郭寶錚教授

學歷

美國Virginia Commonwealth Univ. 生物統計系博士

美國Iowa State Univ. 統計系碩士

國立中興大學糧食作物研究所碩士

國立中興大學農藝系學士

經歷

國立中興大學農藝系 教授 (2002年08月迄今)

國立中興大學農藝系 系主任 (2004年11月至2007年07月；2016年10月至2020年01月)

國立中興大學植物醫學暨安全農業碩士學位學程 主任 (2017年08月至2018年07月)

國立中興大學農業試驗場 場長 (2002年08月至2005年07月)

研究領域

生物統計、試驗設計、NIR光譜資料處理、淨最小平方法之研究、作物生長模式、模擬基改作物花粉飄散、量測不確定度的評估、智慧科技在農業生產上之應用

近五年期刊論文

• 杜元凱、陳涵葳、紀銘坤、方士倫、姚銘輝、郭寶錚。2022。利用高光譜資料建立小果番茄缺水逆境早期預測模型。台灣農業研究，71(2): 87-99。

• Chiang, M. J., Yang, S. K., Kuo, B. J., Sun, W., Fang, S. L., Chuang, C. Y., Ho, C. H., Chang, F. J., & Yao, M. H. (2026). An automated foldable organic photovoltaic system for greenhouses supporting crop productivity and achieving energy self-sufficiency. Cell Reports Physical Science, 103173. https://doi.org/10.1016/j.xcrp.2026.103173

• Fang, S. L., Tsai, B. Y., Chang, S. C., Chang, Y. L., Yao, M. H., Chi, M. K., Wang, W. L., & Kuo, B. J. (2026). Regulated deficit irrigation strategy for greenhouse melons based on water status classification model and crop coefficient–reference evapotranspiration approach. Irrigation Science, 44, 41. https://doi.org/10.1007/s00271-026-01082-9

• Liu, Y. Y., Su, Y. C, Sun, P. W., Dai, H. Y., & Kuo, B. J. (2025). Stability of maize phenology predictions by using calendar days, thermal functions, and photothermal functions. Agriculture, 15(19), 2020. https://doi.org/10.3390/agriculture15192020

• Su, Y. C., Sun , P. W., Dai , H. Y., & Kuo, B. J. (2025). Evaluating the impact of weather variability on maize yield fluctuation for different sowing dates. Agricultural and Forest Meteorology, 371, 110625. https://doi.org/10.1016/j.agrformet.2025.110625

• Fang, S. L., Tsai, B. Y., Wu, C.Y., Chang, S. C., Chang, Y. L., & Kuo, B. J. (2025). The effect of climate change on important climate variables in Taiwan and its potential impact on crop production. Agriculture, 15(7), 766. https://doi.org/10.3390/agriculture15070766

• Lee, M. H., Yao, M. H., Kow, P. Y., Kuo, B. J., & Chang, F. J. (2024). An artificial intelligence-powered environmental control system for resilient and efficient greenhouse farming. Sustainability, 16(24), 10958.

• Su, Y. C., Wu, C. Y., & Kuo, B. J. (2024). Characterizing spatiotemporal patterns of disasters and climates to evaluate hazards to crop production in Taiwan. Agriculture, 14(8), 1384. https://doi.org/10.3390/agriculture14081384

• Fang, S. L., Lin, Y. S., Chang, S. C., Chang, Y. L., Tsai, B. Y., & Kuo, B. J. (2024). Using artificial intelligence algorithms to estimate and short-term forecast the daily reference evapotranspiration with limited meteorological variables. Agriculture, 14(4), 510. https://doi.org/10.3390/agriculture14040510

• Lin, Y. S., Fang, S. L., Kang, L., Chen, C. C., Yao, M. H., & Kuo, B. J. (2024). Combining recurrent neural network and sigmoid growth models for short-term temperature forecasting and tomato growth prediction in a plastic greenhouse. Horticulturae, 10(3), 230. https://doi.org/10.3390/horticulturae10030230

• Su, Y. C., Shen, Y., Wu, C. Y., & Kuo, B. J. (2024). County-scale dataset indicating the effects of disasters on crops in Taiwan from 2003 to 2022. Scientific Data, 11, 205. https://doi.org/10.1038/s41597-024-03053-1

• Fang, S. L., Cheng, Y. J., Tu, Y. K., Yao, M. H., & Kuo, B. J. (2023). Exploring efficient methods for using multiple spectral reflectance indices to establish a prediction model for early drought stress detection in greenhouse tomato. Horticulturae, 9(12), 1317.

• Kuo, C. E., Tu, Y. K., Fang, S. L., Huang, Y. R., Chen, H. W., Yao, M. H., & Kuo, B. J. (2023). Early detection of drought stress in tomato from spectroscopic data: A novel convolutional neural network with feature selection. Chemometrics and Intelligent Laboratory Systems, 104869.

• Su, Y. C. & Kuo, B. J. (2023). Risk assessment of rice damage due to heavy rain in Taiwan. Agriculture, 13(3), 630.

• Fang, S. L., Tu, Y. K., Kang, L., Chen, H. W., Chang, T. J., Yao, M. H. & Kuo, B. J. (2023). CART model to classify the drought status of diverse tomato genotypes by VPD, air temperature, and leaf–air temperature difference. Sci Rep, 13, 602. https://doi.org/10.1038/s41598-023-27798-8

• Fang, S. L., Kuo, Y. H., Kang, L., Chen, C. C., Hsieh, C. Y., Yao, M. H., & Kuo, B. J. (2022). Using sigmoid growth models to simulate greenhouse tomato growth and development. Horticulturae, 8(11), 1021.

• Tu, Y. K., Kuo, C. E., Fang, S. L., Chen, H. W., Chi, M. K., Yao, M. H., & Kuo, B. J. (2022). A 1D-SP-Net to determine early drought stress status of tomato (Solanum lycopersicum) with imbalanced Vis/NIR spectroscopy data. Agriculture, 12(2), 259. https://doi.org/10.3390/agriculture12020259

• Fang, S. L., Chang, T. J., Tu, Y. K., Chen, H. W., Yao, M. H., & Kuo, B. J. (2022). Plant-response-based control strategy for irrigation and environmental controls for greenhouse tomato seedling cultivation. Agriculture, 12(5), 633.

• Hsieh, C. Y., Fang, S. L., Wu, Y. F., Chu, Y. C., & Kuo, B. J. (2021). Using sigmoid growth curves to establish growth models of tomato and eggplant stems suitable for grafting in subtropical countries. Horticulturae, 7(12), 537.

• Jhong, Y. S., Lin, W. S., Yiu, T. J., Su, Y. C., & Kuo, B. J. (2021). Effectiveness of different sampling schemes in predicting adventitious genetically modified maize content in a smallholder farming system. GM Crops & Food, 12(1), 212-223.

• Kuo, B. J., Jhong, Y. S., Yiu, T. J., Su, Y. C., & Lin, W. S. (2021). Bootstrap simulations for evaluating the model estimation of the extent of cross-pollination in maize at the field-scale level. PloS one, 16(5), e0249700.

• Li, G. S., Wu, D. H., Su, Y. C., Kuo, B. J., Yang, M. D., Lai, M. H., Lu, H. Y., & Yang, C. Y. (2021). Prediction of plant nutrition state of rice under water-saving cultivation and panicle fertilization application decision making. Agronomy, 11(8), 1626.

• Su, Y. C., Lee, C. B., Yiu, T. J., & Kuo, B. J. (2021). Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia. Scientific Reports, 11, 22187.

• Tu, Y. K., Chen, H. W., Fang, S. L., Yao, M. H., Tseng, Y. Y., & Kuo, B. J. (2021). Establishing of early discrimination methods for drought stress of tomato by using environmental parameters and NIR spectroscopy in greenhouse. Acta Hortic. 1311, 501-512