The global increasing food demand can be met by efficient energy utilization in mechanized agricultural productions. In this study, input–output energy flow along with CO2 emissions for different wheat production cases (C-I to C-V) were investigated to identify the one that is most energy-efficient and environment-friendly case. Data and information about input and output sources were collected from farmers through questionnaires and face-to-face interviews. Input and output sources were converted into energy units by energy equivalents while CO2 emissions were calculated by emission equivalents. Data envelopment analysis (DEA) was conducted to compare technical efficiencies of the developed cases for optimization of inputs in inefficient cases. Results revealed that case C-Ⅴ (higher inputs, larger fields, the tendency of higher fertilizer application and tillage operations) has the highest energy inputs and outputs than the rest of the cases. Moreover, it possesses the lowest energy use efficiency and energy productivity. The highest CO2 emissions (1548 kg-CO2/ha) referred to C-Ⅴ while lowest emissions per ton of grain yield were determined in C-Ⅳ (higher electricity water pumping, moderate energy input). The grain yield increases directly with input energy in most of the cases, but it does not guarantee the highest values for energy indices. C-Ⅲ (moderate irrigations, educated farmers, various fertilizer applications) was found as an optimum case because of higher energy indices like energy use efficiency of 4.4 and energy productivity of 153.94 kg/GJ. Optimum input and better management practices may enhance energy proficiency and limit the traditionally uncontrolled CO2 emissions from wheat production. Therefore, the agricultural practices performed in C-Ⅲ are recommended for efficient cultivation of wheat in the studied area.

This study investigates the input–output energy-flow patterns and CO₂ emissions from the wheat–rice crop rotation system. In this regard, an arid region of Punjab, Pakistan was selected as the study area, comprising 4150 km². Farmers were interviewed to collect data and information on input/output sources during the 2020 work season. The total energy from these sources was calculated using appropriate energy equivalents. Three energy indices, including energy use efficiency (η_e), energy productivity (η_p), and net energy (ρ), were defined and calculated to investigate overall energy efficiency. Moreover, the data envelopment analysis (DEA) technique was used to optimize the input energy in wheat and rice production. Finally, CO₂ emissions was calculated using emissions equivalents from peer-reviewed published literature. Results showed that the average total energy consumption in rice production was twice the energy consumed in wheat production. However, the values of η_e, η_p, and ρ were higher in wheat production and calculated as 5.68, 202.3 kg/GJ, and 100.12 GJ/ha, respectively. The DEA showed the highest reduction potential in machinery energy for both crops, calculated as −42.97% in rice production and −17.48% in wheat production. The highest CO₂ emissions were found in rice production and calculated as 1762.5 kg-CO₂/ha. Our conclusion indicates that energy consumption and CO₂ emissions from wheat–rice cropping systems can be minimized using optimized energy inputs.

Tractors are manufactured without air-conditioned cabins in Pakistan. This leads to thermal discomfort for tractor operators working under direct solar exposure. Therefore, this study aimed to design and install an air-conditioned cabin on a tractor. Experiments were undertaken to evaluate the installed cabin performance under two scenarios i.e., conventional (S–I) and enhanced (S-II) air distribution. Computational fluid dynamics (CFD) simulations were used to analyze airflow and calculate thermal comfort indices. The results showed that the air-conditioned cabin attained optimum thermal conditions under the enhanced air distribution scenario (S-II). In this scenario, the inside cabin temperature was an average of 27.4 °C, compared with 30.4 °C in S–I. The relative humidity remained similar in both scenarios, around 53 %. The temperature difference between the cabin and the ambient environment was 11.09 °C in S-II, aligning with the thermal comfort conditions outlined in ISO 14269–2. Furthermore, the CFD simulations showed a predicted mean vote (PMV) index of 0.61 and the percentage people dissatisfied (PPD) index of 26.5 %. These results also confirm the provision of optimum thermal conditions for operator inside the cabin. The simulations also demonstrated good agreement with experimental data, with a small difference in air temperature (2 °C) and relative humidity (5.8 %). In the light of these findings, this study recommends installation of air-conditioned cabin on tractors with enhanced air distribution (S-II) in Pakistan to improve thermal comfort of operators.