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| 1 | From Green Super Rice to green agriculture:Reaping the promise of functional genomics research显示文摘Producing sufficient food with finite resources to feed the growing global population while having a smaller impact on the environment has always been a great challenge.Here,we review the concept and practices of Green Super Rice(GSR)that have led to a paradigm shift in goals for crop genetic improvement and models of food production for promoting sustainable agriculture.The momentous achievements and global deliveries of GSR have been fueled by the integration of abundant genetic resources,functional gene discoveries,and innovative breeding techniques with precise gene and whole-genome selection and efficient agronomic management to promote resource-saving,environmentally friendly crop production systems.We also provide perspectives on new horizons in genomic breeding technologies geared toward delivering green and nutritious crop varieties to further enhance the development of green agricul-ture and better nourish the world population. | Sibin Yu Jauhar Ali Shaochuan Zhou Guangjun Ren Huaan Xie Jianlong Xu Xinqiao Yu Fasong Zhou Shaobing Peng Liangyong Ma Dingyang Yuan Zefu Li Dazhou Chen Ruifeng Zheng Zhigang Zhao Chengcai Chu Aiqing You Yu Wei Susong Zhu Qiongyao Gu Guangcun He Shigui Li Guifu Liu Changhua Liu Chaopu Zhang Jinghua Xiao Lijun Luo Zhikang Li Qifa Zhang | 2022 | Molecular Plant2022，15，1： | 6 |
| 2 | Mercury Deposition in Snow near an Industrial Emission Source in the Western U.S. and Comparison to ISC3 Model Predictions显示文摘 | Michael L. Abbott David D. Susong David P. Krabbenhoft Arthur S. Rood | 2002 | Water Air and Soil Pollution (-)2002，，1： | 1 |
| 3 | Fine mapping of S32(t), a new gene causing hybrid embryo sac sterility in a Chinese landrace rice (Oryza sativa L.)显示文摘 | Danting Li Liangming Chen Ling Jiang Susong Zhu Zhigang Zhao Shijia Liu Ning Su Huqu Zhai Hiroshi Ikehashi Jianmin Wan | 2007 | Theoretical and Applied Genetics2007，，3： | 1 |
| 4 | Identification of a new hybrid sterility gene in rice (bi Oryza sativa L.)显示文摘 | Zhigang Zhao Chunming Wang Ling Jiang Susong Zhu Hiroshi Ikehashi Jianmin Wan | 2006 | Euphytica2006，，3： | 1 |
| 5 | Genetic dissection of top three leaf traits in rice using progenies from a japonica × indica cross显示文摘The size of the top three leaves of rice plants is strongly associated with yield; thus, it is important to consider quantitative traits representing leaf size(e.g.,length and width) when breeding novel rice varieties.It is challenging to measure such traits on a large scale in the field, and little is known about the genetic factors that determine the size of the top three leaves. In the present study, a population of recombinant inbred lines(RILs) and reciprocal single chromosomal segment substitution lines(SSSLs) derived from the progeny of a japonica Asominori ? indica IR24 cross were grown under four diverse environmental conditions. Six morphological traits associated with leaf size were measured,namely length and width of the flag, second and third leaves. In the RIL population, 49 QTLs were identified that clustered in 30 genomic region. Twenty-three of these QTLs were confirmed in the SSSL population. A comparison with previously reported genes/QTLs revealed eight novel genomic regions that contained uncharacterized ORFs associated with leaf size. The QTLs identified in this study can be used for markerassisted breeding and for fine mapping of novel genetic elements controlling leaf size in rice. | Changbin Yin Huihui Li Zhigang Zhao Zhiquan Wang Shijia Liu Liangming Chen Xi Liu Yunlu Tian Juan Ma Lidong Xu Dashuang Zhang Susong Zhu Danting Li Jianmin Wan Jiankang Wang | 2017 | Journal of Integrative Plant Biology2017，59，12： | 1 |
| 6 | A spatially distributed energy balance snowmelt model for application in mountain basins显示文摘 | Marks D Domingo J Susong D | 1999 | Hydrological Process1999，13，： | 1 |
| 7 | A spatially distributed energy balance snowmelt model for application in mountain basins 显示文摘 | Marks D Domingo J Susong D | 1999 | Hydrological Processes1999，13，1213： | 1 |
| 8 | A spatially distributed energy balance snowmeh model for application in mountain basins 显示文摘 | Marks D Domingo J Susong D | 1999 | Hydro Process1999，13，： | 1 |
| 9 | Mapping of QTLs Controlling Panicle Length and Effective Panicle Number of Rice显示文摘Panicle length and effective panicle number of rice are closely related to yield.In this experiment,indica V20 B as female parent was crossed with javanica CPSLO17 as male parent,recombinant inbred line( RIL) populations were obtained by single seed descent method,and with the RIL populations as mapping populations,QTL mapping and analysis were performed to the two panicle traits,panicle length and effective panicle.A high-density genetic map was constructed with SLAF labels,interval mapping was performed by software Map QTL5 under the threshold of 3.9,and 7 QTLs were detected on 3 chromosomes in total.Among the 7 QTLs,5 QTLs controlling panicle length( q PL1-1,q PL1-2,q PL6-1,q PL6-2 and q PL6-3) were located on chromosomes 1 and 6,respectively,and showed the contribution rates of 6.41%,22.22%,6.15%,12.24% and 13.01%,respectively,their effect-increasing loci were mainly from CPSLO17,and q PL1-1 is a new QTL; and 2 QTLs controlling effective panicle number( q PN1 and q PN4) were located on chromosomes 1 and 4,respectively,and exhibited the contribution rates of 13.15% and 8.18%,respectively,and the effect-increasing loci were from parent V20 B.The marking of these loci lays a foundation for further cloning of genes controlling panicle length and effective panicle number and molecular marker-assisted selection. | Jiali LI Ying LIU Wenjuan SHI Shengxin YE Qiang PENG Dashuang ZHANG Jianqiang WU Jifeng WANG Peiying HUANG Susong ZHU | 2016 | Agricultural Biotechnology2016，5，5： | 0 |
| 10 | QTL Mapping of Grain Weight Trait in Rice显示文摘To provide new experimental materials for QTL analysis of rice yield trait,we constructed a mapping population of 150 1 ines( recombination inbred lines,R1 L) derived from a cross between rice varieties V20B and CPSLO17,and localized QTLs and evaluated the genetic effects in the two parents and 150 RILs for thousand-grain weight trait by using internal mapping method of software Map QTL5 combining thousand-grain weight phenotypic data of the RILs. The results showed that a new QTL( q TGW-3) related to thousand-grain weight trait was detected. Individual QTL( LOD = 4. 14) explained 11. 9% of the observed phenotypic variance. And the QTL alleles came from the parent V20B. | Xichun ZHANG Ying LIU Dashuang ZHANG Jianqiang WU Jifeng WANG Peiying HUANG Susong ZHU | 2018 | Agricultural Biotechnology2018，7，5： | 0 |
| 11 | QTL Analysis of Cold-tolerance at Seedling Stage in Rice显示文摘To provided the experimental materials for identifying and cloning the quantitative trait loci( QTLs) of cold tolerance at the seedling stage,the authors analyzed QTLs and evaluated the genetic effects of two parents and a mapping population of 213 lines( recombination inbred lines,RILs) derived from a cross between IR24 and Asominori for cold tolerance at the seedling stage with dead seedling rate by using software QTL Ici Mapping 4. 0,based on a genetic linkage map constructed with 141 SSR molecular markers. The QTLs q CTS-6,q CTS-1 1 and q CTS-1 2 related to cold tolerance at the seedling stage were detected on chromosome 6,11 and 12,respectively. Individual QTLs( LOD-3. 194 3,LOD: 4. 688 2,LOD-3. 797 0) explained 5. 662 7%,8. 549 6% and 12. 787 7% of the observed phenotypic variance,respectively. All of the three detected QTLs alleles came from cold-tolerant parent Asominori. | Xichun ZHANG Qiang PENG Dashuang ZHANG Jianqiang WU Jifeng WANG Peiying HUANG Susong ZHU | 2018 | Agricultural Biotechnology2018，7，5： | 0 |
| 12 | RPNet: Rice plant counting after tillering stage based on plant attention and multiple supervision network显示文摘Rice is a major food crop and is planted worldwide. Climatic deterioration, population growth, farmland shrinkage, and other factors have necessitated the application of cutting-edge technology to achieve accurate and efficient rice production. In this study, we mainly focus on the precise counting of rice plants in paddy field and design a novel deep learning network, RPNet, consisting of four modules: feature encoder, attention block, initial density map generator, and attention map generator. Additionally, we propose a novel loss function called RPloss. This loss function considers the magnitude relationship between different sub-loss functions and ensures the validity of the designed network. To verify the proposed method, we conducted experiments on our recently presented URC dataset, which is an unmanned aerial vehicle dataset that is quite challenged at counting rice plants. For experimental comparison, we chose some popular or recently proposed counting methods, namely MCNN, CSRNet, SANet, TasselNetV2, and FIDTM. In the experiment, the mean absolute error(MAE), root mean squared error(RMSE), relative MAE(rMAE) and relative RMSE(rRMSE) of the proposed RPNet were 8.3, 11.2, 1.2% and 1.6%, respectively,for the URC dataset. RPNet surpasses state-of-the-art methods in plant counting. To verify the universality of the proposed method, we conducted experiments on the well-know MTC and WED datasets. The final results on these datasets showed that our network achieved the best results compared with excellent previous approaches. The experiments showed that the proposed RPNet can be utilized to count rice plants in paddy fields and replace traditional methods. | Xiaodong Bai Susong Gu Pichao Liu Aiping Yang Zhe Cai Jianjun Wang Jianguo Yao | 2023 | The Crop Journal2023，11，5： | 0 |
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