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| 1 | Introduction of a multicenter online database for non-metastatic breast cancer in China显示文摘Dear Editor,Breast cancer is now the most frequently diagnosed cancer and is the fifth leading cause of cancer-related death in Chinese women. Therefore, the burden of breast cancer in China is gradually increasing. According to figures released by the Chinese Cancer Center in 2018, the number of newly diagnostic breast cancer is about 278,900 cases, accounting for 16.51%of all women who were diagnosed with the first primary malignant tumors;and 66,000 cases of breast cancer died in 2014 (Chen et al., 2016). | Yaping Yang Jieqiong Liu Min Peng Fengxi Su Xiaoming Xie Zhenzhen Liu Jundong Wu Wei Wei Dongxian Zhou Weiwen Li Ailing Zhang Guosen Su Weixiong Yang Jishang Chen Dekui Ma Yongguang Cai Kai Chen Liling Zhu Qiang Liu Erwei Song | 2020 | Science China(Life Sciences)2020，63，9： | 4 |
| 2 | 增温和放牧对高寒草甸凋落物分解及其养分释放的影响不依赖于凋落物品质显示文摘在放牧生态系统中,增温、放牧和调落物品质共同决定着凋落物分解和养分释放。然而,在以往的研究中这些因子的效应通常被单独地研究。在本研究中,我们在青藏高原高寒草甸开展了一个昼夜非对称增温和中度放牧两因子的调落物分解试验。从每个处理中收集了调落物样品,这些调落物一部分放在它们的来源处理小区,另一部分放在其他处理小区以此来探究增温、放牧以及调落物品质对调落物分解和养分释放的影响。研究结果表明,增温而不是放牧显著增加了调落物质量的损失、单位面积全碳、全氮以及全磷含量的损失,这主要是因为增温增加了落物生物量和分解速率。然而,尽管同时增温放牧处理也加快了调落物分解速率,但由于降低了调落物生物量,所以增温放牧处理并没有显著影响单位面积的凋落物碳和养分释放量。相比木质素含量和碳氮比而言,季节性土壤平均温度能够更好地预测调落物分解速率。增温和放牧对调落物分解存在交互作用,但它们和调落物品质对调落物的影响均不存在交互作用。单位面积的总氮释放的温度敏感性要高于总磷。因此,我们的结果表明,增温对调落物分解以及养分释放的影响要显著大于调落物品质变化对其分解的影响。在高寒草甸,氮释放的增加可能会间接导致土壤磷有效性的缺乏。 | Bowen Li Wangwang Lv Jianping Sun Lirong Zhang Lili Jiang Yang Zhou Peipei Liu Huan Hong Qi Wang Wang A Suren Zhang Lu Xia Zongsong Wang Tsechoe Dorji Ailing Su Caiyun Luo Zhenhua Zhang Shiping Wang | 2022 | Journal of Plant Ecology2022，15，5： | 1 |
| 3 | Classification of Rice Yield Using UAV-Based Hyperspectral Imagery and Lodging Feature显示文摘High-yield rice cultivation is an effective way to address the increasing food demand worldwide.Correct classification of high-yield rice is a key step of breeding.However,manual measurements within breeding programs are time consuming and have high cost and low throughput,which limit the application in large-scale field phenotyping.In this study,we developed an accurate large-scale approach and presented the potential usage of hyperspectral data for rice yield measurement using the XGBoost algorithm to speed up the rice breeding process for many breeders.In total,13 japonica rice lines in regional trials in northern China were divided into different categories according to the manual measurement of yield.Using an Unmanned Aerial Vehicle(UAV)platform equipped with a hyperspectral camera to capture images over multiple time series,a rice yield classification model based on the XGBoost algorithm was proposed.Four comparison experiments were carried out through the intraline test and the interline test considering lodging characteristics at the midmature stage or not.The result revealed that the degree of lodging in the midmature stage was an important feature affecting the classification accuracy of rice.Thus,we developed a low-cost,high-throughput phenotyping and nondestructive method by combining UAV-based hyperspectral measurements and machine learning for estimation of rice yield to improve rice breeding efficiency. | Jian Wang Bizhi Wu Markus VKohnen Daqi Lin Changcai Yang Xiaowei Wang Ailing Qiang Wei Liu Jianbin Kang Hua Li Jing Shen Tianhao Yao Jun Su Bangyu Li Lianfeng Gu | 2021 | Plant Phenomics2021，3，1： | 0 |
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