs of handling, transportation, packaging, and
storage (Bennamoun, Arlabosse, & Léonard, 2013).
Many drying techniques are available nowadays which include advanced
techniques like spray drying, tray drying, oven drying, freeze drying,
vacuum-shelf drying, cross-flow air drying, etc, as well as the simple
and natural solar drying. The suitability of a method depends on many
factors such as the properties and types of the microalgal suspension,
the downstream processes, the end product type and quality, and the
overall cost of production (Chen, Chang, & Lee, 2015). The drying
techniques such as freeze drying (Guldhe, Singh, Rawat, Ramluckan, &
Bux, 2014), thin layer drying (Hosseinizand , Sokhansanj, & Lim, 2018),
microwave drying (Villagracia et al., 2016) etc. are mainly used at a
laboratory-scale, whereas drum drying technique could be useful at
industrial level for drying of large-scale microalgal slurry.
The major advantages of drying the microalgal slurry in a drum dryer are
breaking the cell wall and sterilization of the dried biomass (Show,
Lee, & Mujumdar, 2015). Mahadevaswamy & Venkataraman (1981) reported
that drum drying of Scenedesmus acutus 273-3a biomass for a
detention time of 8-10 sec reduced the microbial load during storage. An
electrically-heated drum dryer was tested for drying ofScenedesmus sp. biomass containing 70% moisture for 10 sec at
120 °C and the energy consumption was calculated to be 52 kWh (Becker &
Venkataraman, 1982). A steam-heated drum drying of Spirulinaslurry was carried out at 120-128 °C for 16 sec for preparing the feed
for aquaculture (Sethi & Naik, 2007). Recently, Wahlen et al. (2017),
used a bench-scale rotary drum dryer for drying the Scenedesmussp. at 50 0C. Thus, for faster drying, a drum dryer
could be a suitable option for large-scale processing of microalgal
slurry.
Machine learning, on the otherhand is a new edge technology used in
every sector of research. It can be divided into two segments, i.e.
supervised learning and unsupervised learning. Supervised learning is
implemented when a structured data set is provided and we know what our
output would look like. Whereas, unsupervised learning allows us to
tackle the problem with little or no knowledge of what our results would
be. It is further divided as shown in the Figure 1.
There are different algorithms to implement the mentioned modules
(Figure 1). Regression can be done using linear regression algorithm and
classification using logistic regression or simple vector machine.
Algorithms like neural networks can be used for both. Unsupervised
learning can be done through K-mean or principal component analysis.
For our defined problem, we have taken the supervised-classification
module into consideration to label the outputs good or poor. Out of
logistic regression and simple vector machine, logistic regression is
employed based on the fact that we have a large number of features
compared to training examples. Here, there was a chance for overfitting
of the decision boundary for which regularization was also executed.
Logistic regression is a predictive algorithm. The present investigation
is thus, aimed at developing a microalgal drying protocol at different
drum surface temperature with varying drum speed using the logistic
regression with regularization to obtain maximum lipid from microalgal
biomass for biodiesel purpose.