[1]Integration of high-throughput phenotyping , GWAS, and predictive models reveals the genetic architecture of plant height in maize. Wang, Weixuan,Guo, Weijun,Le, Liang,Yu, Jia,Wu, Yue,Li, Dongwei,Wang, Yifan,Wang, Huan,Lu, Xiaoduo,Qiao, Hong,Gu, Xiaofeng,Tian, Jian,Zhang, Chunyi,Pu, Li. 2023

[2]Phenotyping, genome-wide dissection, and prediction of maize root architecture for temperate adaptability. Guo, Weijun,Wang, Fanhua,Lv, Jianyue,Yu, Jia,Wu, Yue,Wuriyanghan, Hada,Le, Liang,Pu, Li. 2025

[3]Prediction of nitrogen and phosphorus contents in citrus leaves based on hyperspectral imaging. Liu Yanli,Liu Yanli,Lyu Qiang,He Shaolan,Yi Shilai,Liu Xuefeng,Xie Rangjin,Zheng Yongqiang,Deng Lie. 2015

[4]Analysis of promoters of microRNAs from a Glycine max degradome library. Han, Yi-qiang,Gao, Ya-mei,Hu, Zheng,Zheng, Dian-feng. 2014

[5]Quantitative structure-toxicity relationship study of lethal concentration to tadpole (Bufo vulgaris formosus) for organophosphorous pesticides. Yan, Dongyun,Xu, Shaohui,Yan, Dongyun,Jiang, Xin,Bian, Yongrong,Yu, Guifen,Wang, Ligang.

[6]Spatial distribution prediction and benefits assessment of green manure in the Pinggu District, Beijing, based on the CLUE-S model. Zhang Li-ping,Zhou Zhi-ming,Hou Sen,Huang Yuan-fang,Zhang Shi-wen,Cao Wei-dong.

[7]Artificial Neural Network to Predict Leaf Population Chlorophyll Content from Cotton Plant Images. Li Shao-kun,Wang Ke-ru,Wang Chong-tao,Suo Xing-mei,Jiang Ying-tao,Yang Mei. 2010

[8]Prediction of heterosis using QTLs for yield traits in rapeseed (Brassica napus L.). Shen, Jin-Xiong,Fu, Ting-Dong,Yang, Guang-Sheng,Tu, Jin-Xing,Ma, Chao-Zhi. 2006

[9]EARLY DETECTION OF GREY MOULD DEVELOPMENT IN 'RED GLOBE' GRAPES DURING STORAGE. Guan, Wenqiang,Wu, Xinling,Guan, Wenqiang,Wang, Zhidong,Wang, Xiaotuo,Yan, Ruixiang. 2015

[10]Variability in climatology and agricultural production in China in association with the East Asian summer monsoon and El Nino Southern Oscillation. Tao, FL,Yokozawa, M,Zhang, Z,Hayashi, Y,Grassl, H,Fu, CB.

[11]Equations to predict methane emissions from cows fed at maintenance energy level in pasture-based systems. Stergiadis, Sokratis,Zou, Caixia,Chen, Xianjiang,Wills, David,Yan, Tianhai,Stergiadis, Sokratis,Zou, Caixia,Chen, Xianjiang,Allen, Michelle.

[12]Major controlling factors and predictions for cadmium transfer from the soil into spinach plants. Liang, Zhenfei,Ding, Qiong,Wei, Dongpu,Li, Jumei,Chen, Shibao,Ma, Yibing,Ding, Qiong.

[13]An agent-based population model for China. Chen, Zhongxin,Tang, Huajun,Li, Wenjuan,Chen, Zhongxin,Tang, Huajun,Holm, Einar,Makila, Kalle,Li, Wenjuan,Liu, Shenghe. 2008

[14]Supercritical CO2 dyeing of ramie fiber with disperse dye. Liu, Zhao-Tie,Zhang, Lili,Liu, Zhongwen,Gao, Ziwei,Dong, Wensheng,Xiong, Heping,Peng, Yuande,Tang, Shouwei.

[15]Rapid analysis of layer manure using near-infrared reflectance spectroscopy. Xing, L.,Chen, L. J.,Han, L. J.,Xing, L.,Chen, L. J.,Han, L. J.. 2008

[16]Prediction Of Peanut Protein Solubility B.ased On The Evaluation M odel Established By Supervised Principal Component Regression. Wang, L, Liu, HZ, Liu, L, Wang, Q, Li, SR, Li, QZ. 2017

[17]An Improved Combination Model for the Multi-Scale Prediction of Slope Deformation. Xiangyu Li,Tianjie Lei,Jing Qin,Jiabao Wang,Weiwei Wang,Dongpan Chen,Guansheng Qian,Jingxuan Lu. 2022

[18]Prediction of China's Grain Consumption from the Perspective of Sustainable Development-Based on GM(1,1) Model. Zhang, Xiaoyun,Bao, Jie,Xu, Shiwei,Wang, Yu,Wang, Shengwei. 2022

[19]Transcriptomic and methylomic analyses provide insights into the molecular mechanism and prediction of heterosis in rice. Fu, Chongyun,Ma, Ce,Zhu, Manshan,Liu, Wuge,Ma, Xiaozhi,Li, Jinhua,Liao, Yilong,Liu, Dilin,Gu, Xiaofeng,Wang, Haiyang,Wang, Feng. 2023

[20]ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning. Xiaoti Jia,Pei Zhao,Fuyi Li,Zhaohui Qin,Haoran Ren,Junzhou Li,Chunbo Miao,Quanzhi Zhao,Tatsuya Akutsu,Gensheng Dou,Zhen Chen,Jiangning Song. 2023