In this study, Türkiye's Mediterranean Region Adana Province in artificial neural networks (ANNs) prediction of orange production of greenhouse gases (GHG) by using yield and economic indices model was suitable for analyzing emissions. The energy consumption (EC) of three groups of orange groves consisting of 65 orange producers has been found; Average total energy use and horticultural production yield were found as 31116.50 MJ.ha-1 and 31402.8 kg.ha-1, respectively. In addition, economic indices were found for orange groves. Accordingly, the benefit-cost ratio, productivity, net return, and energy density (ED) are respectively 1.01, 1.01 kg . MJ-1, 286.30 MJ.ha-1, 2.21 MJ.$ -1; In the GHG analysis, the average of the total GHG emissions (G HGE) was found to be approximately 759.58 kgCO2eq.ha-1. Results show that the nitrogen share (41.89%) in GHGE has the highest share for orange production, followed by diesel fuel (14.09%) and electricity (13.77%) consumption, respectively. For the yield and GHGE of orange production, for the 10-6-2 ANN model with the best topology, the determination coefficient (R2) was calculated as 0.974 and 0.986, respectively. At the same time, It was observed that seed and human labor had the highest sensitivity in modeling orange yield and GHGE, with values of 0.026 and 0.058, respectively.