Application of modeling techniques for energy analysis of fruit production systems

Hossein Jargan (), Abbas Rohani () and Armaghan Kosari-Moghaddam ()
Additional contact information
Hossein Jargan: University of Mohaghegh Ardabili
Abbas Rohani: Ferdowsi University of Mashhad
Armaghan Kosari-Moghaddam: Ferdowsi University of Mashhad

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2022, vol. 24, issue 2, No 47, 2616-2639

Abstract: Abstract Moving toward environmental sustainability in the fruit production systems needs accurate monitoring of the systems in terms of energy flow. In this regard, using regression models (i.e., Cobb–Douglas), Multiple Linear Regression (MLR)), and Artificial Neural Network (ANN), this paper examined the energy flow in the pomegranate orchards in Iran. Unlike other similar studies, in the current research, the cross-validation technique was employed to evaluate how choosing datasets would modify the behavior of the models. The results demonstrated that the total energy consumption and energy efficiency of the pomegranate production were 13,634.13 MJ ha−1 and 1.01, respectively. The results also indicated that among investigated MLR models, the pure-quadratic model had the best performance. Besides, among 13 evaluated ANN-training algorithms, the Bayesian regulation algorithm had the highest accuracy in prediction and the best model consisted of one hidden layer with three neurons (5–3–1 topology) with logarithm sigmoid activation function. The results highlighted that the ANN model (R2 = 0.91) outweighs the MLR model (R2 = 0.86). The results also approved that the proposed ANN model was capable to use different datasets with high generalizability. The results of sensitivity analysis claimed the significant role of water and fuel consumption and consequently, the importance of establishing management policies to optimizing the use of these inputs in the pomegranate orchards.

Keywords: Artificial neural network; Energy; Fruit; K-fold cross-validation; Model (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10668-021-01548-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:endesu:v:24:y:2022:i:2:d:10.1007_s10668-021-01548-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/10668

DOI: 10.1007/s10668-021-01548-0

Access Statistics for this article

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development is currently edited by Luc Hens

More articles in Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().