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    20 March 2018, Volume 39 Issue 03
    Study on the Differences of the Impact of Future Climate Change on Wheat Yield in China—Quantitative Review Based on Meta Regression Analysis
    ZHOU Jing-bo,LIU Liang
    2018, 39(03):  141-151.  doi:10.3969/j.issn.1000-6362.2018.03.001
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    In order to explain the differences in wheat yield prediction results and provide a reference for the following-up study in this field, this paper summarized the domestic and foreign researches on the impact of future climate change on China’s wheat yield by 2017, and analyzed the literatures of 26 relatively comprehensive and complete literatures, and discussed the possibility of differences in the results of the original independent research. The results showed that: (1) the effects of future climate change on wheat production were uncertain, and negative impacts of climate trends have been more common than positive ones; the projected reductions in wheat production under the A2 and B2 climate scenarios were 18% and 20% higher than those in other climate scenarios.(2) The non-climatic factors such as policy, technology, market and input could help to adapt to climate change; the yield of wheat considering these factors would increase by 10%. (3) Research data and methods may had a significant impact on the projections; the wheat yield of positive change would increase by 1% and the wheat yield of negative change would decrease by 1% when the projected time interval increased one year; separating yield, using corresponding climate models and crop models would have a significant positive effect on the increasing yield, with the level of 26%, 22% and 18%, respectively. (4) The projections of journal literatures were 5% higher than those outcomes summarized from non-journal literatures.

    Response of Greenhouse Gases Emission Fluxes to Long-term Warming in Alpine Meadow of Northern Tibet
    WANG Xue-xia, GAO Qing-zhu, HASBAGAN Ganjurjav, HU Guo-zheng, LI Wen-han, LUO Wen-rong
    2018, 39(03):  152-161.  doi:10.3969/j.issn.1000-6362.2018.03.002
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    To explore the effects of long-term climate warming on greenhouse gases(GHGs) flux in the alpine meadow, the simulated warming 2 years(2Y, 2015-2016) and 6 years(6Y, 2011-2016) experiments were conducted by the open top chamber(OTC) in an alpine meadow of Tibetan Plateau, then the dynamics of CO2, CH4 and N2O fluxes were measured during growing season. The observations showed that the CO2 flux during growing season was increased with 6Y and decreased with 2Y warming treatment, respectively, compared with the control. And the CO2 flux with 6Y warming treatment was significantly higher than that of 2Y treatment in July. The CH4 absorption flux was increased with 6Y and 2Y warming treatment, but the differences between treatments were not significant in the growing season. The N2O emission flux was showed 6Y>2Y>CK in the growing season, and the differences between treatments were not significant. The relationship between environmental factors and GHGs flux were analyzed by using of correlation analysis. The relationship between CO2, CH4 and N2O fluxes and soil temperature(0-5cm) was not obvious. The soil moisture, aboveground biomass, microbial biomass carbon and invertase were key factors regulating the CO2 fluxes, NO3--N was mainly factor affecting the CH4 absorption flux, and NO3--N and soil urease were the main factors promoting N2O emission flux. Therefore, the CO2 flux was promoted by increasing plant biomass and invertase activity with 6Y warming treatment, and the N2O emission and CH4 absorption flux were improved by increasing the soil urease and NO3--N content with 6Y and 2Y warming treatment.

    Effects of Red/Blue Light Ratio with Different Light Intensity on Growth and Yield of Cherry Radish
    ZHA Ling-yan, LIU Wen-ke
    2018, 39(03):  162-167.  doi:10.3969/j.issn.1000-6362.2018.03.003
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    Two light quality treatments of various red/blue light ratios (1R:1B and 2R:1B) and three light intensity (180, 240, 300μmol·m-2·s-1) treatments were designed to investigate the effects of red/blue light ratio and light intensity on growth and yield of cherry radish grown in environmentally-controlled chamber with LED light source. The results showed that light quality of 2R:1B presented higher new leafy chlorophyll content and lower shoot fresh weight than 1R:1B when cherry radish grown under 180μmol·m-2·s-1. But there were no significant differences in other growth indices between two red/blue light ratio treatments. 2R:1B treatment significantly improved new leafy chlorophyll content, fresh and dry weight of shoot and root, root diameter, root volume and root to shoot ratio compared with 1R:1B under 240μmol·m-2·s-1. When light intensity was 300μmol·m-2·s-1, 2R:1B treatment had slightly lower new leafy chlorophyll content and slightly higher fresh and dry weight of shoot. Under the same red/blue light ratio, the new leafy chlorophyll content, root diameter and fresh, dry weight of root increased with the increment in light intensity. The variation of shoot fresh and dry weight with light intensity depend on light quality. To conclude, suitable light quality and light intensity level are basis for high-efficient production of cherry radish, and appropriate red/blue light ratio could improve the growth of cherry radish significantly when light intensity above a certain value.

    Investigation of Potato Safety Period of Plastic Film Mulching in Intensive Agricultural Region of North China
    QIN Li-juan, LI Hai-ping, LIU Xiu, YAN Chang-rong
    2018, 39(03):  168-176.  doi:10.3969/j.issn.1000-6362.2018.03.004
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    Crop safety period of plastic film mulching means the appropriate choice of a photo-selective mulch film according to the transplant season, to the ecological conditions of the area under cultivation and, finally, to the type of crop. In the days before the transplant, the plastic mulching film should be basic whole, and it works to warm soil and to decrease soil moisture evaporation. Successively, these functions almost reduce.Soil moisture conditions can basically meet the needs of potato growth and temperature is the most important factor to be considered in intensive agricultural region of North China.This study will give a guide in mulching film management and the choice of appropriate degradable mulch in intensive agricultural region of North China in Qingdao by determining the safety period of plastic film mulching of the local crop. The effects of plastic film mulching on the growth of potato were studied, as well as the soil temperature in the 10cm soil layer and the yield, by removing the film at different times.In this experiment, conducted from March to June in 2016, six treatments were set up: planting potatoes without plastic film(T1); planting potatoes with plastic film and removing film after 30d (T2), 60d (T3), 75d (T4), 90d (T5), respectively, and planting potatoes with plastic film for the entire growth period (T6). The results indicated that the plastic film could promote the emergence of potatoes by 5 days, and the emergence rate was significantly higher than T1. It also showed that removing the plastic film after 60 days could shorten the growth period of potatoes and accelerate its growth. The effect of plastic film on soil temperature in the 10cm soil layer was significant between the sowing and seeding stage of the potatoes. During this period, the daily average temperature under plastic film was 1.1℃ higher than without it, and the accumulated temperature was 66.1℃ higher than without it, respectively. The disappearance time threshold of the film mulching effect was about 70 days after the plastic film. The results of the experiment showed that the soil accumulated temperature in the 10cm soil layer was highest at 60 days, which was 96.5℃·d higher than non-mulching in the whole growth period, indicating plastic mulching had an significant warming effect. Within the potato growth process, the warming effect of film mulching was weakened. Film mulching can significantly improve the temperature in the 10cm soil layer between 1 and 60 days after mulching. If removing the film after 60 days, there would be no significant difference among T3, T4, T5 and T6, which indicated that the effect of plastic film on soil temperature was weakened after 60 days. It further demonstrated that the yield under non-mulching had the lowest yield (40.3tha−1). The highest and the second highest yield were occurred when film were removed after 60 days (T3) and 75 days (T4), which were 13.4% and 10.4% higher than T1, respectively. Obviously, removing film after 60-75 days would produce the highest yield. Thus, the potato safety period of plastic film mulching is at 60-75 days in intensive agricultural region of Northern China, which should be the deadline for removing plastic film or degradable plastic film duration.

    Prediction on Heat Index of Rice in Heilongjiang Province Based on Grey Model
    WANG Qiu-jing, MA Guo-zhong, WANG Liang-liang, ZHU Hai-xia, DU Chun-ying, JIANG Li-xia
    2018, 39(03):  177-184.  doi:10.3969/j.issn.1000-6362.2018.03.005
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    Based on eleven agro-meteorological observation stations, Heilongjiang province was divided into three regions, namely east region, west region and south region, by using the data of temperature and rice development from 1971 to 2016. The GM (1, 1) forecasting model for the Heat Index was established from May to August for rice in every region with differential equation dynamic modeling. Then the Heat Index was dynamically forecasted, and chilling damage was monitored during growing season of rice. The results showed that the model assessed well the Heat Index during growing season of rice, and the index had corresponded well with chilling damage year of rice. The association degrees were more than 0.88 between simulation results and the original data, and they passed the association degree test and residual tests. The average regression calculating accuracies of these models were 94.6% to 97.6% from 1971 to 2010, and the monthly forecast effects for July and August were generally better than those for May and June in each region. The average forecast accuracy was above 97% from 2011 to 2016. The results indicated that these models had better simulated effect. The GM (1, 1) was feasible to forecast the Heat Index of Rice during growing season, and to achieve dynamic assessment for chilling damage of rice during growing season.
    Comparison of Temperature Sensitivity During Different Development Stages for Double-season Early and Late Rice
    WANG Zhi-hai, JIN Zhi-feng, WU Ding-rong, MAO Zhi-jun, CHEN Zhong-yun
    2018, 39(03):  185-194.  doi:10.3969/j.issn.1000-6362.2018.03.006
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    In order to explore responses of different crops’ different development stages to climate change, the relative sensitivities of growth duration to temperature of early and late rice in 38 agrometeorological observation stations during 1981-2010 in the Middle-Lower Yangtze Plain were calculated. Both early and late rice’s growth stages were divided into four stages, i.e., emergence to transplanting(E-T), transplanting to reviving(T-R), reviving to booting(R-B) and booting to mature(B-M). Results showed that growth duration decreased with temperature increasing, but its relative sensitivity varied much between all the four stages. The R-B period of early rice was the most sensible to temperature with average relative sensitivity value of −0.094 point·℃−1(P<0.05). The B-M period was less sensible than others, with average value of −0.045 point·℃−1(P<0.05). For the same stage, duration of late rice was more sensible to temperature than early rice before reviving, but was less sensible after reviving. For the two crops, the vegetative growth was more sensible than reproductive growth except T-R period. Further analysis showed that the relative sensitivity was negatively correlated with variation coefficient of duration, indicating in such stations where growth duration varied substantially, the duration would decreased more sharply under warmer condition, especially in the R-B period of early rice, whose correlation coefficient was −0.761 (P<0.001).

    Performance Comparison of Different Interpolation Methods on Missing Values for Time Series Data——A Case Study of Meteorological and Hydrological Data in Subtropical Small Watershed
    GAN Lei, ZHOU Jiao-gen, SHI Jin, LI Xi, SHEN Jian-lin, LV Dian-qing, LI Yu-yuan,WU Jin-shui
    2018, 39(03):  195-204.  doi:10.3969/j.issn.1000-6362.2018.03.007
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    The effective estimation of the missing values of time series data at the scale of point process could improve its data quality. The meteorological and hydrological data sets (daily maximum air temperature, daily minimum air temperature, daily solar radiation, daily rainfall and daily stream flow) were collected through the long-term field experiments in a typically small subtropical watershed in subtropical zone. The performance differences within five interpolation methods of linear interpolation method(LIM), K-Nearest neighbor interpolation method(KNNM), spline interpolation method(SIM), polynomial interpolation method(PIM) and kernel density estimation method(KDEM) were analyzed on the above-mentioned five data sets. The root mean square error(RMSE), absolute mean error(MAE) and Pearson correlation coefficient(r) were selected to evaluate the advantages and disadvantages of the five methods. The results showed that: (1) The estimation performance of LIM, SIM and KDEM was generally superior to the other two methods. (2) The estimation of the missing values of meteorological data (maximum temperature, minimum temperature and solar radiation) produced the varying values of the three evaluation indices with RMSE values of 1.81-6.35, MAE values of 1.30-4.20 and r values of 0.70-0.98 (P<0.05), respectively. In contrast, the estimation of missing values of hydrological data (rainfall and stream flow) had relatively high values of RMSE and MAE which were 12.51-26.28 and 3.60-14.21, respectively, and low values of r (0.07-0.72). So the above-mentioned interpolation methods generally produced better estimation of missing values of meteorological data sets than those of hydrological data. (3) Additionally, the coefficient of variation (CV) of the above data sets linearly correlated with the evaluation indices (RMSE, MAE and r) (P<0.05), and played an important role in affecting the valuation performance of the above-mentioned interpolation methods.