吴龙国，男，讲师，宁夏大学园艺学蔬菜方向和农艺与种业园艺方向硕士生导师，全国研究生、本科生教育评估专家，“园艺学科黄大年教师团队”骨干人员，宁夏青年拔尖人才，第四届宁夏青年科技托举人才，“Plant Methods”期刊副主编，《Plant Phenomics》、《Horticulture Research》、《Plant Hormones》、《蔬菜》青年编委，2017.1至2017.5在美国德克萨斯州的德克萨斯农工大学-金斯维尔分校进行访学交流。主持完成科研项目6项，在研项目3项；参与在研的国家自然基金地区项目4项；参与完成的项目5项，其中国家自然基金项目3项，国家支撑计划项目子课题1项，自治区重点研发计划1项；省级一流仿真软件《番茄温室栽培物联网虚拟仿真实验》，入驻国家虚拟仿真实验教学课程共享平台。作为《TRAC-Trends in Analytical Chemistry》《Journal of Advanced Research》《Food chemistry》《Food control》《Computers and Electronics in Agriculture》《Journal of Food Composition and Analysis》《Biosystems Engineering》《Measurement》《Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy》《Journal of cereal science》《Current research in food science》《Crop Protection》《Scientia Horticulturae》《Microchemical journal》《Journal of visual communication and image representation》《Infrared Physics and Technology》《Vibrational spectroscopy》《Plant Methods》《Sensors》等期刊的评审专家。近5年，获宁夏回族自治区科技进步奖三等奖（排名1），获批教育部园艺虚拟仿真教学实验室，中国农技协红寺堡瓜菜科技小院（首席专家）；以第一作者或通讯作者发表论文30篇（SCI11篇），相关工作已发表在Plant Biotechnology Journal（IF5y=12.1）、LWT-Food Science and Technology、Optics and Laser Technology、Microchemical Journal、Journal of Food Composition and Analysis、Postharvest Biology and Technology、Spectrochimica Acta Part A：Molecular and Biomolecular Spectroscop、Spectroscopy and Spectral Analysis等期刊；发明专利8项（授权1项、受理7项），实用新型专利9项，授权软件著作权12项，团体标准发布13项，著作3部，受邀学术报告12次（国际6次，国内6次），成果登记7项，成果转化62万元；培养研究生6名、本科生7名，青年科技骨干8名，培训技术人员和农民1020人次，科普示范800人次，并在CCTV-13、人民日报、中国青年报、宁夏新闻网、宁夏日报等媒体进行宣传报道。

园艺作物营养精准监测、农产品无损检测。主要研究内容为：

（1）园艺作物表型信息；

（2）果蔬种植过程营养预测与精准供给；

（3）逆境下果实品质形成与调控；

（4）果蔬工厂化种植与装备研制；

（5）旱区果蔬肥水高效利用。

[1] Jie Hao, Yan Yan, Yao Zhang, Yiyang Zhang, Yune Cao，Longguo Wu*. A cross-scale transfer learning framework: prediction of SOD activity from leaf microstructure to macroscopic hyperspectral imaging.Plant Biotechnology Journal, 2025, 23(4):1091-1100.  

[2] Jiarui Cui, Yao Zhang, Jie hao, Yan ma, Jiali Men, Shibo pan, Longguo Wu*. Utilizing wasserstein generative adversarial networks for enhanced hyperspectral imaging: A novel approach to predict soluble sugar content in cherry tomatoes. LWT-Food Science and Technology, 2024, 206:116585.

[3] Jie Hao, Yao Zhang, Yiyang Zhang, Longguo Wu*. Prediction of antioxidant enzyme activity in tomato leaves based on microhyperspectral imaging technique.Optics and Laser Technology, 2024, 179:111292.

[4] Longguo Wu, Ling Ma, Wencheng Pan, Yao Zhang, Yu Tian, Yanzhe Zhu, Xingwu Tian, Yiyang Zhang, Yune Cao.Optimal antioxidant enzyme activity estimation in melon plant leaves based on microhyperspectral imaging technique. Microchemical Journal,2024,206:111626.

[5] Yao Zhang, Ling Ma, Weiguo Yi, Longguo Wu*. Research on the adulteration of Lycium barbarum based on hyperspectralimaging technology combined with deep learning algorithm.Journal of Food Composition and Analysis,2024,136:106765.

[6] Yiyang Zhang, Yao Zhang, Yu Tian, Hua Ma, Xingwu Tian, Yanzhe Zhu, Yanfa Huang, Yune Cao, Longguo Wu*. Determination of soluble solids content in tomatoes with different nitrogen levels based on hyperspectral imaging technique. Journal of Food Science, 2024,89(9):5724-5733.

[7] Longguo Wu, Yao Zhang, Qiufei Jiang, Yiyang Zhang, Ling Ma, Siyan Ma, Jing Wang, Yan Ma, Minghua Du, Jianshe Li, Yanming Gao. Study on the CAT activity of tomato leaf cells under salt stress based on microhyperspectral imaging and transfer learning algorithm, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2023，302，123047.

[8] Longguo Wu, Qiufei Jiang, Yao Zhang, Minghua Du, Ling Ma, Yan Ma. Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique,Horticulturae, 2022, 8: 813.

[9] Longguo Wu, Qiufei Jiang, Yao Zhang, Songlei Wang. Nontraditional detection of soil moisture content based on hyperspectral imaging technique, Bangladesh Journal of Botany, 2022, 50(4): 1039-1049.

[10] Ling Ma, Yao Zhang, Yiyang Zhang, Jing Wang, Jianshe Li, Yanming Gao, Xiaomin Wang, Longguo Wu*. Rapid Nondestructive Detection of Chlorophyll Content in Muskmelon Leaves under Different Light Quality Treatments, Agronomy, 2022, 12: 3223.

[11]杜明华, 杨甜,马燕, 张捷, 吴龙国*.基于NIR高光谱成像技术的番茄叶片叶绿素含量检测[J].江苏农业科学, 2022，50(20),48-55.

[12]张瑶, 高琳, 马桂娟, 王紫昕, 吴龙国*. QuEChERS结合GC-MS/MS法同时测定陈皮中215种农药残留[J].中成药,2022，44(10),3368-3375.

[13]张瑶, 马桂娟, 高琳, 王紫昕, 吴龙国*.固相萃取-气质联用测定黄瓜中62种农药残留[J].中国测试, 2022，48(9), 63-70.

[14]孟露，张捷，杨甜，吴龙国*.基于高光谱成像技术的番茄叶片叶绿素含量可视化分布研究[J].湖北农业科学, 2022，61(14),171-177.

[15]吴龙国, 张瑶.浅层土壤水分特征曲线模拟与运移机理研究 [J].农机化研究, 2021，11,165- 170.

[16]吴龙国, 张瑶, 王松磊, 李建设. 基于高光谱成像技术的土壤盐分含量检测[J].光电子·激光，2020，31(4),388-394.

[17]王静,马玲,吴龙国*,等.植物工厂LED灯不同光照强度对甜瓜植株生长的影响[J].农业科学研究,2024,45(03):34-38.

[18]王静,马玲,马思艳,等.荧光高光谱成像技术对甜瓜叶片过氧化氢酶活性的无损检测[J].光谱学与光谱分析,2024,44(12):3455-3462.

[19]马思艳,马玲,马燕,等.基于深度学习的甘蓝叶片超氧化物歧化酶活性模型构建[J].安徽农业科学,2025,53(01):229-235.

[20]马玲，李亚娇，张祎洋，王静，马燕，马思艳，吴龙国*.基于高光谱成像技术的番茄叶片含水量检测研究[J].南京农业大学学报，2024，47(6)：1221- 1229.

[21]马玲,杜明华,吴龙国*,等.基于高光谱成像技术的番茄叶片叶绿素含量检测[J].江苏农业科学,2023,51(11):167-174.

[22]马玲,马倩,吴龙国*,等.基于高光谱成像技术的不同时期番茄植株的快速无损判别研究[J].分析测试学报,2023,42(02):210-215.