Energy Analysis on Wheat Yield of Mongolian Agriculture
Abstract
1. Introduction
2. Materials and Methods
2.1. Data Sources
2.2. Calculation Method
3. Results and Discussion
3.1. Energy Use for Wheat Production
3.2. The Econometric Results for Energy Use
4. Conclusions
- (1)
- Utilize innovative and technological machinery and equipment (which may have a higher price than old machinery, but will reduce diesel fuel use and save working hours).
- (2)
- Make use of newly tested seeds (disease resistance and drought tolerance have to be high).
- (3)
- Expand the use of green manures (leverage the high number of livestock).
- (4)
- Reduce the need for chemical fertilizer. It is feasible to boost agricultural output by increasing renewable energy inputs; authorities should focus on ensuring environmentally sustainable energy usage in Mongolian agriculture.
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Inputs (Per Hectare) | Unit | Energy Equivalents (MJ) | Reference |
---|---|---|---|
Human labor | h | 1.96 | [1,2,3] |
Machinery | kg | 64.8 | [4] |
Diesel fuel | L | 47.8 | [4,5] |
Pesticide | kg | 101.2 | [4,6] |
Nitrogen (N) | kg | 66.14 | [4,6,7] |
Phosphate (P2O5) | kg | 12.44 | [4,6,7] |
Potassium (K2O) | kg | 11.15 | [7,9] |
Water for irrigation | m3 | 1.02 | [10] |
Electricity | kW·h−1 | 11.93 | [11] |
Seed | kg | 20.10 | [2] |
Output | |||
Wheat yield | kg | 14.48 | [3] |
Years | Human Labor (MJ ha−1) | Machinery Energy (MJ ha−1) | Electricity Energy (MJ ha−1) | Diesel Fuel Energy (MJ ha−1) | Nitrogen Fertilizer Energy (MJ ha−1) | Phosphate Fertilizer Energy (MJ ha−1) | Potassium Fertilizer Energy (MJ ha−1) | Pesticide Energy (MJ ha−1) | Water for Irrigation Energy (MJ ha−1) | Seed Energy (MJ ha−1) | Total Input Energy (MJ ha−1) | Output Energy (MJ ha−1) |
---|---|---|---|---|---|---|---|---|---|---|---|---|
2005 | 160.80 | 42.92 | 292.04 | 445.06 | 405.99 | 300.09 | 399.10 | 49.33 | 233.51 | 30.63 | 2359.50 | 2312.08 |
2006 | 159.99 | 53.35 | 286.41 | 474.44 | 273.94 | 259.38 | 203.93 | 47.66 | 193.29 | 21.26 | 1973.70 | 3217.10 |
2007 | 147.46 | 53.21 | 273.42 | 547.89 | 416.42 | 275.47 | 286.26 | 37.15 | 179.16 | 19.91 | 2236.41 | 3133.74 |
2008 | 176.70 | 44.06 | 338.28 | 470.61 | 398.40 | 308.88 | 247.22 | 51.28 | 212.88 | 31.51 | 2279.88 | 3947.13 |
2009 | 202.28 | 47.33 | 441.80 | 339.32 | 521.51 | 301.46 | 443.76 | 65.84 | 273.93 | 37.21 | 2674.48 | 5301.67 |
2010 | 180.59 | 54.15 | 400.16 | 391.23 | 641.41 | 351.80 | 357.77 | 55.80 | 288.96 | 32.60 | 2754.51 | 4523.95 |
2011 | 198.42 | 61.82 | 442.71 | 452.19 | 574.90 | 389.58 | 470.56 | 46.37 | 328.64 | 34.54 | 2999.76 | 4916.04 |
2012 | 201.70 | 65.98 | 480.40 | 579.78 | 662.89 | 550.69 | 488.39 | 50.12 | 368.34 | 38.71 | 3487.05 | 4984.01 |
2013 | 170.54 | 99.455 | 418.37 | 452.3 | 389.33 | 396.19 | 372.89 | 49.81 | 316.93 | 34.32 | 2700.26 | 4504.28 |
2014 | 181.12 | 123.83 | 483.45 | 594.2 | 502.67 | 515.40 | 448.90 | 60.40 | 372.65 | 39.16 | 3321.84 | 6141.88 |
2015 | 202.86 | 111.79 | 532.34 | 631.62 | 723.18 | 767.87 | 509.51 | 56.81 | 392.97 | 51.57 | 3980.56 | 4204.65 |
2016 | 183.89 | 126.56 | 504.49 | 544.57 | 835.60 | 859.04 | 427.23 | 60.80 | 383.46 | 64.07 | 3989.74 | 6417.05 |
2017 | 194.62 | 121.59 | 556.59 | 519.43 | 495.79 | 768.599 | 572.17 | 58.42 | 382.50 | 50.84 | 3720.58 | 3974.89 |
2018 | 35.83 | 128.40 | 37.77 | 497.25 | 577.97 | 777.42 | 537.36 | 60.20 | 349.66 | 45.70 | 3047.60 | 4562.56 |
Endogenous Variable: Wheat Yield | |||
---|---|---|---|
Exogenous Variables | Coefficient | t-Ratio | MPP |
Formula (9): | |||
Constant | 4.01 | 23.76 ** | |
Human labor | −0.02 | −0.31 ns | −0.09 |
Machinery | 0.08 | 2.33 ** | 0.19 |
Diesel fuel | 0.13 | 3.52 ** | 1.69 |
Pesticide | 0.03 | 1.51 ns | 0.03 |
Nitrogen (N) | 0.16 | 4.45 ** | 2.31 |
Phosphate (P2O5) | −0.01 | −0.17 ns | −0.06 |
Potassium (K2O) | 0.02 | 0.64 ns | 0.27 |
Water for irrigation | 0.11 | 3.09 ** | 0.77 |
Electricity | 0.04 | 0.92 ns | 0.49 |
Seed | 0.03 | 1.13 ns | 0.03 |
Durbin-Watson | 1.65 | ||
R2 | 0.49 | ||
Formula (10): | |||
Constant | 3.16 | 13.32 | |
Direct energy | 0.24 | 4.04 ** | 1.03 |
Indirect energy | 0.29 | 5.25 ** | 1.42 |
Durbin-Watson | 1.71 | ||
R2 | 0.41 | ||
Formula (11): | |||
Constant | 2.98 | 10.5 | |
Renewable energy | 0.10 | 1.73 ns | 0.16 |
Non-Renewable energy | 0.45 | 5.61 ** | 3.50 |
Durbin-Watson | 1.79 | ||
R2 | 0.41 |
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Bayasgalankhuu, L.; Ilahi, S.; Wei, W.; Wu, Y. Energy Analysis on Wheat Yield of Mongolian Agriculture. Processes 2022, 10, 190. https://doi.org/10.3390/pr10020190
Bayasgalankhuu L, Ilahi S, Wei W, Wu Y. Energy Analysis on Wheat Yield of Mongolian Agriculture. Processes. 2022; 10(2):190. https://doi.org/10.3390/pr10020190
Chicago/Turabian StyleBayasgalankhuu, Lyankhua, Sara Ilahi, Wenshan Wei, and Yongchang Wu. 2022. "Energy Analysis on Wheat Yield of Mongolian Agriculture" Processes 10, no. 2: 190. https://doi.org/10.3390/pr10020190
APA StyleBayasgalankhuu, L., Ilahi, S., Wei, W., & Wu, Y. (2022). Energy Analysis on Wheat Yield of Mongolian Agriculture. Processes, 10(2), 190. https://doi.org/10.3390/pr10020190