Modeling and optimizing the exergy flow of tropical crop production in Iran

Agriculture is one of the major energy consumers in food supply chain. In this regard, exergy analysis can be used as a decision support tool toward evaluation of the energy flow of the production system, identification of energy hotspots, and development of new energy management scenarios. This study applied a hybrid exergy analysis + artificial neural networks + genetic algorithm to optimize five tropical crop production systems i.e., banana, mango, jujube, guava, and sapodilla. Cumulative Degree of Perfection and Renewability Index were used for evaluating the exergy flows of the fruit production systems. The results revealed that both indices were higher for banana and equaled 1.21 and 0.68, respectively, implying that the studied banana production system had lower exergy loss and thus it was more exergy-efficient. The optimization results showed that both investigated indices noticeably enhanced in the optimized mode. More specifically, Cumulative Degree of Perfection was increased in banana, mango, jujube, guava, and sapodilla production systems to 2.72, 0.42, 0.56, 0.41, 0.53, respectively. In conclusion, the results approved that managing the inputs consumption would lead to reducing the consumption of non-renewable and chemical inputs in line with improving the energy and exergy use efficiency in tropical crops production systems.

Automated summary

This study applied a hybrid method to optimize five tropical crop production systems and found that managing input consumption can improve the exergy efficiency of the systems.