Abstract
Agricultural mechanization is closely related to the large-scale sustainable production of crops. An ever-increasing specialization is also crucial to the farm landscape and rural settlements in social communities. Therefore, it is highly urgent to comprehensively and quantitatively evaluate the production efficiency, environmental impact, and water consumption in the mechanized mode of crop production. As such, carbon and water footprints were frequently applied in the evaluation of the agricultural production. In this study, a systematic evaluation was performed on the mechanized production modes of soybean in China and Kazakhstan using carbon and water footprints. Two main areas of soybean production were selected as the research sites: One is the Nenjiang Farm (located at 48°07' N, 125°50' E) in the Heilongjiang Land Reclamation Area, China, and another is the Amangel'dy Farm (located at 44°57' N, 78°04' E) in the Almaty Region, Kazakhstan. Then, the carbon footprint, water footprint, and yield were used to analyze mechanized modes of soybean production from multiple perspectives. The Greenhouse Gas (GHG) inventories in the latest Intergovernmental Panel on Climate Change (IPCC) guidelines were used to calculate the carbon footprint. A Cropwat 8.0 software from FAO was used for the water footprint. The meteorological data was obtained from the Climatic Research Unit of the University of East Anglia, and the soil hydraulic properties were from the High-Resolution Soil Hydraulic Properties Map of the World. The carbon footprint was calculated for the N2O emission from managed soil, and other emissions from agricultural inputs, including fertilizer, seeds, pesticides, diesel, and labor, all of which were converted into the CO2 equivalent. The water footprint was calculated for the consumption of indirect water from agricultural materials inputs, and the direct water consumption, including green, blue, and gray water. The results showed that the carbon footprint, water footprint, and yield were 0.51 kg/kg, 1.82 m3/hm2, and 2 875 kg/hm2 in China, and 0.52 kg/kg, 2.76 m3/hm2, and 2 000 kg/hm2 in Kazakhstan, respectively. The carbon footprint in the Amangel'dy Farm was 2.08 % higher, while the water footprint was 51.83 % higher, and the yield was 30.43 % lower, than that in the Nenjiang Farm. It infers that the mechanized mode of soybean production in the Nenjiang Farm was much better than that in the Amangel'dy Farm. In Almaty region, the efficiency of water consumption and yield can be considered as the future improvements in the mechanized mode of soybean production. Specifically, the carbon emissions of Amangel'dy Farm were significantly higher than those of Nenjiang Farm in the stage of soil preparation, while the emissions in the Nenjiang Farm were relatively higher in the sowing stage. The N2O emissions from managed soils in the Nenjiang Farm were much higher than those in the Amangel'dy Farm. The reason can be that more fertilizer was used in the Nenjiang Farm. In the water footprint of direct water consumption, the green water consumption in the Nenjiang Farm was significantly higher due to high precipitation, whereas, the blue water consumption was lower than that in the Amangel'dy Farm. In addition, diesel was the main source of indirect water consumption in two farms. Particularly in the actual practical situation, the water-saving irrigation technology and facilities or equipment were lacking in Kazakhstan, where lots of agricultural machinery were outdated unsuitable for soybean agronomy. The market of soybean seed in Kazakhstan lacked control, indicating incomplete conditions in the standardization of sowing, plant protection, and fertilization techniques. Therefore, the local government can effectively promote the water-saving irrigation technologies and equipment, to update the agricultural machinery, and thereby to establish operational norms for mechanized soybean production. This finding can provide a sound reference to evaluate the mechanized modes of crop production from multiple perspectives in different regions.