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Beigi M, Torki M, Safarinia H, Kaveh M, Szymanek M, Khalife E, Dziwulska-hunek A. Prediction of Almond Nut Yield and Its Greenhouse Gases Emission Using Different Methodologies. Applied Sciences 2022; 12:2036. [DOI: 10.3390/app12042036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The evaluation of a production system to analyze greenhouse gases is one of the most interesting challenges for researchers. The aim of the present study is to model almond nut production based on inputs by employing artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) procedures. To predict the almond nut yield with respect to the energy inputs, several ANN and ANFIS models were developed, evaluated, and compared. Among the several developed ANNs, a network with an architecture of 8-12-1 and a log-sigmoid, and a linear transfer function in the hidden and output layers, respectively, is found to be the best model. In general, both approaches had a good capability for predicting the nut yield. The comparison results revealed that the ANN procedure could predict the nut yield more precisely than the ANFIS models. Furthermore, greenhouse gas (GHG) emissions in almond orchards are determined where the total GHG emission is estimated to be about 2348.85 kg CO2eq ha−1. Among the inputs, electricity had the largest contribution to GHG emissions, with a share of 72.32%.
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Zampiga M, Calini F, Sirri F. Importance of feed efficiency for sustainable intensification of chicken meat production: implications and role for amino acids, feed enzymes and organic trace minerals. WORLD POULTRY SCI J 2021. [DOI: 10.1080/00439339.2021.1959277] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- M. Zampiga
- Department of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - F. Calini
- Advisor to the Feed & Animal Industries, Ravenna, Italy
| | - F. Sirri
- Department of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy
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