Water and radiation use efficiency of sugarcane for bioethanol production in South Africa, benchmarked against other selected crops

Abstract

There are indications that high-fibre sugarcane genotypes may produce more biomass and use resources more efficiently than conventional sugarcane cultivars.The objective of this research was to gather quantitative information on resource use for selected conventional and high-fibre sugarcane genotypes and benchmark it against other bioethanol crops. Although conventional sugarcane initially grew slower than sorghum and Napier grass, it produced very high biomass (about 70 t ha -1 ) and theoretical ethanol (first-and second-generation) yields (about 27 kL ha ), outperforming all other crops except sorghum. The contribution of cellulosic ethanol to total ethanol yield varied hugely, from 89% for the high-fibre sugarcane hybrid to about 48% for conventional sugarcane, to as low as 14% for sugar beet. The highfibre sugarcane hybrid grew faster initially and produced more biomass at eight months (56 t ha -1 vs. 45 t ha -1 ) than the conventional types, but then flowered, reducing its growth rates markedly thereafter. It was also less sensitive to mild drought conditions. Results suggest that cellulosic ethanol production could be a feasible option that could be incorporated into conventional or biomass sugarcane production systems.Keywords: bioethanol crops, biomass, high-fibre sugarcane, stalk fibre composition, theoretical ethanol yield IntroductionThere is increasing interest in renewable energy, including biofuel from crops.Bioethanol can be produced from the fermentation of soluble sugars in the storage organs of feedstock crops, while 2 nd generation lignocellulose technology enables the production of ethanol from cell-wall sugars extracted from plant fibre (Ragauskas et al. 2006). This will greatly enhance the potential ethanol output from feedstock crops and address concerns regarding ethanol production from food crops in high potential production areas.Potential bioethanol crops include maize, switchgrass, Miscanthus, sugarcane, sugar beet, sorghum and poplar. Compared to other crops sugarcane has abundant potential for producing high biomass yield (Alexander, 1985) and consequently high bioethanol yields from sugars in the juice (Renouf et al. 2008) and form leaf and stalk fibre (Waclawovsky et al. 2010, de Souza et al. 2013. Energy cane that produce high biomass rather than high sucrose yield and use natural resources more efficiently, are currently in development (Tew and Cobill 2008). These genotypes 2 could possibly be used for biomass production in marginal production areas where resource levels are low, such as low rainfall areas or areas with poor soils.Very little quantitative information on radiation and water use or crop productivity is available for high-fibre sugarcane types in South Africa. Waclawovsky et al. (2006) quote commercial maximum yields of 29 t ha -1 of dry biomass and puts forward a theoretical maximum of 177 t ha -1. Alexander (1985) hypothesizes that sugarcane yields can be increased two fold by using high-fibre cane and managing water and nitrogen to maximize biomass growth an...

Estimating the light conversion efficiency by sugarcane: the segmented approach

“…The reduced growth phenomena (RGP), a reason for the curve plateau (Figure 1c), is a decrease in biomass accumulation at the end of the crop cycle likely induced by lodging, low specific leaf nitrogen, feedback inhibition of photosynthesis by high sugar content, high respiratory demand (Park et al 2005, van Heerden et al 2010 or even flowering (Olivier et al 2016). We were able to notice RGP with sampling interval varying between 30 and 60 days, with a decrease in ε cs after 270 days (Figure 2 and Figure S2).…”

“…While measuring light interception is simple, non-destructive and can be even automated (Robertson et al 1996, the quantifi cation of biomass is a laborious process, which limits the frequency of data sampling along the crop cycle and then the estimation of ε c . Usually, a single ε c value is estimated for the whole growing season (Robertson et al 1996, Muchow et al 1997, Singels & Smit 2002, Olivier et al 2016). However, any variation of ε c along the crop cycle remains hidden with such oversimplification and we are not able to understand how environmental and physiol ogical conditions affect ε c or even if crops reach the theoretical ε c values during the crop season.…”

Fermentative profile and nutritional composition of sugarcane silages associated with different levels of moringa hay

“…(2020). Samples collected at the opening of the silo were used to determine pH (AOAC, 2016), organic acids including acetic acid, propionic acid, butyric acid, lactic acid (Kung Jr & Ranjit, 2001), and ethanol (Oliver et al., 2016).…”

Potential for Sugarcane Production Under Current and Future Climates in South Africa: Sugar and Ethanol Yields, and Crop Water Use

“…Trait parameters for these were derived using two datasets from seven experiments conducted in four locations in South Africa (Singels et al 2016). The first data set was used for determining cultivar trait parameters for the model for three clones (conventional cultivars N19 and N31, and a high fibre clone 04G0073) grown under different water regimes in Mount Edgecombe (experiment described by Eksteen et al 2014 andNgxaliwe, 2014) and Komatipoort (experiment described by Olivier et al 2016).…”