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20 October 2022, Volume 43 Issue 10

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Effects of Approaches to Estimating Light Extinction Coefficient on Simulating Light Utilization in Maize Canopy

WANG Jun-hao, GU Sheng-hao, XU Tian-jun, CHEN Bo, WEN Wei-liang, ZHANG Li-zhen, GUO Xin-yu

2022, 43(10):  773-785.  doi:10.3969/j.issn.1000-6362.2022.10.001

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A field experiment for the AD268 with large leaf and dwarf structure and the XY335 with small leaf and high structure at three planting densities of low (3 plants·m⁻²), medium (6 plants·m⁻²) and high (9 plants·m⁻²) was conducted. This study integrated the vertical distribution of canopy photosynthetically active radiation (PAR), a 3D canopy model, and a canopy photosynthesis model to analyze responses of the extinction coefficients estimated by the logarithmic approach (k_log) and the regression approach (k_nls) to cultivar and density and their differences, and to evaluate the effects on simulating canopy light utilization. The results showed that there was a difference between k_log and k_nls, and this difference was more obvious for AD268 and aggravated with increasing density. The fitness based on k_nls for canopy light distribution (R²=0.86) was better than k_log (R²=0.77). The daily CO₂ assimilation, above-ground dry matter accumulation and radiation use efficiency of AD268 simulated by k_log and k_nls did not differ significantly at low densities, but the difference became larger with increasing density. The critical densities at which the difference become larger were 0.7-2.5plants·m⁻².

Climate Suitability Analysis of Green Orange Cultivation in Hainan Island under Future Climate Change Scenarios

CHEN Yan-xi, LOU Yun-sheng , REN Li-xuan , SU Lei , TANG Li-ling, YANG Jian-zhou

2022, 43(10):  786-797.  doi:10.3969/j.issn.1000-6362.2022.10.002

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Green orange is a characteristic fruit and plays an important role in local agricultural production in Hainan island. However, few researches have been available regarding the climatic suitability of green orange planting in the island. Based on the last 40a (1980-2019) daily meteorological data, topographical and other factors from 19 meteorological stations in the main island of Hainan island, a spatial analysis model is established to comprehensively determine the climate suitability index for green orange planting in the island. With climate suitability model, this study constructed the suitability models of temperature, sunshine and precipitation, as well as comprehensive suitability model for green orange planting. The methods of geographic information system (GIS) and natural point break were used in finely zoning green orange planting climate suitability. With the model simulation data of RCP4.5 climate scenario, this study assessed the trend of green orange planting suitability zone in the next 30y (2020-2049) under future climate change scenario. The results show that, the most suitable area for green orange planting is mainly distributed in the central region, with the subtotal area being 0.87×10⁴km², and the climate suitability index ranging from 0.9-1.0; the suitable area is mainly distributed in the eastern local region and most of the central and western regions, with the subtotal area being 1.83×10⁴km², and the climate suitability index being 0.7-0.9; the subsuitable area is mainly located in the western coastal, central and western high altitude regions, with subtotal area being 0.51×10⁴km², and the climate suitability index varying from 0.4-0.7; the unsuitable area is mainly distributed in the central mountainous region, with the subtotal area being 0.17×10⁴km², and the climate suitability index ranging from 0-0.4. Under the future climate scenario, the area with suitable temperature and precipitation will have large change, namely, the area with suitable temperature will gradually shrink from the surrounding to the central regions, the area with suitable precipitation will gradually move from the eastern to the central regions. The most climatic suitable area for future green orange planting will mainly distribute in the most parts of Qiongzhong, Tunchang and Baoting counties, western parts of Wanning, central and eastern parts of Baisha county in the island.

Risk Assessment and Premium Rating of Apple Planting in the Base Counties of Shaanxi Province

YANG Xiao-juan, SUN Jing-bo, SUN Yan-kun, LIU Yuan, BAI Wei, CHEN Di, HAN Rui, LIU Bu-chun

2022, 43(10):  798-809.  doi:10.3969/j.issn.1000-6362.2022.10.003

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Apple is the pillar industry of agricultural characteristic economy in Shaanxi province, but it is facing severe weather disasters during the production process, and the agricultural insurance has not effectively dispersed and transferred these risk. The data of apple planting area, production and yield per unit area of 30 base counties in Shaanxi province from 1981 to 2019 were collected, and the mathematical statistical analysis, yield loss distribution models and optimal distribution model screening were used to evaluate and determine the apple planting risk and its insurance premium rate. The results showed that the apple planting area, production and yield per unit area were increased from 1981 to 2019 in Shaanxi province. Luochuan, Liquan and Chunhua had the highest planting area and production, and the average planting area were 2.12×10⁴ha, 2.01×10⁴ha, and 1.94×10⁴ha, the average production were 33.19×10⁴t, 51.26×10⁴t and 34.28×10⁴t respectively from 1981 to 2019. Liquan and Fufeng were characterized by the relatively higher average yield per hectare with 19.71t and 16.89t respectively from 1981 to 2019. The probability of disaster risk was 29.72%, and the mild, medium, severe and extreme disasters were 17.41%, 7.21%, 2.99% and 2.11% respectively for apple planting in Shaanxi province. Yanchuan and Qianyang were prone to extreme disasters with probability of 24.18% and 20.79%. The probability of severe and extreme disasters was negatively correlated to the planting area with the correlation coefficients of −0.50. The average premium rate of apple planting was 5.23% in Shaanxi province, Yanchuan had the highest premium rate of 18.37%, followed by Qianyang (16.61%). Liquan, Luochuan, and Chunhua, the bigger apple-planting counties, had relatively low premium rates of 7.12%, 7.35%, and 8.63% respectively. Therefore, the high risk areas such as Yanchuan and Qianyang should be cautious in "northward expansion", Luochuan, Liquan and Chunhua could be maintained the planting advantages, and the low risk areas such as Fengxiang could be considered in planting expansion. Increasing apple planting in area with low natural disaster risk could effectively spread the risk in space. The differentiated premium rate according to local conditions should be implemented to ensure the scientificity of premium rate and improve the efficiency of agricultural insurance.

Insurance Design of Table Grape Weather Index：Taking the Continuous Rain Disaster in Wafangdian, the Main Production Area around the Bohai Sea as an Example

HE Jin-na, LIU Bu-chun, LIU Yuan, YIN Hong, QIU Mei-juan, YANG Xiao-juan, ZHANG Xiao-nan

2022, 43(10):  810-820.  doi:10.3969/j.issn.1000-6362.2022.10.004

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In order to solve the problem that the forest and fruit agricultural insurance products can not meet the meteorological disaster risk of industrial dispersion due to the serious lack of table grape agricultural insurance loss data, this essay is based on the meteorological data such as precipitation and sunshine of Wafangdian meteorological station around the Bohai Sea and the grape yield data from 1998 to 2019. According to the correlation between continuous cloudy and rainy index(Lu) constructed by sunshine hours and grape yield reduction rate(K), the key disaster causing factors and critical values in the critical period of grape growth and development were determined. Using the regression model established by Lu and K and the method of information diffusion theory, the risk probability is calculated, the insurance premium rate is determined, and the continuous overcast and rainy disaster index insurance products in the critical period of the growth and development of Wafangdian table grapes are designed. The results showed that: (1) continuous rain disaster was the main meteorological disaster affecting the growth, development and yield of table grapes in Wafangdian area. Lu was significantly correlated with K, and the regression model was K=2.93Lu+4.19. (2) Lu of table grapes in Wafangdian area is defined as the cumulative number of rainy days (daily precipitation≥0.1mm, and precipitation≥25mm for at least one day) for three or more consecutive days from April 1 to June 30, during which no rainfall is allowed for one day and sunshine hours≤2h per day. (3) According to ADF test, Lu and K series are stable, which can be used as the basis for designing weather index insurance. The corresponding relationship between the disaster level of continuous rain and yield reduction rate of table grapes in Wafangdian area is: 12.98%≤K<18.84%(3≤Lu<5), 18.84%≤K<24.7%(5≤Lu<7), 24.7%≤K<30.56%(7≤Lu<9), 30.56%≤K<39.35%(9≤Lu<12), K≥39.35%(Lu≥12). (4) Based on the application of information diffusion theory and continuous overcast and rainy disaster index series, the net insurance premium rate is 19.01%. The determination of gross insurance premium rate also depends on the value of safety factor, operating cost coefficient and profit margin. For specific compensation, the grape continuous cloudy and rainy index 3d is taken as the starting point, and the projection pursuit statistical method is used for hierarchical compensation when Lu≥3d.

Risk Assessment of Frost Damage to Production of Forest Fruit Based on Phenological Phase in Hebei Province

WANG Ying, Qiu Xing-lin, LI Yu-xin, Chen Xiao-juan, Chen Xiao-lei

2022, 43(10):  821-831.  doi:10.3969/j.issn.1000-6362.2022.10.005

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The research takes apples and apricots of Hebei province as examples, based on the temperature data of meteorological stations from 1974 to 2015, and calculates accumulated temperature of each region since January, to determine the three phenological periods that are susceptible to frost disasters every year: the starting and the ending of initial budding stage, flowering stage and young fruit stage. Then the research calculates the daily minimum temperature of three phenological periods at different return periods based on the Gumbel distribution, which reveals the dangerous intensity of frost disaster, and evaluates the risk of production reduction due to frost disasters according to the vulnerability curve of the three phenological periods (the yield reduction rate corresponding to the daily minimum temperature) constructed from relevant literature. Taking the once-in-a-hundred-year return period as an example, apples and apricots in northern Hebei province were more likely to be affected by frost during the young fruit period and flowering period. Zhangjiakou city was most affected during each phenological period, with an average yield reduction rate of 47.44%. Among different periods, the risk of flowering period was the highest, the yield was reduced by 59.79%, in the flowering period, the risk of yield reduction of apples and apricots in Chengde city was up to 51.42%, while in the southern region of Hebei province, Xingtai city was relatively special, with the highest yield reduction rate at the initial budding stage, reaching 37.91%. According to the above evaluation results, targeted enhancements at frost disaster monitoring and early warning in each phenological period in these areas can be made. Adjust the planting structure properly, and speed up the development of new environmentally friendly forest and fruit anti-low temperature protection technologies.

Establishment of an Estimation Model for Chlorophyll Content of Strawberry Leaves under High Temperature Conditions at Seedling Stage Based on Hyperspectral Parameters

LUO Jing, YANG Zai-qiang, YANG Li, YUAN Chang-hong, ZHANG Feng-yin, LI Yan-chen, LI Chun-ying

2022, 43(10):  832-845.  doi:10.3969/j.issn.1000-6362.2022.10.006

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The experiments were conducted in the artificial climate chamber from September to November 2021, using "Hongyan" strawberry(Fragaria×ananassa Duch "Benihope") as the test material for dynamic high- temperature environmental control experiments at the seedling stage (9−12 true leaves, leaf length ≥ 5 cm), with a daily maximum temperature of 32°C as the starting point and four levels of daily maximum/daily minimum temperatures of 32°C/22°C, 35°C/25°C, 38°C/28°C, and 41°C/31°C for 2d, 5d, 8d, and 11d, respectively, and 28°C/18°C as the control (CK).The relative air humidity is 60%−70%, the photoperiod is 12h/12h (6:00−18:00), and the light intensity is 800μmol·m⁻²·s⁻¹. The chlorophyll content and hyperspectral reflectance of leaves under different treatments were measured, and the original spectrum was changed to refine the spectral characteristic information. Based on the correlation analysis, the original and first-order sensitive band vegetation indices were established, and then the spectral characteristic parameters that characterize chlorophyll content were screened, in order to build the best estimation model of chlorophyll content. The results showed that: (1) the chlorophyll a, chlorophyll b and total chlorophyll (a+b) contents of strawberry leaves tended to decrease as the temperature increased and the duration of high temperature increased. (2) The original spectra of strawberry leaves had green peaks and red valleys in the visible region, except for the green peaks and red valleys, which did not differ significantly among treatments, and the reflectance in the NIR region under high temperature conditions showed different degrees of increase compared with CK. Compared with the original spectra, the first-order derivative spectral curves oscillated more strongly and were able to highlight the red edge parameters significantly. The red edge position λ_r of each treatment was stable at 716nm, and the difference between the red edge amplitude D_r and the red edge area S_r was significant; while the green peak (near 550 nm) and red valley (near 675nm) of each treatment were completely highlighted in the continuous uniform removal spectra. (3) Based on the correlation analysis between spectral reflectance and chlorophyll content, R₇₄₇, R₈₀₀ and R'₇₁₆, R'₉₀₆, which have the strongest correlation between the original and first derivative spectra in the visible and near-infrared bands, were selected as the combination of sensitive bands to construct the vegetation index. (4) PVI, MSAVI, TSAVI, TSAVI', DVI', MSAVI', PVI', SAVI', Dr and Sr indices correlated with chlorophyll content at highly significant levels and can be used as hyperspectral characteristic parameters to characterize the chlorophyll content of greenhouse strawberry leaves in response to high temperature stress at seedling stage. The stepwise regression model with TSAVI, DVI' and PVI' vegetation indices was the best estimation model for chlorophyll content, with a coefficient of determination (R²) of 0.843, root mean square error (RMSE) of 0.379 and relative error (RE) of 12.65%.

Design and Construction Practice of the Comprehensive Database for Cash- Trees’ Flood and Drought Disasters: A Case Study on Apple and Grape in Northern China

HE Yan-bo, LIU Yuan, JIANG Yue-qing, MAO Liu-xi, LIU Bu-chun, LU Ye-wei

2022, 43(10):  846-859.  doi:10.3969/j.issn.1000-6362.2022.10.007

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Apple and grape are the major cash-trees in China and their main producing areas are located in northern China. The common flood and drought disasters of apples and grapes are adopted as a case how to setup a comprehensive database for cash-trees’ disasters with powerfull abilities, which required by the comprehensive prevention technology and the decision-making service platform, for disaster monitoring and early warning, risk assessment,as well as risk transfer in this study. The database is constructed by plentiful data collections and managements, strict data quality controls and multi-source data formats requirements, as well as detailed design for database overall schemes and database interfaces, by involving the open-source MySQL database building techniques with the C/S architecture. Multi-source and multi-type data are well managed by the comprehensive disasters database, such as long-term meteorological and hydrological data, cash-trees’ disaster and orchard’s producing management information, remote sensing data and its derived information, soil properties and basic geographic information, and so on. These multidiscipline data have been stored in different ways managed by the database system. For example, the quantitative/qualitative attribute data has been input into the database tables, whereas the vector and raster datasets have been kept in the computer operation file system formats and indexed by the database table. For the efficient data management and sharing, a sub-system for database managing activities is developed by using the database software developing tools under the supports of GIS function middleware and Quartz open-source components. Within the sub-system, the Role-Based Access Control (RBAC) model has been introduce to assign the database user’s privileges and to control their behaviors for accessing the database tables. Meanwhile, many functions have been developed for task schedules, data collections and updates, data managements and storages, information statistical analyses and extractions, I/O ports accesses and model links from other platforms, as well as the basic data visualization abilities within the sub-system. Under the supports of the completely comprehensive disaster database, the early warning risk and disasters monitoring can been clearly illustrated in the cash-trees' producing areas by using the stored data and in terms of the preliminary disasters’ indicators. Therefor, the successful case study of building up this comprehensive disasters’ database contributes to promote other disaster database construction for cash-trees’ except for apple and grape, or other disasters except for floods and drought, even or other areas except for northern China.