Transactions of the Chinese Society of Agricultural Engineering, the 1st in Agricultural Engineering, is supervised by China Association for Science and Technology, and sponsored by Chinese Society of Agricultural Engineering. It aims to introduce the latest scientific achievements and developing trends of Agricultural Engineering and provides the academic developments abroad and domestic of the discipline. The scope covers agricultural water-soil engineering, agricultural information and electrical technology, agricultural products processing engineering.
The journal is included in EI, JST, Pж(AJ), CA and CSCD.
Editor-in-Chief Zhu Ming
Deputy Editor-in-Chief Wei Xiuju Zhang Ruihong Xi Weimin Wang Liu Wang Yingkuan Li Pingping Ying Yibin Tong Jin Yun Wenju Zhao Chunjiang Kang Shaozhong
Carbon capture and storage (CCS) is an effective means to reduce greenhouse gas emissions, which sequesters anthropogenic CO
2 in deep geological formations and avoids emissions into the atmosphere while supporting the coal use. Thus, the technology is an attractive way of controlling greenhouse gases in economies heavily dependent on coal energy, such as China, whose goal is to reach an emissions cap by 2030. At present, more than 12 CCS demonstration projects are in development in China. Preliminary estimates show that the reservoirs, such as saline aquifers, depleted oil and gas reservoirs, and un-mineable coal seams, have a CO
2 storage capacity with hundreds of billions of tons. However, there are risk of CCS-stored CO
2 leaking out of the storage reservoirs, and the quick leakage such as failure of injection wells and slow leakage from geological aisle, which shows different environmental impacts. The most visible impact of CCS leakage is the degradation of plant cover. To know the impact of elevated soil CO
2 flux in near-surface ecosystems and the plants’ responses to different CO
2 leaking rates, and to assess and address the risks of elevated soil CO
2 flux, we simulated quick and slow CO
2 leakage, at a rate of 2 000 g/(m·d) and 60% of the soil CO
2 concentration, and compared the differences of maize plant height, root length, leaf number, leaf photosynthetic rate and soil pH value. The experimental device was the self-made combination with gas chambers and soil chambers on top. CO
2 was injected into the bottom of the cultivation container at different flux rates by manually control. The results indicated that, under the quick CO
2 leaking at the rate of 2 000 g/(m·d), the maize photosynthetic rate was decreased from (22.86 ± 0.89)
µmol/(m·s) of CK treatment to (0.1 ± 0.08)
µmol/(m·s), while the height of maize was dropped from (206 ± 10.20) cm to (93.67 ± 4.78) cm and the maize root length was decreased by 75%, from (109 ± 16.83) cm to (20.73 ± 3.73)cm. And the number of plant leaves was decreased significantly, which was 16 in the control group, but only 9 to 11 in the rapid leakage control, and the withered leaf number were significantly increased in the rapid leakage test. Slow leakage under 60% of the soil CO
2 concentration did not inhibit the growth of maize. The height of maize plants in the control group (SCK) was (153.25 ± 13.27) cm, and the plant height at slow leakage treatment was (154 ± 8.09) cm. The root length, the number of leaves and net photosynthetic rate of maize also were not in significant difference, separately. Only the soil pH value in the vicinity of leaking source was decreased slightly, however, the soil pH value remained within a reasonable range of maize growth and therefore did not have a significant impact on maize growth. The different responses of plant to quick and slow stored CO
2 leakage will provide useful information for decision maker to formulate countermeasures.
To carry out the prediction and calculation of the flow rate for further study, the hydraulic performance and the structure optimization of the flow channel in drip irrigation emitter is of great significance. In order to predict and calculate the flow rate of the emitter accurately, in this study, the prediction and calculation method of Support Vector Machine (SVM) with strong generalization ability was introduced, and the flow rate prediction model of the SVM was built. We chose six working pressures and eight geometric parameters of the flow channel as factors, and arranged 300 sets of emitter schemes as training sample of SVM according to the orthogonal experimental design method, and 30 sets of schemes as test sample. Based on these, the prediction model sample set of flow rate of SVM was established. The flow rate of the emitter was simulated by the SST
k-
ω model with high precision in the sample set, and compared with the predicted value of flow rate of the SVM. The pressure and geometric parameter of the emitter was taken as the input item, and the flow rate was taken as the output item of SVM. The prediction and simulation of the flow rate were carried out in State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area, Xi’an University of Technology. In order to eliminate the impact of each factor on the predicted results, the input and output item in the emitter sample were normalized before predicting flow rate. At the same time, the Genetic Algorithm was used to optimize the
C and
δ parameter in the Radial Basis Function (RBF) kernel of the SVM, and then the minimum error between the predicted value and simulated value of flow rate was obtained. The results showed that the relative error between the predicted value of flow rate using SVM and the simulated value was from 0.09% to 6.43%, the average relative error was 1.91%, and the determination coefficient was 0.98 when the optimal values of SVM parameter
C and
δ were 100 and 20, respectively. The predicted value of flow rate of SVM had a good correlation with the simulated value, which satisfied the predicted demand for the flow rate of the emitter. However, when the regression fitting method was adopted and calculated, the relative error between the predicted value and the simulated value was from 0.15% to 26.69%, the average relative error was 6.45%, and the determination coefficient was 0.93, which indicated excellent superiority based on SVM. To further verify the reliability of SVM, the five experimental verification schemes were chosen, and manufactured by using the high-precision engraving technology. The flow rate value of experimental verification sample was tested under different pressure ranges, and was compared with the predicted value of flow rate. The relative error between the predicted value of flow rate using SVM and the experimental value was from 0.14% to 5.13%, and the average relative error was 2.25%, which was within the error range, verifying the accuracy and reliability of predicting flow rate using SVM. The establishment of the flow rate prediction response surface based on SVM can effectively improve the development efficiency of the emitter, and provide the evidence and guidance for the hydraulic performance evaluation, the flow channel structure design and optimization.
Saline-alkaline stress (SAS) is one of the major abiotic stresses affecting the growth of plants. It has been a severe problem that restricts plant production and even the development of the ecological environment. The improvement of plant saline-alkaline tolerance and selection of saline-alkaline tolerance plant varieties are becoming hot spots for research. To develop and select saline-alkaline tolerance plants, an evaluation method that can accurately judge the plant saline-alkaline tolerance must be first established. In the present study, the evaluation of saline-alkaline tolerance of plants is generally based on morphological indicators and physiological and biochemical indicators. These evaluation methods require a large number of samples and long cycle, and cannot be early diagnosed. Moreover, many of the indicators must be obtained through the destructive measurement of test-tube experiments, which are not nondestructive testing. Therefore, the traditional evaluation method has many disadvantages. In order to explore the methods of early, sensitive, in situ and nondestructive testing saline-alkaline tolerance of plants, a complex solution consisting of NaCl, Na
2SO
4, NaHCO
3 and Na
2CO
3 with pH value of 9.09 was used to stress 2 kinds of maize variety seedlings of Zhengdan 958 with poor saline-alkaline tolerance and Mingyu 20 with strong saline-alkaline tolerance. The time-domain waveforms of leaf electrical signals of Zhengdan 958 and Mingyu 20 seedlings during saline-alkaline stress were collected. The marginal spectra of two kinds of maize leaf electrical signals were obtained by Hilbert-Huang transformation (HHT). The changes of marginal spectrum entropy (MSE) of maize leaf electrical signals and the biological significance were analyzed. The results showed that the MSE of leaf electrical signals from maize variety Zhengdan 958 continued to decline in the process of saline-alkaline stress, while the MSE of leaf electrical signals from maize variety Mingyu 20 changed in volatility. It was indicated that the ion transport of leaf cells in Zhengdan 958 was inhibited under saline-alkaline stress, and there was complex metabolic regulation in leaf cells of Mingyu 20 to maintain the dynamic balance of ion transport and normal functional status of leaf cell. The study also found that the malondialdehyde (MDA) content in leaf of Zhengdan 958 was increasing in the process of saline-alkaline stress, and the MDA content in leaves of Mingyu 20 began to increase significantly after 4 days of stress. This phenomenon suggested that there was membrane lipid peroxidation in leaves of Zhengdan 958 in the early stages of saline-alkaline stress, and it was more and more serious with the process of the stress, however, there was significant membrane lipid peroxidation in leaves of Mingyu 20 after 4 days of stress. The membrane lipid peroxidation of leaf cells caused by saline-alkaline stress could be the reason to the decrease of MSE about maize leaf electrical signals. Due to that the variation of the MSE from 2 maize varieties with different saline-alkaline tolerance under saline-alkaline stress was different, the response index (RI) of electrical signal based on the MSE was defined in this paper. The results showed that the RI values of maize varieties Zhengdan 958 and Mingyu 20 were obviously different in the processes of saline-alkaline stress. The influence of saline-alkaline stress on the ion transport and cell membrane injury of maize leaf cell could be sensitive and early quantitatively diagnosed according to the size of RI, and then to achieve in situ measurement and nondestructive evaluating saline-alkaline tolerance of maize seedlings. Since the RI based on plant electrical signals has not relationship with the species, the method proposed in this paper to evaluate the saline-alkaline tolerance of maize seedlings may also have a wide range of applicability. It is expected that the evaluation method about the saline-alkaline tolerance of plant proposed in this paper can be verified through a large number of experiments.
