Journal of Agricultural Big Data ›› 2020, Vol. 2 ›› Issue (4): 20-28.doi: 10.19788/j.issn.2096-6369.200403
Previous Articles Next Articles
Yanqing Chen1,2(), Yongsheng Cao1,2, Yunan Lin1,2, Wei Fang1,2(
)
Received:
2020-11-19
Online:
2020-12-26
Published:
2021-03-11
Contact:
Wei Fang
E-mail:chenyanqing@caas.cn;fangwei@caas.cn
CLC Number:
Yanqing Chen, Yongsheng Cao, Yunan Lin, Wei Fang. A Layout Method for National Crop Germplasm Resource Observation and Identification Station Systems[J].Journal of Agricultural Big Data, 2020, 2(4): 20-28.
Table 1
Pseudo F-value of each level group"
分组数 | 一级分组伪F值 | 二级分组第一小组伪F值 | 二级分组第二小组伪F值 |
---|---|---|---|
2 | 291.0432 | 85.2622 | 94.1622 |
3 | 243.5635 | 83.8287 | 97.9573 |
4 | 233.3227 | 101.7008 | 162.0380 |
5 | 269.1534 | 107.4381 | 146.5259 |
6 | 249.2426 | 115.5728 | 140.8070 |
7 | 242.0424 | 118.5736 | 138.9963 |
8 | 235.9106 | 126.9021 | 137.5531 |
9 | 234.9926 | 135.7732 | 138.5778 |
10 | 265.2248 | 151.0375 | 142.9855 |
11 | 265.3803 | 152.3274 | 153.2233 |
12 | 268.7586 | 154.8697 | 166.4119 |
13 | 269.0556 | 155.2184 | 177.2834 |
14 | 274.8999 | 153.5072 | 176.4605 |
15 | 279.1272 | 153.3548 | 177.1460 |
1 | 中华人民共和国国务院办公厅.国务院办公厅关于加强农业种质资源保护与利用的意见,国办发〔2019〕56号[Z]. 2020-02-11. |
General Office of the State Council of the People's Republic of China. The opinions of the General Office of the State Council on strengthening the protection and utilization of agricultural germplasm resources, GBF〔2019〕No. 56[Z]. 2020-02-11. | |
2 | 中华人民共和国农业部.农业部关于启动农业基础性长期性科技工作的通知,农科教发[2017]5号[Z].2017-3-25. |
The ministry of agriculture of the People's Republic of China.issued on starting the basic long-term scientific and technological work in agriculture,NKJF [2017] No. 5[Z]. 2017-3-25. | |
3 | 沈文忠,赵伟荣,张绪美,等. 太仓市水稻和小麦气候生产潜力估算[J].中国农学通报,2019,35(35):1-10. |
Shen W Z, Zhao W R, Zhang X M, et al. Estimation of Climatic Potential Productivity of Rice and Wheat in Taicang[J], Chinese Agricultural Science Bulletin, 2019,35(35):1-10. | |
4 | 赵放,李秀芬,林伟楠,等. 气候变化对玉米气候生产潜力的影响[J].农业工程,2019,9(08):132-134. |
Zhao F,Li XX F,Lin W N, et al. Impact of Climate Change on Climate Productivity Potential of Maize[J], Agricultural Engineering,2019,9(08):132-134. | |
5 | Gryze S D,Wolf A,Kaffka S R, et al.Simulating green-house gas budgets of four California cropping systems under conventional and alternative management[J].Ecological Applications,2010,(20):1805-1819. |
6 | 李秀芬,赵慧颖,朱海霞,等.黑龙江省玉米气候生产力演变及其对气候变化的响应[J].应用生态学报,2016,27(8):2561-2570. |
Li X F,Zhao H Y,Zhu H X, et al. Evolution of maize climate productivity and its response to climate change in Heilongjiang Province,China[J].Chinese Journal of Applied Ecology, 2016,27(8):2561-2570. | |
7 | Chavas D R,Izaurralde R C,Thomson A M,et al.Longterm climate change impacts on agricultural productivity in eastern China[J].Agricultural and Forest Meteorology,2009(2):1118-1128. |
8 | Han J, Kamber M. Data Mining: concepts and Technique (second edition)[M]. San Francisco: Morgan Kaufmann, 2005. |
9 | Halkidi M, Batistakis Y, Vazirgiannis M. On Clustering Validation Techniques[J]. Intelligent Information Systems, 2001,17(223):107-145. |
10 | Bezdek J, Pal N. Some New Indexes of Cluster Validity[J]. IEEE Transactions on Systems, Man, And Cybernetics-Part B: Cybernetics, 1998,28(3):301-315. |
11 | 刘海燕,顾敏,毛亚萍等. 空间聚类有效性评价方法对比与研究[J].地理信息世界,2020,27(1):72-77, 83. |
Liu H Y Gu M, Mao Y P, et al. A Comparative Study of Validity Evaluation Approaches of Spatial Clustering[J]. Geomatics World, 2020,27(1):72-77, 83. | |
12 | Vendramin L, Ricardo J, Eduardo C, et al. On the Comparison of Relative Clustering Validity Criteria[C]// In:Proceedings of SIAM SDM'09, Sparks, 2009:733-744. |
13 | 周叶林.科学研究中的信息论及其应用[J].今日南国, 2009,5(124):201-202. |
Zhou Y L. Information theory and its application in scientific research[J]. The South of Chinatoday, 2009,5(124):201-202. | |
14 | Dunn J. Well Separated Clusters and Optimal Fuzzy Partitions[J], Journal of Cybernetica, 1974,4: 95-104. |
15 | Sharma S. Applied Multivariate Techniques[M]. State of New Jersey: John Wiley & Sons Inc., 1996. |
16 | Halkidi M, Vazirgiannis M. Clustering Validity Assessment: finding the Optimal Partitioning of a Data Set[C]// |
Proceeding of ICDM2001,187-194. | |
17 | 刘旭,李立会,黎裕,等. 作物种质资源研究回顾与发展趋势,农学学报,2018,8(1):1-6. |
Li u X Li L H, Li Y, et al. Crop Germplasm Resources: Advances and Trends, Journal of Agriculture, 2018,8(1):1-6. | |
18 | 中华人民共和国农业部.农业部办公厅关于确定第一批国家农业科学观测实验站的通知[Z].2018-01-30. |
The ministry of agriculture of the People's Republic of China.Notice of the general office of the Ministry of agriculture on determining the first batch of national agricultural scientific observation and experimental stations[Z].2018-01-30. | |
19 | 中华人民共和国农业农村部. 农业农村部办公厅关于确定第二批国家农业科学观测实验站的通知[Z].2020-1-2. |
Ministry of Agriculture and Rural Affairs of the People’s Republic of China. Notice of the general office of the Ministry of agriculture and rural areas on determining the second batch of national agricultural scientific observation and experimental stations[Z].2020-1-2. | |
20 | , 农用地质量分等规程[S]. |
, Regulations for gradation on agricultural land quality[S]. |
[1] | Yuxiao Sun, Yanli Li, Feng Li, Qian Chen. Research and Development Suggestions on Scientific Data Sharing at Home and Abroad [J]. Journal of Agricultural Big Data, 2022, 4(2): 88-98. |
[2] | Muhan Xue, Shuo Xu, Huiyuan Liu, Feng Lu, Yu Wang, Ao Li. Research on Ocean Fishery Scientific Data Governance and Application Services [J]. Journal of Agricultural Big Data, 2022, 4(2): 99-107. |
[3] | Yapeng Wang, Wenge Zhang, Lin Hu, TingTing Liu, Shanshan Cao, Lei Wang, Wei Sun. 3D Parameter Measurement Dataset of Picea Schrenkiana var. tianshanica by Using Backpack LiDAR in 2019 [J]. Journal of Agricultural Big Data, 2022, 4(1): 119-124. |
[4] | Yun Tao, Xiefeng Cheng. Comparative Study on Regional Big Data Development and Regional Agricultural Big Data Construction Level [J]. Journal of Agricultural Big Data, 2022, 4(1): 125-135. |
[5] | Yahui Fan, Liang Zhu, Hua Zhao, Jianhua Zheng. Research on Intellectual Property Protection of Scientific Data Sharing [J]. Journal of Agricultural Big Data, 2021, 3(4): 3-9. |
[6] | Huijuan Wang, Qian Xu, Ailian Zhou, Xiaohe Liang, Nengfu Xie, Xiaoyu Li, Saisai Wu. The Development of Blockchain and Its Application in Agriculture [J]. Journal of Agricultural Big Data, 2021, 3(3): 76-86. |
[7] | Xiaoding Feng, Xiaodong Wang, Bin Luo, Cheng Wang. Software Research and Development of a Multi-parameter Detection System for Plant Ion Absorption Based on LabVIEW [J]. Journal of Agricultural Big Data, 2021, 3(2): 16-23. |
[8] | Qiang Li, Maofang Gao, Ying Fang. Research on the Construction of the Agricultural Big Data Information Platform [J]. Journal of Agricultural Big Data, 2021, 3(2): 24-30. |
[9] | Rui Yan, Zhen Wang, Yanhao Li, Zhemin Li, Xian Li. The Application, Problems and Development of China's Agricultural Smart Sensors [J]. Journal of Agricultural Big Data, 2021, 3(2): 3-15. |
[10] | Hui Wang, Haijiang Wang, Pan Gao, Ze Zhang, Tongyu Hou, Lü Xin. Methods for Agricultural Resource Data Collection and Integration: A Study of the Xinjiang Production and Construction Corporations [J]. Journal of Agricultural Big Data, 2021, 3(2): 31-41. |
[11] | Fuqiao Chen, Chen Ling. Functional Design and Development of the Big Data Center of the Whole Tea Industry Chain [J]. Journal of Agricultural Big Data, 2021, 3(2): 54-66. |
[12] | Rui Jiang, Fenghong Huang, Yu Wu, Mengjia Huo, Huawei Liu. Big Data Construction of Oil Crops (Rapeseed, Peanut) Whole Industrial Chain [J]. Journal of Agricultural Big Data, 2021, 3(2): 67-74. |
[13] | Jun Gu, Shuhua Jia, Qinghong Zeng. Research of Construction of the Big Data Platform for Agricultural Single Product across the Whole Industry Value Chain Based on Knowledge Center [J]. Journal of Agricultural Big Data, 2021, 3(1): 25-32. |
[14] | Jie Zhang, Shengping Liu, Huili Yue, Lü Chunyang, Wei Hong. Construction and Application of Big Data Platform for Intelligent Apiculture [J]. Journal of Agricultural Big Data, 2021, 3(1): 3-13. |
[15] | Qiuzi Wen‑Han, Yongqiang Zheng, Yang Liu. Research and Application of Citrus Big Data [J]. Journal of Agricultural Big Data, 2021, 3(1): 33-44. |
|