涂柯玲，女，湖南省怀化市人，瑶族。2023年6月毕业于中国农业大学种子科学与技术专业，获农学博士学位，海内外优秀博士引进，主要从事种子表型、种子加工与贮藏、智能化种子质量无损检测等研究。参与北京市科委项目-蔬菜种子无损检测及产品质量提升技术研究应用、公益性行业科研专项-主要农作物高活力种子生产关键技术研究与示范、国家重点研发计划-重点专项-玉米种子活力形成及保持技术研究等项目，主持扬州市青年基金、江苏省高校面上项目。

🔗柯玲 涂 - Web of Science Core Collection (clarivate.cn) 

招生专业：种子科学与技术、智慧农业、作物遗传育种、农艺与种业。

主要荣誉：

1. 2023年扬州市“绿扬金凤计划”优秀博士

2. 2023年北京市优秀毕业生、中国农业大学优秀毕业生

3. 2022年获博士研究生国家奖学金

代表性论文：

1. Tu, K.L.^#; Wen, S.Z.^#; Xu, Y.N.; He, H.J.; Li, H.; Xu, R.G.; Guo, B.J.; Sun, C.M.; Gu, R.L.; Sun, Q. Non-destructive detection strategy of maize seed vigor based on seed phenotyping and the potential for accelerating breeding. Journal of Advanced Research. 2024, https://doi.org/10.1016/j.jare.2024.12.022.  (中科院一区，IF_5Y = 11)

2. Xu, Y.N.; Wu, W.F.; Tu, K.L.; Sun, M.J.; Li, H.; Wang, M.; Sun, Q. AIseed Simulation: A seed simulation sorting software for rapidly determining seed processing procedures and parameters. Computers and Electronics in Agriculture. 2024, 22: 108971. (中科院一区，IF_5Y = 8.4) 

3. Li, H.; Hao, Y.; Wu, W.F.;  Tu, K.L.;  Xu, Y.N.; Zhang, H.; Zhang, D.Y.; Li, M.L.; Gu, R.L.; Sun, Q. Rapid detection of corn seed turtle cracks based on transmitted light image and deep learning method. Computers and Electronics in Agriculture. 2025, 230: 109876. (中科院一区，IF_5Y = 8.4) 

4. Tu, K.L.; Wu, W.F.; Cheng, Y.; Zhang, H.; Xu, Y.N.; Dong, X.H.; Wang, M.; Sun, Q. AIseed: Automated image analysis software for high-throughput phenotyping and quality non-destructive testing of individual seeds. Computers and Electronics in Agriculture. 2023, 207: 107740. (中科院一区，IF_5Y = 8.4) 

5. Tu, K.L.; Yin, Y.L.; Yang, L.M.; Wang, J.H.; Sun, Q. Discrimination of Individual Seed Viability by Using Oxygen Consumption Technique and Headspace Gas Chromatography-Ion Mobility Spectrometry. Journal of Integrative Agriculture. 2023, 22(3): 727-737. (中科院一区，IF_5Y = 4.5) 

6. Tu, K.L.#; Wen, S.Z.#; Cheng, Y.; Xu, Y.N.; Pan, T.; Hou, H.N.; Gu, R.L.; Wang, J.H.; Wang, F.G.; Sun, Q. A Model for Genuineness Detection in Genetically and Phenotypically Similar Maize Variety Seeds Based on Hyperspectral Imaging and Machine Learning. Plant Methods. 2022,18: 81. (中科院二区，IF_5Y = 5.6) 

7. Tu, K.L.; Cheng, Y.; Pan, T.; Wang, J.H.; Sun, Q. Effects of Seed Priming on Vitality and Preservation of Pepper Seeds. Agriculture. 2022, 12. (中科院二区，IF_5Y = 3.5)

8. Tu, K.L.; Cheng, Y.; Ning, C.L.; Yang, C.M; Dong, X.H; Cao, H.L; Sun, Q. Non-Destructive Viability Discrimination for Individual Scutellaria baicalensis Seeds Based on High-Throughput Phenotyping and Machine Learning. Agriculture. 2022, 12: 1616. (中科院二区，IF_5Y = 3.5) 

9. Tu, K.L.#; Wen, S.Z.#; Cheng, Y.; Zhang, T.T.; Pan, T.; Wang, J.; Wang, J. H.; Sun, Q. A Non-Destructive and Highly Efficient Model for Detecting the Genuineness of Maize Variety ’JINGKE 968′ Using Machine Vision Combined with Deep Learning. Computers and Electronics in Agriculture. 2021,182: 106002. (中科院一区，IF_5Y = 8.4) 

10. Tu, K.L.; Li, L.J., Yang, L.M., Wang, J.H., Sun Q. Selection for high quality pepper seeds by machine vision and classifiers. Journal of Integrative Agriculture. 2018,17(9): 1999-2006. (中科院一区，IF_5Y = 4.5)