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Wheat The main contents of this column are the research reports, experimental briefs, comprehensive reviews, experience exchange, application technologies, scientific and technological newsletters and information research papers published in journals on wheat crop planting, breeding and field management.

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Please wait a minute... For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails Select Breeding Value of Wheat Key Parent Material ‘Lumai 14’ Nina Sun, Ming Zhao, Dongmei Wang, Liang Sun, Meiling Yan, Qian Zhao, Hongming Jiang, Jingchuan Yu, Linzhi Li Chinese Agricultural Science Bulletin    2020, 36 (10): 13-17.   DOI: 10.11924/j.issn.1000-6850.casb18120068 Abstract + (523)    HTML (12)    PDF (1178KB) (379)       Knowledge map    To carry out a theoretical research on wheat and improve the breeding effect, the design and creative thinking, the prominent characteristics and the varieties bred with ‘Lumai 14’ as parent were analyzed in this paper. From 2001 to 2018, 39 new wheat varieties were bred directly and 92 new wheat varieties were bred indirectly with ‘Lumai 14’ as parent by 89 scientific research units and breeding enterprises including Chinese Academy of Sciences, Chinese Academy of Agricultural Sciences, China Agricultural University and those in Shandong, Jiangsu, Hebei, Anhui, Henan, Shanxi, Shaanxi, Xinjiang, Guizhou and Tianjin. All the varieties were authorized 166 times in 9 provinces and 2 municipalities and obtained national authorized certification 36 times. ‘Lumai 14’, as a new generation of key parents, has contributed greatly to the wheat production and breeding in China. Select Preliminary Test Report on Cultivation of Chenopodium quinoa in Beijing Greenhouse Li Mei, Jihua Zhou, Junying Wang Chinese Agricultural Science Bulletin    2020, 36 (10): 53-59.   DOI: 10.11924/j.issn.1000-6850.casb19010100 Abstract + (324)    HTML (8)    PDF (1311KB) (61)       Knowledge map    To explore the cultivation methods of quinoa vegetables in greenhouse, quinoa seeds harvested in Beijing were used as experimental materials. The dynamic monitoring of quinoa vegetable growth, the comparison of sowing amount and sowing method, the influence of fertilizer on quinoa, the optimal suitable mechanical sowing amount of quinoa, and the comparison of quinoa leaves and grains and other vegetables in nutritional composition were reported to provide a technical reference for the cultivation of quinoa vegetables. The results show that quinoa is a healthy vegetable which is rich in protein, dietary fiber, potassium, magnesium, and low in sodium. From sowing to harvesting, ≥10℃ accumulated temperature is 933.24℃. To facilitate mechanized production and ensure the neat of the group, it is better to choose drill sowing. When the sowing amount was 22.5-24 kg/hm 2, the yield could reach 15143.55-15442.95 kg/hm 2. Compared with the application of chicken dung and non-fertilization, the yield of quinoa under sheep dung is better, and the yield of edible part is 15722.10 kg/hm 2. Select Simulation of Grain Filling Rate of Winter Wheat Under Water and Nitrogen Stress Yuli Chen, Ping Yang, Fajiang Gong, Haibin Bi, Minghui Gao, Gui Qi, Huawei Li Chinese Agricultural Science Bulletin    2020, 36 (10): 8-12.   DOI: 10.11924/j.issn.1000-6850.casb18120113 Abstract + (442)    HTML (14)    PDF (1365KB) (83)       Knowledge map    To quantitatively analyze the effects of water and nitrogen stress on winter wheat grain filling rate, we carried out field experiments in 2016-2017 and 2017-2018 growing seasons using winter wheat variety ‘Jimai 22’ under various water and nitrogen application levels. On the basis of experiment data collected in the 2017-2018 growing season, a simulation model of winter wheat grain filling rate under water and nitrogen stress was built by analyzing the influence rule of water and nitrogen stress on winter wheat grain filling rate, as well as introducing the water and nitrogen impact factors, and could be specifically described as: S(j,t)=S(W3N300,t)×(1+FN)×(1+FW). The model was then validated with an independent dataset collected in the 2016-2017 growing season. Except the ratio of mean absolute error (da) to the mean observation (dap), the root mean squared error (RMSE), mean absolute error (da), and correlation (r) all showed that the simulated values were well identical to the measured ones. The model can be used to simulate the effects of water and nitrogen stress on winter wheat growth and yield.