Wheat with its advantages of high yield stability, well-mastered crop management and the possibility of long-term storage is suitable for ethanol production. Ethanol production has to be cost-effective and, therefore, wheat used in production should have a high potential for ethanol production. Previous works showed that low-nitrogen grain content is important for the relative ethanol yield and the agronomic yield for the absolute ethanol yield per area is important. In this work, importance of grain nitrogen and starch content for ethanol conversion efficiency was verified. Furthermore, environmental effects in relation to the ethanol conversion efficiency and ethanol yield in conditions of Central Europe were studied. With regard to the environmental factors, the annual rainfall sum was found to be the most important factor for ethanol conversion efficiency, while the grain yield was found to be the most important factor for the ethanol yield. On the basis of these findings it can be considered that wheat varieties possessing high yields of low protein grain planted in areas with higher rainfall amount would be ideal for the production of ethanol.
Authors:A. Etminan, A. Pour-Aboughadareh, R. Mohammadi, L. Shooshtari, M. Yousefiazarkhanian, and H. Moradkhani
In the present study, efficiency of the artificial neural network (ANN) method to identify the best drought tolerance indices was investigated. For this purpose, 25 durum genotypes were evaluated under rainfed and supplemental irrigation environments during two consecutive cropping seasons (2011–2013). The results of combined analysis of variance (ANOVA) revealed that year, environment, genotype and their interaction effects were significant for grain yield. Mean grain yield of the genotypes ranged from 184.93 g plot–1 under rainfed environment to 659.32 g plot–1 under irrigated environment. Based on the ANN results, yield stability index (YSI), harmonic mean (HM) and stress susceptible index (SSI) were identified as the best indices to predict drought-tolerant genotypes. However, mean productivity (MP) followed by geometric mean productivity (GMP) and HM were found to be accurate indices for screening drought tolerant genotypes. In general, our results indicated that genotypes G9, G12, G21, G23 and G24 were identified as more desirable genotypes for cultivation in drought-prone environments. Importantly, these results could provide an evidence that ANN method can play an important role in the selection of drought tolerant genotypes and also could be useful in other biological contexts.