1986
DOI: 10.1080/10408398609527444
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Optimal energy management in grain drying

Abstract: Grain drying is very specific to the geographic location, kind of drying system, and the type of grain. Under a given set of conditions, the optimal system can be selected based on careful evaluation. However, a good choice of drying systems, procedures, and management practices can be made from the information already available. The review of several grain-drying procedures has provided some insight in making a quick evaluation of the process and arriving at the most suitable system for a particular applicati… Show more

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Cited by 27 publications
(17 citation statements)
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“…This suggests that allowing water to diffuse through the cranberries during power-off time is a practical strategy to maximize drying efficiency (Gunasekaran 1990). efficiencies reported in this study were higher than those for conventional drying of food grains, which ranged from 4.5-8.0 MJ/kg (Gunasekaran 1986). It may be possible to further increase the drying efficiency of PD by optimizing power-on time and power-off time combinations.…”
Section: Energy Utilization Coefficient and Drying Efficiency Frommentioning
confidence: 60%
“…This suggests that allowing water to diffuse through the cranberries during power-off time is a practical strategy to maximize drying efficiency (Gunasekaran 1990). efficiencies reported in this study were higher than those for conventional drying of food grains, which ranged from 4.5-8.0 MJ/kg (Gunasekaran 1986). It may be possible to further increase the drying efficiency of PD by optimizing power-on time and power-off time combinations.…”
Section: Energy Utilization Coefficient and Drying Efficiency Frommentioning
confidence: 60%
“…However, Gunasekaran and Thompson (1986) stated that drying of crops actually requires from 3000 to 8000 kJ/kg water. Therefore, the efficiency of a drying process depends on how drying is performed.…”
Section: Introductionmentioning
confidence: 98%
“…[14,15] Despite its benefits, the artificial drying process is energy intensive and costly, and this drawback continues to motivate dryer design, taking precedence over capacity and reliability. [16][17][18] The high capital and operational costs associated with the present drying technologies make them unavailable to small-scale farmers, who account for up to 70% of the total maize production in Kenya, [19] and if broad adoptability of cobed maize drying is to be achieved, this raises the stakes for innovation. Innovation is enhanced by the quality of information made available through research; hence the need for smart experimentation (innovate to innovate).…”
Section: An Introduction To Computational Sensor Psychrometrics For Tmentioning
confidence: 99%