Effect of corn grain variety on the bioethanol production efficiency

Gumienna, Małgorzata; Szwengiel, Artur; Lasik, M.; Szambelan, Katarzyna; Majchrzycki, Dariusz; Adamczyk, J.; Nowak, J.; Czarnecki, Z.

doi:10.1016/j.fuel.2015.10.033

Cited by 32 publications

(14 citation statements)

References 23 publications

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“…Determining the most appropriate variety and harvest time of cassava is also essential for the ethanol production industry. There have been many reports about the effect of the feedstock variety and harvest time on the yield and efficiency of ethanol production, such as sugarcane , corn , sorghum , and sweet potato . However, our understanding of the effect of the cassava variety and harvest time on the properties that are relevant to their industrial applications is still limited.…”

Section: Introductionmentioning

confidence: 99%

Rheological characteristics and genotype correlation of cassava root for very high gravity ethanol production: The influence of cassava varieties and harvest times

Sakdaronnarong

Sraphet

Srisawad

et al. 2019

Biotech and App Biochem

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In very high gravity (VHG) ethanol fermentation, the rheological properties of native cassava significantly influence heat and mass transfer, mixing energy, and, thus, the yield of all steps. This study investigated the effect of cassava varieties and their harvest times on starch liquefaction, saccharification, and fermentation. The genotype correlation of the starch properties was revealed for the most suitable cassava varieties. First, the starch content, amylose content, total reducing sugar from liquefaction and saccharification, pasting properties, and ethanol yields of six cassava varieties (Huay Bong 60, Hanatee, Kasetsart 50, Pirun 1, Pirun 2, and Rayong 11) at 6‐, 9‐, 12‐, and 15‐month harvest times were evaluated. The amylose content increased significantly from the 6th to the 12th month but slightly decreased at the 15th month. It was observed that the starch content contributed to a more substantial influence on the change in peak viscosity than on the amylose content. Ethanol fermentation using Saccharomyces cerevisiae TISTR5606 showed that the Rayong 11 variety at the 15‐month harvest time provided the highest ethanol concentration of 104.7 ± 4.1 g L−1 and an ethanol yield of 0.4 ± 0.1 g ethanol g−1 reducing sugar, which corresponded to 74.5% of the theoretical yield.

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Section: Introductionmentioning

confidence: 99%

Rheological characteristics and genotype correlation of cassava root for very high gravity ethanol production: The influence of cassava varieties and harvest times

Sakdaronnarong

Sraphet

Srisawad

et al. 2019

Biotech and App Biochem

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“…In addition, it was slightly higher when compared with the results of a study by Sivamani et al [30], where they used cassava peel and ethanol yield was 83% of the theoretical ethanol yield. The same is true when the result is compared with the study by Gumienna et al [22] where the outcome of each was 81.33%. 44 U/mL and 74.87 spm, respectively.…”

Section: Ethanol Production From Manihot Glazioviimentioning

confidence: 61%

“…The results of reducing in this study are similar to a study by Naguleswaran et al [25], with corn and triticale (80.8%-84.5%) as a feedstock, but slightly lower than that of wheat (90.8%-95.1%). Gumienna et al [22] also conduct the enzyme hydrolysis for corn starch and obtained reducing sugar of 11.7 g/L (69.40%). Moreover, Tasić et al [24] performed acid hydrolysis on potato and produced a 114 g/L (64%) concentration of reducing sugar.…”

Section: Relationship Between the Independent Variables Of The Starchmentioning

confidence: 99%

Optimization of Reducing Sugar Production from Manihot glaziovii Starch Using Response Surface Methodology

et al. 2017

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Abstract:Bioethanol is known as a viable alternative fuel to solve both energy and environmental crises. This study used response surface methodology based on the Box-Behnken experimental design to obtain the optimum conditions for and quality of bioethanol production. Enzymatic hydrolysis optimization was performed with selected hydrolysis parameters, including substrate loading, stroke speed, α-amylase concentration and amyloglucosidase concentration. From the experiment, the resulting optimum conditions are 23.88% (w/v) substrate loading, 109.43 U/g α-amylase concentration, 65.44 U/mL amyloglucosidase concentration and 74.87 rpm stroke speed, which yielded 196.23 g/L reducing sugar. The fermentation process was also carried out, with a production value of 0.45 g ethanol/g reducing sugar, which is equivalent to 88.61% of ethanol yield after fermentation by using Saccharomyces cerevisiae (S. cerevisiae). The physical and chemical properties of the produced ethanol are within the specifications of the ASTM D4806 standard. The good quality of ethanol produced from this study indicates that Manihot glaziovii (M. glaziovii) has great potential as bioethanol feedstock.

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“…In order to find the 'best' number of clusters, v-fold cross validation was performed (Janisová et al 2014;Flanagan & Cerrato 2015;Gumienna et al 2016). The benefit of v-fold cross validation is that the number of clusters will be determined from the data and must not be known a priori which means prior knowledge about the number of clusters is not essential.…”

Section: Discussionmentioning

confidence: 99%

Analysing Data of the Integrated Administration and Control System (IACS) to Detect Patterns of Agricultural Land-Use Change at Municipality Level

Lüker-Jans

Simmering²,

Otte

2016

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European landscapes have featured considerable changes towards intensification and marginalisation. These major trends are expected to continue in the future. Besides, the cultivation of bioenergy crops has become an important factor in agricultural land use. A thorough understanding of land-use processes for management purposes is needed. In this study, the spatial and temporal pattern of agricultural land use and land-use change was classified at the scale of municipalities from 2005 to 2010. The study region was the German federal state Hesse. By using data of the Integrated Administration and Control System (IACS) of the European Union and with the help of k-means cluster analysis, five types of agricultural land-use patterns and dynamics (TLPDs) were detected. These TLPDs represent different sub-regions. Sub-regions with favourable physical conditions for cultivation are dominated by arable land. A progressive land-use change occurred by conversion of grassland to arable land. In sub-regions, where physical conditions are rather unfavourable, especially in mountainous areas, grassland is the predominant land use. But on the remaining arable land, there is a slight change in favour of maize. The knowledge of sub-regions with spatially and temporally different agricultural land use could be utilised to develop land management instruments like site-specific agri-environmental schemes.

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Effect of corn grain variety on the bioethanol production efficiency

Cited by 32 publications

References 23 publications

Rheological characteristics and genotype correlation of cassava root for very high gravity ethanol production: The influence of cassava varieties and harvest times

Rheological characteristics and genotype correlation of cassava root for very high gravity ethanol production: The influence of cassava varieties and harvest times

Optimization of Reducing Sugar Production from Manihot glaziovii Starch Using Response Surface Methodology

Analysing Data of the Integrated Administration and Control System (IACS) to Detect Patterns of Agricultural Land-Use Change at Municipality Level

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