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20 January 2021, Volume 42 Issue 01

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Estimation of Soil Organic Carbon and Total Nitrogen Storages under Conservation Tillage as Influenced by Sampling Depths and Calculation Methods

GAO Qi-qi, ZHANG Wei, MA Li-xiao, REN Tu-sheng, ZHANG Ai-ping, LI Gui-chun, HU Zheng-jiang, DU Zhang-liu

2021, 42(01):  1-12.  doi:10.3969/j.issn.1000-6362.2021.01.001

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The objectives of this study were to investigate the profile distribution and accumulation characteristics of soil organic carbon (SOC) and total nitrogen (TN) under different tillage treatments, and further to compare the effects of sampling depths and calculation methods on the evaluation of SOC and TN storages. Two field experiments were established at the Shandong Huantai (5 years) and Hebei Luancheng (17 years) sites. The experiments included three tillage treatments (with residue): conventional tillage (CT), rotary tillage (RT) and no-tillage (NT). Soil samples were collected down to 60 and 50cm depths at Huantai and Luancheng site respectively. Soil bulk density (b) and the distribution of SOC and TN concentrations were determined. The SOC and TN storages were calculated by the fixed depth (FD) and equivalent soil mass (ESM) methods. The results showed that soil depth significantly affected the soil b, the concentrations and storages of SOC and TN (P<0.001). Compared with CT, NT enhanced SOC and TN storages in the top layer, and increased the stratification ratio (SR) of SOC and TN concentrations, though the SR value of SOC at Luancheng site was not significant. RT (cf. CT) increased the storages of SOC and TN in the top layer and the SR value of TN concentration at the Luancheng site. Specifically, at the Huantai site, the SOC and TN storages under NT were 29% and 30% higher than that of CT in the 0−5cm soil layer (P<0.05), but were 8% and 10% lower in the 0−60cm soil profile. At the Luancheng site, the SOC storage in the NT and RT was higher by 10% and 14% than CT; but there was no significant differences in SOC and TN storages between tillage treatments in the deeper profiles (i.e., ≥20cm). Due to the varied soil b between the treatments in the surface layer, the FD method overestimated the SOC and TN storages in the NT soil at the Huantai site, but underestimated them at the Luancheng site. Therefore, to accurately assess the SOC sequestration induced by tillage conversion, the ESM instead of FD method was recommended to calculate SOC storages together with the ＂deeper sampling＂ strategy (≥30cm). Our study implicates that although conservation tillage has positive effect on soil quality, the potential for mitigating climate change through SOC sequestration should not be overestimated.

Dynamic Modeling and Prediction of Soil Moisture Based on Real-Time Water Content Data

WANG Tie-ying, WANG Yang-ren, ZHAN Guo-long, NIU Shao-qing, YAO Li

2021, 42(01):  13-23.  doi:10.3969/j.issn.1000-6362.2021.01.002

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Real-time and accurate prediction of moisture content is to carry out irrigation forecasts, and to achieve precise management of farmland water, which is an important measure to improve water efficiency. Based on the principle of water balance in the root zone (0−60cm soil layer), the crop transpiration and water flux at the lower interface of the root zone are linearized by using the Taylor series. On this basis, a dynamic soil moisture prediction model was constructed with the real-time average soil moisture content of the root zone as an independent variable. The real-time monitoring data (soil moisture content at 30cm and 60cm below the ground surface) of the wireless soil moisture monitoring system (including three monitoring points) in Xilv Village, Wuqing District, Tianjin City are used, and 5 days, 10 days, 15 days and 20 days are selected as the modeling series length respectively, and regression analysis is performed to determine the model parameters. The prediction accuracy of soil moisture was analyzed, using the two forecast periods of 10 days and 15 days. The results showed that: (1)the real-time prediction model fits well, and the deterministic coefficients under the condition of the three modeling series length can above 0.80 (the number of samples are all greater than 550).(2) The relative error of 15 days modeling series is the smallest.(3) Under the conditions of 15 days modeling series length, 15 days prediction period, and 10% relative error limit value, the moisture prediction pass rates of the three monitoring points reached 98%, 100% and 89%, respectively. It can be seen that the real-time moisture prediction model proposed by the research has high prediction accuracy, which is convenient for modeling and analysis, and provides a new method for soil moisture prediction.

Relationship between Negative Air Ion and Relative Humidity in Quercus variabilis Plantation under Natural Conditions

SHI Guang-yao, SANG Yu-qiang, ZHANG Jin-song, MENG Ping, CAI Lu-lu, PEI Song-yi

2021, 42(01):  24-33.  doi:10.3969/j.issn.1000-6362.2021.01.003

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Negative air ion is an important indicator of measuring air cleanliness in an area, and it plays an important role in promoting the psychological and physiological functions of the human body. With the rise of forest eco-tourism, the produce process and influence mechanism of negative air ion have become research hotspots in related fields such as biometeorology, forest ecology, and forest health. In this study, the Quercus variabilis plantation in the hilly area of North China was taken as the experimental object. The negative air ions and micrometeorological parameters of the canopy were obtained by positioning observation under the condition of relatively constant leaf area of forest from June to September in 2018 and 2019, respectively. Python software was used to screen out the observation data under the condition that the photosynthetically active radiation is about zero and the temperature, wind speed, and pollutant concentration were relatively constant. The impact of relative air humidity on negative air ions was analyzed. The results show that negative air ion present three changing trends with the increase of air humidity, which is relatively stable within the range from 35% to 55% of relative air humidity; rapidly increase within the range from 55% to 75% of relative air humidity, represents a linearly increasing relationship; moderately decrease within the range of 75% to 95% of relative air humidity, represents a linear decreasing relationship. Based on this, the piecewise fitting equations of negative air ion and air relative humidity are constructed as NAI=729 (RH35%−55%); NAI=9.396RH+198.994 (RH55%−75%), and the coefficient of determination (R2) is 0.807 (P<0.01); NAI=−4.849RH+1232.992 (RH75%−95%), and the coefficient of determination (R2) is 0.642 (P<0.01). There is no found a significant difference between the measured value and predicted value of the constructed piecewise fitting function through the analysis and comparison. The root means square error (RMSE) is 6.175, 7.091, and 8.213, respectively, while the coefficient of determination (R2) is 0.806 and 0.836 within RH55%−75% and RH75%−95%, respectively. The accuracy of the model is high and the root means square error is small. Therefore, the piecewise fitting function constructed in this study can accurately reflect the impact of air humidity on negative air ion, thereby providing a working foundation for further research on the response mechanism of negative air ion to meteorological changes.

Dynamic Simulation Effect of Physiological Characteristics and Nutritional Quality of Chinese Cabbage Based on Light and Temperature Function

CAI Shu-fang, WU Bao-yi, LEI Jin-gui

2021, 42(01):  34-43.  doi:10.3969/j.issn.1000-6362.2021.01.004

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Studying the relationship among ambient temperature, photosynthetically active radiation and physiological characteristics, nutritional quality of Chinese cabbage in greenhouse can provide reference for growth management and environmental optimization of facility cultivating Chinese cabbage. From June to September 2020, the ＂New Zaoshu No.5＂ Chinese cabbage was used as the test material for carrying out 3 experiments. Ambient temperature and photosynthetically active radiation data in greenhouse were collected automatically by automatic acquisition system, and physiological characteristics, nutritional quality of Chinese cabbage were measured once every 3 days. Light and temperature function, thermal effectiveness and photosynthetically active radiation, growing degree days of experiment days were calculated. One period experiment data was used to establish dynamic simulation models of physiological characteristics and nutritional quality. The prediction effect of the dynamic simulation models was verified and compared with the data of another 2 period experiments. The results showed that the average daily ambient temperature during the experiments was 33.06−38.31℃, and the daily photosynthetically active radiation was 3.84−19.37mol·m−2·d−1. The simulation effect of LTF models on physiological characteristics and nutritional quality of Chinese cabbage was good, which R2 was > 0.956, RMSE was < 46.752 and RE was < 11.99%. The degree of fit and simulation accuracy of LTF models were better than that of GDD and TEP models. Among them, soluble sugar, soluble protein and vitamin C showed the change of single peak curve, which LTF model could be expressed as extreme function. Nitrate showed the change of N-shaped curve, which LTF model could be expressed as Poly5 function. Cellulose, root activity, chlorophyll (a, b, a+b) and carotenoids showed the change of S-type curve, among them, Cellulose LTF model could be expressed as Gompertz function, and the other indexes LTF model could be expressed as Logistic function. LTF method can accurately predict physiological characteristics and nutritional quality of Chinese cabbage in greenhouse based on ambient temperature and photosynthetically active radiation. LTF method can provide a reference for the establishment of a more general growth model of Chinese cabbage in greenhouse.

Establishment of Critical Nitrogen Model and Nitrogen Nutrition Diagnosis of Tomato under High Temperature Stress

LI Jia-jia, YANG Zai-qian

2021, 42(01):  44-55.  doi:10.3969/j.issn.1000-6362.2021.01.005

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The critical nitrogen concentration (Nc) is the minimum nitrogen concentration when the maximum biomass is obtained in a certain growth period. It is of great significance for real-time understanding of crop nitrogen nutrition status, improving crop quality and yield, and avoiding fertilizer waste. In order to study the nitrogen management rule of greenhouse tomato under high temperature stress and determine the critical nitrogen concentration (Nc), a comprehensive experiment of high temperature and nitrogen application rate was conducted in the Venlo greenhouse of Nanjing University of Information Technology. Four temperature levels (T1 (25℃/15℃, CK), T2 (30℃ /20℃), T3 (35℃ /25℃) and T4 (40℃ /30℃) were set up, namely, no nitrogen N1, 0.5 times recommended fertilization N2 (1.3g·plant−1), 0.75 times recommended fertilization N3 (1.95g·plant−1), normal recommended fertilization N4 (2.6g·plant−1, CK), 1.25 times recommended fertilization N5 (3.75g·plant−1). After the potted tomato plants began to absorb fertilizer, the high temperature test was carried out in the climate box with different temperature treatment. After 7 days of high temperature treatment, the tomato plants were moved to the Venlo type experimental greenhouse at normal temperature for continuous cultivation. From the second day, the plant biomass and nitrogen content of each organ were systematically measured by periodic destructive sampling. The results showed that the dry matter mass (DM) of tomato plants increased with the development of growth period under different high temperature nitrogen treatments, and the relationship between critical nitrogen concentration and aboveground biomass of greenhouse tomato was in accordance with power index：Nc=a·DM−b, among them, T1：Nc= 4.167DM−0.252；T2：Nc= 4.689DM−0.375；T3：Nc= 3.287DM−0.353；T4：Nc=3.812DM−0.403. With the aggravation of high temperature stress, the critical nitrogen concentration of tomato first increased and then decreased, the dry matter accumulation of low nitrogen treatment was higher than that of high nitrogen treatment; with the increase of nitrogen application rate, the plant nutrition index (NNI) under each temperature treatment increased, and with the extension of treatment time, the plant nutrient index showed a downward trend.

Discussion on the Mechanism of Effects of High Temperature and Humidity on Tomato Flower Bud Differentiation in Seedling Stage

HUANG Qin-qin, YANG Zai-qiang, LIU Xian-nan, WANG Xue-lin, XU Chao, DING Yu-hui, LI Jia-jia, ZHENG Qian-tong

2021, 42(01):  56-68.  doi:10.3969/j.issn.1000-6362.2021.01.006

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In order to study the mechanism of high temperature and humidity affecting the differentiation of tomato flower buds, the tomato variety ＂Shouhe Fenguan＂ was used as the test material. The orthogonal test of air temperature, air relative humidity and treatment days was conducted in the agricultural meteorological experimental station of Nanjing University of information technology from April to July 2020. The air temperature (day temperature / night temperature) was set with four treatment levels: T1 (32℃/22℃), T2 (35℃/25℃), T3 (38℃/28℃), T4 (41℃/31℃); The air humidity was set at three levels: H1 (50%), H2(70%) and H3（90%）, error range is ±5 percentage points. The treatment time was 2,4,6 and 8 days. The treatments of day / night temperature 28℃/18℃ and air relative humidity 45% − 55% were used as control (CK). The contents of endogenous hormones, starch and soluble sugar were measured at different stages of tomato flower bud differentiation, and stem diameter, dry weight of single plant, strong seedling index and chlorophyll content were measured at budding stage to study the mechanism of high temperature and high humidity on flower bud differentiation of tomato. The results showed that: (1) with the increase of temperature, the whole process of flower bud differentiation was prolonged with the increase of temperature, while the air relative humidity and treatment days had little effect on the process of tomato flower bud differentiation. (2) Under different treatments, the contents of IAA and GA3 in the top buds of tomato decreased, increased and decreased with the flower bud differentiation, while the contents of ZT and ABA showed the opposite trend with IAA. The contents of IAA, ZT and GA3 decreased with the increase of temperature, relative humidity and treatment days, while ABA content increased with the increase of stress degree. (3) The content of starch and chlorophyll in tomato leaves decreased gradually with the process of flower bud differentiation. Soluble sugar content increased gradually from non differentiation stage to stamen differentiation stage, and decreased gradually during pistil differentiation stage. With the deepening of stress degree, there were significant differences among the treatments. The results showed that the inhibitory effect of high temperature and high humidity on tomato flower bud differentiation might be related to the change of endogenous hormone content and the decrease of nutrients. The environmental temperature should be controlled at the level of CK at the initial stage of flower bud differentiation. The higher the temperature, the more unfavorable it would be. The results can provide some scientific basis for tomato growth environment regulation and disaster warning.

Temporal and Spatial Characteristics of Drought in China under Climate Change

ZHAO Hai-yan, ZHANG Wen-qian, ZOU Xu-kai, ZHANG Qiang, SHEN Zi-qi, Mei Ping

2021, 42(01):  69-79.  doi:10.3969/j.issn.1000-6362.2021.01.007

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Droughts are the most frequent natural hazards which have caused the second most economic loss in China. In recent years, the trend of annual air mean temperature has been gradually decreased and precipitation has been increased in China. The research of temporal and spatial characteristics of agricultural drought is focused on under new climate background. In order to adapt to climate change and take actions for government and farmers, the spatial patterns, frequency, long-term trends and stage variability characteristics of agricultural drought were analyzed using provincial drought disaster data from 1951 to 2018. The results showed that: (1) the mean area affected by drought, area of drought disasters, area percentage affected by drought and area percentage of drought disasters were used to represent spatial characteristics. Area affected by drought and area of drought disasters were more serious in Inner Mongolia, Shanxi and Hebei province than those in other regions. (2) Based on Warning Grade of Agricultural Drought GB/T 34817−2017 and the definition of area affected by drought, extreme drought, severe drought and moderate drought were classified. The frequency of agriculture drought was more in Inner Mongolia, Shanxi and Shaanxi province than that in other regions. (3) Annual area affected by drought, area of drought disasters, area percentage affected by drought and area percentage of drought disasters were analyzed by fitting at least squares principle. Regression coefficients were used to analyze long-term trends of those four indices. Area affected by drought and percentage experienced decreasing trends in 16 provinces, while they showed increasing trends in most regions with area of drought disasters in 23 provinces and percentage in 27 provinces. (4)According to climate warming trends in China, nearly 70 years were divided into three stages, 1951−1984(stage I), 1985−1997(stage II) and 1998−2018(stage III). It was found that agriculture drought was comparatively less at stage I in China, and it was increasing apparently at stage II. Area affected by drought, area of drought disasters and area percentage affected by drought decreased widely, but area percentage of drought disasters was continued to increase at stage III. Above all, agricultural drought was severer and more frequent in the north of China than that in the south of China, so more attentions should be paid to defending agriculture drought in the north of China.