Liu, J.; Fu, Y.; Wang, H.; Peng, Z.; Fan, X.; Weng, Y.; Yao, W. Simulation of Winter Durum Wheat Flour Yield Based on Structural Equation Modeling. Preprints2019, 2019120403. https://doi.org/10.20944/preprints201912.0403.v1
Liu, J., Fu, Y., Wang, H., Peng, Z., Fan, X., Weng, Y., & Yao, W. (2019). Simulation of Winter Durum Wheat Flour Yield Based on Structural Equation Modeling. Preprints. https://doi.org/10.20944/preprints201912.0403.v1
Liu, J., Yun Weng and Wenbin Yao. 2019 "Simulation of Winter Durum Wheat Flour Yield Based on Structural Equation Modeling" Preprints. https://doi.org/10.20944/preprints201912.0403.v1
Flour yield determined the profitability of flour mill, but the intrinsic variability of the grain makes it very complex to analysis and estimate wheat grain flour yield. Simulation for flour yield attributes offer considerable advantages in flour mill, if reliable predictions of flour yield can be provided, because the wheat grain characteristics can be tested before milling. If this is possible, the characteristics thus observed could be quantified more reliably and objectively by Structural Equation Modelling (SEM). SEM was used to look for the most important wheat grain characteristics on flour yield, and then these wheat grain characteristics were used to simulate flour yield. Furthermore, the regressive equation was verified by the field experiment. The coefficient of variation of grain characteristics was low and distributed rather closely. The results of SEM showed that test weight had the most significantly effects on flour yield, followed by the hardness index. Test weight and hardness index could excellently estimate flour yield by multiplicative effect of test weight and hardness index, and which could determine 68% of the variation in flour yield. The simulation result can not only predict flour yield, but also look for the important grain characteristics for the flour yield.
Biology and Life Sciences, Agricultural Science and Agronomy
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