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【Objective】This paper explored the temporal and spatial expansion characteristics and industrial operation mode of farmers’ cooperatives in different topographical areas of Chongqing, mastered the development law of farmers’ cooperatives in Chongqing and analyzed the differences in the selection of different industrial modes, in order to provide data support for promoting the classified cultivation of cooperatives and the formulation of differentiated support policies.【Method】This paper used 2528 farmers’ cooperatives in Chongqing as a sample, comprehensively used terrain distribution index, standard deviation ellipse and other methods to analyze the temporal and spatial patterns and expansion characteristics of cooperatives of different industrial types in four types of terrain. And combined with the questionnaire survey, combed and refined the cooperative operation mode. 【Result】（i） The development of farmers’ cooperatives in Chongqing showed four growth stages in general, with slow growth from 2002 to 2006, rapid growth from 2007 to 2010, the growth rate slowed down from 2011 to 2014, and the growth rate from 2015 to 2018 has dropped significantly. From the perspective of topographical area, the growth rate of Area Ⅳ is the fastest, followed by Area Ⅱ and Area Ⅰ, and Area Ⅲ had the slowest growth rate.（ii） The growth advantages of cooperatives in different industries vary significantly. The growth advantage zone of livestock and poultry industry was Area Ⅳ. The growth advantage zone of the fruit and vegetable, grain and oil, and comprehensive industries were Area Ⅰ and Area Ⅱ. The growth advantage zone of the flower, tree, tea, and peppercorn industries are Area Ⅱ, the tobacco and Chinese medicinal materials industries are Area Ⅲ and Area Ⅳ.（iii） Except for the grain and oil industry cooperatives in the southeast-northwest direction from 2002 to 2006, the rest of the industrial cooperatives had a southwest-northeast distribution at various stages.（iv） There were six main modes of cooperative industrial operation, the livestock, poultry, fruit and vegetable, flower and tree and grain and oil industries use the ‘company + farmers’ cooperative + base + farmer’ model. The ‘company + farmers’ cooperative + farmer’ model was used by fruits and vegetables, flower and tree, grain and oil industries. The industries that use the ‘farmers’ cooperative + base + farmer’ model include fruit and vegetable, flower and tree industries, and the industries that use the ‘Internet+ farmers’ cooperative + farmer’model include livestock, poultry and other industries. The industries of the ‘farmers’ cooperative + farmer household’ model include fruit and vegetable, grain and oil industries, and livestock industry using the model of ‘company + farmers’ cooperative + base + family farm’. 【Conclusion】The number of farmers’ cooperatives in Chongqing is growing, and the advantageous area of different industries has a difference, and it has evolved in the northeast direction, and the operation mode of each industry is diverse. According to the spatio-temporal expansion characteristics of the cooperative and the local conditions, we should accurately find the mode of industrial operation and promote the steady development of cooperatives. [ABSTRACT FROM AUTHOR]

[Objective] The paper provides references for the prevention of heavy metal pollution and the protection of cultivated soil environ- ment through exploring the content characteristics and the risk of heavy metals elements of paddy soil in Chongqing. 【Method】230 paddy soil samples were collected from 7 major and typical rice-growing regions in Chongqing, and the pH and the content of 5 heavy metal elements in- cluding Cd, Hg, As, Pb and Cr in paddy soil samples were analyzed. The Nemero pollution index evaluation method and the land accumula- tion index evaluation method were used to analyze the degree of pollution, and compared with the background value of heavy metals in Chongqing soil and the risk screening value of agricultural land soil. The characteristics of heavy metal pollution in Chongqing paddy soil were analyzed and evaluated. Then, the possible sources of heavy metal pollution in soil were explored through Pearson correlation analysis and cluster analysis. 【Result】 The average contents of Pb, Cd, Cr, As and Hg in the paddy soil of the research area were 25.4, 0.312, 66. 8, 4.71 and 0.0827 mg/kg, respectively. Through the analysis of single factor pollution index and Nemero pollution index evaluation methods, 19.57% of the paddy soil sites in the study area were in the state of Cd light pollution, 0.43% was in the state of Hg medium pol- lution, and the remaining points were in the state of no pollution. According to Geo-accumulation index, the paddy soil was lightly polluted by Cd, while the remaining heavy metal elements were at a non-polluted level. However, there were very few soils with extremely high ground accumulation index of Hg (4.03, belonging to the level of strong to extremely strong pollution). It was found that the content of Cd and Hg elements exceeded the background value of Chongqing soil, 2. 84 times and 1.38 times of the background value, respectively, with a cumulative effect; The content of Pb, Cr, As elements was slightly lower than the background value of Chongqing soil, and there was basi- cally no enrichment. The average content of heavy metals in the surveyed paddy soil was lower than the corresponding agricultural land soil risk screening value. Correlation and cluster analysis showed that heavy metal pollution mainly originated from soil formation processes and human factors. [Conclusion] The paddy soil in Chongqing is generally in a clean state, but there is a risk of Cd and Hg contamination. [ABSTRACT FROM AUTHOR]

【Objective】According to the climatic characteristics such as the lack of sunshine in Chongqing, combined with the different light demand of different crops and different growth stages, the present study explored the distribution law of the plane light field of the cultivation tank under the conditions of different plant fill light heights and light intensity ratio in the plant factory, and established a quantitative relationship model between the fill light height, light intensity ratio and the plane light field intensity of the cultivation tank, so as to provide support for the automatic, accurate and on-demand regulation of the fill light height and light intensity. 【Method】In the closed intelligent simulation agricultural environment laboratory of Chongqing Academy of Agricultural Sciences, and taking the intelligent LED fill light as the research object, the paper explored the light field intensity change law of the cultivation tank under the conditions of different fill light height and light intensity ratio. The regression support vector machine algorithm was used to construct the spatial light field intensity prediction model of fill light, which took the fill light height, fill light intensity ratio and spatial position information as the input and the plane light field intensity of cultivation tank as the output. Based on this model, the intensity of the plane light field in the cultivation tank was predicted, and the height of the fill light suitable for different crops and different growth stages was adjusted as needed. 【Result】Exploring the law of light field distribution on the plane of cultivation tank under different heights and light intensity ratios, it was found that with the increase of the proportion of light intensity at the same height, the value of light field intensity on the surface of the cultivation tank plane light field also increased; Under the same light intensity ratio, with the increase of fill light height, the light field intensity value in the center area of the plane light field surface of the cultivation tank decreased, while the light field intensity value in the edge area of the light field surface increased to a certain extent. By comparing the five modeling methods, it was found that SVR algorithm had the best performance on the data set. At the same time, the training accuracy R~2 of the plane light field intensity prediction model of the cultivation tank constructed in this study could reach 0.9897, and the testing accuracy R~2 could reach 0.9815, which proved that the model had good reliability. 【Conclusion】 The distribution law of light field intensity in the cultivation tank plane of LED array fill light in plant factory was analyzed, which proved the necessity of building the prediction model of light field intensity in the cultivation trough plane. The precise construction of this model has laid a good support for the optimal dynamic regulation of light source location and intensity in different crops and different growth stages under the conditions of installment agriculture or plant factories. [ABSTRACT FROM AUTHOR]

【Objective】 The present paper aimed to carry out research on dynamic change characteristics of paddy field and dry land resources in Chongqing, identify the main factors driving the loss of paddy field and dry land resources, analyze the regional differences in the utilization of cultivated land resources, and provide support for improving the utilization rate of cultivated land resources, strengthening the management of provincial agricultural resources, and ensuring regional food security. 【Method】 Based on the interpretation results of historical remote sensing image data, the dynamic change characteristics and spatial differentiation of paddy field and dry land in the two historical stages of Chongqing from 1980 to 2000 and from 2000 to 2018 were quantitatively studied by using geographic gravity center analysis, cultivated land loss rate and other indicators and methods. 【Result】 The study found that areas of paddy field and dry land in each district of Chongqing decreased in the past 40 years. The loss area of paddy field was less than dry land, but the loss rate of paddy field was higher than dry land. The loss of paddy field and dry land both showed a trend from slow scattered occupation to rapid agglomeration occupation over time, and the area gravity center of both cultivated lands had gradually shifted to the northeast, indicating the shift from the western low-altitude area（with high economic growth rate and high-quality cultivated land） to the northeast hilly area（with relatively low economic growth rate and low quality cultivated land）. From 1980 to 2000, the area gravity center shift distances of paddy field and dry land were 0.58,0.97 kilometers, respectively, while that distances from 2000 to 2018 were 2.14,1.57 kilormeters. According to the result of cultivated land loss rate index, paddy field and dry land in most districts belonged to the slow loss type, and the losing rate from 2000 to 2018 was much higher than that from 1980 to 2000. Severely loss regions of paddy field were mainly located in the urban area and suburban areas. The regions of rapid loss were mainly concentrated in the northeast of Chongqing, and the severe and fast loss areas of dry land are concentrated in the urban area. Construction occupation was the primary factor of paddy field loss, and the ecological occupation was the secondary factor. Considering the loss rate of cultivated land resources and the types of cultivated land transformation, the dynamic types of cultivated land resources in paddy field and dry land could be divided into 4 categories, which were construction occupation dominated, ecological occupation dominated, no dominant type, and cultivated land type transformation. Furthermore, 10 subcategories can be identified based on their loss speed. 【Conclusion】There are regional differences in the main characteristics and driving forces of the loss of paddy field and dry land in Chongqing. It is necessary to strengthen the zoning management of paddy field and dry land based on the characteristics of regional cultivated land loss, optimize the ecological and landscape functions of existing cultivated land in the development zone, improve the resource utilization rate and comprehensive production capacity of cultivated land, and ensure food security. [ABSTRACT FROM AUTHOR]

[ Objective]This paper aimed to explore the law of germanium migration and transformation in soil-rice system and its influencing factors under actual production conditions in the field. [Method] 60 samples of rice root soil, 60 samples of grain and 10 samples of root, stem and leaf were collected systematically In Xianfeng county, Enshi prefecture, Hubei province. Nutrient elements such as germanium and selenium, organic matter content, pH value in rice root soil and content of germanium and some nutritive elements in root, stem and leaf of rice were tested, the correlation analysis of germanium content in soil and rice seeds was conducted, and the factors affecting the bioabsorption coeffi. cient of germanium in rice and the regularity of germanium transfer and transformation in soil-rice system were studied. [ Result] The average germanium content in the rice root soil of Xianfeng county was 1. 58 mykg, slightly lower than the background value of germanium content in soil in China ( 1. 70 mwkg). The average content of germanium in rice seeds was only 0. 031 mwkg,but the content of germanium in rice seeds in Pingbaying town in the south of Xianfeng county was much higher than that in Nanchuan district of Chongqing city and Changshan county of Zhejiang province, which had been reported. The average content of selenium in rice seeds in the whole region was also 0. 072 my kg, which showed great potential for the development of rice rich in germanium and selenium. The bioabsorption coefficient of germanium in rice was generally low, only 0. 29% - 6. 04%, and the accumulation rule of germanium in rice was only 30 %, which completely conformed to the rule and result of previous experiments : stem and leaf > root > brown rice, most of them still conformed to the general element migration law: root > stem and leaf > brown rice. [ Conclusion ] Correlation analysis showed that the germanium absorption capacity of rice was very significantly positively correlated with soil organic matter content, Ge and S content in root soil, and significantly positively correlated with pH value. However, there was an insignificant negative correlation with the nutrient elements Na2O, SiO2,Al2O3 and K2O. [ABSTRACT FROM AUTHOR]